Bernardo Cândido - Profile on Academia.edu (original) (raw)

Papers by Bernardo Cândido

Research paper thumbnail of UAV-Based Soil Water Erosion Monitoring: Current Status and Trends

Drones, 2025

Soil erosion affects land productivity, water quality, and ecosystem resilience. Traditional moni... more Soil erosion affects land productivity, water quality, and ecosystem resilience. Traditional monitoring methods are often time-consuming, labor-intensive, and resource-demanding, while unmanned aerial vehicles (UAVs) provide high-resolution, near-real-time data, improving accuracy. This study conducts a bibliometric analysis of UAV-based soil erosion research to explore trends, technologies, and challenges. A systematic review of Web of Science and Scopus articles identified 473 relevant studies after filtering for terms that refer to types of soil erosion. Analysis using R's bibliometrix package shows research is concentrated in Asia, Europe, and the Americas, with 304 publications following a surge. Multi-rotor UAVs with RGB sensors are the most common. Gully erosion is the most studied form of the issue, followed by landslides, rills, and interrill and piping erosion. Significant gaps remain in rill and interrill erosion research. The integration of UAVs with satellite data, laser surveys, and soil properties is limited but crucial. While challenges such as data accuracy and integration persist, UAVs offer cost-effective, near-real-time monitoring capabilities, enabling rapid responses to erosion changes. Future work should focus on multi-source data fusion to enhance conservation strategies.

Research paper thumbnail of Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation

This study tackles the challenge of accurately estimating pasture biomass by integrating proximal... more This study tackles the challenge of accurately estimating pasture biomass by integrating proximal sensing, remote sensing, and machine learning techniques. Field measurements of vegetation height collected using the PaddockTrac ultrasonic sensor were combined with vegetation indices (e.g., NDVI, MSAVI2) derived from Landsat 7 and Sentinel-2 satellite data. We applied the Boruta algorithm for feature selection to identify influential biophysical predictors and evaluated four machine learning models-Linear Regression, Decision Tree, Random Forest, and XGBoost-for biomass prediction. XGBoost consistently performed the best, achieving an R 2 of 0.86, an MAE of 414 kg ha-1 , and an RMSE of 538 kg ha-1 using Landsat 7 data across multiple years. Sentinel-2's red-edge indices did not substantially improve predictions, suggesting a limited benefit from finer spectral resolutions in this homogenous pasture context. Nonetheless, these indices may offer value in more complex vegetation scenarios. The findings emphasize the effectiveness of combining detailed ground-based measurements with advanced machine learning and remote sensing data, providing a scalable and accurate approach to biomass estimation. This integrated framework provides practical insights for precision agriculture and optimized pasture management, significantly advancing efficient and sustainable rangeland monitoring.

Research paper thumbnail of The Loss of Soil Parent Material: Detecting and Measuring the Erosion of Saprolite

Soil parent material is a fundamental natural resource for the generation of new soils. Through w... more Soil parent material is a fundamental natural resource for the generation of new soils. Through weathering processes, soil parent materials provide many of the basic building blocks for soils and have a significant bearing on the physico-chemical makeup of the soil profile. Parent materials are critical for governing the stock, quality, and functionality of the soil they form. Most research on soil parent materials to date has aimed to establish and measure the processes by which soil is generated from them. Comparatively little work has been performed to assess the rates at which soil parent materials erode if they are exposed at the land surface. This is despite the threat that the erosion of soil parent materials poses to the process of soil formation and the loss of the essential ecosystem services those soils would have provided. A salient but unanswered question is whether the erosion of soil parent materials, when exposed at the land surface, outpaces the rates at which soils form from them. This study represents one of the first to detect and measure the loss of soil parent material. We applied Uncrewed Aerial Vehicle Structure-From-Motion (UAV-SfM) photogrammetry to detect, map, and quantify the erosion rates of an exposed saprolitic (i.e., weathered bedrock) surface on an agricultural hillslope in Brazil. We then utilized a global inventory of soil formation to compare these erosion rates with the rates at which soils form in equivalent lithologies and climatic contexts. We found that the measured saprolite erosion rates were between 14 and 3766 times faster than those of soil formation in similar climatic and lithological conditions. While these findings demonstrate that saprolite erosion can inhibit soil formation, our observations of above-ground vegetation on the exposed saprolitic surface suggests that weathered bedrock has the potential to sustain some biomass production even in the absence of traditional soils. This opens up a new avenue of enquiry within soil science: to what extent can saprolite and, by extension, soil parent materials deliver soil ecosystem services?

Research paper thumbnail of Does soil thinning change soil erodibility? An exploration of long-term erosion feedback systems

Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This im... more Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This imbalance leads to soil thinning (i.e. truncation), whereby subsoil horizons and their underlying parent material become progressively closer to the land surface. As soil erosion is a selective process and subsurface horizons often have contrasting properties to the original topsoil, truncation-induced changes to soil properties might affect erosion rates and runoff formation through a soil erosion feedback system. However, the potential interactions between soil erosion and soil truncation are poorly understood due to a lack of empirical data and the neglection of long-term erodibility dynamics in erosion simulation models. Here, we present a novel modelbased exploration of the soil erosion feedback system over a period of 500 years using measured soil properties from a diversified database of 265 agricultural soil profiles in the UK. For this, we adapted the Modified Morgan-Morgan-Finney model (MMMF) to perform a modelling experiment in which topography, climate, land cover, and crop management parameters were held constant throughout the simulation period. As selective soil erosion processes removed topsoil layers, the model gradually mixed subsurface soil horizons into a 0.2 m plough layer and updated soil properties using mass-balance mixing models. Further, we estimated the uncertainty in model simulations with a forward error assessment. We found that modelled erosion rates in 99 % of the soil profiles were sensitive to truncation-induced changes in soil properties. The soil losses in all except one of the truncation-sensitive profiles displayed a decelerating trend, which depicted an exponential decay in erosion rates over the simulation period. This was largely explained by decreasing silt contents in the soil surface due to selective removal of this more erodible particle size fraction and the presence of clayey or sandy substrata. Moreover, the soil profiles displayed an increased residual stone cover, which armoured the land surface and reduced soil detachment. Contrastingly, the soils with siltier subsurface horizons continuously replenished the plough layer with readily erodible material, which prevented the decline of soil loss rates over time. Although our results are limited by the edaphoclimatic conditions represented in our data, as by our modelling assumptions, we have demonstrated how modelled soil losses can be sensitive to erosion-induced changes in soil properties. These findings are likely to affect how we calculate soil lifespans and make long-term projections of land degradation.

Research paper thumbnail of Improving RUSLE predictions through UAV-based soil cover management factor (C) assessments: A novel approach for enhanced erosion analysis in sugarcane fields

Improving RUSLE predictions through UAV-based soil cover management factor (C) assessments: A novel approach for enhanced erosion analysis in sugarcane fields

Journal of Hydrology, 2023

The Universal Soil Loss Equation (USLE) and its derivatives express the combined effects of crop ... more The Universal Soil Loss Equation (USLE) and its derivatives express the combined effects of crop cover and rainfall patterns by the cover and management factor (C). Thus, the C-factor links the combined effect of soil surface roughness, vegetation, biomass cover, and rainfall patterns on soil erosion. This evaluation should be at each phenological stage. Due to the significant time and effort needed to access this factor for a crop, simplified methods are often used, disregarding the expected intra-annual variability and consequently increasing the uncertainty for soil loss modeling. In this scenario, we proposed a framework to collect input data at a fine-scale to estimate the C-factor by the original approach. For this, we collected data with a low-cost UAV at the middle of each phenological stage of sugarcane: sprouting, tillering, elongation, and maturation. We used orthomosaics, three vegetation indices (ExRmG, MGRVI, ViGREEN), digital surface models (DSM), and digital terrain model (DTM) to determine the canopy cover (CC), surface cover (SC), and soil roughness (SR), accessing the soil loss ratio (SLR) per phenological stage. Late on, we estimate the C-factor weighting the SLR by the rainfall erosivity. Our annual C-factor aligns with the most values applied to sugarcane studies and ranged from 0.0241 to 0.2938. Our results pointed out that using the proposed methods can access suitable annual C-factor for sugarcane areas. Furthermore, we highlighted the ViGREEN because it presented a significant performance in orthomosaics classification and has a potential already reported in other studies on C-factor at different scales.

Research paper thumbnail of How suitable are vegetation indices for estimating the (R)USLE C-factor for croplands? A case study from Southeast Brazil

ISPRS Open Journal of Photogrammetry and Remote Sensing, 2023

The cover and management factor (C-factor) of the Universal Soil Loss Equation (USLE) represents ... more The cover and management factor (C-factor) of the Universal Soil Loss Equation (USLE) represents the effects of crop cover, weighted by rainfall pattern, on predicted soil erosion rates. This requires an estimate of seasonal rainfall erosivity and soil protection afforded by the crop at different phenological stages, expressed by a soil loss ratio (SLR). However, soil erosion modelers often rely on vegetation-index-based regressions to directly estimate the cover and management factor (C-factor) of the USLE from satellite images. Since this approach is based on a single or very few images, it does not characterize the seasonality of the crop cover or reflect the seasonality of the rainfall erosivity. Here, we evaluated five vegetation indices (NDVI, NDRE, SFDVI, ViGREEN, and MGRVI) in predicting SLRs and the C-factor for a sugarcane plot in Southeast Brazil. We used Sentinel-2 images and orthomosaics obtained by UAV surveys performed at the middle of each phenological stage. We compared the estimates of the C-factor based on the SLRs and rainfall erosivity against direct regressions from the literature. Our results confirmed the expected poor correlation between the C-factor and the vegetation indices. On the other hand, using the proposed vegetation indices proved to be a reliable alternative to predict the SLR in sugarcane areas, especially the NDVI, the NDRE, and MGRVI. In particular, the MGRVI accurately predicted the SLR and classified the UAV-derived orthomosaics.

Research paper thumbnail of Optical and portable equipment for characterizing soil roughness

Knowledge of surface roughness with the consequent presence of crust in the soil is important inf... more Knowledge of surface roughness with the consequent presence of crust in the soil is important information for the rational management of environmental resources. Soil surface roughness can be determined by contact and noncontact methods. Contact methods have lower values and precision than noncontact methods. Therefore, the objective of this study was to develop low-cost, portable and robust optical equipment to characterize the roughness and presence of crust in the soil through an illumination system with a line laser and monocular vision. The mean roughness was calculated by the difference in height between a point and its neighbours and the presence of crust was determined by a semivariogram. The developed equipment was used in different experimental areas: an eroded area and a compost barn. For the validation of the results, the surface roughness of the same areas analysed by the equipment was also analysed by existing techniques: for the area with erosion, a noncontact technique, i.e., structure from motion (SfM), and for the compost barn, a contact technique, i.e., a pin meter. From the results, it was found that the optical equipment developed to characterize the soil surface roughness and the presence of crust in the soil proved to be valid and provided reliable results.

Research paper thumbnail of UAV-based vegetation monitoring for assessing the impact of soil loss in olive orchards in Brazil

UAV-based vegetation monitoring for assessing the impact of soil loss in olive orchards in Brazil

Geoderma Regional, 2022

Vegetation cover is one of the most critical factors in soil erosion processes. Notably, olive or... more Vegetation cover is one of the most critical factors in soil erosion processes. Notably, olive orchards have been cultivated in shallow and sloping soils, with low vegetation cover and increasing the soil exposure to raindrop impact. In the tropics, considerable care is required to adequately use cover crops to control water erosion in new frontiers of olive plantations. In this context, we proposed a new technique to correlate the cover-management factor (C-factor) with vegetation indices from images obtained by unmanned aerial vehicle (UAV) and evaluate soil erosion losses under natural rainfall. We studied the relationship between different cover indices (vegetation cover index, non-photosynthetic vegetation cover index, and total cover index) with the C-factor of the USLE/RUSLE. This study was carried out in standard erosion plots with different vegetation cover systems associated with olive cultivation. UAV images were classified by Random Forest algorithm, and soil losses were quantified by sampling after each erosive rainfall event. Results showed a good performance in UAV image classification: average user's accuracy of 94% for vegetation class and 91% for bare soil. The Total cover index presented a better performance in predicting soil loss and determining the C-factor for exponential model (R2 = 0.87). UAV-based imaging demonstrates promising potential in monitoring vegetation cover crops and their impact on soil erosion. Total cover index performs better in estimating C-factor and predicting soil loss. However, the result of response surface analysis suggested that the association between total cover index and rainfall erosivity using second-order model presented the best prediction (R2 = 0.98), positive correlation between rainfall erosivity and C-Factor, and negative correlation between C-factor and total cover index and rainfall erosivity.

Research paper thumbnail of Seasonal behavior of vegetation determined by sensor on an unmanned aerial vehicle

Geographic information systems make it possible to obtain fi ne scale maps for environmental moni... more Geographic information systems make it possible to obtain fi ne scale maps for environmental monitoring from airborne sensors on aerial platforms, such as unmanned aerial vehicles (UAVs), which offer products with low costs and high spacetime resolution. The present study assessed the performance of an UAV in the evaluation of the seasonal behavior of fi ve vegetation coverages: Coffea spp., Eucalyptus spp., Pinus spp. and two forest remnants. For this, vegetation indices (Excess Green and Excess Red minus Green), meteorological data and moisture of surface soils were used. In addition, Sentinel-2 satellite images were used to validate these results. The highest correlations with soil moisture were found in coffee and Forest Remnant 1. The Coffea spp. had the indices with the highest correlation to the studied soil properties. However, the UAV images also provided relevant results for understanding the dynamics of forest remnants. The Excess Green index (p = 0.96) had the highest correlation coeffi cients for Coffea spp., while the Excess Red minus Green index was the best index for forest remnants (p = 0.75). The results confi rmed that low-cost UAVs have the potential to be used as a support tool for phenological studies and can also validate satellite-derived data.

Research paper thumbnail of Soil quality assessment using erosion-sensitive indices and fuzzy membership under different cropping systems on a Ferralsol in Brazil

Soil quality assessment using erosion-sensitive indices and fuzzy membership under different cropping systems on a Ferralsol in Brazil

Geoderma Regional, 2021

The objective of this study was to evaluate soil quality under different cropping systems through... more The objective of this study was to evaluate soil quality under different cropping systems through two erosion-sensitive indexing methodologies applying fuzzy membership functions to a minimum data set (MDS) of soil properties. The experiment was conducted in a Ferralsol, in annual growing cycles from 2007 to 2014. The evaluated cropping systems included individual and intercropped treatments using: sunn hemp (Crotalaria juncea L.), pearl millet (Pennisetum glaucum L.), jack bean (Canavalia ensiformis L.), pigeon pea (Cajanus cajan L. Huth), and maize (Zea mays L.). Sampling in an adjacent area under native forest was also performed as a reference ecosystem. Soil properties such as bulk density, micro-, macro- and total porosity, aggregates stability, laboratorial soil fertility properties, and soil organic matter content were selected as MDS of physical and chemical properties, being used to compute two soil quality indices: 1) Integrated Quality Index (IQI), and 2) Nemoro Quality Index (NQI). Soil quality results showed the lowest values of soil and water losses corresponded to the largest soil quality indices evidencing that the usage of water-erosion-sensitive indices can be useful for the prediction of soil quality status. The selected MDS of soil properties were adequate indicators of soil quality as reduced water erosion was associated with large soil quality indices, e.g. negative correlation between soil macroporosity and soil erosion processes. The fuzzy methodology was effective in predicting soil quality using a MDS of soil property indicators, which can benefit various stakeholders in their decision-making process to ensure continuing and sustainable crop production.

Research paper thumbnail of High-resolution monitoring of diffuse (sheet or interrill) erosion using structure-from-motion

High-resolution monitoring of diffuse (sheet or interrill) erosion using structure-from-motion

Geoderma, 2020

Sheet erosion is common on agricultural lands, and understanding the dynamics of the erosive proc... more Sheet erosion is common on agricultural lands, and understanding the dynamics of the erosive process as well as the quantification of soil loss is important for both soil scientists and managers. However, measuring rates of soil loss from sheet erosion has proved difficult due to requiring the detection of relatively small surface changes over extended areas. Consequently, such measurements have relied on the use of erosion plots, which have limited spatial coverage and have high operating costs. For measuring the larger erosion rates characteristic of rill and gully erosion, structure-from-motion (SfM) photogrammetry has been demonstrated to be a valuable tool. Here, we demonstrate the first direct validation of UAV-SfM measurements of sheet erosion using sediment collection data collected from erosion plots.
Three erosion plots (12 m × 4 m) located at Lavras, Brazil, with bare soil exposed to natural rainfall from which event sediment and runoff was monitored, were mapped during two hydrological years (2016 and 2017), using a UAV equipped with a RGB camera. DEMs of difference (DoD) were calculated to detect spatial changes in the soil surface topography over time and to quantify the volumes of sediments lost or gained. Precision maps were generated to enable precision estimates for both DEMs to be propagated into the DoD as spatially variable vertical uncertainties.
The point clouds generated from SfM gave mean errors of ~2.4 mm horizontally (xy) and ~1.9 mm vertically (z) on control and independent check points, and the level of detection (LoD) along the plots ranged from 1.4 mm to 7.4 mm. The soil loss values obtained by SfM were significantly (p < 0.001) correlated (r2 = 95.55%) with those derived from the sediment collection. These results open up the possibility to use SfM for erosion studies where channelized erosion is not the principal mechanism, offering a cost-effective method for gaining new insights into sheet, and interrill, erosion processes.

Research paper thumbnail of MULTISPECTRAL AND THERMOGRAPHIC IMAGES FOR MONITORING THE WATER CONDITIONS OF SUGARCANE

Among the main production chains in the state of São Paulo, sugarcane stands out, w... more Among the main production chains in the state of São Paulo, sugarcane stands out, with the cultivation of extensive areas and economic importance for sugar, ethanol and bioenergy production. One of the techniques that permeate sugarcane crops in large areas and can contribute to higher productivity and production quality is irrigation. Therefore, it is essential to know the different irrigation management that can be applied in extensive areas aimed at the efficient use of water and considering the water status and plant development. In this sense, remote sensing brought benefits for sugarcane cultivation with studies of biomass estimation, plant growth and vigor, but few studies have shown results on monitoringthe water status of the plant aiming at irrigation management possibilities considering the water deficit of plants. In this context, this study evaluated alternatives for monitoring the water status of sugarcane with the use of thermographic and multispectral cameras embedded in an unmanned aerial vehicle. The evaluations allowed recording differences between irrigated treatments compared to treatments without irrigation in the two cameras used. Thermographic images can evaluate the water status of sugarcane plants quickly, nondestructively and efficiently.

Research paper thumbnail of Sediment source and volume of soil erosion in a gully system using UAV photogrammetry

Gully erosion is a severe way of land degradation. Gullies threaten the sustainability of agro-ec... more Gully erosion is a severe way of land degradation. Gullies threaten the sustainability of agro-ecosystems, causing quantitative and qualitative reduction of groundwater, farmland productivity, and waterways sedimentation. Since the gully development on the surface begins with water flow and sheet erosion, accurate monitoring of the erosive processes in a gully system and its quantification is key for the development of effective strategies to control soil erosion in gullies. Here, we demonstrate the first use of unmanned aerial vehicle (UAV) and structure-from-motion/multiview-stereo photogrammetry to evaluate the relative contribution of the different types of erosion (sheet, rill, and gully sidewall) in the gully development. A gully located at Lavras, Brazil, was surveyed using a UAV equipped with a RGB camera. The Precision Maps (PM) variant of the Multiscale Model to Model Cloud Compare (M3C2) algorithm was used to calculate spatial changes in the soil surface topography and to quantify the volumes of sediments lost and gained in the gully system. The point clouds showed root mean square errors of order ~ 3 mm on xyz on check points. The spatial variation of precision along the gully ranged from 0.006 to 0.276 m, considering the M3C2-PM uncertainty values. The results revealed that the main source of sediment in the gully studied was due to the mass movement processes. Rills and laminar erosions contributed 8 and 3 %, respectively, to the total sediment yield, while the mass movements corresponded with most of the sediment generation in the gully. Of the total sediment produced in the system, only 24 % was stored in the gully, indicating its high activity and instability. For the first time, the sediment sources of a gully were quantified remotely and with millimetric precision. The UAV photogrammetry generated high-resolution measurements, allowing evaluation of the contribution of sheet erosion in the generation of sediment of the gully. This opens up new possibilities in the studies involving the dynamics of gullies, since the understanding of the spatial and temporal behaviour of the erosive processes are important in the development of control strategies and monitoring of the evolution of a gullies complex.

Research paper thumbnail of Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera

The permanent monitoring of vegetation cover is important to guarantee a sustainable management o... more The permanent monitoring of vegetation cover is important to guarantee a sustainable management of agricultural activities, with a relevant role in the reduction of water erosion. This monitoring can be carried out through different indicators such as vegetation cover indices. In this study, the vegetation cover index was obtained using uncalibrated RGB images generated from a digital photographic camera on an unmanned aerial vehicle (UAV). In addition, a comparative study with 11 vegetation indices was carried out. The vegetation indices CIVE and EXG presented a better performance and the index WI presented the worst performance in the vegetation classification during the cycles of jack bean and millet, according to the overall accuracy and Kappa coefficient. Vegetation indices were effective tools in obtaining soil cover index when compared to the standard Stocking method, except for the index WI. Architecture and cycle of millet and jack bean influenced the behavior of the studied vegetation indices. Vegetation indices generated from RGB images obtained by UAV were more practical and efficient, allowing a more frequent monitoring and in a wider area during the crop cycle.

Research paper thumbnail of Assessing Water Erosion Processes in Degraded Area Using Unmanned Aerial Vehicle Imagery

The use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) techniques can contrib... more The use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) techniques can contribute to increase the accessibility, accuracy, and resolution of Digital Elevation Models (DEMs) used for soil erosion monitoring. This study aimed to evaluate the use of four DEMs obtained over a year to monitor erosion processes in an erosion-degraded area, with occurrence of rill and gully erosions, and its correlation with accumulated rainfall during the studied period. The DEMs of Geomorphic Change Detection (GCD) of horizontal and vertical resolutions of 0.10 and 0.06 m were obtained. It was possible to detect events of erosion and deposition volumes of the order of 2 m 3 , with a volumetric error of ~50 %, in rills and gullies in the initial stage denominated R and GS-I, respectively. Events of the order of 100 m 3 , with a volumetric error around 14 % were found for advanced gullies, a segment denominated GS-II. In the three studied erosion situations, the deposition volume increased with the accumulated rainfall. The segments R and GS-I presented an inverse relationship between erosion volume and accumulated rainfall during the studied period. This behaviour can be explained by the dynamics of the deposition and erosion volumes during the erosion process. In the GS-II segment, erosion and deposition volumes were proportional and a direct relation with the cumulative rainfall over the studied period and a low percentage of volumetric error were found.

Research paper thumbnail of Water erosion post-planting in eucalyptus forests in the Parana river basin, eastern Mato Grosso do Sul, Brazil

Revista Brasileira de Ciência do Solo, 2014

In tropical regions, the damage caused to soil by rainwater, i.e., soil erosion, is the most sign... more In tropical regions, the damage caused to soil by rainwater, i.e., soil erosion, is the most significant form of soil degradation. In Brazil, eucalyptus plantations are mainly located in ecosystems sensitive to anthropogenic disturbances for reasons such as the occurrence of plantations in soils with low clay contents, soils with low natural fertility, and most plantations being established on areas previously occupied by agriculture or by degraded pastures. Thus, the need arises for understanding the processes that control water erosion and their relationship to soil and water losses in forest systems. The aim of this study was to calculate the values of rainfall erosivity (R factor - EI30), to estimate tolerance to soil loss (T) for the representative soil classes in the areas under study, to evaluate soil and water losses by water erosion, and, through the use of principal component analysis (PCA), to verify the influence of soil physical attributes and soil organic mater (SOM) on water erosion in the post-planting stage, with minimum tillage. Treatments consisted of different systems of waste management and planting arrangements (contour and downslope) in two distinct biomes, cerrado (tropical savanna) and forest, and bare soil. The soils were classified as Latossolo Vermelho distrófico típico (Oxisol), upper-middle texture in forest phase (LVd1), and Latossolo Vermelho distrófico típico (Oxisol), medium-low texture in cerrado phase (LVd2). The study was conducted in experimental areas of eucalyptus plantations located in Três Lagoas, in the Parana River basin, eastern Mato Grosso do Sul, Brazil. The annual erosivity index obtained was 6,792.7 MJ mm ha-1 h-1 yr-1. The T values ranged from 9.0 to 11.0 Mg ha-1 yr-1 for LVd2 and LVd1, respectively. Soil losses for eucalyptus plantation were well below the tolerance limits for the soil classes studied, at 0 to 0.505 Mg ha-1 in LVd1, and 0 to 0.853 Mg ha-1 no LVd2. Among the forest systems, eucalyptus under contour planting with maintenance of the residue was closest to native vegetation in relation to soil and water losses. The PCA proved to be effective in discriminating management systems based on the interaction between physical properties and soil organic matter and their relationship to water erosion, enabling clear visualization of the influence of soil management systems on these properties and their relationship to soil and water losses.

Research paper thumbnail of Spatialization of soil quality index in the Sub-Basin of Posses, Extrema, Minas Gerais

Revista Brasileira de Engenharia Agrícola e Ambiental, 2016

This study aimed to determine and spatialize the soil quality index (SQI), in relation to chemica... more This study aimed to determine and spatialize the soil quality index (SQI), in relation to chemical and physical attributes, and evaluate its use in the payment for environmental services in the Sub-Basin of Posses, Extrema-MG, Brazil, which represents the Atlantic Forest Biome. SQI values were influenced by both the replacement of native forests by stands of eucalyptus and by pastures and annual crops, reflecting in the reduction of soil quality in the sampled layer in the evaluated systems. The spatialization of SQI showed values ranging from 0.40 to 0.80, with some specific areas with high values and others with values above 1.00 (native forest). The reforestation with eucalyptus conditioned most of the soils with low chemical and physical deterioration, due to accumulation of litter. The lowest SQI values are associated with pastures. SQI adjusted to the exponential model, which allowed the use of ordinary Kriging. The SQI has a great potential of use in the payment to farmers wh...

Research paper thumbnail of Use of Air-Based Photogrammetry for Soil Erosion Assessment

Water erosion affects all types of soils around the world at different intensities. However, in t... more Water erosion affects all types of soils around the world at different intensities. However, in the tropics, water-based processes are the most important of the erosion processes and have received much attention in the last decades. Understanding and quantifying the processes involved in each type of water erosion (sheet, rill and gully erosion) is key to developing and managing soil conservation and erosion mitigation strategies. This study aims to investigate the efficiency of unmanned aerial vehicle (UAV) structure-from-motion (SfM) photogrammetry for soil erosion assessment, as well as to address some gaps in our understanding of the evolution of erosive processes. For the first time, we used a UAV-SfM technique to evaluate the relative contribution of different types of erosion (sheet, rill and gully sidewall) in gully development. This was possible due to the millimetric level of precision of the point clouds produced, which allowed us to evaluate the contribution of laminar erosion as a new component to gullies studies. As a result, it was possible to quantify sediment volumes stored in the channels and lost from the gully system, as well as to determine the main sediment sources. The UAV-SfM proved to be effective for detailed gully monitoring, with the results suggesting that the main source of sediments in the gully was mass movement, followed by rills and sheet erosion. Our findings support the use of UAV-based photogrammetry as a sufficiently precise tool for detecting soil surface change, which can be used to assess water erosion in its various forms. In addition, UAV-SfM has proven to be a very useful technique for monitoring soil erosion over time, especially in hard-to-reach areas.

Research paper thumbnail of Predicting Runoff Risks by Digital Soil Mapping

Digital soil mapping (DSM) permits continuous mapping soil types and properties through raster fo... more Digital soil mapping (DSM) permits continuous mapping soil types and properties through raster formats considering variation within soil class, in contrast to the traditional mapping that only considers spatial variation of soils at the boundaries of delineated polygons. The objective of this study was to compare the performance of SoLIM (Soil Land Inference Model) for two sets of environmental variables on digital mapping of saturated hydraulic conductivity and solum depth (A + B horizons) and to apply the best model on runoff risk evaluation. The study was done in the Posses watershed, MG, Brazil, and SoLIM was applied for the following sets of co-variables: 1) terrain attributes (AT): slope, plan curvature, elevation and topographic wetness index. 2) Geomorphons and terrain attributes (GEOM): slope, plan curvature, elevation and topographic wetness index combined with geomorphons. The most precise methodology was applied to predict runoff areas risk through the Wetness Index based on contribution area, solum depth, and saturated hydraulic conductivity. GEOM was the best set of co-variables for both properties, so this was the DSM model used to predict the runoff risk. The runoff risk showed that the critical months are from November to March. The new way to classify the landscape to use on DSM was demonstrated to be an efficient tool with which to model process that occurs on watersheds and can be used to forecast the runoff risk.

Research paper thumbnail of INDICATOR INDEXING METHODS IN ASSESSMENT OF SOIL QUALITY IN RELATION TO WATER EROSION

Assessing the quality of agricultural soils is important for defining and adopting management pra... more Assessing the quality of agricultural soils is important for defining and adopting management practices that ensure socioeconomic and environmental sustainability. The methods for indexation of quality indicators called the Integrated Quality Index (IQI) and the Nemoro Quality Index (NQI) were used in this study to evaluate soil quality in experimental plots planted to eucalyptus. The selection of these indicators was made based on nine soil quality indicators: geometric mean diameter, water permeability, organic matter, macro- and microporosity, total porosity, bulk density, penetration resistance, and flocculation index, which are related to water erosion. Treatments consisted of eucalyptus planted on level land, with and without maintenance of residues on the soil surface, planted on a downslope, and planted on bare soil in two distinct biomes, whose native vegetation are Cerrado (Brazilian tropical savanna) and Forest. The soil quality indices (SQI) were highly correlated with erosion. Among the management systems, Eucalyptus with maintenance of the residues had higher values in both indices, highlighting the importance of plant cover and organic matter for soil and water conservation in forest systems. The SQI had a high inverse correlation coefficient with soil and water losses. Places with the highest rates of water erosion also had the lowest IQI and NQI values. Thus, the indices tested allowed efficient evaluation of the effects of the management practices adopted on soil quality in relation to water erosion.

Research paper thumbnail of UAV-Based Soil Water Erosion Monitoring: Current Status and Trends

Drones, 2025

Soil erosion affects land productivity, water quality, and ecosystem resilience. Traditional moni... more Soil erosion affects land productivity, water quality, and ecosystem resilience. Traditional monitoring methods are often time-consuming, labor-intensive, and resource-demanding, while unmanned aerial vehicles (UAVs) provide high-resolution, near-real-time data, improving accuracy. This study conducts a bibliometric analysis of UAV-based soil erosion research to explore trends, technologies, and challenges. A systematic review of Web of Science and Scopus articles identified 473 relevant studies after filtering for terms that refer to types of soil erosion. Analysis using R's bibliometrix package shows research is concentrated in Asia, Europe, and the Americas, with 304 publications following a surge. Multi-rotor UAVs with RGB sensors are the most common. Gully erosion is the most studied form of the issue, followed by landslides, rills, and interrill and piping erosion. Significant gaps remain in rill and interrill erosion research. The integration of UAVs with satellite data, laser surveys, and soil properties is limited but crucial. While challenges such as data accuracy and integration persist, UAVs offer cost-effective, near-real-time monitoring capabilities, enabling rapid responses to erosion changes. Future work should focus on multi-source data fusion to enhance conservation strategies.

Research paper thumbnail of Integrating Proximal and Remote Sensing with Machine Learning for Pasture Biomass Estimation

This study tackles the challenge of accurately estimating pasture biomass by integrating proximal... more This study tackles the challenge of accurately estimating pasture biomass by integrating proximal sensing, remote sensing, and machine learning techniques. Field measurements of vegetation height collected using the PaddockTrac ultrasonic sensor were combined with vegetation indices (e.g., NDVI, MSAVI2) derived from Landsat 7 and Sentinel-2 satellite data. We applied the Boruta algorithm for feature selection to identify influential biophysical predictors and evaluated four machine learning models-Linear Regression, Decision Tree, Random Forest, and XGBoost-for biomass prediction. XGBoost consistently performed the best, achieving an R 2 of 0.86, an MAE of 414 kg ha-1 , and an RMSE of 538 kg ha-1 using Landsat 7 data across multiple years. Sentinel-2's red-edge indices did not substantially improve predictions, suggesting a limited benefit from finer spectral resolutions in this homogenous pasture context. Nonetheless, these indices may offer value in more complex vegetation scenarios. The findings emphasize the effectiveness of combining detailed ground-based measurements with advanced machine learning and remote sensing data, providing a scalable and accurate approach to biomass estimation. This integrated framework provides practical insights for precision agriculture and optimized pasture management, significantly advancing efficient and sustainable rangeland monitoring.

Research paper thumbnail of The Loss of Soil Parent Material: Detecting and Measuring the Erosion of Saprolite

Soil parent material is a fundamental natural resource for the generation of new soils. Through w... more Soil parent material is a fundamental natural resource for the generation of new soils. Through weathering processes, soil parent materials provide many of the basic building blocks for soils and have a significant bearing on the physico-chemical makeup of the soil profile. Parent materials are critical for governing the stock, quality, and functionality of the soil they form. Most research on soil parent materials to date has aimed to establish and measure the processes by which soil is generated from them. Comparatively little work has been performed to assess the rates at which soil parent materials erode if they are exposed at the land surface. This is despite the threat that the erosion of soil parent materials poses to the process of soil formation and the loss of the essential ecosystem services those soils would have provided. A salient but unanswered question is whether the erosion of soil parent materials, when exposed at the land surface, outpaces the rates at which soils form from them. This study represents one of the first to detect and measure the loss of soil parent material. We applied Uncrewed Aerial Vehicle Structure-From-Motion (UAV-SfM) photogrammetry to detect, map, and quantify the erosion rates of an exposed saprolitic (i.e., weathered bedrock) surface on an agricultural hillslope in Brazil. We then utilized a global inventory of soil formation to compare these erosion rates with the rates at which soils form in equivalent lithologies and climatic contexts. We found that the measured saprolite erosion rates were between 14 and 3766 times faster than those of soil formation in similar climatic and lithological conditions. While these findings demonstrate that saprolite erosion can inhibit soil formation, our observations of above-ground vegetation on the exposed saprolitic surface suggests that weathered bedrock has the potential to sustain some biomass production even in the absence of traditional soils. This opens up a new avenue of enquiry within soil science: to what extent can saprolite and, by extension, soil parent materials deliver soil ecosystem services?

Research paper thumbnail of Does soil thinning change soil erodibility? An exploration of long-term erosion feedback systems

Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This im... more Soil erosion rates on arable land frequently exceed the pace at which new soil is formed. This imbalance leads to soil thinning (i.e. truncation), whereby subsoil horizons and their underlying parent material become progressively closer to the land surface. As soil erosion is a selective process and subsurface horizons often have contrasting properties to the original topsoil, truncation-induced changes to soil properties might affect erosion rates and runoff formation through a soil erosion feedback system. However, the potential interactions between soil erosion and soil truncation are poorly understood due to a lack of empirical data and the neglection of long-term erodibility dynamics in erosion simulation models. Here, we present a novel modelbased exploration of the soil erosion feedback system over a period of 500 years using measured soil properties from a diversified database of 265 agricultural soil profiles in the UK. For this, we adapted the Modified Morgan-Morgan-Finney model (MMMF) to perform a modelling experiment in which topography, climate, land cover, and crop management parameters were held constant throughout the simulation period. As selective soil erosion processes removed topsoil layers, the model gradually mixed subsurface soil horizons into a 0.2 m plough layer and updated soil properties using mass-balance mixing models. Further, we estimated the uncertainty in model simulations with a forward error assessment. We found that modelled erosion rates in 99 % of the soil profiles were sensitive to truncation-induced changes in soil properties. The soil losses in all except one of the truncation-sensitive profiles displayed a decelerating trend, which depicted an exponential decay in erosion rates over the simulation period. This was largely explained by decreasing silt contents in the soil surface due to selective removal of this more erodible particle size fraction and the presence of clayey or sandy substrata. Moreover, the soil profiles displayed an increased residual stone cover, which armoured the land surface and reduced soil detachment. Contrastingly, the soils with siltier subsurface horizons continuously replenished the plough layer with readily erodible material, which prevented the decline of soil loss rates over time. Although our results are limited by the edaphoclimatic conditions represented in our data, as by our modelling assumptions, we have demonstrated how modelled soil losses can be sensitive to erosion-induced changes in soil properties. These findings are likely to affect how we calculate soil lifespans and make long-term projections of land degradation.

Research paper thumbnail of Improving RUSLE predictions through UAV-based soil cover management factor (C) assessments: A novel approach for enhanced erosion analysis in sugarcane fields

Improving RUSLE predictions through UAV-based soil cover management factor (C) assessments: A novel approach for enhanced erosion analysis in sugarcane fields

Journal of Hydrology, 2023

The Universal Soil Loss Equation (USLE) and its derivatives express the combined effects of crop ... more The Universal Soil Loss Equation (USLE) and its derivatives express the combined effects of crop cover and rainfall patterns by the cover and management factor (C). Thus, the C-factor links the combined effect of soil surface roughness, vegetation, biomass cover, and rainfall patterns on soil erosion. This evaluation should be at each phenological stage. Due to the significant time and effort needed to access this factor for a crop, simplified methods are often used, disregarding the expected intra-annual variability and consequently increasing the uncertainty for soil loss modeling. In this scenario, we proposed a framework to collect input data at a fine-scale to estimate the C-factor by the original approach. For this, we collected data with a low-cost UAV at the middle of each phenological stage of sugarcane: sprouting, tillering, elongation, and maturation. We used orthomosaics, three vegetation indices (ExRmG, MGRVI, ViGREEN), digital surface models (DSM), and digital terrain model (DTM) to determine the canopy cover (CC), surface cover (SC), and soil roughness (SR), accessing the soil loss ratio (SLR) per phenological stage. Late on, we estimate the C-factor weighting the SLR by the rainfall erosivity. Our annual C-factor aligns with the most values applied to sugarcane studies and ranged from 0.0241 to 0.2938. Our results pointed out that using the proposed methods can access suitable annual C-factor for sugarcane areas. Furthermore, we highlighted the ViGREEN because it presented a significant performance in orthomosaics classification and has a potential already reported in other studies on C-factor at different scales.

Research paper thumbnail of How suitable are vegetation indices for estimating the (R)USLE C-factor for croplands? A case study from Southeast Brazil

ISPRS Open Journal of Photogrammetry and Remote Sensing, 2023

The cover and management factor (C-factor) of the Universal Soil Loss Equation (USLE) represents ... more The cover and management factor (C-factor) of the Universal Soil Loss Equation (USLE) represents the effects of crop cover, weighted by rainfall pattern, on predicted soil erosion rates. This requires an estimate of seasonal rainfall erosivity and soil protection afforded by the crop at different phenological stages, expressed by a soil loss ratio (SLR). However, soil erosion modelers often rely on vegetation-index-based regressions to directly estimate the cover and management factor (C-factor) of the USLE from satellite images. Since this approach is based on a single or very few images, it does not characterize the seasonality of the crop cover or reflect the seasonality of the rainfall erosivity. Here, we evaluated five vegetation indices (NDVI, NDRE, SFDVI, ViGREEN, and MGRVI) in predicting SLRs and the C-factor for a sugarcane plot in Southeast Brazil. We used Sentinel-2 images and orthomosaics obtained by UAV surveys performed at the middle of each phenological stage. We compared the estimates of the C-factor based on the SLRs and rainfall erosivity against direct regressions from the literature. Our results confirmed the expected poor correlation between the C-factor and the vegetation indices. On the other hand, using the proposed vegetation indices proved to be a reliable alternative to predict the SLR in sugarcane areas, especially the NDVI, the NDRE, and MGRVI. In particular, the MGRVI accurately predicted the SLR and classified the UAV-derived orthomosaics.

Research paper thumbnail of Optical and portable equipment for characterizing soil roughness

Knowledge of surface roughness with the consequent presence of crust in the soil is important inf... more Knowledge of surface roughness with the consequent presence of crust in the soil is important information for the rational management of environmental resources. Soil surface roughness can be determined by contact and noncontact methods. Contact methods have lower values and precision than noncontact methods. Therefore, the objective of this study was to develop low-cost, portable and robust optical equipment to characterize the roughness and presence of crust in the soil through an illumination system with a line laser and monocular vision. The mean roughness was calculated by the difference in height between a point and its neighbours and the presence of crust was determined by a semivariogram. The developed equipment was used in different experimental areas: an eroded area and a compost barn. For the validation of the results, the surface roughness of the same areas analysed by the equipment was also analysed by existing techniques: for the area with erosion, a noncontact technique, i.e., structure from motion (SfM), and for the compost barn, a contact technique, i.e., a pin meter. From the results, it was found that the optical equipment developed to characterize the soil surface roughness and the presence of crust in the soil proved to be valid and provided reliable results.

Research paper thumbnail of UAV-based vegetation monitoring for assessing the impact of soil loss in olive orchards in Brazil

UAV-based vegetation monitoring for assessing the impact of soil loss in olive orchards in Brazil

Geoderma Regional, 2022

Vegetation cover is one of the most critical factors in soil erosion processes. Notably, olive or... more Vegetation cover is one of the most critical factors in soil erosion processes. Notably, olive orchards have been cultivated in shallow and sloping soils, with low vegetation cover and increasing the soil exposure to raindrop impact. In the tropics, considerable care is required to adequately use cover crops to control water erosion in new frontiers of olive plantations. In this context, we proposed a new technique to correlate the cover-management factor (C-factor) with vegetation indices from images obtained by unmanned aerial vehicle (UAV) and evaluate soil erosion losses under natural rainfall. We studied the relationship between different cover indices (vegetation cover index, non-photosynthetic vegetation cover index, and total cover index) with the C-factor of the USLE/RUSLE. This study was carried out in standard erosion plots with different vegetation cover systems associated with olive cultivation. UAV images were classified by Random Forest algorithm, and soil losses were quantified by sampling after each erosive rainfall event. Results showed a good performance in UAV image classification: average user's accuracy of 94% for vegetation class and 91% for bare soil. The Total cover index presented a better performance in predicting soil loss and determining the C-factor for exponential model (R2 = 0.87). UAV-based imaging demonstrates promising potential in monitoring vegetation cover crops and their impact on soil erosion. Total cover index performs better in estimating C-factor and predicting soil loss. However, the result of response surface analysis suggested that the association between total cover index and rainfall erosivity using second-order model presented the best prediction (R2 = 0.98), positive correlation between rainfall erosivity and C-Factor, and negative correlation between C-factor and total cover index and rainfall erosivity.

Research paper thumbnail of Seasonal behavior of vegetation determined by sensor on an unmanned aerial vehicle

Geographic information systems make it possible to obtain fi ne scale maps for environmental moni... more Geographic information systems make it possible to obtain fi ne scale maps for environmental monitoring from airborne sensors on aerial platforms, such as unmanned aerial vehicles (UAVs), which offer products with low costs and high spacetime resolution. The present study assessed the performance of an UAV in the evaluation of the seasonal behavior of fi ve vegetation coverages: Coffea spp., Eucalyptus spp., Pinus spp. and two forest remnants. For this, vegetation indices (Excess Green and Excess Red minus Green), meteorological data and moisture of surface soils were used. In addition, Sentinel-2 satellite images were used to validate these results. The highest correlations with soil moisture were found in coffee and Forest Remnant 1. The Coffea spp. had the indices with the highest correlation to the studied soil properties. However, the UAV images also provided relevant results for understanding the dynamics of forest remnants. The Excess Green index (p = 0.96) had the highest correlation coeffi cients for Coffea spp., while the Excess Red minus Green index was the best index for forest remnants (p = 0.75). The results confi rmed that low-cost UAVs have the potential to be used as a support tool for phenological studies and can also validate satellite-derived data.

Research paper thumbnail of Soil quality assessment using erosion-sensitive indices and fuzzy membership under different cropping systems on a Ferralsol in Brazil

Soil quality assessment using erosion-sensitive indices and fuzzy membership under different cropping systems on a Ferralsol in Brazil

Geoderma Regional, 2021

The objective of this study was to evaluate soil quality under different cropping systems through... more The objective of this study was to evaluate soil quality under different cropping systems through two erosion-sensitive indexing methodologies applying fuzzy membership functions to a minimum data set (MDS) of soil properties. The experiment was conducted in a Ferralsol, in annual growing cycles from 2007 to 2014. The evaluated cropping systems included individual and intercropped treatments using: sunn hemp (Crotalaria juncea L.), pearl millet (Pennisetum glaucum L.), jack bean (Canavalia ensiformis L.), pigeon pea (Cajanus cajan L. Huth), and maize (Zea mays L.). Sampling in an adjacent area under native forest was also performed as a reference ecosystem. Soil properties such as bulk density, micro-, macro- and total porosity, aggregates stability, laboratorial soil fertility properties, and soil organic matter content were selected as MDS of physical and chemical properties, being used to compute two soil quality indices: 1) Integrated Quality Index (IQI), and 2) Nemoro Quality Index (NQI). Soil quality results showed the lowest values of soil and water losses corresponded to the largest soil quality indices evidencing that the usage of water-erosion-sensitive indices can be useful for the prediction of soil quality status. The selected MDS of soil properties were adequate indicators of soil quality as reduced water erosion was associated with large soil quality indices, e.g. negative correlation between soil macroporosity and soil erosion processes. The fuzzy methodology was effective in predicting soil quality using a MDS of soil property indicators, which can benefit various stakeholders in their decision-making process to ensure continuing and sustainable crop production.

Research paper thumbnail of High-resolution monitoring of diffuse (sheet or interrill) erosion using structure-from-motion

High-resolution monitoring of diffuse (sheet or interrill) erosion using structure-from-motion

Geoderma, 2020

Sheet erosion is common on agricultural lands, and understanding the dynamics of the erosive proc... more Sheet erosion is common on agricultural lands, and understanding the dynamics of the erosive process as well as the quantification of soil loss is important for both soil scientists and managers. However, measuring rates of soil loss from sheet erosion has proved difficult due to requiring the detection of relatively small surface changes over extended areas. Consequently, such measurements have relied on the use of erosion plots, which have limited spatial coverage and have high operating costs. For measuring the larger erosion rates characteristic of rill and gully erosion, structure-from-motion (SfM) photogrammetry has been demonstrated to be a valuable tool. Here, we demonstrate the first direct validation of UAV-SfM measurements of sheet erosion using sediment collection data collected from erosion plots.
Three erosion plots (12 m × 4 m) located at Lavras, Brazil, with bare soil exposed to natural rainfall from which event sediment and runoff was monitored, were mapped during two hydrological years (2016 and 2017), using a UAV equipped with a RGB camera. DEMs of difference (DoD) were calculated to detect spatial changes in the soil surface topography over time and to quantify the volumes of sediments lost or gained. Precision maps were generated to enable precision estimates for both DEMs to be propagated into the DoD as spatially variable vertical uncertainties.
The point clouds generated from SfM gave mean errors of ~2.4 mm horizontally (xy) and ~1.9 mm vertically (z) on control and independent check points, and the level of detection (LoD) along the plots ranged from 1.4 mm to 7.4 mm. The soil loss values obtained by SfM were significantly (p < 0.001) correlated (r2 = 95.55%) with those derived from the sediment collection. These results open up the possibility to use SfM for erosion studies where channelized erosion is not the principal mechanism, offering a cost-effective method for gaining new insights into sheet, and interrill, erosion processes.

Research paper thumbnail of MULTISPECTRAL AND THERMOGRAPHIC IMAGES FOR MONITORING THE WATER CONDITIONS OF SUGARCANE

Among the main production chains in the state of São Paulo, sugarcane stands out, w... more Among the main production chains in the state of São Paulo, sugarcane stands out, with the cultivation of extensive areas and economic importance for sugar, ethanol and bioenergy production. One of the techniques that permeate sugarcane crops in large areas and can contribute to higher productivity and production quality is irrigation. Therefore, it is essential to know the different irrigation management that can be applied in extensive areas aimed at the efficient use of water and considering the water status and plant development. In this sense, remote sensing brought benefits for sugarcane cultivation with studies of biomass estimation, plant growth and vigor, but few studies have shown results on monitoringthe water status of the plant aiming at irrigation management possibilities considering the water deficit of plants. In this context, this study evaluated alternatives for monitoring the water status of sugarcane with the use of thermographic and multispectral cameras embedded in an unmanned aerial vehicle. The evaluations allowed recording differences between irrigated treatments compared to treatments without irrigation in the two cameras used. Thermographic images can evaluate the water status of sugarcane plants quickly, nondestructively and efficiently.

Research paper thumbnail of Sediment source and volume of soil erosion in a gully system using UAV photogrammetry

Gully erosion is a severe way of land degradation. Gullies threaten the sustainability of agro-ec... more Gully erosion is a severe way of land degradation. Gullies threaten the sustainability of agro-ecosystems, causing quantitative and qualitative reduction of groundwater, farmland productivity, and waterways sedimentation. Since the gully development on the surface begins with water flow and sheet erosion, accurate monitoring of the erosive processes in a gully system and its quantification is key for the development of effective strategies to control soil erosion in gullies. Here, we demonstrate the first use of unmanned aerial vehicle (UAV) and structure-from-motion/multiview-stereo photogrammetry to evaluate the relative contribution of the different types of erosion (sheet, rill, and gully sidewall) in the gully development. A gully located at Lavras, Brazil, was surveyed using a UAV equipped with a RGB camera. The Precision Maps (PM) variant of the Multiscale Model to Model Cloud Compare (M3C2) algorithm was used to calculate spatial changes in the soil surface topography and to quantify the volumes of sediments lost and gained in the gully system. The point clouds showed root mean square errors of order ~ 3 mm on xyz on check points. The spatial variation of precision along the gully ranged from 0.006 to 0.276 m, considering the M3C2-PM uncertainty values. The results revealed that the main source of sediment in the gully studied was due to the mass movement processes. Rills and laminar erosions contributed 8 and 3 %, respectively, to the total sediment yield, while the mass movements corresponded with most of the sediment generation in the gully. Of the total sediment produced in the system, only 24 % was stored in the gully, indicating its high activity and instability. For the first time, the sediment sources of a gully were quantified remotely and with millimetric precision. The UAV photogrammetry generated high-resolution measurements, allowing evaluation of the contribution of sheet erosion in the generation of sediment of the gully. This opens up new possibilities in the studies involving the dynamics of gullies, since the understanding of the spatial and temporal behaviour of the erosive processes are important in the development of control strategies and monitoring of the evolution of a gullies complex.

Research paper thumbnail of Determination of vegetation cover index under different soil management systems of cover plants by using an unmanned aerial vehicle with an onboard digital photographic camera

The permanent monitoring of vegetation cover is important to guarantee a sustainable management o... more The permanent monitoring of vegetation cover is important to guarantee a sustainable management of agricultural activities, with a relevant role in the reduction of water erosion. This monitoring can be carried out through different indicators such as vegetation cover indices. In this study, the vegetation cover index was obtained using uncalibrated RGB images generated from a digital photographic camera on an unmanned aerial vehicle (UAV). In addition, a comparative study with 11 vegetation indices was carried out. The vegetation indices CIVE and EXG presented a better performance and the index WI presented the worst performance in the vegetation classification during the cycles of jack bean and millet, according to the overall accuracy and Kappa coefficient. Vegetation indices were effective tools in obtaining soil cover index when compared to the standard Stocking method, except for the index WI. Architecture and cycle of millet and jack bean influenced the behavior of the studied vegetation indices. Vegetation indices generated from RGB images obtained by UAV were more practical and efficient, allowing a more frequent monitoring and in a wider area during the crop cycle.

Research paper thumbnail of Assessing Water Erosion Processes in Degraded Area Using Unmanned Aerial Vehicle Imagery

The use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) techniques can contrib... more The use of Unmanned Aerial Vehicles (UAVs) and Structure from Motion (SfM) techniques can contribute to increase the accessibility, accuracy, and resolution of Digital Elevation Models (DEMs) used for soil erosion monitoring. This study aimed to evaluate the use of four DEMs obtained over a year to monitor erosion processes in an erosion-degraded area, with occurrence of rill and gully erosions, and its correlation with accumulated rainfall during the studied period. The DEMs of Geomorphic Change Detection (GCD) of horizontal and vertical resolutions of 0.10 and 0.06 m were obtained. It was possible to detect events of erosion and deposition volumes of the order of 2 m 3 , with a volumetric error of ~50 %, in rills and gullies in the initial stage denominated R and GS-I, respectively. Events of the order of 100 m 3 , with a volumetric error around 14 % were found for advanced gullies, a segment denominated GS-II. In the three studied erosion situations, the deposition volume increased with the accumulated rainfall. The segments R and GS-I presented an inverse relationship between erosion volume and accumulated rainfall during the studied period. This behaviour can be explained by the dynamics of the deposition and erosion volumes during the erosion process. In the GS-II segment, erosion and deposition volumes were proportional and a direct relation with the cumulative rainfall over the studied period and a low percentage of volumetric error were found.

Research paper thumbnail of Water erosion post-planting in eucalyptus forests in the Parana river basin, eastern Mato Grosso do Sul, Brazil

Revista Brasileira de Ciência do Solo, 2014

In tropical regions, the damage caused to soil by rainwater, i.e., soil erosion, is the most sign... more In tropical regions, the damage caused to soil by rainwater, i.e., soil erosion, is the most significant form of soil degradation. In Brazil, eucalyptus plantations are mainly located in ecosystems sensitive to anthropogenic disturbances for reasons such as the occurrence of plantations in soils with low clay contents, soils with low natural fertility, and most plantations being established on areas previously occupied by agriculture or by degraded pastures. Thus, the need arises for understanding the processes that control water erosion and their relationship to soil and water losses in forest systems. The aim of this study was to calculate the values of rainfall erosivity (R factor - EI30), to estimate tolerance to soil loss (T) for the representative soil classes in the areas under study, to evaluate soil and water losses by water erosion, and, through the use of principal component analysis (PCA), to verify the influence of soil physical attributes and soil organic mater (SOM) on water erosion in the post-planting stage, with minimum tillage. Treatments consisted of different systems of waste management and planting arrangements (contour and downslope) in two distinct biomes, cerrado (tropical savanna) and forest, and bare soil. The soils were classified as Latossolo Vermelho distrófico típico (Oxisol), upper-middle texture in forest phase (LVd1), and Latossolo Vermelho distrófico típico (Oxisol), medium-low texture in cerrado phase (LVd2). The study was conducted in experimental areas of eucalyptus plantations located in Três Lagoas, in the Parana River basin, eastern Mato Grosso do Sul, Brazil. The annual erosivity index obtained was 6,792.7 MJ mm ha-1 h-1 yr-1. The T values ranged from 9.0 to 11.0 Mg ha-1 yr-1 for LVd2 and LVd1, respectively. Soil losses for eucalyptus plantation were well below the tolerance limits for the soil classes studied, at 0 to 0.505 Mg ha-1 in LVd1, and 0 to 0.853 Mg ha-1 no LVd2. Among the forest systems, eucalyptus under contour planting with maintenance of the residue was closest to native vegetation in relation to soil and water losses. The PCA proved to be effective in discriminating management systems based on the interaction between physical properties and soil organic matter and their relationship to water erosion, enabling clear visualization of the influence of soil management systems on these properties and their relationship to soil and water losses.

Research paper thumbnail of Spatialization of soil quality index in the Sub-Basin of Posses, Extrema, Minas Gerais

Revista Brasileira de Engenharia Agrícola e Ambiental, 2016

This study aimed to determine and spatialize the soil quality index (SQI), in relation to chemica... more This study aimed to determine and spatialize the soil quality index (SQI), in relation to chemical and physical attributes, and evaluate its use in the payment for environmental services in the Sub-Basin of Posses, Extrema-MG, Brazil, which represents the Atlantic Forest Biome. SQI values were influenced by both the replacement of native forests by stands of eucalyptus and by pastures and annual crops, reflecting in the reduction of soil quality in the sampled layer in the evaluated systems. The spatialization of SQI showed values ranging from 0.40 to 0.80, with some specific areas with high values and others with values above 1.00 (native forest). The reforestation with eucalyptus conditioned most of the soils with low chemical and physical deterioration, due to accumulation of litter. The lowest SQI values are associated with pastures. SQI adjusted to the exponential model, which allowed the use of ordinary Kriging. The SQI has a great potential of use in the payment to farmers wh...

Research paper thumbnail of Use of Air-Based Photogrammetry for Soil Erosion Assessment

Water erosion affects all types of soils around the world at different intensities. However, in t... more Water erosion affects all types of soils around the world at different intensities. However, in the tropics, water-based processes are the most important of the erosion processes and have received much attention in the last decades. Understanding and quantifying the processes involved in each type of water erosion (sheet, rill and gully erosion) is key to developing and managing soil conservation and erosion mitigation strategies. This study aims to investigate the efficiency of unmanned aerial vehicle (UAV) structure-from-motion (SfM) photogrammetry for soil erosion assessment, as well as to address some gaps in our understanding of the evolution of erosive processes. For the first time, we used a UAV-SfM technique to evaluate the relative contribution of different types of erosion (sheet, rill and gully sidewall) in gully development. This was possible due to the millimetric level of precision of the point clouds produced, which allowed us to evaluate the contribution of laminar erosion as a new component to gullies studies. As a result, it was possible to quantify sediment volumes stored in the channels and lost from the gully system, as well as to determine the main sediment sources. The UAV-SfM proved to be effective for detailed gully monitoring, with the results suggesting that the main source of sediments in the gully was mass movement, followed by rills and sheet erosion. Our findings support the use of UAV-based photogrammetry as a sufficiently precise tool for detecting soil surface change, which can be used to assess water erosion in its various forms. In addition, UAV-SfM has proven to be a very useful technique for monitoring soil erosion over time, especially in hard-to-reach areas.

Research paper thumbnail of Predicting Runoff Risks by Digital Soil Mapping

Digital soil mapping (DSM) permits continuous mapping soil types and properties through raster fo... more Digital soil mapping (DSM) permits continuous mapping soil types and properties through raster formats considering variation within soil class, in contrast to the traditional mapping that only considers spatial variation of soils at the boundaries of delineated polygons. The objective of this study was to compare the performance of SoLIM (Soil Land Inference Model) for two sets of environmental variables on digital mapping of saturated hydraulic conductivity and solum depth (A + B horizons) and to apply the best model on runoff risk evaluation. The study was done in the Posses watershed, MG, Brazil, and SoLIM was applied for the following sets of co-variables: 1) terrain attributes (AT): slope, plan curvature, elevation and topographic wetness index. 2) Geomorphons and terrain attributes (GEOM): slope, plan curvature, elevation and topographic wetness index combined with geomorphons. The most precise methodology was applied to predict runoff areas risk through the Wetness Index based on contribution area, solum depth, and saturated hydraulic conductivity. GEOM was the best set of co-variables for both properties, so this was the DSM model used to predict the runoff risk. The runoff risk showed that the critical months are from November to March. The new way to classify the landscape to use on DSM was demonstrated to be an efficient tool with which to model process that occurs on watersheds and can be used to forecast the runoff risk.

Research paper thumbnail of INDICATOR INDEXING METHODS IN ASSESSMENT OF SOIL QUALITY IN RELATION TO WATER EROSION

Assessing the quality of agricultural soils is important for defining and adopting management pra... more Assessing the quality of agricultural soils is important for defining and adopting management practices that ensure socioeconomic and environmental sustainability. The methods for indexation of quality indicators called the Integrated Quality Index (IQI) and the Nemoro Quality Index (NQI) were used in this study to evaluate soil quality in experimental plots planted to eucalyptus. The selection of these indicators was made based on nine soil quality indicators: geometric mean diameter, water permeability, organic matter, macro- and microporosity, total porosity, bulk density, penetration resistance, and flocculation index, which are related to water erosion. Treatments consisted of eucalyptus planted on level land, with and without maintenance of residues on the soil surface, planted on a downslope, and planted on bare soil in two distinct biomes, whose native vegetation are Cerrado (Brazilian tropical savanna) and Forest. The soil quality indices (SQI) were highly correlated with erosion. Among the management systems, Eucalyptus with maintenance of the residues had higher values in both indices, highlighting the importance of plant cover and organic matter for soil and water conservation in forest systems. The SQI had a high inverse correlation coefficient with soil and water losses. Places with the highest rates of water erosion also had the lowest IQI and NQI values. Thus, the indices tested allowed efficient evaluation of the effects of the management practices adopted on soil quality in relation to water erosion.