Thermal and Multispectral Remote Sensing for the Detection and Analysis of Archaeologically Induced Crop Stress at a UK Site (original) (raw)
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Archaeological Prospection, 2018
Diminishing returns of archaeological crop marks in lowland areas from traditional observer‐directed visible spectrum aerial survey with standard photographic cameras highlights a need to explore alternative approaches to maintain the effectiveness of survey programmes. Developments in low‐cost multispectral remote sensing have in part been driven by the growth of precision agriculture and, whilst contributing to the intensification of land use, these technologies may offer new spectral and temporal capacities for detecting, recording and monitoring historic landscapes. However, there are significant challenges to the deployment of such approaches, not least the costs of data acquisition and uncertainty about the best conditions for data collection. This study assesses the effectiveness of the Parrot Sequoia, a relatively low‐cost multispectral sensor recently developed for agricultural applications, for the detection of crop marks to inform archaeological survey. A series of observations were taken with the sensor mounted on an unmanned aerial vehicle (UAV) at Ravenshall, Fife, Scotland, between April and July 2017. The resulting reflectance maps are compared to red, green and blue (RGB) photographs taken with a Nikon D800E digital camera during seven light aircraft surveys, with the aim of testing the sensors' comparative ability to record crop mark developments over time. The contrast in reflectance between vegetation samples growing over buried archaeological remains and the surrounding field was assessed through separability in regional histogram values across different image band combinations. Separable values indicative of crop marks were found in both the multispectral and RGB results from June 2017 onwards. Several vegetation index (VI) maps, particularly the Simple Ratio (SR) and Normalised Difference Vegetation Index (NDVI), were found to be effective for distinguishing crop marks in the multispectral results. The Sequoia is a cost‐effective sensor offering improved spectral resolution over the RGB photographs, showing potential for subtle crop mark detection across compact study areas.
Remote Sensing, 2022
Monitoring within-field crop variability at fine spatial and temporal resolution can assist farmers in making reliable decisions during their agricultural management; however, it traditionally involves a labor-intensive and time-consuming pointwise manual process. To the best of our knowledge, few studies conducted a comparison of Sentinel-2 with UAV data for crop monitoring in the context of precision agriculture. Therefore, prospects of crop monitoring for characterizing biophysical plant parameters and leaf nitrogen of wheat and barley crops were evaluated from a more practical viewpoint closer to agricultural routines. Multispectral UAV and Sentinel-2 imagery was collected over three dates in the season and compared with reference data collected at 20 sample points for plant leaf nitrogen (N), maximum plant height, mean plant height, leaf area index (LAI), and fresh biomass. Higher correlations of UAV data to the agronomic parameters were found on average than with Sentinel-2 data with a percentage increase of 6.3% for wheat and 22.2% for barley. In this regard, VIs calculated from spectral bands in the visible part performed worse for Sentinel-2 than for the UAV data. In addition, large-scale patterns, formed by the influence of an old riverbed on plant growth, were recognizable even in the Sentinel-2 imagery despite its much lower spatial resolution. Interestingly, also smaller features, such as the tramlines from controlled traffic farming (CTF), had an influence on the Sentinel-2 data and showed a systematic pattern that affected even semivariogram calculation. In conclusion, Sentinel-2 imagery is able to capture the same large-scale pattern as can be derived from the higher detailed UAV imagery; however, it is at the same time influenced by management-driven features such as tramlines, which cannot be accurately georeferenced. In consequence, agronomic parameters were better correlated with UAV than with Sentinel-2 data. Crop growers as well as data providers from remote sensing services may take advantage of this knowledge and we recommend the use of UAV data as it gives additional information about management-driven features. For future perspective, we would advise fusing UAV with Sentinel-2 imagery taken early in the season as it can integrate the effect of agricultural management in the subsequent absence of high spatial resolution data to help improve crop monitoring for the farmer and to reduce costs.
2015
Die Arbeit untersucht das Potential kleiner unbemannter Luftfahrtsysteme (UAS) in Landwirtschaft und Archäologie. Der Begriff UAS beinhaltet dabei: Fluggerät, Antriebsmechanismus, Sensorik, Bodenstation, Kommunikationsmittel zwischen Bodenstation und Fluggerät und weiteres Equipment. Aufgrund ihrer Flexibilität, fanden UAS seit der Jahrtausendwende eine blühende Entwicklung. Um die wachsende Weltbevölkerung zu ernähren, muss die landwirtschaftliche Produktion sensibel und nachhaltig intensiviert werden, um Nahrungssicherheit für alle zu gewährleisten und weitere Boden- und Landdegradation zu vermeiden. Präzisionslandwirtschaft umfasst technologische Verbesserungen hin zur effizienteren und weniger schädlichen landwirtschaftlichen Praxis. Hierbei ist die Verfügung über zeitnahe, leicht zugängliche hoch aufgelöste räumliche Daten eine Voraussetzung für die Nahrungsmittelproduktion. UAS schließen hier die Lücke zwischen Bodendaten und teuren bemannten Luftfahrtsysteme und selteneren Sa...
Monitoring of crop fields using multispectral and thermal imagery from UAV
European Journal of Remote Sensing, 2018
In the following paper, an application of Unmanned Aerial Vehicle (UAV) for agricultural purposes will be presented. The field of interest to be monitored is situated in the Western part of the Czech Republic. It is located in the area of the Vysoké Sedliště village, close to the city of Planá. There are two main crops cultivated in the areacorn and barley. The surrounding territory is mostly covered with grass. The research team carried out numerous unmanned flights with a fixed-wing platform with two different sensorsmultispectral and thermal. Three vegetation indices were computed. Moreover, two thermal maps are presented to indicate the relation between vegetation and soil temperature.
Proceedings, 2024
“How far down can it see?” is one of the typical questions when it comes to UAV multi- spectral remote sensing for archaeology. Since the identification of buried remains is indirect through cropmarks observation, we asked ourselves how deep cropmarks can reveal the buried remains by analysing the complex relationship they have with vegetation. A selected number of contexts of the pre-Roman cities from Falerii and Veii have been studied through agronomic analysis on the one hand and GPR and stratigraphic excavation on the other. The results confirmed the effectiveness of this methodology for land survey, and not only do they demonstrate the ability to identify remains at a greater depth than might have been expected, but they have also made evident the difficulties of environmental analysis, which is crucial at the start of any remote sensing campaign, as well as in the subsequent study of anomalies.
Unmanned drone multispectral imaging for assessment of wheat and oilseed rape habitus
2021
Stoyanova, M., Kandilarov, A., Koutev, V., Nitcheva, O. & Dobreva, P. (2021). Unmanned drone multispectral imaging for assessment of wheat and oilseed rape habitus. Bulg. J. Agric. Sci., 27 (5), 875–879 The use of unmanned drones has been increased in precision farming. From multispectral images of terrain and crops to spraying and sowing, their application and development is becoming more and more popular in the public sector. Using different sensors and equipment farmers could take optimal management decisions. The aim of the present study is to analyze the data from a multispectral camera, to survey the development of the crops on the field, to perform an agronomic assessment and to make recommendations for optimization of the production by soil and plant sampling in order to increase yields and reducing the cost of production. Effectiveness of multispectral observation methods on agricultural crops was tested at the end of October 2018 in a pilot study on the territory of Northe...
Drones
The increasing use of geospatial information from satellites and unmanned aerial vehicles (UAVs) has been contributing to significant growth in the availability of instruments and methodologies for data acquisition and analysis. For better management of vineyards (and most crops), it is crucial to access the spatial-temporal variability. This knowledge throughout the vegetative cycle of any crop is crucial for more efficient management, but in the specific case of viticulture, this knowledge is even more relevant. Some research studies have been carried out in recent years, exploiting the advantage of satellite and UAV data, used individually or in combination, for crop management purposes. However, only a few studies explore the multi-temporal use of these two types of data, isolated or synergistically. This research aims to clearly identify the most suitable data and strategies to be adopted in specific stages of the vineyard phenological cycle. Sentinel-2 data from two vineyard p...
Use of multispectral and thermal imagery in precision viticulture
Journal of Physics: Conference Series, 2019
The increasing demand for higher quality and yield of wine production has led to a growing interest in precision viticulture, i.e., practices of monitoring and managing spatial variations in variables related to productivity within a vineyard. This paper presents a few applications of optical measurements, in combination with monitoring systems making use of geolocation and remote/proximal sensing, to calculate vegetation indices related to plant vigour and water stress in vineyards. Measurements were performed on vineyards in Burgenland, Austria, by both aerial and proximal (terrestrial) sensing techniques. A remote-sensing, four-band multispectral sensor, placed on an Unmanned Aerial Vehicle (UAV), has been used to detect the spectral signature of the vineyard and to calculate the NDVI index, useful to selectively address the harvest on the basis of quality and quantity of grapes. Proximal, thermal infrared imaging complemented the investigation providing information about the wat...
With the growth of the low altitude remote sensing (LARS) industry in recent years, their practical application in precision agriculture seems all the more possible. However, only a few scientists have reported using LARS to monitor crop conditions. Moreover, there have been concerns regarding the feasibility of such systems for producers given the issues related to the post-processing of images, technical expertise, and timely delivery of information. The purpose of this study is to showcase actual requests by farmers to monitor crop conditions in their fields using an unmanned aerial vehicle (UAV). Working in collaboration with farmers in northeastern Ontario, we use optical and near-infrared imagery to monitor fertilizer trials, conduct crop scouting and map field tile drainage. We demonstrate that LARS imagery has many practical applications. However, several obstacles remain, including the costs associated with both the LARS system and the image processing software, the extent of professional training required to operate the LARS and to process the imagery, and the influence from local weather conditions (e.g. clouds, wind) on image acquisition all need to be considered. Consequently, at present a feasible solution for producers might be the use of LARS service provided by private consultants or in collaboration with LARS scientific research teams.