A new rapid, low-cost and GPS-centric unmanned aerial vehicle incorporating in-situ multispectral oil palm trees health detection (original) (raw)
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Mapping multispectral Digital Images using a Cloud Computing software: applications from UAV images
Heliyon, 2019
Due to technology development related to agricultural production, aircrafts such as the Unmanned Aerial Vehicle (UAV) and technologies such as Multispectral photogrammetry and Remote Sensing, have great potential in supporting some of the pressing problems faced by agricultural production in terms of analysis and testing of variables. This paper reports an experience related to the analysis of a vineyard with multispectral photogrammetry technology and UAVs and it demonstrates its great potential to analyze the Normalized Difference Vegetation Index (NDVI), the Near-Infrared Spectroscopy (NIRS) and the Digital Elevation Model (DEM) applied in the agriculture framework to collect information on the vegetative state of the crop, soil and plant moisture, and biomass density maps of. In addition, the collected information is analyzed with the PIX4D Cloud Computing technology software and its advantages over software that work with other data processing are highlighted. This research shows, therefore, the possibility that efficient plantations can be developed with the use of multispectral photogrammetry and the analysis of digital images from this process.
A UAV Platform Based on a Hyperspectral Sensor for Image Capturing and On-Board Processing
IEEE Access, 2019
Application-oriented solutions based on the combination of different technologies such as unmanned aerial vehicles (UAVs), advanced sensors, precise GPS, and embedded devices have led to important improvements in the field of cyber-physical systems. Agriculture, due to its economic and social impact on the global population, arises as a potential domain which could enormously benefit from this paradigm in terms of savings in time, resources and human labor, not to mention aspects related to sustainability and environment respect. This has led to a new revolution named precision agriculture (or precision farming), based on observing and measuring inter and intra-field variability in crops. A key technology in this scenario is the use of hyperspectral imaging, firstly used in satellites and later in manned aircraft, composed by hundreds of spectral bands which facilitate hidden data to be converted into useful information. In this paper, a hyperspectral flying platform is presented and the construction of the whole system is detailed. The proposed solution is based on a commercial DJI Matrice 600 drone and a Specim FX10 hyperspectral camera. The challenge in this work has been to adopt this latter device, mainly conceived for industrial applications, into a flying platform in which weight, power budget, and connectivity are paramount. Additionally, an embedded board with advanced processing capabilities has been mounted on the drone in order to control its trajectory, manage the data acquisition, and allow on-board processing, such as the evaluation of different vegetation indices (the normalized difference vegetation index, NDVI, the modified chlorophyll absorption ratio index, MCARI, and the modified soil-adjusted vegetation index, MSAVI), which are numerical and/or graphical indicators of the vegetation properties and compression, which is of crucial relevance due to the huge amounts of data captured. The whole system was successfully tested in a real scenario located on the island of Gran Canaria, Spain, where a vineyard area was inspected between May and August of the year 2018. INDEX TERMS Unmanned aerial vehicle, hyperspectral, pushbroom sensor, vegetation index, on-board processing.
Remote Sensing, 2017
Traditional imagery-provided, for example, by RGB and/or NIR sensors-has proven to be useful in many agroforestry applications. However, it lacks the spectral range and precision to profile materials and organisms that only hyperspectral sensors can provide. This kind of high-resolution spectroscopy was firstly used in satellites and later in manned aircraft, which are significantly expensive platforms and extremely restrictive due to availability limitations and/or complex logistics. More recently, UAS have emerged as a very popular and cost-effective remote sensing technology, composed of aerial platforms capable of carrying small-sized and lightweight sensors. Meanwhile, hyperspectral technology developments have been consistently resulting in smaller and lighter sensors that can currently be integrated in UAS for either scientific or commercial purposes. The hyperspectral sensors' ability for measuring hundreds of bands raises complexity when considering the sheer quantity of acquired data, whose usefulness depends on both calibration and corrective tasks occurring in pre-and post-flight stages. Further steps regarding hyperspectral data processing must be performed towards the retrieval of relevant information, which provides the true benefits for assertive interventions in agricultural crops and forested areas. Considering the aforementioned topics and the goal of providing a global view focused on hyperspectral-based remote sensing supported by UAV platforms, a survey including hyperspectral sensors, inherent data processing and applications focusing both on agriculture and forestry-wherein the combination of UAV and hyperspectral sensors plays a center role-is presented in this paper. Firstly, the advantages of hyperspectral data over RGB imagery and multispectral data are highlighted. Then, hyperspectral acquisition devices are addressed, including sensor types, acquisition modes and UAV-compatible sensors that can be used for both research and commercial purposes. Pre-flight operations and post-flight pre-processing are pointed out as necessary to ensure the usefulness of hyperspectral data for further processing towards the retrieval of conclusive information. With the goal of simplifying hyperspectral data processing-by isolating the common user from the processes' mathematical complexity-several available toolboxes that allow a direct access to level-one hyperspectral data are presented. Moreover, research works focusing the symbiosis between UAV-hyperspectral for agriculture and forestry applications are reviewed, just before the paper's conclusions.
Multispectral aerial image processing system for precision agriculture
Sistemas y Telemática
Cuban agriculture has the growing need to increase its productivity. To achieve this, precision agriculture can play a fundamental role. It is necessary to develop an image processing system able to process all the crops information and calculate vegetation indexes in a satisfactory way. This will entail in accurate measurements of the nitrogen lack, the hydric stress, and the vegetal strength, among other aspects, seeking to improve the accuracy in the care of these aspects. This document reports the results of an investigation pointed to develop a procedure for capturing and processing multispectral aerial images obtained from Unmanned Aerial Vehicles [UAV]. This procedure searched to measure the vegetation indexes of sugarcane crops that may be correlated with the level of vegetal strength, the number of stems, and the foliar mass per lot. We used a USENSE-X8 UAV together with a Sequoia multispectral sensor and the QGIS processing software. The procedure was experimentally valida...
Folia Forestalia Polonica, 2015
The main purpose of this publication is to present the current progress of the work associated with the use of a lightweight unmanned platforms for various environmental studies. Current development in information technology, electronics and sensors miniaturisation allows mounting multispectral cameras and scanners on unmanned aerial vehicle (UAV) that could only be used on board aircraft and satellites. Remote Sensing Division in the Institute of Aviation carries out innovative researches using multisensory platform and lightweight unmanned vehicle to evaluate the health state of forests in Wielkopolska province. In this paper, applicability of multispectral images analysis acquired several times during the growing season from low altitude (up to 800m) is presented. We present remote sensing indicators computed by our software and common methods for assessing state of trees health. The correctness of applied methods is verified using analysis of satellite scenes acquired by Landsat...
OPTIMIZED POST-PROCESSING OF MULTIPLE UAV IMAGES FOR FORESTRY INSPECTIONS
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
The following paper discusses possible optimized post-processing and data tracking of UAV imagery for forestry inspection. The survey took place in the National Natural Reserve Božídarské rašeliniště-The Wetland of Božídar from 2015 till now. The purpose of this study is to provide with a suitable post-processing method of UAV images in a protected area with no necessity of human interaction with the species. The authors used UAV imagery from RGB and multispectral sensors. The focus of the paper is the postprocessing which relies solely on open-source tools. The results of the paper are a script for automatic computation of vegetation indices, a script for canopy height model in a certain part of the mapped area a possible GIS solution for storing and tracking the data.
The Usefulness Of Unmanned Airborne Vehicle (UAV) Imagery For Automated Palm Oil Tree Counting
Palm oil plantations are not exceptional, one of the most valuable resources that needs to be accurately measured for better and effective management; which commonly requires not only a reliable, timely but also up-to-date data that remote sensing can provide. High resolution data are crucial in plantation management, as it provide detailed information to plantation managers for better decision making. To combine the advantages of these conventional remote sensing platforms such as high resolution and flexibility of airborne platforms and cost effectiveness of spaceborne platforms, recently Unmanned Aerial Vehicle (UAV) platform is being deployed for many remote sensing applications. Tree counting is crucial for plantation and environmental management, biodiversity monitoring and many other applications. Despite of the factor that satellite and airborne images have been widely used to detect, delineate and count individual tree in plantations, still such high resolution data sets are expensive. Hence the need to deploy the use of UAV imagery for automated palm oil tree counting. The objective of the study is to assess the usefulness of images obtained from Unman Aerial vehicle (UAV) for Automatic palm oil tree counting. The methodology is based on the concept of crown geometry and vegetation response to radiation. Spatial analysis involving the use of convolution and morphological analysis are used to detect and delineates the palm oil crown; and image thresholding is used for creating the palm oil tree centroids. The result of the thresholding was later used as input for automated palm oil tree counting. The automated tree counting was executed using ENVI EX software and an open source program “ImageJ”. The result shows that UAV data set is crucial for palm oil tree counting. The accuracy of the result was assessed by comparing with ground truth; and it is found to be 96.5% accurate. This proves that the UAV date set is suitable for automatic palm oil tree counting. The omission error may be due to the factors such as canopy overlapping or due to the image blurriness. However, 96.5% accuracy can be considered as within the range of the standard accuracy for palm oil tree counting.
Image analysis aplications in precision agriculture
Revista Visión electrónica, 2017
Unmanned Aircraft Vehicles (UAVs) are currently used for multiple applications in various fields: forestry, geology, the livestock sector and security. Among the most common applications, it is worth to stand out the image acquisition, irrigation, transport, surveillance and others. The study that one presents treats of the implementations that are realized by means of aerial images acquired with UAVs directed to the farming. Images acquired until recent years had been using satellites, however due to the high costs that are incurred and low accessibility to these technologies, UAVs, have become a tool for greater precision and scope for making decisions in agriculture. Information from databases of international magazines, groups and research centers is taken to determine the current state of implementations in Precision Agriculture (PA). This article describes tasks such as: soil preparation; limits and land areas, vegetation monitoring; classification of vegetation, growth, height, plant health; diseases management, pests and weeds, fertilization and inventory developed from analysis of aerial images acquired with UAVs