The use of 3D sensors combined with appropriate data processing and analysis has provided tools t... more The use of 3D sensors combined with appropriate data processing and analysis has provided tools to optimise agricultural management through the application of precision agriculture. The recent development of low-cost RGB-Depth cameras has presented an opportunity to introduce 3D sensors into the agricultural community. However, due to the sensitivity of these sensors to highly illuminated environments, it is necessary to know under which conditions RGB-D sensors are capable of operating. This work presents a methodology to evaluate the performance of RGB-D sensors under different lighting and distance conditions, considering both geometrical and spectral (colour and NIR) features. The methodology was applied to evaluate the performance of the Microsoft Kinect v2 sensor in an apple orchard. The results show that sensor resolution and precision decreased significantly under middle to high ambient illuminance (>2000 lx). However, this effect was minimised when measurements were cond...
One of the challenges in orchard management, in particular of hedgerow tree plantations, is the d... more One of the challenges in orchard management, in particular of hedgerow tree plantations, is the delineation of management zones on the bases of high-precision data. Along this line, the present study analyses the applicability of vegetation indices derived from UAV images to estimate the key structural and geometric canopy parameters of an almond orchard. In addition, the classes created on the basis of the vegetation indices were assessed to delineate potential management zones. The structural and geometric orchard parameters (width, height, cross-sectional area and porosity) were characterized by means of a LiDAR sensor, and the vegetation indices were derived from a UAV-acquired multispectral image. Both datasets summarized every 0.5 m along the almond tree rows and were used to interpolate continuous representations of the variables by means of geostatistical analysis. Linear and canonical correlation analyses were carried out to select the best performing vegetation index to es...
Different sampling schemes were tested to estimate yield (kg/tree), fruit firmness (kg) and the r... more Different sampling schemes were tested to estimate yield (kg/tree), fruit firmness (kg) and the refractometric index (°Baumé) in a peach orchard. In contrast to simple random sampling (SRS), the use of auxiliary information (NDVI and apparent electrical conductivity, ECa) allowed sampling points to be stratified according to two or three classes (strata) within the plot. Sampling schemes were compared in terms of accuracy and efficiency. Stratification of samples improved efficiency compared to SRS. However, yield and quality parameters may require different sampling strategies. While yield was better estimated using stratified samples based on the ECa, fruit quality (firmness and °Baumé) showed better results when stratifying by NDVI.
This work assesses the potential of Sentinel-2A images in precision agriculture for Barley produc... more This work assesses the potential of Sentinel-2A images in precision agriculture for Barley production in a case study. Two workflows are proposed: 1) images were acquired with a relatively simple methodology to follow the crop development; 2) two images around harvest time were downloaded and processed using a more complex and accurate methodology to calculate four vegetation indices (NDVI, WDRVI, GRVI and GNDVI) to be correlated to yield with linear regression models. Yield data were acquired with a yield monitor installed in a combine harvester. Green-based vegetation indices performed slightly better. However, the highest correlation coefficient was 0.48. Better results may be achieved with earlier imagery and other vegetation indices. Sentinel-2 is a promising tool for precision agriculture in large arable crop fields.
Continuous canopy status monitoring is an essential factor to support and precisely apply orchard... more Continuous canopy status monitoring is an essential factor to support and precisely apply orchard management actions such as pruning, pesticide and foliar treatment applications, or fertirrigation, among others. For that, this work proposes the use of multispectral vegetation indices to estimate geometric and structural orchard parameters from remote sensing images (high temporal and spatial resolution) as an alternative to more time-consuming processing techniques, such as LiDAR surveys or UAV photogrammetry. A super-intensive almond (Prunus dulcis) orchard was scanned using a mobile terrestrial laser (LiDAR) in two different vegetative stages (after spring pruning and before harvesting). From the LiDAR point cloud, canopy orchard parameters, including maximum height and width, cross-sectional area and porosity, were summarized every 0.5 m along the rows and interpolated using block kriging to the pixel centroids of PlanetScope (3 × 3 m) and Sentinel-2 (10 × 10 m) image grids. To s...
1 2 Jaume Arnó · Alexandre Escolà · Josep M. Vallès · Jordi Llorens · Ricardo Sanz · 3 Joan Masip... more 1 2 Jaume Arnó · Alexandre Escolà · Josep M. Vallès · Jordi Llorens · Ricardo Sanz · 3 Joan Masip · Jordi Palacín · Joan R. Rosell-Polo 4 5 6 7 8 Jaume Arnó () · Alexandre Escolà · Josep M. Vallès · Ricardo Sanz · Joan Masip · 9 Joan R. Rosell-Polo 10 Department of Agricultural and Forest Engineering – Research Group on AgroICT and 11 Precision Agriculture, University of Lleida, Rovira Roure, 191, Lleida, 25198, Spain 12 E-mail: JArno@eagrof.udl.cat 13 Tel.: +34 973 702 859 14 Fax: +34 973 702 673 15 URL: www.grap.udl.cat 16 17 Jordi Llorens 18 Department of Agri Food Engineering and Biotechnology, Politechnical University of 19 Catalunya, Campus del Baix Llobregat, Edifici D4, Esteve Terradas, 8, Castelldefels, 20 08860, Spain 21 22 Jordi Palacín 23 Department of Computer Science and Industrial Engineering, University of Lleida, 24 Jaume II, 69, Lleida, 25197, Spain 25 26 27 28 29 30 Abstract Estimation of grapevine vigour using mobile proximal sensors can provide an 31
The use of 3D sensors combined with appropriate data processing and analysis has provided tools t... more The use of 3D sensors combined with appropriate data processing and analysis has provided tools to optimise agricultural management through the application of precision agriculture. The recent development of low-cost RGB-Depth cameras has presented an opportunity to introduce 3D sensors into the agricultural community. However, due to the sensitivity of these sensors to highly illuminated environments, it is necessary to know under which conditions RGB-D sensors are capable of operating. This work presents a methodology to evaluate the performance of RGB-D sensors under different lighting and distance conditions, considering both geometrical and spectral (colour and NIR) features. The methodology was applied to evaluate the performance of the Microsoft Kinect v2 sensor in an apple orchard. The results show that sensor resolution and precision decreased significantly under middle to high ambient illuminance (>2000 lx). However, this effect was minimised when measurements were cond...
One of the challenges in orchard management, in particular of hedgerow tree plantations, is the d... more One of the challenges in orchard management, in particular of hedgerow tree plantations, is the delineation of management zones on the bases of high-precision data. Along this line, the present study analyses the applicability of vegetation indices derived from UAV images to estimate the key structural and geometric canopy parameters of an almond orchard. In addition, the classes created on the basis of the vegetation indices were assessed to delineate potential management zones. The structural and geometric orchard parameters (width, height, cross-sectional area and porosity) were characterized by means of a LiDAR sensor, and the vegetation indices were derived from a UAV-acquired multispectral image. Both datasets summarized every 0.5 m along the almond tree rows and were used to interpolate continuous representations of the variables by means of geostatistical analysis. Linear and canonical correlation analyses were carried out to select the best performing vegetation index to es...
Different sampling schemes were tested to estimate yield (kg/tree), fruit firmness (kg) and the r... more Different sampling schemes were tested to estimate yield (kg/tree), fruit firmness (kg) and the refractometric index (°Baumé) in a peach orchard. In contrast to simple random sampling (SRS), the use of auxiliary information (NDVI and apparent electrical conductivity, ECa) allowed sampling points to be stratified according to two or three classes (strata) within the plot. Sampling schemes were compared in terms of accuracy and efficiency. Stratification of samples improved efficiency compared to SRS. However, yield and quality parameters may require different sampling strategies. While yield was better estimated using stratified samples based on the ECa, fruit quality (firmness and °Baumé) showed better results when stratifying by NDVI.
This work assesses the potential of Sentinel-2A images in precision agriculture for Barley produc... more This work assesses the potential of Sentinel-2A images in precision agriculture for Barley production in a case study. Two workflows are proposed: 1) images were acquired with a relatively simple methodology to follow the crop development; 2) two images around harvest time were downloaded and processed using a more complex and accurate methodology to calculate four vegetation indices (NDVI, WDRVI, GRVI and GNDVI) to be correlated to yield with linear regression models. Yield data were acquired with a yield monitor installed in a combine harvester. Green-based vegetation indices performed slightly better. However, the highest correlation coefficient was 0.48. Better results may be achieved with earlier imagery and other vegetation indices. Sentinel-2 is a promising tool for precision agriculture in large arable crop fields.
Continuous canopy status monitoring is an essential factor to support and precisely apply orchard... more Continuous canopy status monitoring is an essential factor to support and precisely apply orchard management actions such as pruning, pesticide and foliar treatment applications, or fertirrigation, among others. For that, this work proposes the use of multispectral vegetation indices to estimate geometric and structural orchard parameters from remote sensing images (high temporal and spatial resolution) as an alternative to more time-consuming processing techniques, such as LiDAR surveys or UAV photogrammetry. A super-intensive almond (Prunus dulcis) orchard was scanned using a mobile terrestrial laser (LiDAR) in two different vegetative stages (after spring pruning and before harvesting). From the LiDAR point cloud, canopy orchard parameters, including maximum height and width, cross-sectional area and porosity, were summarized every 0.5 m along the rows and interpolated using block kriging to the pixel centroids of PlanetScope (3 × 3 m) and Sentinel-2 (10 × 10 m) image grids. To s...
1 2 Jaume Arnó · Alexandre Escolà · Josep M. Vallès · Jordi Llorens · Ricardo Sanz · 3 Joan Masip... more 1 2 Jaume Arnó · Alexandre Escolà · Josep M. Vallès · Jordi Llorens · Ricardo Sanz · 3 Joan Masip · Jordi Palacín · Joan R. Rosell-Polo 4 5 6 7 8 Jaume Arnó () · Alexandre Escolà · Josep M. Vallès · Ricardo Sanz · Joan Masip · 9 Joan R. Rosell-Polo 10 Department of Agricultural and Forest Engineering – Research Group on AgroICT and 11 Precision Agriculture, University of Lleida, Rovira Roure, 191, Lleida, 25198, Spain 12 E-mail: JArno@eagrof.udl.cat 13 Tel.: +34 973 702 859 14 Fax: +34 973 702 673 15 URL: www.grap.udl.cat 16 17 Jordi Llorens 18 Department of Agri Food Engineering and Biotechnology, Politechnical University of 19 Catalunya, Campus del Baix Llobregat, Edifici D4, Esteve Terradas, 8, Castelldefels, 20 08860, Spain 21 22 Jordi Palacín 23 Department of Computer Science and Industrial Engineering, University of Lleida, 24 Jaume II, 69, Lleida, 25197, Spain 25 26 27 28 29 30 Abstract Estimation of grapevine vigour using mobile proximal sensors can provide an 31
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