Remote sensing for precision agriculture: Sentinel-2 improved features and applications

J Segarra, ML Buchaillot, JL Araus, SC Kefauver - Agronomy, 2020 - mdpi.com
The use of satellites to monitor crops and support their management is gathering increasing
attention. The improved temporal, spatial, and spectral resolution of the European Space …

Practices for upscaling crop simulation models from field scale to large regions

VS Manivasagam, O Rozenstein - Computers and Electronics in Agriculture, 2020 - Elsevier
Most crop models were developed and tested in homogeneous field conditions. However,
these crop models are increasingly applied beyond the field scale for larger regions …

[HTML][HTML] Prediction of maize crop coefficient from UAV multisensor remote sensing using machine learning methods

G Shao, W Han, H Zhang, L Zhang, Y Wang… - Agricultural Water …, 2023 - Elsevier
In the upcoming irrigation management in agricultural production, accurate mapping of crop
water consumption with a high spatial and temporal resolution at a farm scale is needed. In …

Mapping maize crop coefficient Kc using random forest algorithm based on leaf area index and UAV-based multispectral vegetation indices

G Shao, W Han, H Zhang, S Liu, Y Wang… - Agricultural Water …, 2021 - Elsevier
Rapid and accurate acquisition of crop coefficient (K c) values is essential for estimating field
crop evapotranspiration (ET). The lack of rapid access to the high-resolution spatial and …

[HTML][HTML] Using Sentinel-1 and Sentinel-2 imagery for estimating cotton crop coefficient, height, and Leaf Area Index

G Kaplan, L Fine, V Lukyanov, N Malachy… - Agricultural Water …, 2023 - Elsevier
In cotton, an optimal balance between vegetative and reproductive growth will lead to high
yields and water-use efficiency. Remote sensing estimations of vegetation variables such as …

Comparison of machine learning methods for mapping the stand characteristics of temperate forests using multi-spectral sentinel-2 data

K Ahmadi, B Kalantar, V Saeidi, EKG Harandi… - Remote Sensing, 2020 - mdpi.com
The estimation and mapping of forest stand characteristics are vital because this information
is necessary for sustainable forest management. The present study considers the use of a …

Normalizing the local incidence angle in sentinel-1 imagery to improve leaf area index, vegetation height, and crop coefficient estimations

G Kaplan, L Fine, V Lukyanov, VS Manivasagam… - Land, 2021 - mdpi.com
Public domain synthetic-aperture radar (SAR) imagery, particularly from Sentinel-1, has
widened the scope of day and night vegetation monitoring, even when cloud cover limits …

Wheat leaf traits monitoring based on machine learning algorithms and high-resolution satellite imagery

M Jamali, S Soufizadeh, B Yeganeh, Y Emam - Ecological Informatics, 2023 - Elsevier
The leaf, which is a crucial indicator for evaluating crop status, plays an important role in
plants' functions. Determining and monitoring leaf parameters can facilitate the detection …

Determining water use and crop coefficients of drip-irrigated cotton in south Xinjiang of China under various irrigation amounts

X Hou, J Fan, F Zhang, W Hu, F Yan, C Xiao… - Industrial Crops and …, 2022 - Elsevier
Crop evapotranspiration (ET c) and crop coefficient (K c) can vary among various
geographical locations and cultivated species. Therefore, determining regional-and species …

[HTML][HTML] Data-driven estimation of actual evapotranspiration to support irrigation management: Testing two novel methods based on an unoccupied aerial vehicle and …

O Rozenstein, L Fine, N Malachy, A Richard… - Agricultural Water …, 2023 - Elsevier
Recent advances in remote sensing and machine learning show potential for improving
irrigation use efficiency. In this study, two independent methods to determine the irrigation …