Remote sensing for agricultural applications: A meta-review

M Weiss, F Jacob, G Duveiller - Remote sensing of environment, 2020 - Elsevier
Agriculture provides humanity with food, fibers, fuel, and raw materials that are paramount
for human livelihood. Today, this role must be satisfied within a context of environmental …

Crop yield estimation based on assimilation of crop models and remote sensing data: A systematic evaluation

L Luo, S Sun, J Xue, Z Gao, J Zhao, Y Yin, F Gao… - Agricultural …, 2023 - Elsevier
CONTEXT With the warming trend and the increasing frequency of extreme weather events,
accurate crop yield estimation is becoming urgent. Crop yield estimation mainly consists of …

Soybean yield prediction from UAV using multimodal data fusion and deep learning

M Maimaitijiang, V Sagan, P Sidike, S Hartling… - Remote sensing of …, 2020 - Elsevier
Preharvest crop yield prediction is critical for grain policy making and food security. Early
estimation of yield at field or plot scale also contributes to high-throughput plant phenoty** …

Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches

Y Cai, K Guan, D Lobell, AB Potgieter, S Wang… - Agricultural and forest …, 2019 - Elsevier
Wheat is the most important staple crop grown in Australia, and Australia is one of the top
wheat exporting countries globally. Timely and reliable wheat yield prediction in Australia is …

Integrating multi-source data for rice yield prediction across China using machine learning and deep learning approaches

J Cao, Z Zhang, F Tao, L Zhang, Y Luo, J Zhang… - Agricultural and Forest …, 2021 - Elsevier
Timely and reliable yield prediction at a large scale is imperative and prerequisite to prevent
climate risk and ensure food security, especially with climate change and increasing …

[HTML][HTML] An LSTM neural network for improving wheat yield estimates by integrating remote sensing data and meteorological data in the Guanzhong Plain, PR China

H Tian, P Wang, K Tansey, J Zhang, S Zhang… - Agricultural and Forest …, 2021 - Elsevier
Crop growth condition and production play an important role in food management and
economic development. Therefore, estimating yield accurately and timely is of vital …

A deep learning framework combining CNN and GRU for improving wheat yield estimates using time series remotely sensed multi-variables

J Wang, P Wang, H Tian, K Tansey, J Liu… - … and Electronics in …, 2023 - Elsevier
Accurate and timely crop yield estimation is crucial for crop market planning and food
security. Combining remotely sensed big data with deep learning for yield estimation has …

Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery

X Zhou, HB Zheng, XQ Xu, JY He, XK Ge, X Yao… - ISPRS Journal of …, 2017 - Elsevier
Timely and non-destructive assessment of crop yield is an essential part of agricultural
remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a …

[HTML][HTML] Winter wheat yield prediction at county level and uncertainty analysis in main wheat-producing regions of China with deep learning approaches

X Wang, J Huang, Q Feng, D Yin - Remote Sensing, 2020 - mdpi.com
Timely and accurate forecasting of crop yields is crucial to food security and sustainable
development in the agricultural sector. However, winter wheat yield estimation and …