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Remote-sensing data and deep-learning techniques in crop map** and yield prediction: A systematic review
Reliable and timely crop-yield prediction and crop map** are crucial for food security and
decision making in the food industry and in agro-environmental management. The global …
decision making in the food industry and in agro-environmental management. The global …
Highlighting the role of agriculture and geospatial technology in food security and sustainable development goals
Food security is a global challenge that aligns with several Sustainable Development Goals
(SDGs), including SDG 1‐“No Poverty”, SDG 2‐“Zero Hunger,” SDG 3‐“Good Health and …
(SDGs), including SDG 1‐“No Poverty”, SDG 2‐“Zero Hunger,” SDG 3‐“Good Health and …
Multiscale 3-D–2-D mixed CNN and lightweight attention-free transformer for hyperspectral and LiDAR classification
The effective combination of hyperspectral image (HSI) and light detection and ranging
(LiDAR) data can be used for land cover classification. Recently, deep-learning-based …
(LiDAR) data can be used for land cover classification. Recently, deep-learning-based …
[HTML][HTML] Evaluation of 18 satellite-and model-based soil moisture products using in situ measurements from 826 sensors
Abstract Information about the spatiotemporal variability of soil moisture is critical for many
purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction …
purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction …
Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis
There is a dearth of literature that provides a bibliometric analysis concerning the role of
Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this …
Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this …
Assessment for crop water stress with infrared thermal imagery in precision agriculture: A review and future prospects for deep learning applications
With the increasing global water scarcity, efficient assessment methods for crop water stress
have become a prerequisite to perform precision irrigation scheduling. The 1accessibility of …
have become a prerequisite to perform precision irrigation scheduling. The 1accessibility of …
Multi-layer high-resolution soil moisture estimation using machine learning over the United States
The lack of proper understanding of multi-layer soil moisture (SM) profile (signals) remains a
persistent challenge in sustainable agricultural water management and food security …
persistent challenge in sustainable agricultural water management and food security …
Using the plant height and canopy coverage to estimation maize aboveground biomass with UAV digital images
The rapid and efficient estimation of aboveground biomass (AGB) in maize proves
advantageous for growth assessment, grain quality and yield prediction, and timely field …
advantageous for growth assessment, grain quality and yield prediction, and timely field …
[HTML][HTML] A parallel-cascaded ensemble of machine learning models for crop type classification in Google earth engine using multi-temporal sentinel-1/2 and landsat-8 …
The accurate map** of crop types is crucial for ensuring food security. Remote Sensing
(RS) satellite data have emerged as a promising tool in this field, offering broad spatial …
(RS) satellite data have emerged as a promising tool in this field, offering broad spatial …
[HTML][HTML] Remote sensing monitoring of rice diseases and pests from different data sources: A review
Rice is an important food crop in China, and diseases and pests are the main factors
threatening its safety, ecology, and efficient production. The development of remote sensing …
threatening its safety, ecology, and efficient production. The development of remote sensing …