Due to current global population growth, resource shortages, and climate change, traditional
agricultural models face major challenges. Precision agriculture (PA), as a way to realize the …

This review paper adopts bibliometric and meta-analysis approaches to explore the
application of supervised machine learning regression models in satellite-based water …

In this article, seven filter algorithms were compared. The Lee sigma method was more
suitable for estimating soil moisture (SM) than the other filtering methods under different land …

This article aims to explore the applicability of SMMI (soil moisture monitoring index),
MSMMI (modified soil moisture monitoring index), PDI (perpendicular drought index), and …

Soil moisture (SM) is of paramount importance in irrigation scheduling, infiltration, runoff,
and agricultural drought monitoring. This work aimed at evaluating the performance of the …

Remote sensing presents great potential for soil moisture map**, although a lack of high-
resolution, all-season suitable data and model-based complications hinders continuous …

Successive re-calibrations were implemented in Landsat-8 TIRS data since launch. This
paper evaluates the performances of both:(1) these re-calibrations, up to the last calibration …

Thermal infrared remote sensing have been extensively applied to estimate global-or
regional-extent surface soil moisture. Meanwhile, potentials of the remotely sensed data for …

Soil moisture is a key parameter for the circulation of water and energy exchange between
surface and the atmosphere, playing an important role in hydrology, agriculture, and …

Environmental hazards like drought lead to degrading food production and adversely impact
the agro-economy. This study investigates the contributions of different climatic and socio …