Results 281 to 290 of about 2,336,597 (324)
Harmonizing Terrestrial Carbon Cycle Observations Over CONUS NEON Sites: Assessing the Information Contributions of Multiple Data Constraints. [PDF]
Glob Chang BiolZhang D +4 more
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A lightweight soil moisture prediction model based on irrigation cycle segmentation and Kalman filtering. [PDF]
Front Plant SciMa J, Cai J, Li M, Chao L.
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Generating high accuracy multi-layer soil moisture at daily scale in the black soil region of China. [PDF]
Sci DataChen L +9 more
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Pervasive seasonal divergence in lagged responses of vegetation growth to compound drought-heat stress on the Tibetan Plateau. [PDF]
Front Plant SciLi W +5 more
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Agricultural Water Management, 2022
Abstract Soil moisture (SM) is an important indicator of the photosynthetic rate and growth status of crops. A few related parameters, such as the red-edge parameters and spectral indices, have been adopted for retrieving the SM of winter wheat. To further study their abilities to detect the SM, field-scale water stress experiments on winter wheat ...
Shoujia Ren +5 more
openaire +2 more sources
Abstract Soil moisture (SM) is an important indicator of the photosynthetic rate and growth status of crops. A few related parameters, such as the red-edge parameters and spectral indices, have been adopted for retrieving the SM of winter wheat. To further study their abilities to detect the SM, field-scale water stress experiments on winter wheat ...
Shoujia Ren +5 more
openaire +2 more sources
IEEE Transactions on Geoscience and Remote Sensing
We introduce a physics-informed machine learning (PIML) algorithm based on a feed-forward neural network (FFNN) to estimate surface soil moisture from limited in situ measurements and Sentinel-1/2 satellite images on the alluvial fan of the Kosi River by
Abhilash Singh, Kumar Gaurav
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We introduce a physics-informed machine learning (PIML) algorithm based on a feed-forward neural network (FFNN) to estimate surface soil moisture from limited in situ measurements and Sentinel-1/2 satellite images on the alluvial fan of the Kosi River by
Abhilash Singh, Kumar Gaurav
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Long-term changes in surface soil moisture based on CCI SM in Yunnan Province, Southwestern China
Journal of Hydrology, 2020Abstract Soil moisture (SM) plays an important role in regional runoff variations, energy dynamics, and vegetation productivity. It is also widely used to detecting agricultural drought. Recently, a severe drought occurred in Yunnan Province in southwestern China, so long-term changes in surface SM were of concern.
Siyu Ma +3 more
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Spatial Representativeness of Soil Moisture Stations and Its Influential Factors at a Global Scale
IEEE Transactions on Geoscience and Remote SensingThe spatial representativeness error of in situ soil moisture (SM) is recognized as a major source of uncertainty when validating satellite SM products with a spatial resolution of tens of kilometers.
Chenchen Peng +7 more
semanticscholar +1 more source
Journal of Korea Water Resources Association, 2016
본 연구에서는 수원 성균관대학교 내 Frequency Domain Reflectometry (FDR) 토양수분 측정 장비 및 COSMIC-ray 중성자 측정 장비를 통한 토양수분 지점 관측 사이트를 확립하였다. 또한 양질의 토양수분 데이터 확보를 위해 연구지역 내 토질실험, 토질별 FDR 토양수분 데이터 및 COSMIC-ray 중성자 개수의 시계열 분석, 관측한 토양수분 데이터와 위성 기반 토양수분 데이터와의 비교분석을 실시하였다. 2014년도부터 6개 지점에서 표층으로부터 5 cm에서 40 cm까지 총 24개의 FDR 센서를 5~10 cm 깊이별로 설치하여 토양수분 데이터를 측정하였다.
Hyunglok Kim +3 more
openaire +1 more source
본 연구에서는 수원 성균관대학교 내 Frequency Domain Reflectometry (FDR) 토양수분 측정 장비 및 COSMIC-ray 중성자 측정 장비를 통한 토양수분 지점 관측 사이트를 확립하였다. 또한 양질의 토양수분 데이터 확보를 위해 연구지역 내 토질실험, 토질별 FDR 토양수분 데이터 및 COSMIC-ray 중성자 개수의 시계열 분석, 관측한 토양수분 데이터와 위성 기반 토양수분 데이터와의 비교분석을 실시하였다. 2014년도부터 6개 지점에서 표층으로부터 5 cm에서 40 cm까지 총 24개의 FDR 센서를 5~10 cm 깊이별로 설치하여 토양수분 데이터를 측정하였다.
Hyunglok Kim +3 more
openaire +1 more source
IEEE Transactions on Geoscience and Remote Sensing
Since agricultural drought plays a leading role in restricting agricultural productivity, accurate forecasting is crucial for agricultural management.
Zhenhua Xiong +8 more
semanticscholar +1 more source
Since agricultural drought plays a leading role in restricting agricultural productivity, accurate forecasting is crucial for agricultural management.
Zhenhua Xiong +8 more
semanticscholar +1 more source