A classification-based spatiotemporal adaptive fusion model for the evaluation of remotely sensed evapotranspiration in heterogeneous irrigated agricultural area-Reference-Cited by-同舟云学术

A classification-based spatiotemporal adaptive fusion model for the evaluation of remotely sensed evapotranspiration in heterogeneous irrigated agricultural area

Published:2022-05 Issue: Volume:273 Page:112962
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Wang Shuai,Wang Chaozi,Zhang Chenglong,Xue Jingyuan,Wang Pu,Wang Xingwang,Wang Weishu,Zhang Xin,Li Wangcheng,Huang Guanhua,Huo Zailin

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference66 articles.

1. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—model;Allen;J. Irrig. Drain. Eng.,2007

2. Impact of insolation data source on remote sensing retrievals of evapotranspiration over the California delta;Anderson;Remote Sens.,2019

3. Responses of field evapotranspiration to the changes of cropping pattern and groundwater depth in large irrigation district of Yellow River basin;Bai;Agric. Water Manag.,2017

4. Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches;Barrett;Remote Sens. Environ.,2014

5. A remote sensing surface energy balance algorithm for land (SEBAL). Part 1: formulation;Bastiaanssen;J. Hydrol.,1998

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Generating high-resolution hyperspectral time series datasets based on unsupervised spatial-temporal-spectral fusion network incorporating a deep prior;Information Fusion;2024-11

2. Mapping Crop Evapotranspiration by Combining the Unmixing and Weight Image Fusion Methods;Remote Sensing;2024-07-01

3. A spatial downscaling method for SMAP soil moisture considering vegetation memory and spatiotemporal fusion;International Journal of Digital Earth;2024-07

4. Efficient agricultural water research under elevated global carbon dioxide concentration – Based on bibliometric analysis;Agricultural Water Management;2024-06

5. Machine-learning-driven discovery of metal–organic framework adsorbents for hexavalent chromium removal from aqueous environments;Journal of Colloid and Interface Science;2024-05