Evaluating a spatiotemporal shape-matching model for the generation of synthetic high spatiotemporal resolution time series of multiple satellite data-Reference-Cited by-同舟云学术

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Evaluating a spatiotemporal shape-matching model for the generation of synthetic high spatiotemporal resolution time series of multiple satellite data

Published:2021-12 Issue: Volume:104 Page:102545
ISSN:0303-2434
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Zhang Xiaoyang,Gao Feng,Wang Jianmin,Ye Yongchang

Funder

U.S. Geological Survey

NASA Goddard Space Flight Center

National Aeronautics and Space Administration

U.S. Department of Agriculture

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference72 articles.

1. Field-scale assessment of land and water use change over the California delta using remote sensing;Anderson;Remote Sens.,2018

2. Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery;Bolton;Remote Sens. Environ.,2020

3. Bullock, E.L., Woodcock, C.E., Holden, C.E., 2020. Improved change monitoring using an ensemble of time series algorithms. Remote Sens. Environ. 238.

4. Combining medium and coarse spatial resolution satellite data to improve the estimation of sub-pixel NDVI time series;Busetto;Remote Sens. Environ.,2008

5. Mapping daily evapotranspiration at field scales over rainfed and irrigated agricultural areas using remote sensing data fusion;Cammalleri;Agric. For. Meteorol.,2014

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