Spatial-aware SAR-optical time-series deep integration for crop phenology tracking-Reference-Cited by-同舟云学术

Spatial-aware SAR-optical time-series deep integration for crop phenology tracking

Published:2022-07 Issue: Volume:276 Page:113046
ISSN:0034-4257
Container-title:Remote Sensing of Environment
language:en
Short-container-title:Remote Sensing of Environment

Author:

Zhao Wenzhi,Qu Yang,Zhang Liqiang,Li Kaiyuan

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geology,Soil Science

Reference55 articles.

1. Large-scale crop type and crop area mapping across Brazil using synthetic aperture radar and optical imagery;Ajadi;Int. J. Appl. Earth Obs. Geoinf.,2021

2. Improved monitoring of vegetation dynamics at very high latitudes: a new method using MODIS NDVI;Beck;Remote Sens. Environ.,2006

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

4. Using phenocams to monitor our changing earth: toward a global phenocam network;Brown;Front. Ecol. Environ.,2016

5. Scaling Phenocam GCC, NDVI, and EVI2 with harmonized Landsat-sentinel using Gaussian processes;Burke;Agric. For. Meteorol.,2021

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