Spatial Downscaling of Vegetation Productivity in the Forest From Deep Learning-Reference-Cited by-同舟云学术

Spatial Downscaling of Vegetation Productivity in the Forest From Deep Learning

Published:2022 Issue: Volume:10 Page:104449-104460
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Yu Tao¹^ORCID,Pang Yong¹^ORCID,Sun Rui²^ORCID,Niu Xiaodong¹

Affiliation:

1. Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing, China

2. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China

Funder

Fundamental Research Funds of the Chinese Academy of Forestry

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09904574.pdf?arnumber=9904574

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4. Development of a global 30 m impervious surface map using multisource and multitemporal remote sensing datasets with the Google Earth Engine platform

5. Fine Land-Cover Mapping in China Using Landsat Datacube and an Operational SPECLib-Based Approach

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