Effectiveness of upscaling the vegetation temperature condition index retrieved from Landsat data using an algorithm combining the trend surface analysis and the spatial variation weight method-Reference-Cited by-同舟云学术

Effectiveness of upscaling the vegetation temperature condition index retrieved from Landsat data using an algorithm combining the trend surface analysis and the spatial variation weight method

Published:2020-12-31 Issue:1 Volume:54 Page:29-41
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Bai X. J.¹,Kang H. X.¹,Wang P. X.²,Liu Z.³

Affiliation:

1. National Engineering Laboratory for Transportation Safety and Emergency Informatics, China Transport Telecommunications and Information Center, Beijing, China

2. College of Information and Electrical Engineering, China Agricultural University, Beijing, China

3. Faculty of Education, Beijing Normal University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/22797254.2020.1847603

Reference35 articles.

1. An Up-Scaled Vegetation Temperature Condition Index Retrieved From Landsat Data with Trend Surface Analysis

2. A comparative study of NOAA–AVHRR derived drought indices using change vector analysis

3. A multivariable approach for mapping sub-pixel land cover distributions using MISR and MODIS: Application in the Brazilian Amazon region

4. Semivariograms of digital imagery for analysis of conifer canopy structure

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