Dataset List

Vol.|Area

No.11 Vol.11,2024
No.10 Vol.11,2024
No.09 Vol.11,2024
No.08 Vol.11,2024
No.07 Vol.11,2024
No.06 Vol.11,2024
No.05 Vol.11,2024
No.04 Vol.11,2024
No.03 Vol.11,2024
No.02 Vol.11,2024
No.01 Vol.11,2024
No.12 Vol.10,2023
No.11 Vol.10,2023
No.10 Vol.10,2023
No.09 Vol.10,2023
No.08 Vol.10,2023
No.07 Vol.10,2023
No.06 Vol.10,2023
No.05 Vol.10,2023
No.04 Vol.10,2023
No.03 Vol.10,2023
No.02 Vol.10,2023
No.01 Vol.10,2023
No.12 Vol.9,2022
No.11 Vol.9,2022
No.10 Vol.9,2022
No.09 Vol.9,2022
No.08 Vol.9,2022
No.07 Vol.9,2022
No.06 Vol.9,2022
No.05 Vol.9,2022
No.04 Vol.9,2022
No.03 Vol.9,2022
No.02 Vol.9,2022
No.01 Vol.9,2022
No.12 Vol.8,2021
No.11 Vol.8,2021
No.10 Vol.8,2021
No.09 Vol.8,2021
No.08 Vol.8,2021
No.07 Vol.8,2021
No.06 Vol.8,2021
No.05 Vol.8,2021
No.04 Vol.8,2021
No.03 Vol.8,2021
No.03 Vol.8,2021
No.02 Vol.8,2021
No.01 Vol.8,2021
No.09 Vol.7,2020
No.08 Vol.7,2020
No.07 Vol.7,2020
No.06 Vol.7,2020
No.05 Vol.7,2020
No.04 Vol.7,2020
No.03 Vol.7,2020
No.02 Vol.7,2020
No.01 Vol.7,2020
No.06 Vol.6,2019
No.05 Vol.6,2019
No.04 Vol.6,2019
No.03 Vol.6,2019
No.02 Vol.6,2019
No.01 Vol.6,2019
No.08 Vol.5,2018
No.07 Vol.5,2018
No.06 Vol.5,2018
No.05 Vol.5,2018
No.04 Vol.5,2018
No.03 Vol.5,2018
No.02 Vol.5,2018
No.01 Vol.5,2018
No.04 Vol.4,2017
No.03 Vol.4,2017
No.02 Vol.4,2017
No.01 Vol.4,2017
No.09 Vol.3,2016
No.08 Vol.3,2016
No.07 Vol.3,2016
No.06 Vol.3,2016
No.05 Vol.3,2016
No.04 Vol.3,2016
No.03 Vol.3,2016
No.02 Vol.3,2016
No.01 Vol.3,2016
No.02 Vol.2,2015
No.01 Vol.2,2015
No.02 Vol.1,2014
No.01 Vol.1,2014
China
Asia
Oceanic region
African
European
North American
South American
Arctic
Global Scale
Data Details

Temperature Vegetation Dryness Index 1-km Grid Dataset in Amur River Basin (2007-2018)


ZHOU Yezhi1,2WANG Juanle*1
1 State Key Laboratory of Resources and Environmental Information System，Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China2 College of Geoscience and Surveying Engineering，China University of Mining & Technology (Beijing)，Beijing 100083，China

DOI:10.3974/geodb.2021.05.02.V1

Published:May 2021

Visitors：10364       Data Files Downloaded：68      
Data Downloaded：21745.61 MB      Citations：

Key Words：

Amur River Basin,growing season,TVDI,2007-2018

Abstract：

The temperature vegetation dryness index 1-km grid dataset in Amur River Basin (2007-2018) was developed based on integration among the monthly MOD13A3 NDVI, MOD11A2 Land Surface Temperature (LST) and ASTER-DEM data with the NDVI-LST feature space and TVDI model. The dataset is archived in .tif data format, and consists of 84 data files with data size of 362 MB (compressed to one single file with 319 MB).Browse

Foundation Item：

Chinese Academy of Sciences (Y9X90050Y2）；China Knowledge Center for Engineering Sciences and Technology (CKCEST-2020-2-4)

Data Citation：

ZHOU Yezhi, WANG Juanle*. Temperature Vegetation Dryness Index 1-km Grid Dataset in Amur River Basin (2007-2018)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2021. https://doi.org/10.3974/geodb.2021.05.02.V1.

ZHOU Yezhi, WANG Juanle, LI Kai. Temperature vegetation dryness index 1-km grid dataset in Heilongjiang River basin (2007-2018) [J]. Journal of Global Change Data & Discovery, 2021, 5(3): 333-345. https://doi.org/10.3974/geodp.2021.03.11.

References：

[1] Sandholt, I., Rasmussen, K., Andersen, J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status [J]. Remote Sensing of Environment, 2002, 79(2): 213-224.
     [2] Huang, Y. F., Li, T. J., Lv, E. Z., et al. Boundary data of the Amur River Basin [J/DB/OL]. Digital Journal of Global Change Data Repository, 2016. DOI: 10.3974/geodb.2016.03.11.V1.
     [3] Huang, Y. F., Li, T. J., Lv, E. Z., et al. Boundary data of the Amur River Basin [J]. Journal of Global Change Data & Discovery, 2017, 1(1): 114. DOI: 10.3974/geodp.2017.01.18.
     [4] Chen, Y. Z., Feng, X. M., Fu, B. J. Global 10-day surface soil moisture dataset (RSSSM, 2003-2018) [J/DB/OL]. Digital Journal of Global Change Data Repository, 2021. DOI: 10.3974/geodb.2021.02.01.V1.
     [5] Chen, Y. Z., Feng, X. M., Fu, B. J. An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003-2018 [J], Earth System Science Data, 2021, 13: 1-31. DOI: 10.5194/essd-13-63-2021.
     

Data Product:

ID Data Name Data Size Operation
0Datapaper_TVDI_AmurRiverBasin_2007-2018.pdf2638.00kbDownLoad
1 TVDI_AmurRiverBasin_2007-2018.rar 327463.38KB
Co-Sponsors
Superintend