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Data Details

1 km/ 5-day NDVI Product over China and the Association of Southeast Asian Nations for 2013


LI Jing1ZENG Yelu1LIU Qinhuo1ZHONG Bo1WU Shanlong1PENG Jingjing1
1State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences

DOI:10.3974/geodb.2015.01.16.V1

Published:Jun. 2015

Visitors:14609       Data Files Downloaded:7324      
Data Downloaded:1855097.98 MB      Citations:

Key Words:

China-ASEAN,NDVI,BRDF,Quality grade

Abstract:

A synergized algorithm is developed to generate 1km/5-day Normalized Difference Vegetation Index (NDVI) product using multi-source remote sensing dataset over China and the Association of Southeast Asian Nations (ASEAN) for 2013 (MuSyQ-NDVI-1km-2013). The multi-source dataset include five satellite data at 1-km spatial resolution including Terra/MODIS,Aqua/MODIS,NOAA18/AVHRR,FY3A/VIRR, and FY3B/VIRR. The quality of the multi-source observation data varies with sensors and atmospheric conditions. For the effective use of the dataset, the proposed algorithm firstly classifies the multi-angular observations into three levels by the residual thresholds of 10%, 20% and “larger than 20%” in a robust NDVI-weighted kernel-driven Bidirectional Reflectance Distribution Function (BRDF) model. The observations with the residual larger than 20% are considered as cloudy and will be excluded for following NDVI compositing. Then the NDVI is composited by the main algorithm or backup algorithm according to the number of good quality observations. The composited NDVI is compared with the MODIS NDVI product in the Heihe River Basin, China. Results indicate that the number of good quality observations increase by the multi-source synergized retrieval, and the temporal resolution is increased from quasi-8-day to 5-day. The evaluation by the ASTER images at the 15-m resolution indicates that the determination coefficient (R2) is significantly higher for the multi-source NDVI, than the MODIS-only NDVI product. The China–ASEAN NDVI product is produced in the Sinusoidal tile grid, and is distributed in 40 adjacent non-overlapping tiles that are approximately 10��10� (at the equator). The spatial/temporal resolution of the product is 1 km/5 days. The dataset is archived in *.tif format, and is compressed in 40 .zip files with the total volume of 9.89GB.

Foundation Item:

Data Citation:

LI Jing,ZENG Yelu,LIU Qinhuo,ZHONG Bo,WU Shanlong,PENG Jingjing.1 km/ 5-day NDVI Product over China and the Association of Southeast Asian Nations for 2013[DB/OL].Global Change Data Repository,2015.DOI:10.3974/geodb.2015.01.16.V1.

Li, J., Zeng, Y. L, Liu, Q. H., et al. 1 km/5 day NDVI data product over China-ASEAN (2013) [J]. Journal of Global Change Data & Discovery, 2017, 1(3): 268-277. DOI: 10.3974/geodp.2017. 03.03.

Data Product:

ID Data Name Data Size Operation
1 H23V04.zip 246425.91KB
2 H23V05.zip 248684.31KB
3 H24V04.zip 251311.10KB
4 H24V05.zip 262655.19KB
5 H24V06.zip 279609.25KB
6 H25V03.zip 284285.84KB
7 H25V04.zip 227305.40KB
8 H25V05.zip 262051.22KB
9 H25V06.zip 303887.59KB
10 H26V03.zip 249508.42KB
11 H26V04.zip 273894.24KB
12 H26V05.zip 297070.50KB
13 H26V06.zip 319430.03KB
14 H26V07.zip 203915.75KB
15 H27V04.zip 291022.04KB
16 H27V05.zip 280812.80KB
17 H27V06.zip 306562.22KB
18 H27V07.zip 291165.67KB
19 H27V08.zip 241285.24KB
20 H27V09.zip 207961.19KB
21 H28V04.zip 233214.27KB
22 H28V05.zip 267561.91KB
23 H28V06.zip 285346.46KB
24 H28V07.zip 277260.10KB
25 H28V08.zip 251383.84KB
26 H28V09.zip 262087.45KB
27 H29V05.zip 250837.91KB
28 H29V06.zip 222791.68KB
29 H29V07.zip 232964.92KB
30 H29V08.zip 269746.19KB
31 H29V09.zip 272780.35KB
32 H29V10.zip 228929.05KB
33 H30V07.zip 221119.07KB
34 H30V08.zip 242233.58KB
35 H30V09.zip 246616.17KB
36 H30V10.zip 256687.35KB
37 H31V08.zip 202877.12KB
38 H31V09.zip 277760.23KB
39 H31V10.zip 273526.72KB
40 H32V09.zip 276028.00KB
Co-Sponsors

Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences

The Geographical Society of China

Parteners

Committee on Data for Science and Technology (CODATA) Task Group on Preservation of and Access to Scientific and Technical Data in/for/with Developing Countries (PASTD)

Jomo Kenyatta University of Agriculture and Technology

Digital Linchao GeoMuseum