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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:3529       Data Files Downloaded:5214      
Data Downloaded:1318881.52 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.2015.1 km/ 5-day NDVI Product over China and the Association of Southeast Asian Nations for 2013 ( MuSyQ-NDVI-1km-2013 ) ,Global Change Research Data Publishing & Repository,DOI:10.3974/geodb.2015.01.16.V1

Data Product:

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