Title :
Combining Spot4-vegetation and meteorological data derived land cover map in China
Author :
Bingfang, Wu ; Wenting, Xu ; Huiping, Huang ; Changzhen, Yan ; Wenbo, Xu
Author_Institution :
Inst. of Remote Sensing Applications, Chinese Sci. Acad., Beijing, China
Abstract :
The global version of the 1km spatial resolution land cover map have been finished at the end of 2003, which is initiated by the European Commission´s Joint Research Center, named Global Land Cover 2000 Project (GLC-2000). As a part of GLC2000, the China window has been developed with the 10-day composite SPOT VGT NDVI data over a period of 01 January 2000 to 31 December 2000, DEM and the Meteorological data (Multi-annual average temperature, multi-annual average precipitation data) collected from 313 weather stations distributed over the China from 1971 to 2000. In order to remove cloud contamination and interpolate the missing data masked by cloud, the Harmonic Analysis of Time Series (HANTS) was applied to NDVI data. With the assistance of Erdas ISODATA algorithm, the classification has been carried out, and 22 types of land cover has labeled in the whole China by interpreting according to the Land Cover Classification System (LCCS) developed by the UN Food and Agriculture Organization (FAO) in the framework of the AFRICOVER project. Preliminary comparisons with the statistic data from Chinese Statistics Bureau and TM data show very promising results, and the accuracv assessment of the GLC-2000 is underway.
Keywords :
atmospheric precipitation; atmospheric techniques; atmospheric temperature; data assimilation; image classification; time series; vegetation mapping; AD 1971 to 2000; AFRICOVER project; China; Chinese Statistics Bureau; Erdas ISODATA algorithm; GLC-2000; Global Land Cover 2000 Project; Land Cover Classification System; SPOT VGT NDVI data; Spot4; TM data; UN Food and Agriculture Organization; cloud contamination; harmonic analysis; image classification; land cover map; meteorological data; multiannual average precipitation; multiannual average temperature; spatial resolution; time series; vegetation data; weather station; Clouds; Databases; Ecosystems; Land surface temperature; Meteorology; Remote sensing; Resource management; Satellites; Spatial resolution; Statistics;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
Print_ISBN :
0-7803-8742-2
DOI :
10.1109/IGARSS.2004.1369850