JOURNAL OF NATURAL RESOURCES ›› 2006, Vol. 21 ›› Issue (1): 126-132,166.doi: 10.11849/zrzyxb.2006.01.016

• Special Column:Celebration of the 70th Anniversary of IGSNRR, CAS • Previous Articles     Next Articles

Dynamic Monitoring of Vegetation Fraction by Remote Sensing in Changting County of Fujian Province

JIANG Hong, WANG Qin-min, WANG Xiao-qin   

  1. Key Laboratory of Data Mining & Information Sharing of Ministry of Education,Spatial Information Research Center of Fujian Province,Fuzhou University,Fuzhou 350002,China
  • Revised:2005-09-13 Online:2006-02-25 Published:2006-02-25

Abstract: Vegetation index(VI)and the transformation method of VI are two key factors in estimating vegetation fraction by Remote Sensing.Based on the common VI and the FCD(Forest Canopy Density)Model principle put forward by ITTO(International Tropical Timber Organization),VBSI vegetation index was proposed in this paper that can decrease the interferences from mountain shadows,soil background,rocks and building.It is expressed as VBSI=f(VI,BI,SI)=VI+n·BI+SI which is suitable for estimating vegetation coverage in mountainous areas.Furthermore,mixed pixel model is one of the good transformation methods from VI to vegetation fraction,which can apply to images from different phases.The expression is:fc=(S-Snon)/(Sveg-Snon).Vegetation fraction estimation in 1994-2003 was processed with ERDAS software system aimed at Chang-ting County,Fujian Province,China.The results show that(1)With VBSI,the error of vegetation fraction resulted from the area of image shadow can be decreased,and the error is 50% of that from Normalized Difference Vegetation Index(NDVI).The overall accuracy from the vegetation fraction estimation based on VBSI and mixed pixel model is more than 80%,which meets the requirements for vegetation fraction dynamic monitoring in region.(2)The coverage of high vegetation in the study area increased by 150.47km2,or an increase of 4.9% of the total land area from 1994 to 2003.This is correlative with the work of soil and water conservation in recent years in Changting County.

Key words: mixed pixel model, dynamic monitoring by RS, vegetation fraction, VBSI vegetation index