Investigating relationship between Landsat ETM+ data and LAI in a semi-arid grassland of Northwest China

Author

Lu, L. ; Li, X. ; Ma, M.G. ; Che, T. ; Huang, C.L. ; Veroustraete, F. ; Dong, Q.H. ; Ceulemans, R. ; Bogaert, J.

Author_Institution

Cold & Arid Regions Environ. & Eng. Res. Inst., Chinese Acad. of Sci., Lanzhou

Volume

6

fYear

2004

fDate

20-24 Sept. 2004

Firstpage

3622

Abstract

A field campaign was executed in a semi-arid grassland of northwest China from July 11th-July 15th, 2002. According to the VALERI (Validation of Land European Remote Sensing Instruments) sampling procedures, the leaf area index (LAI) were intensively measured within a homogenous 3times3 km² square by using LAI-2000 and TRAC instrument. A quarter scene of Landsat7 ETM+ with acquisition times close to the field campaign time was processed by proper geo-registration and atmospheric correction. Three kinds of spectral vegetation index including NDVI, SR and MSAVI in the sampling area were derived from the corrected ETM+ image. The two sets of LAI data measured with LAI-2000 and TRAC instrument at the same site were inter-compared. The relationships between the measured LAI and vegetation indices were investigated as well. The results elicit that the statistical relationships between measured LAI and the different vegetation indices are consistent. Among them, NDVI seems the most promising estimator for the extraction of LAI. In addition, the LAI-2000 seems to perform better for LAI measurement in the semi-arid grassland than the TRAC instrument

Keywords

data acquisition; terrain mapping; vegetation mapping; AD 2002 07 11 to 15; LAI measurement; LAI-2000; Landsat ETM+ data; Landsat7 ETM+; MSAVI; NDVI; Northwest China; SR; TRAC instrument; VALERI; Validation of Land European Remote Sensing Instruments; atmospheric correction; data acquisition; georegistration; leaf area index; semiarid grassland; spectral vegetation index; statistical relationships; Area measurement; Atmospheric measurements; Image sampling; Instruments; Layout; Remote sensing; Sampling methods; Satellites; Strontium; Vegetation mapping;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International

Conference_Location

Anchorage, AK

Print_ISBN

0-7803-8742-2

Type

conf

DOI

10.1109/IGARSS.2004.1369902

Filename

1369902