Comparative analysis of HJ-1, SPOT, and TM data for leaf area index estimation in a mountainous area

Author

Huaan Jin ; Ainong Li ; Jinhu Bian

Author_Institution

Inst. of Mountain Hazards & Environ., Chengdu, China

fYear

2013

fDate

21-26 July 2013

Firstpage

2782

Lastpage

2785

Abstract

The leaf area index is one of key parameters for ecosystem monitoring, global carbon circulation and climate change. The remote sensing data from different satellites have become the primary data source for estimating leaf area index from regional to global scale. In this study, we assess the potential use of Landsat TM, HJ-1 CCD, and SPOT HRVIR sensors for leaf area index estimation in a mountainous area. Results suggest that three sensors behave similarly for LAI inversion over complicated terrain. The maximum correlation coefficients are in the order of broadleaf forest (0.82) > shrub/grass (0.78) > all plots (0.61) > needleleaf forest (0.53), which are derived from the field LAI-SPOT SWVI, TM SR, SPOT SWVI, and SPOT RSR relationships for all plots, needleleaf forest, broadleaf forest, and shrub/grass, respectively.

Keywords

remote sensing; vegetation; HJ-1 data; HJ-I CCD sensor; LAI-SPOT SWVI field; Landsat TM sensor; SPOT RSR field; SPOT SWVI field; SPOT VIR sensor; SPOT data; TM SR field; TM data; broadleaf forest; climate change; ecosystem monitoring; global carbon circulation; leaf area index; maximum correlation coefficients; mountainous area; remote sensing data; Earth; Indexes; Remote sensing; Satellite broadcasting; Satellites; Sensors; Vegetation mapping; HJ-1 CCD; Landsat TM; Leaf area index; SPOT4 HRVIR; mountainous area;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6723401

Filename

6723401