Paper
21 November 2012 Study on forest above-ground biomass synergy inversion from GLAS and HJ-1 data
Zhou Fang, Chunxiang Cao, Wei Ji, Min Xu, Wei Chen
Author Affiliations +
Proceedings Volume 8524, Land Surface Remote Sensing; 85241D (2012) https://doi.org/10.1117/12.977449
Event: SPIE Asia-Pacific Remote Sensing, 2012, Kyoto, Japan
Abstract
The need exists to develop a systematic approach to inventory and monitor global forests, both for carbon stock evaluation and for land use change analysis. The use of freely available satellite-based data for carbon stock estimation mitigates both the cost and the spatial limitations of field-based techniques. Spaceborne lidar data have been demonstrated as useful for forest aboveground biomass (AGB) estimation over a wide range of biomass values and forest types. However, the application of these data is limited because of their spatially discrete nature. Spaceborne multispectral sensors have been used extensively to estimate AGB, but these methods have been demonstrated as inappropriate for forest structure characterization in high-biomass mature forests. This study uses an integration of ICESat Geospatial Laser Altimeter System (GLAS) lidar and HJ-1 satellites data to develop methods to estimate AGB in an area of Qilian Mountains, Northwest China. Considering the study area belongs to mountainous terrain, the difficulties of this article are how to extract canopy height from GLAS waveform metrics. Combining with HJ-1 data and ground survey data of the study area, we establish forest biomass estimation model for the GLAS data based on BP neural network model. In order to estimate AGB, the training sample data includes the canopy height extracted from GLAS, LAI, vegetation coverage and several kinds of vegetation indices from HJ-1 data. The results of forest aboveground biomass are very close to the fields measured results, and are consistent with land cover data in the spatial distribution.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhou Fang, Chunxiang Cao, Wei Ji, Min Xu, and Wei Chen "Study on forest above-ground biomass synergy inversion from GLAS and HJ-1 data", Proc. SPIE 8524, Land Surface Remote Sensing, 85241D (21 November 2012); https://doi.org/10.1117/12.977449
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KEYWORDS
Vegetation

Data modeling

Biological research

LIDAR

Neural networks

Remote sensing

Satellites

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