Estimating tropical forest biomass more accurately by integrating ALOS PALSAR and Landsat-7 ETM+ data
| Autor: | Andrew K. Skidmore, Tyas Mutiara Basuki, Yousif A. Hussin, Iris van Duren |
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| Přispěvatelé: | Department of Natural Resources, Faculty of Geo-Information Science and Earth Observation, UT-I-ITC-FORAGES |
| Rok vydání: | 2013 |
| Předmět: |
Synthetic aperture radar
Discrete wavelet transform Backscatter jers-1 sar satellite estimation multiresolution wavelet transform lidar Remote sensing decomposition Forest inventory band sar queensland Wavelet transform Vegetation PE&RC Sample (graphics) Lidar ITC-ISI-JOURNAL-ARTICLE Wildlife Ecology and Conservation 2023 OA procedure General Earth and Planetary Sciences Environmental science multisensor image fusion aboveground biomass |
| Zdroj: | International Journal of Remote Sensing 34 (2013) 13 International journal of remote sensing, 34(13), 4871-4888. Taylor & Francis International Journal of Remote Sensing, 34(13), 4871-4888 |
| ISSN: | 1366-5901 0143-1161 |
| Popis: | Integration of multisensor data provides the opportunity to explore benefits emanating from different data sources. A fusion between fraction images derived from spectral mixture analysis of Landsat-7 ETM+ and phased array L-band synthetic aperture radar (PALSAR) is introduced. The aim of this fusion is to improve the estimation accuracy of above-ground biomass (AGB) in lowland mixed dipterocarp forest. Spectral mixture analysis was applied to decompose a mixture of spectral components of Landsat-7 ETM+ into vegetation, soil, and shade fractions. These fraction images were integrated with PALSAR data using the discrete wavelet transform (DWT) and Brovey transform. As a comparison, spectral reflectance of Landsat-7 ETM+ was fused directly with PALSAR data. Backscatter of horizontal-horizontal and horizontal-vertical polarizations was also used to estimate AGB. Forest inventory was carried out in 77 randomly distributed plots, the data being used for either model development or validation. A local allometric equation was applied to calculate AGB per plot. Regression models were developed by integrating field measurements of 50 sample plots with remotely sensed data, e.g. fraction images, reflectance of Landsat-7 ETM+, and PALSAR data. The models developed were validated using 27 independent sample plots. The results showed that not all fused images significantly improved the accuracy of AGB estimation. The model based on Brovey transform using the reflectance of Landsat-7ETM+ and PALSAR produced an R 2 of only 0.03-0.10. By contrast, fusion between PALSAR data and fraction images using Brovey transform improved the accuracy of R 2 to 0.33-0.46. Further improvement in the accuracy of estimating AGB was observed when DWT was applied to integrate PALSAR with the reflectance of Landsat-7ETM+ (R 2 = 0.69-0.72) and PALSAR with fraction images (R 2 = 0.70-0.75). |
| Databáze: | OpenAIRE |
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