期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2010
卷号：XXXVIII - Part 8
页码：902-907
出版社：Copernicus Publications
摘要：Vegetation species maps are useful for forestry managements and environmental ecological study. From the forestry management, broad and conifer leaf forest should be mapped. In addition to them, land-cover mapping data with high resolution is needed as validation data sets for low resolution's land-cover mapping results. SGLI sensor on board GCOM-C satellite, which will be launched in 2014, has 250m spatial resolution and it's data will be used for making global land-cover data set. ALOS satellite was launched in 2006. It has AVNIR-2 sensor and PRISM sensor. AVNIR-2 sensor has four spectral bands 460, 560, 650 and 830nm with 10-m spatial resolution. PRISM sensor has panchromatic band from 520nm to 770 nm with 2.5m spatial resolution. If use the both of image, pseudo high spatial multi-spectal image can be processed. Because of the spatial resolution and multi-spectral information, these sensor data are expected to useful for making high resolution land-cover data set. We have developed Universal Pattern Decomposition Method (UPDM)( Zhang, L.F. et.al, 2006 (Zhang et al., 2006)) and Modified Vegetation Index based on UPDM (MVIUPD)(Zhang, L.F. et. al, 2007 (Zhang et al., 2007) and Xiong, Y., 2005 (.)) for satellite sensor data analysis for land cover mapping and vegetation monitoring. In the UPDM method, three coefficients of water, vegetation and soil is calculated using three standard patterns of water, vegetation and soil. One of this method's characteristics is the UPDM coefficients from different sensors for the same object being same as each other. The capability of vegetation species mapping was studied with ALOS/AVNIR-2 data and UPDM method. Japanese cedar, Japanese cypress, deciduous forest, bamboo forest, orchard and grass land can be classified using AVNIR-2 summer and winter data. In this study, AVNIR-2 and PRISM data are used for vegetation types mapping using universal pattern decomposition method. Firstly, the pan-sharpen image was processed using AVNIR-2 and PRISM data. Each band's Digital Number (DN) value of AVNIR-2's band is calculated using DN of PRISM and AVNIR-2. The re.ectance of AVNIR-2 is calculated from calculated DN values. UPDM method is applied to the set of re-calculated re.ectance. Using the coefficients of UPDM and vegetation index, evergreen forest and deciduous forest were classified using two seasonal data. These results are compared with forest resource information. The tendency was agree with each other, although detailed validation is needed. From these results, the UPDM method can be applied to pan-sharpen image and the pan-sharpen image can be used for vegetation type classification. In the near future, calculation methods with retaining the original re.ectance should be improved
