In this paper, a digital identification method for the extraction of altitudinal belt spectra of montane natural belts is presented. Acquiring the sequential spectra of digital altitudinal belts in mountains at an acc...In this paper, a digital identification method for the extraction of altitudinal belt spectra of montane natural belts is presented. Acquiring the sequential spectra of digital altitudinal belts in mountains at an acceptable temporal frequency and over a large area requires extensive time and work if traditional methods of field investigation are to be used. Such being the case, often the altitudinal belts of a whole mountain or the belts at a regional scale are represented by single points. However, single points obviously cannot accurately reflect the spatial variety of altitudinal belts. In this context, a digital method was developed to extract the spectra of altitudinal belts from remote sensing data and SRTM DEM in the We.st Kunlun Mountains. By means of the 4km resolution SPOT-4 vegetation 10-day composite NDVI, the horizontal distribution of altitudinal belts were extracted through supervised classification, with a total classification accuracy of 72.23%. Then, a way of twice-scan was used to realize the automatic transition of horizontal maps to vertical belts. The classification results of remote-sensing data could thus be transformed automatically to sequential spectra of digital altitudinal belts. The upper and lower lines of the altitudinal belts were then extracted by vertical scanning of the belts. Relationships between the altitudinal belts based on the montane natural zones concerning vegetation types and the geomorphological altitudinal belts discussed. As a tentative method, were also the digital extraction method presented here is effective at digitally identifying altitudinal belts, and could be helpful in rapid information extraction over large-scale areas.展开更多
A regional map of mangrove forests was produced for six islands located in the southern part of Japan by integrating the spectral analyses of Landsat Enhanced Thematic Mapper plus (ETM+) images with a digital elevatio...A regional map of mangrove forests was produced for six islands located in the southern part of Japan by integrating the spectral analyses of Landsat Enhanced Thematic Mapper plus (ETM+) images with a digital elevation model (DEM). Several attempts were applied to propose a reliable method, which can be used to map the distribution of mangrove forests at a regional scale. The methodology used in this study comprised of obtaining the difference between Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI), band ratio 5/4, and band 5, from Landsat ETM+, and integrating them with the topographic information. The integration of spectral analyses with topographic data has clearly separated the mangrove forests from other vegetation. An accuracy assessment was carried out in order to check the accuracy of the results. High overall accuracy ranging from 89.3% to 93.6% was achieved, which increased the opportunity to use this methodology in other countries rich in mangrove forests.展开更多
基金funded by the National Natural Science Foundation of China (Grant No.40801045)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. kzcx2-yw-141)+2 种基金the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. 0609211120)the National Natural Science Foundation of China (Grant No. 40801186)support from the postdoctoral project of UNAM
文摘In this paper, a digital identification method for the extraction of altitudinal belt spectra of montane natural belts is presented. Acquiring the sequential spectra of digital altitudinal belts in mountains at an acceptable temporal frequency and over a large area requires extensive time and work if traditional methods of field investigation are to be used. Such being the case, often the altitudinal belts of a whole mountain or the belts at a regional scale are represented by single points. However, single points obviously cannot accurately reflect the spatial variety of altitudinal belts. In this context, a digital method was developed to extract the spectra of altitudinal belts from remote sensing data and SRTM DEM in the We.st Kunlun Mountains. By means of the 4km resolution SPOT-4 vegetation 10-day composite NDVI, the horizontal distribution of altitudinal belts were extracted through supervised classification, with a total classification accuracy of 72.23%. Then, a way of twice-scan was used to realize the automatic transition of horizontal maps to vertical belts. The classification results of remote-sensing data could thus be transformed automatically to sequential spectra of digital altitudinal belts. The upper and lower lines of the altitudinal belts were then extracted by vertical scanning of the belts. Relationships between the altitudinal belts based on the montane natural zones concerning vegetation types and the geomorphological altitudinal belts discussed. As a tentative method, were also the digital extraction method presented here is effective at digitally identifying altitudinal belts, and could be helpful in rapid information extraction over large-scale areas.
文摘A regional map of mangrove forests was produced for six islands located in the southern part of Japan by integrating the spectral analyses of Landsat Enhanced Thematic Mapper plus (ETM+) images with a digital elevation model (DEM). Several attempts were applied to propose a reliable method, which can be used to map the distribution of mangrove forests at a regional scale. The methodology used in this study comprised of obtaining the difference between Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI), band ratio 5/4, and band 5, from Landsat ETM+, and integrating them with the topographic information. The integration of spectral analyses with topographic data has clearly separated the mangrove forests from other vegetation. An accuracy assessment was carried out in order to check the accuracy of the results. High overall accuracy ranging from 89.3% to 93.6% was achieved, which increased the opportunity to use this methodology in other countries rich in mangrove forests.
