Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional meth...Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.展开更多
In order to characterize the forest fires in the province of Sidi Bel Abbes （North West of Algeria） and depending on a statistical data analysis of a 17-year period （1996-2012）, our works are oriented toward a stu...In order to characterize the forest fires in the province of Sidi Bel Abbes （North West of Algeria） and depending on a statistical data analysis of a 17-year period （1996-2012）, our works are oriented toward a study of the area covered by forest fires in the 53 constituent municipalities of the region. To do this, we depended on the archives of the forest fires balance sheets in forest conservation in the wilaya of Sidi Bel Abbes. The results show that the region lost an annual average 29,929 ha of its total forest area for a maximum of 11,817.5 ha recorded in 2012. On the other hand, the use of the fire severity index ＂FSI＂ by town and its cartography in which we used the map of administrative division of the study area as support, has divided the region into six classes according to the risk of fire, where the municipalities belonging to the forest of Telagh whose land is rugged represent the risk of fire is greater. Indeed, this situation category the study area among the most exposed wilaya and the most affected by this problem at the national level and require new approaches to forest management for its conservation. These are paramount in reducing the risk of fires based on appropriate management plans to be established for each forest conservation area.展开更多
Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrolo...Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.展开更多
基金Under the auspices of National Natural Science Foundation of China (No. 40871241, 40771170)National High Technology Research and Development Program of China (No. 2007AA12Z176)
文摘Wetland research has become a hot spot linking multiple disciplines presently. Wetland classification and mapping is the basis for wetland research. It is difficult to generate wetland data sets using traditional methods because of the low accessibility of wetlands, hence remote sensing data have become one of the primary data sources in wetland research. This paper presents a case study conducted at the core area of Honghe National Nature Reserve in the Sanjiang Plain, Northeast China. In this study, three images generated by airship, from Thematic Mapper and from SPOT 5 were selected to produce wetland maps at three different wetland landscape levels. After assessing classification accuracies of the three maps, we compared the different wetland mapping results of 11 plant communities to the airship image, 6 plant ecotypes to the TM image and 9 landscape classifications to the SPOT 5 image. We discussed the different characteristics of the hierarchical ecosystem classifications based on the spatial scales of the different images. The results indicate that spatial scales of remote sensing data have an important link to the hierarchies of wetland plant ecosystems displayed on the wetland landscape maps. The richness of wetland landscape information derived from an image closely relates to its spatial resolution. This study can enrich the ecological classification methods and mapping techniques dealing with the spatial scales of different remote sensing images. With a better understanding of classification accuracies in mapping wetlands by using different scales of remote sensing data, we can make an appropriate approach for dealing with the scale issue of remote sensing images.
文摘In order to characterize the forest fires in the province of Sidi Bel Abbes （North West of Algeria） and depending on a statistical data analysis of a 17-year period （1996-2012）, our works are oriented toward a study of the area covered by forest fires in the 53 constituent municipalities of the region. To do this, we depended on the archives of the forest fires balance sheets in forest conservation in the wilaya of Sidi Bel Abbes. The results show that the region lost an annual average 29,929 ha of its total forest area for a maximum of 11,817.5 ha recorded in 2012. On the other hand, the use of the fire severity index ＂FSI＂ by town and its cartography in which we used the map of administrative division of the study area as support, has divided the region into six classes according to the risk of fire, where the municipalities belonging to the forest of Telagh whose land is rugged represent the risk of fire is greater. Indeed, this situation category the study area among the most exposed wilaya and the most affected by this problem at the national level and require new approaches to forest management for its conservation. These are paramount in reducing the risk of fires based on appropriate management plans to be established for each forest conservation area.
基金Under the auspices of National High Technology Research and Development Program of China (No. 2007AA12Z176)National Natural Science Foundation of China (No. 40771170)Natural Science Foundation of Beijing (No. 8082010)
文摘Taking a typical inland wetland of Honghe National Nature Reserve (HNNR), Northeast China, as the study area, this paper studied the application of L-band Synthetic Aperture Radar (SAR) image in extracting eco-hydrological information of inland wetland. Landsat-5 TM and ALOS PALSAR HH backscatter images were first fused by using the wavelet-IHS method. Based on the fused image data, the classification method of support vector machines was used to map the wetland in the study area. The overall mapping accuracy is 77.5%. Then, the wet and dry aboveground biomass estimation models, including statistical models and a Rice Cloudy model, were established. Optimal parameters for the Rice Cloudy model were calculated in MATLAB by using the least squares method. Based on the validation results, it was found that the Rice Cloudy model produced higher accuracy for both wet and dry aboveground biomass estimation compared to the statistical models. Finally, subcanopy water boundary information was extracted from the HH backscatter image by threshold method. Compared to the actual water borderline result, the extracted result from L-band SAR image is reliable. In this paper, the HH-HV phase difference was proved to be valueless for extracting subcanopy water boundary information.
