Using aerial photos and high resolution satellite images of the year of 2004,this paper establishes remote sensing interpretation marks of the Great Wall of Ming Dynasty's damaged levels. Based on field survey and remote sensing survey in 1984,we analyzed present situation and changing characteristics being of the Great Wall of Ming Dynasty in Beijing. The results show that about 7.02% of the wall is well-preserved (about 25861 m); 31.5% of the wall is slightly or moderately dam-aged (about 115989 m); 61.5% of the wall is badly damaged (about 226379 m). This paper analyzes the dynamic change of the Great Wall of Ming Dynasty. It shows that the damaged situation of the Great Wall of Ming Dynasty in Beijing is serious. From 1984 to 2004,the well-preserved wall is decreased by 33206 m (decreased by 56%); badly damaged wall increased by 51207 m (increased by 67%). Finally,this paper analyzes the influence factors of damaging Great Wall. The conclusion is as follows: The damaged Great Wall is generally near the roads and villages,small slope,and easily arriving land.
LI XiaoJuan,GONG HuiLi,ZHANG Ou,ZHANG WeiGuang & SUN YongHua The Key Lab of 3D Information Acquisition and Application,MOE,the Key Lab of Beijing Resource Envi-ronment and GIS,and College of Resource Environment & Tourism,Capital Normal University,Beijing 100037,China
Based on multi-source data,this paper evaluated the economic value of ecological services in the Yeyahu Wetland Nature Reserve,Beijing,China.The ecological services of wetland included gas regulation,water quality im-provement,biodiversity maintenance,erosion control,water supply,recreational opportunity,raw material supply and existence value.Multiple conventional evaluation methods were used to calculate the value of eight wetland services.The results showed that significant values came from biodiversity maintenance and recreational opportunity.The main reasons were as follows.Firstly,Yeyahu Wetland Nature Reserve was the habitat for migrant birds,and government had payed more efforts to protect precious birds.Secondly,the population is large in Beijing.People enjoyed going outside and enjoyed the natural and artificial wetland scenes.At the same time,most people were prepared to pay for wetland conservation.The decline of vegetation cover made the economic value of erosion control the lowest.While the shrink of water resource and the deteriorative water quality caused the economic value of water supply lower.The evaluation results could help decision-makers understand the present status of the Yeyahu Wetland Nature Reserve and provide a scientific basis for strategic decision.
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.
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.
SUN YonghuaGONG HuiliLI XiaojuanPU RuiliangLI Shuang
