Two wetland maps for the entire China have been produced based on Landsat data acquired around 1990 and 2000. Wetlands in China have been divided into 3 broad categories with 15 sub-categories except rice fields. In 1990, the total wetland area in China was 355208 km2 whereas in 2000 it dropped to 304849 km2 with a net loss of 50360 km2. During an approximate 10-year period, inland wetland reduced from 318326 to 257922 km2, coastal wetland dropped from 14335 to 12015 km2, while artificial wetland increased from 22546 to 34911 km2. The greatest natural wetland loss occurred in Heilongjiang, Inner Mon- golia, and Jilin with a total loss of over 57000 km2 of wetland. In western China, over 13000 km2 of wetlands were newly formed in Xinjiang, Tibet, and Qinghai. About 12000 km2 of artificial wetlands were also added for fish farm and reservoir constructions. The newly formed wetlands in western China were caused primarily by climate warming over that region whereas the newly created artificial wetlands were caused by economic developments. China’s wetland loss is caused mainly by human activities.
In this paper,I propose a personal view on the general contents of remote sensing science and technology,which includes sensor research and manufacturing,remotely sensed data acquisition,data processing,information extraction and remote sensing applications.Serving as the basis for all these components is radiative transfer process modeling and inversion.Also of importance is the effective visualization of remotely sensed data and their efficient distribution to end users.In all these areas,there are critical research questions.In particular,I consider 4 fundamental areas for improved application of remote sensing.These include the scale and angular issues in remote sensing,removal of topographic effects on the radiance and geometry of remotely sensed imagery and the related question of multisource and multitemporal data registration,integrating knowledge and remotely sensed data into effective information extraction,and four dimensional data assimilation techniques.Strategies of information extraction can be broadly divided into manual visual analysis and computer-based analysis.The computer based information analysis include radiative transfer model inversion,image classification,regression analysis,three dimensional information extraction,shape analysis and change detection.Successful information extraction is the key to the success of remote sensing.There are many important issues that need to be solved including how to make better use of the spatial and temporal data present in remotely sensed data in information extraction.How to effectively combine the strength of both computer analysis and human interpretation? Finally,4D data assimilation is the new direction that allows for the integration of instantaneous observation with process-based climate,hydrological and ecological models.Further work along this direction will enhance the contribution of remote sensing in global change studies.In return,the quality of remotely sensed parameters can be improved.
Using China Bird Report(2003-2007) as data source in combination with descriptions about bird habitats,we built up the China Bird Watching Database.We also developed spherical GIS software "Global Analyst" to create the point-based database which contains accurate spatial-temporal information.The China Bird Watching Database can reflect the achievement of Chinese bird watchers and complement the basic knowledge of bird distribution.Now a total of 30936 records from 17 Orders,70 Families and 1078 Species of 5 years are included in the database,representing over 80% of all bird species in China.Till 2007,the geographic coverage has encompassed all provincial level administrative districts in China,with the exception of Hong Kong and Taiwan.The China Bird Watching Database also recorded a group of species which are additions at national and provincial levels,including 14 species which are additions to the national checklist and 109 species which appeared outside their original distributions.Comparing the new records with their original distributions,we found the trend that species move to higher latitude and higher elevation regions and some species of waterfowls in Xinjiang Uygur Autonomous Region,including a suite of rare seabirds in the China's Mainland.The majority of bird watchers come from the Eastern Region of China,but their covering range is spreading northwest.At the same time,we appeal to adopting a suite of new technologies for observation,and building up sharing platform of bird watching data to capture the distribution dynamics of birds in China and provide a direct foundation for bird conservation.
Schistosomiasis is a serious public health problem in the middle-lower Yangtze River Basin in China. Study of spatial variation of snail distribution that is related to microgeographic factors can help to choose pertinent measures for snail extinguishment and environment rebuilding. This paper studied the theoretical architecture of weights-of-evidence approach. The case study was made for spatial relation between the occurrence of infected snails and geographic factor combinations in Waijiazhou marshland of Poyang Lake region in China. The multievidence data came from the geographical factor combinations by crossing operation of vegetation coverage grade layer, cattle route distance grade layer, and special environment layer (181 combinations in total) in GIS. The calculation of weight contrast index shows that high vegetation coverage, cattle route distance of <45 meters, and special geographic factor "ground depression" had direct spatial relation with the occurrence of infected snails. The verification by crossing operation in GIS indicated 72.45% of the infected snails concentrated on the areas of positive weight contrast index (sequenced in an order of weight contrast index from high to low), demonstrating the high efficiency of the model established in finding infected snails according to the geographic factor combinations that can be explicitly discerned in the study area.
