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    Remote sensing analysis on lake area variation of Lake Chad
    LIU Tiantian, LIU Ronggao, GE Quansheng
    PROGRESS IN GEOGRAPHY    2013, 32 (6): 906-912.   DOI: 10.11820/dlkxjz.2013.06.007
    Abstract1040)      PDF (8491KB)(1097)      
    Lake Chad, on the border of the Sahara desert in central Africa, is well known for its high sensitivity to hydroclimatic events. Over the last 40 years, Lake Chad, once the sixth largest lake in the world, has shrunk by more than 90% in area. In this paper, variations of the open water areas, extracted from multi-source remote sensing data during 1973-2012, are analyzed. The results showed that in general Lake Chad was getting smaller and smaller during 1973-2012. Between 1973 and 1975 its area sharply reduced by about 71%. From then on its area ranges from 2000 km 2 to 5000 km 2. In order to validate the reliability of the trends, this paper first compares it with Birkett's results to analyze area accuracy, and next compares the results of MODIS with Landsat and AVHRR to validate the comparability of multi-source data, and last monitors monthly variation of Lake Chad area to validate the feasibility of multi-temporal data. Meteorological data analysis showed that the area of Lake Chad and the fluctuation of annual precipitation were in good correlation. Secondly, a large number of reservoirs built are another important cause of area reduction. Lastly, the Great Barrier that divided the lake into two smaller lakes has made it more vulnerable to water loss.
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    Assessment of forest damage due to ice storm using image thresholding techniques: A case study of Yunnan Province
    WU Jiansheng, CHEN Sha, PENG Jian
    PROGRESS IN GEOGRAPHY    2013, 32 (6): 913-923.   DOI: 10.11820/dlkxjz.2013.06.008
    Abstract986)      PDF (4832KB)(908)      
    Ice storms are one of the severe disruptions to forest ecological systems, causing vegetation loss and reduction of the ecological systems' functions. For this reason it is vital to assess the damages to forests after ice storms. Using SPOT Normalized Difference Vegetation Index( NDVI) time serial images of Yunnan Province of China during 2000-2011, forest damage caused by ice storms in 2008 was assessed based on image thresholding techniques of post-storm NDVI time series after Savitzky-Golay filtering by TIMESAT software. The damage threshold was determined by the difference of standard deviation between the years with ice storms and those without, which eventually turned out to be 21%. The range of extracted forest damage is almost consistent with the ice storm extent of Yunnan in the national monthly disaster report, therefore the result is reliable. The destroyed vegetation accounted for 12.09% of the total area of forest. Forest within Diqing County and Nujiang County, in northwest Yunnan, suffered the most losses. On the whole, seven counties took the worst hit by the natural adversity, while thirteen were moderately affected and forty five slightly affected. The most severe damage of forest occurred at the elevation of 3300 m to 4000 m, the slope of 5 to 15 degree, the middle slope position and the east or northeast aspect. Even so, it had little to do with slope position because the most of vegetation is located in the middle slope position. In-situ measurement was not employed here to verify the results because of time and money limits, which compromised the overall accuracy. However, with the acceptable precision, the research method can be used as a real-time forest loss assessment, which is of great significance for taking effective measures to avoid secondary impacts and starting the process of recovery.
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    Cited: CSCD(8)
    Spatial distribution and evolution of city management events based on the spatial point pattern analysis: A case study of Jianghan District, Wuhan City
    SHE Bing, ZHU Xinyan, GUO Wei, XU Xiao
    PROGRESS IN GEOGRAPHY    2013, 32 (6): 924-931.   DOI: 10.11820/dlkxjz.2013.06.009
    Abstract1130)      PDF (2208KB)(1752)      
    Large amounts of data of historical events have been accumulated for many years through the operations of the Urban Grid Management System. These events are spatially aggregated. By examining the spatial distribution of these events and measuring the corresponding aggregation levels, we can provide important support for making sound decisions on allocation and distribution of urban management resources. Spatial point pattern analysis studies the distribution patterns of geographical point entities or events, and has been widely used in various disciplines including criminal statistics, ecology and public health. In this paper, we investigated two major types of city management events in Jianghan District, Wuhan City, traffic-blocking stall and garbage disposal events, from January to August in 2011. The results show that: the number of hotspots with traffic-blocking stall events had a decreasing trend, while that of garbage disposal events had an increasing trend. Both types of events presented significant spatial aggregation with roughly the same spatial scale of 1000 m. The spatiotemporal aggregation index indicated strong spatiotemporal correlations for both types of events where the space difference is below 500 m and time difference below 3 hours. The research shows that: with the help of spatial point pattern analysis, we can provide city managers with efficient visual analytics tools to identify spatial aggregation patterns of the events, and a quantitative method to measure the degree of spatial aggregation, which also lays a foundation for further statistical modeling.
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    Cited: CSCD(12)
    Comparison of land-use structure fractal dimension based on vector and raster data: A case study of Suzhou City
    ZHANG Jing, PU Lijie, ZHU Ming, XU Yan, LI Peng
    PROGRESS IN GEOGRAPHY    2013, 32 (6): 932-939.   DOI: 10.11820/dlkxjz.2013.06.010
    Abstract1114)      PDF (1614KB)(917)      
    Land use system is the product of natural and human activities, and typically as a complex nonlinear dynamical system, its structure is irregular, unstable, complex and non-linear. Fractal theory, as a new technique, has been proved to be practical for analyzing irregular and nonlinear objects. The fractal dimension, one of the most important indices in fractal theory, is often calculated from raster data, but most land-use data are stored as vector data. Conversion of vector data to grid images to calculate fractal dimension may result in inaccurate values. Accuracy of the calculation on raster data is closely related to the grain size of the grid images. Taking a case study of the 1:100000 land use data of Suzhou City in 2008, this paper first analyzed the fractal characteristics of the study area by calculating the fractal dimension, investigated the scale effects of land use fractal dimension by changing the grain size of raster data, and then established a quantitative relationship between fractal dimension and the grain size, and lastly used the math model to calculate fractal dimensions from vector data based on the raster data. The results showed that land use structure of Suzhou City followed the general rules of fractal theory, which proved that this method was suitable for the analysis of the characteristics of land use system in such a rapidly urbanizing area. Furthermore, the overall land use degree of Suzhou City was high; human activities have different effects on the different land types. For example, under the influence of human activities the structures of arable land and construction land were relatively simple, but unused land and forest-grassland are quite complex. The morphology of water was less complex than other land use types, indicating that water was more affected by human activities such as water conservation facilities and irrigation ditches. The effect of the grain size on the fractal dimension in this area showed that the fractal dimension increased with expanding grain size, and the result of statistical analysis suggested that the relationship between fractal dimension and the grain size fit with the quadratic-polynomial-model which provided a bridge between the vector data and raster date for the calculation of the fractal dimension. If the vector data were viewed as raster data of 0 m grain size, vector fractal dimension can be calculated from raster data according to the quadratic-polynomial-model. The difference between the calculated results and the fractal dimension values directly using the vector data was minimal. Thus, fractal dimension of vector land use data (the grain size is 0 m×0 m) could be deduced by this relationship within the margin of error.
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    Cited: CSCD(2)
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