PROGRESS IN GEOGRAPHY ›› 2012, Vol. 31 ›› Issue (7): 911-920.doi: 10.11820/dlkxjz.2012.07.010
• Original Articles •
LIN Chen1,2, ZHOU Shenglu2, WU Shaohua2
Monitoring the soil erosion dynamically is an important part in soil erosion research. The studies mainly reflected in two aspects: The first is the monitoring of erosion intensity, and the second is the simulation of soil erosion tendency. However, the studies are mainly based on neighborhood transition rules and the mathematical meaning is emphasized, while the transition possibility of the cell itself has been ignored to a certain degree, which cannot fully reflect the complexity of soil erosion evolution. These shortages not only reduce the simulation accuracy, but also decrease the integration of erosion intensity assessment and erosion tendency simulation, which are not conducive to the formation of a complete research system. This study suggested that the spatial and temporal evolution of soil erosion is determined by its own status of soil erosion, natural conditions and neighborhood transformation rules, so the cellular algorithms of erosion intensity index, cellular erosion intensity functions and cellular neighborhood transition function were designed and the traditional GeoCA was optimized. Finally, the integration model of optimized GeoCA was designed and calculated with the support of GIS and remote sensing technologies, and the spatial and temporal soil erosion transition tendency was analyzed in Changting County, Fujian Province. The results showed that there are characteristics of concentration and contiguity in erosion distribution, and the highest erosion intensity is observed in central Changting, and the soil erosion has been mitigated in the past 30 years, especially in the 1990s, Soil erosion control has achieved remarkable results, and the improving tendency was clearly accelerating, but slow down since 2000. It is expected that by the year 2020, the proportion of soil erosion area would decrease from 40% to about 20%. By comparison, the accuracy of optimized integration model can reach 72.7%, higher than the erosion intensity assessment algorithm and traditional GeoCA model, which proves that the optimized model of GeoCA is not only an effective means to simulate soil erosion, but also provides reference for further study of GeoCA.
spatial and temporal evolution
LIN Chen, ZHOU Shenglu, WU Shaohua. Simulation of Spatial-temporal Evolution of Soil Erosion Based on Optimized GeoCA: A Case Study in Changting County, Fujian Province[J].PROGRESS IN GEOGRAPHY, 2012, 31(7): 911-920.
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