KEYWORDS: Remote sensing, Wavelet transforms, Neural networks, Coastal modeling, Geography, Information science, Information technology, Current controlled current source
Soft classification methods can be used for mixed-pixel classification on remote sensing imagery by estimating different land cover class fractions of every pixel. However, the spatial distribution and location of these class components within the pixel remain unknown. To map land cover at subpixel scale and increase the spatial resolution of land cover classification maps, in this paper, a prediction model combining wavelet transform and Radial Basis Functions (RBF) neural network, abbreviated as Wavelet-RBFNN, is constructed by predicting high-frequency wavelet coefficients from low-frequency coefficients at the same resolution with RBF network and taking wavelet coefficients at coarser resolution as training samples. According to different land cover class fraction images obtained from mixed-pixel classification, based on the assumption of neighborhood dependence of wavelet coefficients, subpixel mapping on remote sensing imagery can be accomplished through two steps, i.e., prediction of land cover class compositions within subpixels and hard classification. The experimental results obtained with artificial images, QuickBird image and Landsat 7 ETM+ image indicate that the subpixel mapping method proposed in this paper can successfully produce super-resolution land cover classification maps from remote sensing imagery, outperforming cubic B-spline and Kriging interpolation method in visual effect and prediction accuracy. The Wavelet-RBFNN model can also be applied to simulate higher spatial resolution image, and automatically identify and locate land cover targets at the subpixel scales, when the cost and availability of high resolution imagery prohibit its use in many areas of work.
This study couples Laplacian-of-Gaussian filter (LoG) and wavelet multi-scale edge detection approaches to extract the waterlines of Chongming Island from Landsat images. The digital elevation model (DEM) of the Chongming tidal flat is constructed by means of the "waterline method". From multi-temporal images obtained under different tidal conditions, it is possible to build up a set of heighted waterlines within the tidal zone, and gridded DEM is then generated by the Australian National University Digital Elevation Model (ANUDEM) method. The results indicate that the methods proposed by this paper can effectively reproduce the coastal near shore topography of Chongming Island, and the precision of the DEM of Dongtan tidal flat is acceptable.
The research on land use / land cover change (LUCC) can provide an important means to understand the relationship between ecological environmental change and human being's activity. The study area, in this paper, Jintai District and Weibin District, is the suburban area of Baoji City, which is located at the frontier of Western Development in China. To explore the typical pattern of land cover change in western China, the LUCC of the study area from 1988 to 2004 is analyzed, using remote sensing technology. Based on these, Markov model is applied to predict the tendency of the LUCC of this area in the next 16 years, and the results indicate that human being's activity, especially in the western cities, will have an increasingly great influence on the regional ecological environment in the current pattern of land use. Faced with the contradiction between land and people and severe ecological environment, establishing land use regulation indices and spatial optimal designs favorable to ecological environment by setting up general land use planning scientifically is important to satisfy reasonable demand of land with economic development and accelerated urbanization and improve ecological environment in western cities in China.
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