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Many methods have been employed to study Land Use Change (LUC) in different areas, including some new algorithms from Artificial Intelligence (AI) field, such as Case-Based Reasoning (CBR), Artificial Neural Network (ANN), Bayesian Network (BN) and Support Vector Machine (SVM). Applications of some new methods have indicated both advantages and limitations. This paper presents a comparison between...
In the low-resolution MODIS satellite remote sensing images, the edge of a small water body is often blurred due to the resolution limitation. The existence of mixed pixels is not conducive to water information extraction and observation. Two Dimension Scattered Points (2DSP)-Classification(C) NDVI method is introduced to area estimation of the small water body. This method first analyzes band 1 and...
The rapid growth of urban space and its environmental challenges require precise mapping techniques to represent complex earth surface features more accurately. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and GIS post-processing) using SPOT image to predict urban land use and land cover of Mile city, Yunnan province, China. A new stratified sampling...
In this paper, a novel artificial neural network ensemble rainfall forecasting model is proposed for rainfall forecasting based on K-nearest neighbor nonparametric estimation of regression. In this model, original data set are partitioned into some different training subsets via Bagging technology. Then different ANN algorithms and different network architecture generate diverse individual neural...
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