Spectral mixture analysis (SMA) is a major approach for estimating fractional land covers through modeling the relationship between the spectral signatures of a mixed remote sensing pixel and those of the comprised pure land covers (also termed as endmembers). When SMA is implemented, endmember variability has proven to have significant impact on the accuracy of land cover fraction estimates. To address the endmember variability problem, this article developed a geostatistical temporal mixture analysis (GTMA) technique, with which spatially varying per-pixel endmember sets were estimated using an ordinary kriging interpolation technique. The method was applied to time-series moderate-resolution imaging spectroradiometer normalized difference vegetation index imagery in Wisconsin and North Carolina, United States to estimate regional impervious surface distributions. Analysis of results suggests that GTMA has achieved a promising accuracy. Detailed analysis indicates that a better performance has been achieved in less-developed areas than developed areas, and slight underestimation and slight overestimation have been detected in developed areas and less-developed areas, respectively. Moreover, while the performance of GTMA is comparable to those of phenology-based TMA and phenology-based multiple endmember TMA over the entire study area and in less-developed areas, a much better performance has been achieved in developed areas. Finally, this article argues that endmember variability may be more essential in developed areas when compared to less-developed areas. 相似文献
Given a grid of cells each having an associated cost value, a raster version of the least-cost path problem seeks a sequence of cells connecting two specified cells such that its total accumulated cost is minimized. Identifying least-cost paths is one of the most basic functions of raster-based geographic information systems. Existing algorithms are useful if the path width is assumed to be zero or negligible compared to the cell size. This assumption, however, may not be valid in many real-world applications ranging from wildlife corridor planning to highway alignment. This paper presents a method to solve a raster-based least-cost path problem whose solution is a path having a specified width in terms of Euclidean distance (rather than by number of cells). Assuming that all cell values are positive, it does so by transforming the given grid into a graph such that each node represents a neighborhood of a certain form determined by the specified path width, and each arc represents a possible transition from one neighborhood to another. An existing shortest path algorithm is then applied to the graph. This method is highly efficient, as the number of nodes in the transformed graph is not more than the number of cells in the given grid and decreases with the specified path width. However, a shortcoming of this method is the possibility of generating a self-intersecting path which occurs only when the given grid has an extremely skewed distribution of cost values. 相似文献
If a geochemical compositional datasetX (n×p)is a realization of a physical mixing process, then each of its sample (row) vectors will approximately be a convex combination (mixture) of a fixed set of (l×p)extreme compositions termed endmembers. The kpoints in p-space corresponding to a specified set of k (k
linearly independent endmember estimates associated with a p-variate (n×p)compositional datasetX,define the vertices of a (k–1)dimensional simplexH.The nestimated mixturesX (n×p)which together account for the systematic variation in the datasetX,should each be convex combinations of the kfixed endmember estimates. Accordingly,the npoints in p-space which represent these mixtures should be interior points of the simplexH.Otherwise, for each sample point which lies outsideH,at least one of the mixture coefficients (endmember contributions) will be negative. The purpose of this paper is to describe procedures for expandingHin the situation that its vertices are not a set of extreme points for the set which represents the mixtures. 相似文献