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Li H.,Wuhan University | Li H.,Key Laboratory of Geographic Information System | Xu L.,Hangzhou Dingchuan Information Technology Co. | Shen H.,Wuhan University | Zhang L.,Wuhan University
ISPRS Journal of Photogrammetry and Remote Sensing

Topographic shadows are inevitable obstacles for the interpretation of remote sensing images covering rugged terrain. A general variational topographic correction (TC) framework is proposed in this paper by considering not only self shadows but also cast shadows. Cast shadows are first detected by integrating the radiometric and topographic features of the observed region. The cosine values of the incidence angles for the cast shadows are then corrected by the variational framework. The corrected incidence angles can be used in any traditional TC model to compensate for the shadows in mountainous regions. The proposed variational framework was utilized in eight different traditional TC models, and the results were compared with the traditional results. Images from two different regions were employed to test the framework. The results suggest that the proposed framework can raise the accuracy of shadow correction by both subjective and objective evaluations, owing to the correction of the cast shadows. © 2016 . Source

Tian J.,Key Laboratory of Geographic Information System | Tian J.,Wuhan University | Xiong F.,Wuhan University | Lei Y.,Wuhan University | Zhan Y.,Wuhan University
Advances in Geographic Information Science

The strokes in road networks refer to a set of connected and non-branching road segments that follow the principle of good continuity. Generating strokes plays an important role in road network generalization, topological analysis, pattern recognition, and schematic map generation. In this study, the self-best-fit strategy for generating strokes was improved by prescribing road segment processing order based on the importance of the road segments. The importance of the road segments was determined by four parameters: length, degree, closeness and betweenness. The road networks of Detroit and Birmingham were used for experiments. Different stroke generating strategies were compared in terms of network functionality and visual recognition. In terms of network functionality, the improved self-best-fit strategy is superior to the every-best-fit strategy, and in terms of averages, it is superior to the self-best-fit strategy as well as the self-fit strategy. From a visual recognition perspective, the improved self-best-fit strategy tends to generate longer strokes with global property compared to the every-best-fit strategy. © Springer International Publishing Switzerland 2015. Source

Liu Y.,Wuhan University | Liu Y.,Key Laboratory of Geographic Information System | Zhao X.,Wuhan University | Ma X.,Wuhan University | Liu D.,Wuhan University
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica

Assessing the quality of atmospheric correction products retrieved from TM/ETM+imagery is a necessary means to improve the product's quality, and it is also important to the scientists who use the imagery. At the basis of the summarization of the present methods, a new approach using the available global land survey surface reflectance product as reference imagery for validating the accuracy of atmospheric correction products retrieved from TM/ETM+is proposed. The steps are as follow: Firstly, the spectrum sampling strategy is designed to get spectrum samples from the product imagery and the reference imagery, then using the coefficient of variation to determine homogeneous samples. After obtaining the homogeneous samples from the imagery, the PIFs (pseudo invariant features, PIFs) samples are identified by using the spectrum correlation coefficient R and the normalized difference vegetation index (NDVI) differential between the product imagery and the reference imagery. Finally, the quality consistencies between the multi-temporal imagery are evaluated based on the PIFs samples. Experimental results have shown that the new approach can accurately identify the PIFs and obtain the quality information rapidly, and it is very suitable for large-scale applications and can provide the global/region change researchers with some essential quality information on base imagery. Source

Liu Y.,Key Laboratory of Geographic Information System | Liu Y.,Wuhan University | Zheng B.,Huazhong University of Science and Technology | Zheng B.,Land and Resources and Real Estate Research Center | And 3 more authors.
International Journal of Applied Earth Observation and Geoinformation

Distantial attenuation is a significant characteristic of the urban environment. In this paper we explore the relative contributions of different land uses to the urban residential environment according to distances with an analysis on the most significant scope of these factors. Two types of models are developed. One employs the distance to city center, main road, public facilities and environment factors as the variables for macro environment analysis, and the another one includes all factors to analyze the influences of the micro environment. In the models of the latter type, the contributions of the neighboring land uses are magnified with a specially designed variable measurement scheme in which variables are evaluated specially for each model so that the contributions of the variables become comparable from model to model. With an application to the case study of Danyang, China, we measure the distantial functions of the urban environment (e.g. the surrounding land uses) including both the most influential scopes and the relative contributions by means of model summary and regression coefficient comparisons. Finally, case comparison on the samples is introduced to figure out the difference of the functions under micro environment. © 2009 Elsevier B.V. Source

Liu Y.,Design Survey Research Institute | Lan Z.,Design Survey Research Institute | Lan Z.,Wuhan University | Liu Y.,Wuhan University | Liu Y.,Key Laboratory of Geographic Information System
Acta Geodaetica et Cartographica Sinica

In this article, we design, implement, and evaluate a new approach in classification that places class-interval selection into a multi-criterion framework. In this framework, we consider not only number-line relationships, but also the area covered by each class, the fragmentation of the resulting classifications, and the degree to which they are spatially autocorrelated. This task is accomplished through the use of a genetic algorithm (SIMMOGA) that creates optimal classifications with respect to multiple criteria. Finally, the method has been tested in the urban land grading of Hubei Province. Source

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