Shadow is one of the major problems in remotely sensed imagery which hampers the accuracy of information extraction and change detection.In these images,shadow is generally produced by different objects,namely,cloud,m...Shadow is one of the major problems in remotely sensed imagery which hampers the accuracy of information extraction and change detection.In these images,shadow is generally produced by different objects,namely,cloud,mountain and urban materials.The shadow correction process consists of two steps:detection and de-shadowing.This paper reviews a range of techniques for both steps,focusing on urban regions(urban shadows),mountainous areas(topographic shadow),cloud shadows and composite shadows.Several issues including the problems and the advantages of those algorithms are discussed.In recent years,thresholding and recovery techniques have become important for shadow detection and de-shadowing,respectively.Research on shadow correction is still an important topic,particularly for urban regions(in high spatial resolution data) and mountainous forest(in high and medium spatial resolution data).Moreover,new algorithms are needed for shadow correction,especially given the advent of new satellite images.展开更多
In this paper, we developed a novel method of combining remote sensing tools at the sub-pixel level for accurate identification of impervious surface time series changes. We examined the use of the red-green-blue impe...In this paper, we developed a novel method of combining remote sensing tools at the sub-pixel level for accurate identification of impervious surface time series changes. We examined the use of the red-green-blue impervious surface model (RGB-IS) in detecting time series internal modification of urban regions by integrating Landsat data collected over four different periods between 1987 and 2009 (i.e., 1987, 2000, 2002, and 2009). The performance of this approach was compared with two conventional methods, namely standard RGB-normalized difference vegetation index (NDVI) and post-classification technique. In contrast to conventional techniques, RGB-IS could monitor between-class changes, within-class changes, and location of these modifications. The proposed method was independent of seasonal changes and was also able to serve as a useful alternative for quick mapping growth hotspots and updating transportation corridor map. The results also showed that Cixi County, Zhejiang Province, China experienced tremendous impervious surface changes, especially along the corridors of newly constructed highways and around urban areas over the past 22 years.展开更多
基金Under the auspices of National Technology Research and Development Program of China(No.2006BAJ05A02)National Natural Science Foundation of China(No.31172023)
文摘Shadow is one of the major problems in remotely sensed imagery which hampers the accuracy of information extraction and change detection.In these images,shadow is generally produced by different objects,namely,cloud,mountain and urban materials.The shadow correction process consists of two steps:detection and de-shadowing.This paper reviews a range of techniques for both steps,focusing on urban regions(urban shadows),mountainous areas(topographic shadow),cloud shadows and composite shadows.Several issues including the problems and the advantages of those algorithms are discussed.In recent years,thresholding and recovery techniques have become important for shadow detection and de-shadowing,respectively.Research on shadow correction is still an important topic,particularly for urban regions(in high spatial resolution data) and mountainous forest(in high and medium spatial resolution data).Moreover,new algorithms are needed for shadow correction,especially given the advent of new satellite images.
基金Project (No. 2006BAJ05A02) supported by the National Science and Technology Pillar Program during the 11th Five-Year Plan Period of China
文摘In this paper, we developed a novel method of combining remote sensing tools at the sub-pixel level for accurate identification of impervious surface time series changes. We examined the use of the red-green-blue impervious surface model (RGB-IS) in detecting time series internal modification of urban regions by integrating Landsat data collected over four different periods between 1987 and 2009 (i.e., 1987, 2000, 2002, and 2009). The performance of this approach was compared with two conventional methods, namely standard RGB-normalized difference vegetation index (NDVI) and post-classification technique. In contrast to conventional techniques, RGB-IS could monitor between-class changes, within-class changes, and location of these modifications. The proposed method was independent of seasonal changes and was also able to serve as a useful alternative for quick mapping growth hotspots and updating transportation corridor map. The results also showed that Cixi County, Zhejiang Province, China experienced tremendous impervious surface changes, especially along the corridors of newly constructed highways and around urban areas over the past 22 years.
