Image Fusion-Based Change Detection for Flood Extent Extraction Using Bi-Temporal Very High-Resolution Satellite Images
Change detection based on satellite images acquired from an area at different dates is of widespread interest, according to the increasing number of flood-related disasters. The images help to generate products that support emergency response and flood management at a global scale. In this paper, a novel unsupervised change detection approach based on image fusion is introduced. The approach aims to extract the reliable flood extent from very high-resolution (VHR) bi-temporal images. The method takes an advantage of the spectral distortion that occurs during image fusion process to detect the change areas by flood. To this end, a change candidate image is extracted from the fused image generated with bi-temporal images by considering a local spectral distortion. This can be done by employing a universal image quality index (UIQI), which is a measure for local evaluation of spectral distortion. The decision threshold for the determination of changed pixels is set by applying a probability mixture model to the change candidate image based on expectation maximization (EM) algorithm. We used bi-temporal KOMPSAT-2 satellite images to detect the flooded area in the city of N′djamena in Chad. The performance of the proposed method was visually and quantitatively compared with existing change detection methods. The results showed that the proposed method achieved an overall accuracy (OA = 75.04) close to that of the support vector machine (SVM)-based supervised change detection method. Moreover, the proposed method showed a better performance in differentiating the flooded area and the permanent water body compared to the existing change detection methods.
Application of Remote Sensing in Flood Management with Special Reference to Monsoon Asia: A Review
The conventional means to record hydrological parameters of aflood often fail to record an extreme event. Remote sensingtechnology along with geographic information system (GIS)has become the key tool for flood monitoring in recent years.Development in this field has evolved from optical to radarremote sensing, which has provided all weather capabilitycompared to the optical sensors for the purpose of flood mapping.The central focus in this field revolves around delineation of floodzones and preparation of flood hazard maps for the vulnerable areas.In this exercise flood depth is considered crucial for flood hazardmapping and a digital elevation model (DEM) is considered to bethe most effective means to estimate flood depth from remotelysensed or hydrological data. In a flat terrain accuracy of floodestimation depends primarily on the resolution of the DEM. Riverflooding in the developing countries of monsoon Asia is very acutebecause of their heavy dependence on agriculture but any floodestimation or hazard mapping attempt in this region is handicappedby poor availability of high resolution DEMs. This paper presents areview of application of remote sensing and GIS in flood managementwith particular focus on the developing countries of Asia.
Die Populationsdynamik Von Canthocampt Us Staphylinus (Jurine) (Copepoda, Harpacticoida) Im Litoral Des Bodensees
The population dynamics of Canthocamptus staphylinus in the littoral zone of Lake Constance are described (fig. 2). Adult animals aestivate as cysts. The main part of the population emerges from the cysts in autumn. During the resting stage and the first spell after emerging, mortality is very low (fig. 3). Reproduction, expressed as numbers of ovigerous females, begins in November and reaches its maximum in January. The new generation becomes adult in May/June and encysts without previous reproduction. According to Sarvala (1979) it may be possible, that in littoral populations dormancy is induced by long day periods and temperatures of over 12° C (figs. 1, 2). In the profundal zone C. staphylinus also forms cysts, however, both light and temperature are not likely to induce this stage in depths of over 60 m.