Wetland mapping in the Balqash Lake Basin Using Multi-source Remote Sensing Data and Topographic features Synergic Retrieval

AbstractWetland plays a major role in the hydrological cycle, the carbon sink (carbon sequestration), nitrogen absorption, geochemical cycle, water conservation, biological diversity. Traditional field surveys for mapping wetlands distribution in large areas are very difficult to undertake. Remote sensing techniques offer promising solutions to this problem. But spectral confusion with other land cover classes and different types of wetlands, it is difficult to extract wetland information automatically. The overarching goal of this study was to develop a hybrid method for lake wetlands automated delineation by integrated using multi-source remote sensing data and DEM data. Firstly, it is to do radiance correction and convert image DN value to reflectance or radiance. Secondly, spectral index calculation and topographic indices derive, such as NDVI, NDWI, TVDI, slope and others topographic feature indices and etc. Thirdly, water bodies extraction through the NDWI iterative computation. Finally, it is to retrieve marsh land from image via comprehensive information of soil moisture character, topographic factors and spatial analysis. By the above steps, we got the ultimate wetlands distribution information. The methodology was evaluated by the balqash lake basin wetland extraction in Kazakhstan. Experiments result shows that the hybrid method performs well in lake wetlands delineation. The overall accuracies of wetland classes exceed 85%, which can meet the application requirements

Parameter Optimization for Image Denoising Based on Block Matching and 3D Collaborative Filtering

Clinical MRI images are generally corrupted by random noise during acquisition with blurred subtle structure features. Many denoising methods have been proposed to remove noise from corrupted images at the expense of distorted structure features. Therefore, there is always compromise between removing noise and preserving structure information for denoising methods. For a specific denoising method, it is crucial to tune it so that the best tradeoff can be obtained. In this paper, we define several cost functions to assess the quality of noise removal and that of structure information preserved in the denoised image. Strength Pareto Evolutionary Algorithm 2 (SPEA2) is utilized to simultaneously optimize the cost functions by modifying parameters associated with the denoising methods. The effectiveness of the algorithm is demonstrated by applying the proposed optimization procedure to enhance the image denoising results using block matching and 3D collaborative filtering. Experimental results show that the proposed optimization algorithm can significantly improve the performance of image denoising methods in terms of noise removal and structure information preservation

Impact <i>Eichhornia crassipes</i> Cultivation on Water Quality in the Caohai Region of Dianchi Lake Using Multi-Temporal Sentinel-2 Images

In order to comprehensively and accurately evaluate the adsorption effect of Eichhornia crassipes planting on algae in water, this study used 131 cloudless Sentinel-2 images to monitor the scale and growth dynamics of Eichhornia crassipes planting in Caohai and its surrounding waters. Based on the single and multi-peak histogram characteristics of the NDWI image in the study area, the empirical threshold and the optimized histogram slope adaptive threshold (OHSAT) segmentation methods were respectively used and manual inspection was added to accurately segment the water bodies and Eichhornia crassipes. The results of the analysis of Eichhornia crassipes area, growth status (NDVI), water body algae density (NDVI), and their spatial–temporal co-variation and trends show that the Eichhornia crassipes has a significant enrichment effect on algae, showing a significant decreasing trend of water bloom centered on it. The size and growth status of Eichhornia crassipes are inversely proportional to the water body NDVI, and reasonable harvesting plans based on these findings are expected to achieve optimized pollution control effects

Joint Probability Space Based Self-adaptive Remote Sensing Change Detection Method

A variety of factors has led to radiometric variations of the land cover, which severely limits the threshold based change detection method performance. To overcome this problem, we propose a joint probability density space based self adaptive multi-threshold change detection approach. Firstly, the two images of the same geographic area acquired at different time are transformed into the joint probability space. In which, the land cover change pixels are defined as outliers and identified by an iterative method. Then, the extracted outliers are mapped back to the original image space and determine the change area. To illustrate the performance of the proposed method, an experimental analysis on two classical applications is reported and discussed, results show that the proposed method over performed the state of art method in true rate, false alarm rate and omit alarm rate, with high stability

Three-dimensional carbonate reservoir geomodeling based on the digital outcrop model

To better know the spatial distribution and architecture of carbonate reservoirs, three-dimensional carbonate reservoir geologic modeling based on the digital outcrop model (DOM) is proposed. Based on the traditional geologic study of outcrops, combined with digitizing the outcrop walls by utilizing the advanced instrument (LIDAR, RTK-GPS, GPR, Gigapan, etc), DOM is built, from which geological information based on measured sections and samples (litho-facies, porosity, permeability, sonic velocity) is extracted and used to build the 3-D outcrop reservoir geologic model by modeling software. Eventually the 3-D reservoir geologic model of outcrop is used to guide the subsurface research. The DOM-based 3-D reservoir geologic model for oolitic reservoirs of Triassic Feixianguan Formation in Yudongliang outcrop, NW Sichuan Basin, reveals more realistic spatial distribution of litho-facies, porosity and permeability, and their relationship, consequently providing more reliable evidence for seismic data interpretation and reservoir prediction of subsurface reservoirs with similar geological conditions. Key words: digital outcrop model, carbonate reservoir, 3-D geologic modeling, Triassic Feixianguan Formation, oolitic beac

A Fast Algorithm to Estimate the Deepest Points of Lakes for Regional Lake Registration.

When conducting image registration in the U.S. state of Alaska, it is very difficult to locate satisfactory ground control points because ice, snow, and lakes cover much of the ground. However, GCPs can be located by seeking stable points from the extracted lake data. This paper defines a process to estimate the deepest points of lakes as the most stable ground control points for registration. We estimate the deepest point of a lake by computing the center point of the largest inner circle (LIC) of the polygon representing the lake. An LIC-seeking method based on Voronoi diagrams is proposed, and an algorithm based on medial axis simplification (MAS) is introduced. The proposed design also incorporates parallel data computing. A key issue of selecting a policy for partitioning vector data is carefully studied, the selected policy that equalize the algorithm complexity is proved the most optimized policy for vector parallel processing. Using several experimental applications, we conclude that the presented approach accurately estimates the deepest points in Alaskan lakes; furthermore, we gain perfect efficiency using MAS and a policy of algorithm complexity equalization

A Fast Algorithm to Estimate the Deepest Points of Lakes for Regional Lake Registration.

When conducting image registration in the U.S. state of Alaska, it is very difficult to locate satisfactory ground control points because ice, snow, and lakes cover much of the ground. However, GCPs can be located by seeking stable points from the extracted lake data. This paper defines a process to estimate the deepest points of lakes as the most stable ground control points for registration. We estimate the deepest point of a lake by computing the center point of the largest inner circle (LIC) of the polygon representing the lake. An LIC-seeking method based on Voronoi diagrams is proposed, and an algorithm based on medial axis simplification (MAS) is introduced. The proposed design also incorporates parallel data computing. A key issue of selecting a policy for partitioning vector data is carefully studied, the selected policy that equalize the algorithm complexity is proved the most optimized policy for vector parallel processing. Using several experimental applications, we conclude that the presented approach accurately estimates the deepest points in Alaskan lakes; furthermore, we gain perfect efficiency using MAS and a policy of algorithm complexity equalization

Carbonate karst reservoirs of the Tarim Basin, northwest China: Types, features, origins, and implications for hydrocarbon exploration

Karst reservoirs are important exploration targets in marine carbonates of hydrocarbon-bearing basins around the world. In the Tarim Basin of northwest China, four types of carbonate karst reservoirs were delineated using data from more than 200 wells, including cores, thin sections, wireline logs, drilling logs, and production data; these were supplemented with seismic and other data. The four types of karst reservoirs described were all formed by meteoric water circulation but not limited in the vadose or phreatic zones, including buried tower karst, interlayer karst, overlying-aquiclude confining karst, and fault-related karst. Buried tower karst occurred in the carbonate successions underneath a regional unconformity (buried tower area), resembling the active karsting in the Guilin Region of South China. Interlayer karst developed during a relatively shorter exposure period compared with buried tower karst but is also situated on a paleouplift. Overlying-aquiclude confining karst is essentially a by-product and on the fringes of buried tower karst, and though it appears to be distributed evenly below a disconformity, it is not related to the disconformity in origin. Fault-related karst occurred in the carbonate succession of a high steep anticline with faults cutting through aquicludes and into the carbonates; dissolution is concentrated along faults and the crest of the anticline. We studied three previously undocumented types of karst and proved that karst reservoirs in the Tarim Basin occur not only in the carbonate succession under a regional unconformity, but also where no significant unconformity is recognized. Similar examples have been found in other basins of China and are expected to occur in other basins worldwide, particularly in areas of complex geologic history

adaptive water body information extraction using rs tupu computing model

A RS TUPU computing mechanism is designed, considering the advantages of the features of spatial clustered layer and non-linear spectral mapping layer, which aims to approach the accurate regional boundary of thematic area step by step. Meanwhile, extraction parameters in the process are adjusted automatically by adaptive information computing method. Subsequently, the RS TUPU computing model is proposed, which will be applied in water body extraction. The existing valid methods for water body extraction are analyzed first. On this basis, an adaptive water body extraction method using RS TUPU computing model (WERSTP) is proposed, where ETM image is selected as experimental data source. WERSTP combines with the advantages of methods based on index computing and spectral classification, and the experimental results show that this method obtains an effective extraction result to make it achieve the level of accuracy and automation in water body information extraction.A RS TUPU computing mechanism is designed, considering the advantages of the features of spatial clustered layer and non-linear spectral mapping layer, which aims to approach the accurate regional boundary of thematic area step by step. Meanwhile, extraction parameters in the process are adjusted automatically by adaptive information computing method. Subsequently, the RS TUPU computing model is proposed, which will be applied in water body extraction. The existing valid methods for water body extraction are analyzed first. On this basis, an adaptive water body extraction method using RS TUPU computing model (WERSTP) is proposed, where ETM image is selected as experimental data source. WERSTP combines with the advantages of methods based on index computing and spectral classification, and the experimental results show that this method obtains an effective extraction result to make it achieve the level of accuracy and automation in water body information extraction