Mine geological environment evaluation is an important measure to realize the reasonable exploitation and utilization of mineral resources and environmental *** paper studied the mine geological environment characteri...
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Mine geological environment evaluation is an important measure to realize the reasonable exploitation and utilization of mineral resources and environmental *** paper studied the mine geological environment characteristics and the main mine geological environment problems in geological environment problem area of Xiaoyi mining area systematically based on the high score 2 remote sensing image data, and determined the evaluation index system of mine geological environment Based on the image information hierarchy, experiment uses the Euclidean two-index method to calculate the optimal segmentation parameters of each layers, and selects an appropriate feature factor to establish a fuzzy rule set;Besides, this experiment uses adopts a layered mask method to separate out the large-scale geological environment background elements;And then, this experiment uses random forest model to classify the rest of the geological environmental categories in metallic mineral research area that located in Xiaoyi mining area;Finally, with the confusion matrix and Kappa coefficient for accuracy evaluation, the result shows that the classification accuracy is 87% and Kappa coefficient is 0.74 of the random forest *** research results have important reference value for guiding the sustainable development and utilization of mineral resources in the area of geological environment of Xiaoyi mining area.
Cotton is an important economic crop and plays an important role in the national economy. Therefore, timely and accurate access to crop planting area and spatial distribution information is very important for governme...
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ISBN:
(纸本)9781728121161
Cotton is an important economic crop and plays an important role in the national economy. Therefore, timely and accurate access to crop planting area and spatial distribution information is very important for government departments to make economic decisions and adjust cotton planting structure. At the same time, crop census and cotton growth monitoring There are also important applications in terms of production estimates and disaster assessment. This study is based on Google Earth Engine remote sensing big data cloud computing platform and Sentinel-2 data, taking Zaoqiang County of Itengshui City, Hebei Province as an example, using nearly 50 scenes of Sentinel-2 data, combined with interest area index calculation, S-G filtering method, etc. The time series phenotypic analysis method was constructed to analyze the phenological characteristics of the main crop cotton and the interfering crop corn in Zaoqiang County. Based on the phenological analysis results, the key time phase data of cotton extraction was screened, and the object-oriented information extraction method was combined with spectral features and texture features. The cotton distribution information of Zaoqiang County was extracted, and the accuracy of the results was analyzed with the field sample data. The overall accuracy was 92%, which satisfied the cotton monitoring application demand of Zaoqiang County.
High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classif...
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ISBN:
(纸本)0780390504
High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classification can't satisfy high-resolution satellite image's classification precision and produce large data redundancy. object-oriented information extraction not only depends on spectrum character, but also uses geometry and structure information. It can provide an accessible truly revolutionary approach. Using Beijing Quickbird and high-resolution image and object-oriented classification with the eCognition software, we accomplish the cultures' precise classification. The test areas have five culture types including water, vegetation, road, building and bare hands. We use nearest neighbor classification and appraise the overall classification accuracy. The average of five species reaches 0.90. All of maximum is 1. The standard deviation is less than 0.11. The overall accuracy can reach 95.47%. This method offers a new technology for high-resolution satellite images' available applications in remote sensing culture classification.
作者：
Sun, KaiminChen, YanLi, DerenWuhan Univ
Sch Remote Sensing Informat Engn 129 Luoyu Rd Wuhan 430079 Peoples R China Wuhan Univ
Natl Lab Informat Engn Surveying Maping & Remote Wuhan 430079 Peoples R China
The diversity of the spatial scale of landscape raises the requirement of multiscale analysis of remote sensing (RS) images. Usually the first step to analyze remote sensing images is image segmentation, in which the ...
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ISBN:
(纸本)9780819465283
The diversity of the spatial scale of landscape raises the requirement of multiscale analysis of remote sensing (RS) images. Usually the first step to analyze remote sensing images is image segmentation, in which the muitiscale effect should be taken into account to achieve satisfactory segmentation results. This paper describes an effective approach to segment remote sensing images in multiscale. Based on the fact that in a specific scale of a remote sensing image the same objects are similar, the image is first segmented in a small scale by uniting the most similar objects. After that, a set of multiscale objects with full topological relationship can be obtained. Based on the set of multiscale objects, the authors explore the application of this approach in object-oriented information extraction from remote sensing images.
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