Research of long-term changes in the coastal territories of the Sea of Azov on the basis of satellite data by the methods of image classification of ArcGIS Pro

O. Arkhipova, K.V. Glazko
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引用次数: 0

Abstract

With the advent of new methods for tracking the Earth’s surface, the priority of the data source for environmental monitoring has shifted in favor of remote sensing (RS) data. The processing of remote sensing data of the territory is the possibility of modern tracking and control of hazardous processes. During the study, by comparing satellite images for different years using various methods of the ArcGIS Pro geoinformation environment, an analysis was made of changes in the coastal zone of the Sea of Azov. Three methods for finding changes in the coastal zone associated with dangerous landslide-abrasion processes were evaluated: detection of changes in the coastal zone by replacing the red channel in an earlier image with the red channel of a later image (Composite Bands method); deep Learning method; compute Change method. The study showed the advantage of the Compute Change method on this sample of first data, which made it possible to assess the impact of landslide and abrasion processes on the coastal zone of the Sea of Azov. The results obtained are consistent with the data of field studies of the coastal zone of the Sea of Azov and the data of environmental control of the Krasnodar territory.
基于卫星数据的亚速海沿岸地区长期变化的ArcGIS Pro图像分类方法研究
随着地球表面跟踪新方法的出现,环境监测的数据源优先转向遥感(RS)数据。对领土遥感数据的处理是对危险过程进行现代跟踪和控制的可能性。在研究过程中,利用ArcGIS Pro地理信息环境下的不同方法,对比不同年份的卫星影像,分析亚速海海岸带的变化。评估了三种发现与危险滑坡磨损过程相关的海岸带变化的方法:用后期图像的红色通道替换早期图像中的红色通道来检测海岸带变化(复合波段法);深度学习法;compute Change法。该研究显示了Compute Change方法在第一批数据样本上的优势,这使得评估亚速海海岸带滑坡和磨损过程的影响成为可能。所得结果与亚速海沿岸地区的实地考察资料和克拉斯诺达尔地区的环境控制资料相吻合。
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来源期刊
CiteScore
0.90
自引率
0.00%
发文量
2
审稿时长
8 weeks
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