gis技术在学生地理学家野外实践中实施大规模制图的可能性

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引用次数: 1

摘要

本文讨论了3 ~ 60 m波段不同分辨率遥感卫星数据处理的实验结果。本文的目的是提出并证明使用卫星图像数据和地理信息系统(GIS技术)技术来解决各种问题的各种选择,同时考虑到以前的研究经验。主要材料。作者建议使用Sentinel-2和PlanetScope编制不同大小地区的大比例尺地图。在改进作者先前使用的方法的基础上,提出利用遥感数据将植物类群作为指示性等高线的指示性对象进行区分。第二个参考对象是水体的轮廓。我们建议使用颜色(RGB)、形状和粗糙度来识别物体的轮廓,但要考虑到关键区域的实际材料输出。这些特征可以间接决定地貌。基于光谱特征图像,我们考虑了季节、植被期和领土。在实地实践中,学生处理不同时期的数据集并分析这些信息以研究景观变化。根据2015年至2019年的研究,正在形成保护区景观监测数据库。作者与学生和其他研究人员已经确定有必要分别分析斯洛博赞斯基国家自然公园的北部和南部。QGis和ArcGis工具允许您准备数据并进行覆盖分析,以编译假设地图,然后生成结果地图。结论及进一步研究。建立了类的数量和分类方法取决于研究对象的性质。采用关键区域自动分类的方法分离植物群落的等高线,效果最好。实验证明,PlanetScope在小范围内对卫星图像的解码效果最好。对于更大的区域,Sentinel-2的解码效果最好,其主题图像数据更加一般化。根据从专题图中获得的信息,我们获得了每个等高线的地形、地质结构、土壤的属性数据。所有信息将用于斯洛博赞斯基国家自然公园的景观监测基地。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Possibilities of GIS-technologies in implementing large-scale mapping during field practices of students-geographers
Experimental results of remote satellite data processing with different resolution from 3 to 60 m of bands are discussed in the article. The purpose of the article is to present and justify various options for using satellite imagery data and technologies of geographic information systems (GIS technologies) to solve various problems, taking into account previous research experience. The main material. The author suggests using Sentinel-2 and PlanetScope to compile large-scale maps of territories of different sizes. Based on the improvement of the methodology (previously used by the author), it is proposed to distinguish plant groups as indicative objects of indicative contours using remote sensing data. The second reference object is the contours of water bodies. We propose using colors (RGB), shapes and roughness to identify the contours of objects, but given the actual material of the field outputs to key areas. These characteristics can indirectly determine geomorphology. Based on spectral characteristic images, we consider the seasons, vegetation periods, and territory. During the filed practice students process a data set for different periods and analyze this information to study landscape changes. Based on studies from 2015 to 2019, a database for landscape monitoring of the protected area is being formed. The author with students and other researchers have determined that it is necessary to separately analyze northern and southern parts of the Slobozhansky National Nature Park. QGis and ArcGis tools allow you to prepare data and do overlay analysis to compile a hypothesis map, and then the resulting map. Conclusions and further research. It is established that the number of classes and the classification method depend on the properties of the objects of study. The best results were shown by isolating the contours of plant communities by the method of automatic classification by identifying key areas. It has been experimentally established that the decoding of satellite images PlanetScope gives the best results in small areas. For decoding of a larger area, Sentinel-2 gives the best results, the thematic image data of which is more generalized. Based on the information received from thematic maps, we have attributive data on the topography, geological structure, soil for each contour. All information will be used for the landscape monitoring base in the Slobozhansky National Nature Park.
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