基于机器学习算法的基于不同用途土地分类的多光谱卫星图像处理地理区域制图与分类

Apurva Saksena, Anushka Ringshia, Arnnava Sharma, Aparna Halbe
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引用次数: 0

摘要

从地理上讲,城市的特点是集约土地利用的拼凑。土地利用是一种合理而明智的方法,可以将可用的土地资源分配给城市内的不同活动(如定居点、耕地、牧场和管理森林)。土地利用是一种利用土地的方式,包括土地资源的分配、规划和管理。一块特定土地的使用和它的物理特性是联系在一起的。然而,尽管地理空间数据激增,但建立这种联系的研究仍然缺乏。将城市的物理形态与其功能联系起来是本文的目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geographical Area Mapping and Classification Utilizing Multispectral Satellite Imagery Processing Based on Machine Learning Algorithms Classifying Land based on its use for different purposes
Geographically, a city is characterized as a patchwork of intensive land-uses. Land-use is the rational and judicious approach of allocating available land resources for different activities (such as settlements, arable fields, pastures, and managed woods) within a city. It is a way of utilizing the land, including the allocation, planning, and management of its resources. The use of a particular patch of land and its physical character are linked. However, research that establishes this link is lacking despite the proliferation of geospatial data. Linking a city's physical form with its function is the goal of this paper.
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