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Open land-use map: a regional land-use mapping strategy for incorporating OpenStreetMap with earth observations

机译:开放式土地利用图:将OpenStreetMap与地球观测相结合的区域性土地利用图策略

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摘要

A land-use map at the regional scale is a heavy computation task yet is critical to most landowners,researchers,and decision-makers,enabling them to make informed decisions for varying objectives.There are two major difficulties in generating land classification maps at the regional scale:the necessity of large data-sets of training points and the expensive computation cost in terms of both money and time.Volunteered Geographic Information opens a new era in mapping and visualizing the physical world by providing an open-access database valuable georeferenced information collected by volunteer citizens.As one of the most well-known VGI initiatives,OpenStreetMap (OSM),contributes not only to road network distribution information but also to the potential for using these data to justify and delineate land patterns.Whereas,most large-scale mapping approaches-including regional and national scales-confuse"land cover"and "land-use",or build up the land-use database based on modeled land cover data-sets,in this study,we clearly distinguished and differentiated land-use from land cover.By focusing on our prime objective of mapping land-use and management practices,a robust regional land-use mapping approach was developed by integrating OSM data with the earth observation remote sensing imagery.Our novel approach incorporates a vital temporal component to large-scale land-use mapping while effectively eliminating the typically burdensome computation and time/money demands of such work.Furthermore,our novel approach in regional scale land-use mapping produced robust results in our study area:the overall internal accuracy of the classifier was 95.2% and the external accuracy of the classifier was measured at 74.8%.
机译:区域规模的土地利用图是一项繁重的计算任务,但对大多数土地所有者,研究人员和决策者而言至关重要,使他们能够针对不同的目标做出明智的决策。在土地使用图上生成土地分类图有两个主要困难。区域规模:需要大量训练点数据集,并且在金钱和时间方面都需要昂贵的计算成本。自愿提供的地理信息通过提供一个开放的数据库,提供有价值的地理参考信息,开创了绘制和可视化物理世界的新时代作为最著名的VGI计划之一,OpenStreetMap(OSM)不仅为道路网络分布信息做出了贡献,而且还为利用这些数据证明和描绘土地格局的潜力做出了贡献。尺度制图方法(包括区域和国家尺度)混淆“土地覆被”和“土地利用”,或基于建模的土地利用价值模型建立土地利用数据库在本研究中,我们通过数据集清楚地将土地利用与土地覆盖区分开来。通过关注我们对土地利用和管理实践进行绘图的主要目标,通过整合OSM数据,开发了一种强大的区域土地利用绘图方法我们的新颖方法将重要的时间成分纳入了大规模土地利用制图,同时有效消除了此类工作通常会带来的繁重计算和时间/金钱需求。此外,我们在区域尺度土地上的新颖方法是使用映射在我们的研究领域产生了稳健的结果:分类器的整体内部精度为95.2%,而分类器的外部精度为74.8%。

著录项

  • 来源
    《地球空间信息科学学报(英文版)》 |2017年第3期|269-281|共13页
  • 作者单位

    Department of Geography, University of Florida, Gainesville, FL, USA;

    Land Use and Environmental Change Institute, University of Florida,Gainesville, FL, USA;

    Department of Geography, University of Florida, Gainesville, FL, USA;

    Land Use and Environmental Change Institute, University of Florida,Gainesville, FL, USA;

    Department of Geography, University of Florida, Gainesville, FL, USA;

    Beijing Key Laboratory of Precision Forestry, Beijing Forestry University, Beijing, China;

  • 收录信息 中国科学引文数据库(CSCD);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2024-01-27 09:00:55
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