A Long-Term Land Cover And Land Use Mapping Methodology For The Andean Amazon

M. Borja, R. Camargo, N. Moreno, E. Turpo, S. Villacís
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引用次数: 2

Abstract

The data developed by the MapBiomas Amazon initiative http://amazonia.mapbiomas.org/) led by the Amazon Geo-referenced Socio-environmental Information Network’s (RAISG) is of unprecedented spatial and temporal resolution for the Andes region. It’s comprised by a series of annual maps for the years 2000 to 2017 that allow to monitor the extent of transformation in this region using a single regional methodological approach. Several variables were included to solve Andes-specific methodological challenges and they represent adaptations of RAISG’s Amazonian methodology to the Andean region. Among such, is the use of the novel NDFIb index (Turpo, 2018), an adaptation of the NDFI index that aims at mapping Andean Wetlands. Glaciers identification was aided by the fractional abundance of snow (Turpo, 2018), as well as small water bodies identification with McFeeters (1996) NDWI water index. This experience unfolds promising accessibility to novel land cover and land use regional reconstructions and comparisons possible only by the use of large-scale cloud-computing data processing tools, open source technology, spatially and temporally comprehensive remote sensing data, along with RAISG’s standardized protocols and frameworks.
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安第斯亚马逊地区长期土地覆盖和土地利用制图方法
由亚马逊地理参考社会环境信息网络(RAISG)领导的MapBiomas亚马逊计划(http://amazonia.mapbiomas.org/)开发的数据对安第斯地区具有前所未有的空间和时间分辨率。它由2000年至2017年的一系列年度地图组成,这些地图可以使用单一的区域方法来监测该地区的转型程度。为了解决安第斯地区特有的方法挑战,包括了几个变量,它们代表了RAISG的亚马逊方法对安第斯地区的适应。其中包括使用新的NDFI指数(Turpo, 2018),该指数是对NDFI指数的改编,旨在绘制安第斯湿地。积雪分数丰度有助于冰川识别(Turpo, 2018),以及mcfeters (1996) NDWI水指数有助于小水体识别。这一经验表明,只有通过使用大规模云计算数据处理工具、开源技术、空间和时间综合遥感数据以及RAISG的标准化协议和框架,才能实现新的土地覆盖和土地利用区域重建和比较。
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