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Soil class map of the Rio Jardim watershed in Central Brazil at 30 meter spatial resolution based on proximal and remote sensed data and MESMA method

机译:基于近端和遥感数据以及MESMA方法的巴西中部Rio Jardim流域30米空间分辨率的土壤分类图

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摘要

Geospatial soil information is critical for agricultural policy formulation and decision making, land-use suitability analysis, sustainable soil management, environmental assessment, and other research topics that are of vital importance to agriculture and economy. Proximal and Remote sensing technologies enables us to collect, process, and analyze spectral data and to retrieve, synthesize, visualize valuable geospatial information for multidisciplinary uses. We obtained the soil class map provided in this article by processing and analyzing proximal and remote sensed data from soil samples collected in toposequences based on pedomorphogeological relashionships. The soils were classified up to the second categorical level (suborder) of the Brazilian Soil Classification System (SiBCS), as well as in the World Reference Base (WRB) and United States Soil Taxonomy (ST) systems. The raster map has 30 m resolution and its accuracy is 73% (Kappa coefficient of 0.73). The soil legend represents a soil class followed by its topsoil color.
机译:地理空间土壤信息对于农业政策制定和决策,土地用途适宜性分析,可持续土壤管理,环境评估以及其他对农业和经济至关重要的研究主题至关重要。近程和遥感技术使我们能够收集,处理和分析光谱数据,并检索,合成和可视化有价值的地理空间信息,以供多学科使用。我们通过处理和分析基于古地貌地质关系的序列中的近地和遥感数据,获得了本文提供的土壤分类图。根据巴西土壤分类系统(SiBCS)以及世界参考基准(WRB)和美国土壤分类法(ST)系统,将土壤分类到第二类(次级)。栅格地图的分辨率为30 m,其准确度为73%(卡伯系数为0.73)。土壤图例代表土壤类别,后跟其表层土壤颜色。

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