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首页> 外文期刊>European Journal of Remote Sensing >K-NN FOREST: a software for the non-parametric prediction and mapping of environmental variables by the k -Nearest Neighbors algorithm
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K-NN FOREST: a software for the non-parametric prediction and mapping of environmental variables by the k -Nearest Neighbors algorithm

机译:K-NN FOREST:用于通过k-最近邻算法进行环境变量的非参数预测和映射的软件

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In the last decades researchers investigated the possibility of extending the information collected in sampling units during a field survey to wider geographical areas through the use of remotely sensed images. One of the most widely adopted approaches is based on the non-parametric k -Nearest Neighbors ( k -NN) algorithm. This contribution describes the software K-NN FOREST we developed to provide a complete tool for the implementation of the k -NN technique to generate spatially explicit estimations (maps) of a response variable acquired in the field by sampling units through the use of remotely sensed data or other ancillary variables. K-NN FOREST is designed to guide the user through a graphic user interface in the different phases of the process. K-NN FOREST is freely available for download and it is designed to run under Windows environment in conjunction with the GIS software IDRISI.
机译:在过去的几十年中,研究人员研究了通过使用遥感图像将在野外调查中以采样单位收集的信息扩展到更广阔的地理区域的可能性。一种最广泛采用的方法是基于非参数k最近邻居(k -NN)算法。此文稿描述了我们开发的软件K-NN FOREST,它为实施k-NN技术提供了一个完整的工具,该技术可通过使用遥感技术通过采样单位生成在现场获取的响应变量的空间显式估计(图)数据或其他辅助变量。 K-NN FOREST旨在在过程的不同阶段通过图形用户界面引导用户。 K-NN FOREST可免费下载,并且可与GIS软件IDRISI一起在Windows环境下运行。

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