Please use this identifier to cite or link to this item: http://hdl.handle.net/2067/2333
Title: K-NN FOREST: a software for the non-parametric prediction and mapping of environmental variables by the k-Nearest Neighbors algorithm
Authors: Chirici, Gherardo
Corona, Piermaria
Marchetti, Marco
Mastronardi, Alessandro
Maselli, Fabio
Bottai, Lorenzo
Travaglini, Davide
Keywords: Environmental Inventory and Mapping;Prediction;Remote Sensing;k-Nearest Neighbors
Issue Date: 2012
Publisher: Associazione Italiana di Telerilevamento
Source: Chirici, G. et al. 2012. K-NN FOREST: a software for the non-parametric prediction and mapping of environmental variables by the k-Nearest Neighbors algorithm. "European Journal of Remote Sensing " 45: 433-442
Abstract: 
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.
URI: http://hdl.handle.net/2067/2333
ISSN: 2279-7254
DOI: 10.5721/EuJRS20124536
Appears in Collections:DiSAFRi - Archivio della produzione scientifica

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