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 p...
Estimation and mapping of forest attributes are a fundamental support for forest management planning...
This study was designed to compare the performance – in terms of bias and accuracy – of four differe...
The increasing availability of remote sensing data at no or low costs can be used as ancillary data ...
In the last decades researchers investigated the possibility of extending the information collected ...
The k-nearest neighbours (k-NN) method constitutes a possible approach to improve the precision of t...
L'articolo è disponibile sul sito dell'editore www.sciencedirect.comThe statistical properties of th...
Inferences for forest-related spatial problems can be enhanced using remote sensing-based maps const...
L'articolo è disponibile sul sito dell'editore www.sciencedirect.comThis paper describes application...
The integration of forest inventory and mapping has emerged as a major issue for assessing forest at...
Routinely, applications of nonparametric estimation methods to satellite data for assisting the crea...
Dottorato di ricerca in Scienze e tecnologie per la gestione forestale e ambientaleGli inventari for...
The k-nearest neighbors (kNN) method has proven to be a very useful technique to classify and propa...
The k-Nearest Neighbors (k-NN) technique is a popular method for producing spatially contiguous pred...
Estimation and mapping of forest attributes are a fundamental support for forest management planning...
This study was designed to compare the performance – in terms of bias and accuracy – of four differe...
The increasing availability of remote sensing data at no or low costs can be used as ancillary data ...
In the last decades researchers investigated the possibility of extending the information collected ...
The k-nearest neighbours (k-NN) method constitutes a possible approach to improve the precision of t...
L'articolo è disponibile sul sito dell'editore www.sciencedirect.comThe statistical properties of th...
Inferences for forest-related spatial problems can be enhanced using remote sensing-based maps const...
L'articolo è disponibile sul sito dell'editore www.sciencedirect.comThis paper describes application...
The integration of forest inventory and mapping has emerged as a major issue for assessing forest at...
Routinely, applications of nonparametric estimation methods to satellite data for assisting the crea...
Dottorato di ricerca in Scienze e tecnologie per la gestione forestale e ambientaleGli inventari for...
The k-nearest neighbors (kNN) method has proven to be a very useful technique to classify and propa...
The k-Nearest Neighbors (k-NN) technique is a popular method for producing spatially contiguous pred...
Estimation and mapping of forest attributes are a fundamental support for forest management planning...
This study was designed to compare the performance – in terms of bias and accuracy – of four differe...
The increasing availability of remote sensing data at no or low costs can be used as ancillary data ...