The k-nearest neighbors (kNN) method has proven to be a very useful technique to classify and propagate forest field plot information through the landscape. This classification and estimation process reproduces the covariance structure of the observed data and retains the full range of variability inherent in the sample. The applications described here are for use with Landsat TM satellite imagery and USDA Forest Service Forest Inventory and Analysis (FIA) data for Minnesota. However, these applications can be readily adapted to other imagery and forest inventory data formats. The software provides a range of statistical and map analysis and output.Research supported by NASA, the USDA Forest Service, the National Council on Air and Str...
The purpose of this study was to estimate of forestry-biomass using by k-Nearest Neighbor (k-NN) alg...
Accurate information about forest volumes is essential for forest management planning. The survey in...
Inferences for forest-related spatial problems can be enhanced using remote sensing-based maps const...
In the last decades researchers investigated the possibility of extending the information collected ...
The k-Nearest Neighbors (k-NN) technique is a popular method for producing spatially contiguous pred...
This paper discusses the usability of non-parametric knn (k-nearest neighbour) method to detect chan...
The integration of forest inventory and mapping has emerged as a major issue for assessing forest at...
From the combination of optical satellite data, digital map data, and forest inventory plot data, co...
The k-nearest neighbour (kNN) algorithm is commonly used in Scandinavia and North America for the ma...
The use of optical and radar data for estimation of forest variables has been investigated and evalu...
Mapping forest variables and associated characteristics is fundamental for forest planning and manag...
To the best of our knowledge, one or more authors of this paper were federal employees when contribu...
Estimation and mapping of tropical forest biomass is important for periodic carbon accounting, as tr...
Estimation and mapping of forest attributes are a fundamental support for forest management planning...
Forest surveys provide critical information for many diverse interests. Data are often collected fro...
The purpose of this study was to estimate of forestry-biomass using by k-Nearest Neighbor (k-NN) alg...
Accurate information about forest volumes is essential for forest management planning. The survey in...
Inferences for forest-related spatial problems can be enhanced using remote sensing-based maps const...
In the last decades researchers investigated the possibility of extending the information collected ...
The k-Nearest Neighbors (k-NN) technique is a popular method for producing spatially contiguous pred...
This paper discusses the usability of non-parametric knn (k-nearest neighbour) method to detect chan...
The integration of forest inventory and mapping has emerged as a major issue for assessing forest at...
From the combination of optical satellite data, digital map data, and forest inventory plot data, co...
The k-nearest neighbour (kNN) algorithm is commonly used in Scandinavia and North America for the ma...
The use of optical and radar data for estimation of forest variables has been investigated and evalu...
Mapping forest variables and associated characteristics is fundamental for forest planning and manag...
To the best of our knowledge, one or more authors of this paper were federal employees when contribu...
Estimation and mapping of tropical forest biomass is important for periodic carbon accounting, as tr...
Estimation and mapping of forest attributes are a fundamental support for forest management planning...
Forest surveys provide critical information for many diverse interests. Data are often collected fro...
The purpose of this study was to estimate of forestry-biomass using by k-Nearest Neighbor (k-NN) alg...
Accurate information about forest volumes is essential for forest management planning. The survey in...
Inferences for forest-related spatial problems can be enhanced using remote sensing-based maps const...