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Forest type mapping Data Set
Download: Data Folder, Data Set Description

Abstract: Multi-temporal remote sensing data of a forested area in Japan. The goal is to map different forest types using spectral data.

Data Set Characteristics:  

Multivariate

Number of Instances:

326

Area:

Life

Attribute Characteristics:

N/A

Number of Attributes:

27

Date Donated

2015-05-25

Associated Tasks:

Classification

Missing Values?

N/A

Number of Web Hits:

65800


Source:

Brian Johnson
johnson '@' iges.or.jp
Institute for Global Environmental Strategies


Data Set Information:

This data set contains training and testing data from a remote sensing study which mapped different forest types based on their spectral characteristics at visible-to-near infrared wavelengths, using ASTER satellite imagery. The output (forest type map) can be used to identify and/or quantify the ecosystem services (e.g. carbon storage, erosion protection) provided by the forest.


Attribute Information:

Class: 's' ('Sugi' forest), 'h' ('Hinoki' forest), 'd' ('Mixed deciduous' forest), 'o' ('Other' non-forest land)
b1 - b9: ASTER image bands containing spectral information in the green, red, and near infrared wavelengths for three dates (Sept. 26, 2010; March 19, 2011; May 08, 2011.
pred_minus_obs_S_b1 - pred_minus_obs_S_b9: Predicted spectral values (based on spatial interpolation) minus actual spectral values for the 's' class (b1-b9).
pred_minus_obs_H_b1 - pred_minus_obs_H_b9: Predicted spectral values (based on spatial interpolation) minus actual spectral values for the 'h' class (b1-b9).


Relevant Papers:

Johnson, B., Tateishi, R., Xie, Z., 2012. Using geographically-weighted variables for image classification. Remote Sensing Letters, 3 (6), 491-499.



Citation Request:

Johnson, B., Tateishi, R., Xie, Z., 2012. Using geographically-weighted variables for image classification. Remote Sensing Letters, 3 (6), 491-499.


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