Effect evaluation of topographic attributes on forest coverage ratios based on digital elevation model

Shojiro Tanaka, Ryuei Nishii

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Identification of the factors involved in deforestation could lead to a comprehensive understanding of deforestation on a broad scale, as well as a prediction capability. Tanaka and Nishii [7, 8] explored regression models with two explanatory variables - human population density (N) and relief energy (R), i.e., the difference between the maximum and minimum altitudes in a sampled area- as to whether they could elucidate aspects of deforestation. As relative appropriateness of the models, Akaike's Information Criterion was used to evaluate the models on real data. Although they suceeded in identifying the fuctional form of g(N) in Asian four test areas, the topographic term h(R) remained intact in terms of alternative possible variable forms. In this research, detailed verifications of the topographic feature were employed, and it was revealed that addition of mean altitude on the same cell will give great improvement to the model.

Original languageEnglish
Title of host publication2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
Pages2661-2664
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Melbourne, VIC, Australia
Duration: Jul 21 2013Jul 26 2013

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2013 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
CountryAustralia
CityMelbourne, VIC
Period7/21/137/26/13

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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