Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy

Ryuei Nishii, Shojiro Tanaka

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

1 Citation (Scopus)

Abstract

Deforestation is caused by various factors. In the literature, the impact of human activities as well as geographic circumstances on forests has been extensively discussed. Tanaka and Nishii have studied statistical models for prediction of forest area ratio by covariates: human population density and relief energy [1-3] observed in a grid-cell system. Parametric non-linear regression functions of the covariates were used for predicting forest coverage ratio [1], and cubic spline functions were also used for detection of small fluctuation of regression functions [2]. Furthermore, zero-one inflated distributions were proposed for classification of each site into one of three categories: completely-deforested, fully-forest-covered or partly-deforested areas [3]. These methods took the spatial dependency into the modeling, which is not an easy task.

Original languageEnglish
Title of host publication2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2552-2555
Number of pages4
Volume2015-November
ISBN (Electronic)9781479979295
DOIs
Publication statusPublished - Nov 10 2015
EventIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Milan, Italy
Duration: Jul 26 2015Jul 31 2015

Other

OtherIEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
CountryItaly
CityMilan
Period7/26/157/31/15

Fingerprint

population density
relief
prediction
modeling
Deforestation
energy
Splines
deforestation
human activity
human population
Statistical Models

All Science Journal Classification (ASJC) codes

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

Cite this

Nishii, R., & Tanaka, S. (2015). Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings (Vol. 2015-November, pp. 2552-2555). [7326332] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2015.7326332

Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy. / Nishii, Ryuei; Tanaka, Shojiro.

2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. p. 2552-2555 7326332.

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

Nishii, R & Tanaka, S 2015, Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy. in 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. vol. 2015-November, 7326332, Institute of Electrical and Electronics Engineers Inc., pp. 2552-2555, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015, Milan, Italy, 7/26/15. https://doi.org/10.1109/IGARSS.2015.7326332
Nishii R, Tanaka S. Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy. In 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Vol. 2015-November. Institute of Electrical and Electronics Engineers Inc. 2015. p. 2552-2555. 7326332 https://doi.org/10.1109/IGARSS.2015.7326332
Nishii, Ryuei ; Tanaka, Shojiro. / Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy. 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. pp. 2552-2555
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