TY - GEN
T1 - Unified modeling based on SVM and SVR for prediction of forest area ratio by human population density and relief energy
AU - Nishii, Ryuei
AU - Tanaka, Shojiro
N1 - Publisher Copyright:
© 2015 IEEE.
Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.
PY - 2015/11/10
Y1 - 2015/11/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84962539865&partnerID=8YFLogxK
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U2 - 10.1109/IGARSS.2015.7326332
DO - 10.1109/IGARSS.2015.7326332
M3 - Conference contribution
AN - SCOPUS:84962539865
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2552
EP - 2555
BT - 2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015
Y2 - 26 July 2015 through 31 July 2015
ER -