TY - GEN
T1 - Non-linear regression models to identify functional forms of deforestation
AU - Tanaka, Sojiro
AU - Nishii, Ryuei
PY - 2008
Y1 - 2008
N2 - Identification of limited number of factors shall provide comprehensive general understanding of deforestation at broad scale, as well as the projection for the future. Only two factors - human population and relief energy (difference of minimum altitude from the maximum in a sampled area) - were verified if they give sufficient elucidation of deforestation by a regression model, whose functional forms identified by linear combinations of dummy variables firstly explored with use of high-precision Japanese data. Likelihood with spatial dependency was derived and applied then to East-Asian data, with which our models systematically showed eminently good relative appropriateness to the real data.
AB - Identification of limited number of factors shall provide comprehensive general understanding of deforestation at broad scale, as well as the projection for the future. Only two factors - human population and relief energy (difference of minimum altitude from the maximum in a sampled area) - were verified if they give sufficient elucidation of deforestation by a regression model, whose functional forms identified by linear combinations of dummy variables firstly explored with use of high-precision Japanese data. Likelihood with spatial dependency was derived and applied then to East-Asian data, with which our models systematically showed eminently good relative appropriateness to the real data.
UR - http://www.scopus.com/inward/record.url?scp=67649732455&partnerID=8YFLogxK
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U2 - 10.1109/IGARSS.2008.4779653
DO - 10.1109/IGARSS.2008.4779653
M3 - Conference contribution
AN - SCOPUS:67649732455
SN - 9781424428083
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 49
EP - 52
BT - 2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2008 IEEE International Geoscience and Remote Sensing Symposium - Proceedings
Y2 - 6 July 2008 through 11 July 2008
ER -