TY - GEN
T1 - Statistical frameworking of deforestation models based on human population density and relief energy
AU - Nishii, Ryuei
AU - Miyata, Daiki
AU - Tanaka, Shojiro
PY - 2012
Y1 - 2012
N2 - This paper establishes a statistical framework of forest coverage models for spatio-temporal data. The forest coverage ratio of grid-cell data is modeled by taking human population density and relief energy as explanatory variables. The likelihood of the forest ratios is decomposed by the product of two likelihoods. The first likelihood discussed by Nishii and Tanaka (2010) is due to trinomial logistic distributions on three categories: the ratios take zero, one, or values between zero and one. We consider a precise modeling to the second likelihood for partly-deforested ratios by considering a) spline functions to the additive mean structure, b) wide spatial dependency of normal error terms, and c) an extended logistic type transform to the forest ratio. For spatio-temporal data, we implement auto-regressive terms based on the ratios observed in past. The proposed model was applied to real grid-cell data and resulted significant improvement compared to our previous model.
AB - This paper establishes a statistical framework of forest coverage models for spatio-temporal data. The forest coverage ratio of grid-cell data is modeled by taking human population density and relief energy as explanatory variables. The likelihood of the forest ratios is decomposed by the product of two likelihoods. The first likelihood discussed by Nishii and Tanaka (2010) is due to trinomial logistic distributions on three categories: the ratios take zero, one, or values between zero and one. We consider a precise modeling to the second likelihood for partly-deforested ratios by considering a) spline functions to the additive mean structure, b) wide spatial dependency of normal error terms, and c) an extended logistic type transform to the forest ratio. For spatio-temporal data, we implement auto-regressive terms based on the ratios observed in past. The proposed model was applied to real grid-cell data and resulted significant improvement compared to our previous model.
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U2 - 10.1117/12.974583
DO - 10.1117/12.974583
M3 - Conference contribution
AN - SCOPUS:84875660582
SN - 9780819492784
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Earth Resources and Environmental Remote Sensing/GIS Applications III
T2 - Earth Resources and Environmental Remote Sensing/GIS Applications III
Y2 - 24 September 2012 through 26 September 2012
ER -