TY - JOUR
T1 - Assessment of Wildfire Hazards with a Semiparametric Spatial Approach
T2 - A Case Study of Wildfires in South America
AU - Acevedo-Cabra, Ricardo
AU - Wiersma, Yolanda
AU - Ankerst, Donna
AU - Knoke, Thomas
N1 - Publisher Copyright:
© 2014, Springer International Publishing Switzerland.
PY - 2014/12/1
Y1 - 2014/12/1
N2 - Rural households in agricultural economies are vulnerable to several environmental risks such as fires, floods, and droughts that may affect their productivity in whole or in part. These hazards are especially relevant in developing countries where farmers have few or no access to traditional risk-transfer techniques, such as insurance and finance, and where low governmental investments in rural infrastructure, risk assessment techniques, or early warning systems makes the aftermath of such hazards more expensive and results in slower recovery for those who are affected. In this paper, we use historical satellite data (Terra) of burned areas in South America to fit a semiparametric spatial model, based on kernel smoothing and on a nonlinear relationship between average time between events and damage, to assess the environmental hazard affecting the land’s productivity. The results were twofold: first, we were able to develop a spatial assessment of fire hazard, and second, we were able to evaluate how much a farmer may lose in terms of productivity per hectare due to the environmental hazard. The methodology may be easily adapted to other world regions; to different environmental hazards such as floods, windbreak, windthrow, or related land-use changes; or to integrate various environmental hazards simultaneously, as long as they can be monitored via remote sensing (e.g., satellite imagery, aerial photographs, etc).
AB - Rural households in agricultural economies are vulnerable to several environmental risks such as fires, floods, and droughts that may affect their productivity in whole or in part. These hazards are especially relevant in developing countries where farmers have few or no access to traditional risk-transfer techniques, such as insurance and finance, and where low governmental investments in rural infrastructure, risk assessment techniques, or early warning systems makes the aftermath of such hazards more expensive and results in slower recovery for those who are affected. In this paper, we use historical satellite data (Terra) of burned areas in South America to fit a semiparametric spatial model, based on kernel smoothing and on a nonlinear relationship between average time between events and damage, to assess the environmental hazard affecting the land’s productivity. The results were twofold: first, we were able to develop a spatial assessment of fire hazard, and second, we were able to evaluate how much a farmer may lose in terms of productivity per hectare due to the environmental hazard. The methodology may be easily adapted to other world regions; to different environmental hazards such as floods, windbreak, windthrow, or related land-use changes; or to integrate various environmental hazards simultaneously, as long as they can be monitored via remote sensing (e.g., satellite imagery, aerial photographs, etc).
KW - Average time between events
KW - Environmental risk assessment
KW - Fire risk
KW - Kernel smoothing
KW - Satellite imagery
KW - Semiparametric
UR - http://www.scopus.com/inward/record.url?scp=84939885871&partnerID=8YFLogxK
U2 - 10.1007/s10666-014-9411-9
DO - 10.1007/s10666-014-9411-9
M3 - Article
AN - SCOPUS:84939885871
SN - 1420-2026
VL - 19
SP - 533
EP - 546
JO - Environmental Modeling and Assessment
JF - Environmental Modeling and Assessment
IS - 6
ER -