TY - JOUR
T1 - Distinguishing the windthrow and hydrogeological effects of typhoon impact on agricultural lands
T2 - An integrative OBIA and PPGIS approach
AU - Chen, Tzu Hsin
AU - Lin, Kuan Hui Elaine
N1 - Publisher Copyright:
© 2017 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/1/2
Y1 - 2018/1/2
N2 - The agricultural impacts of tropical cyclones remain the primary threat to livelihoods in Southeast Asia and Latin America. The impacts take two forms, one is windthrow, i.e. uprooted or snapped trees, caused by strong wind, and the other is hydrogeological effects from heavy precipitation. The empirical effects are different for the two forms. However, little previous research has been devoted to distinguishing the two effects to estimate agricultural losses, and even fewer have used moderate-resolution (10 m resolution) images. This study presents a methodological progression to address this deficiency. First, an object-based image analytical method distinguishes the two effects using Satellite Pour l’Observation de la Terre — 5 satellite images. Various object-based features are compared to acquire their spectral, textural, and geometric characteristics for the interpretation. Second, a public participation geographical information system (PPGIS) approach is developed that combines community empowerment and collaborative field survey to rebuild and represent ground truth during disasters for image validation. The method is applied to a case study of typhoon Bopha that struck Compostela Valley, eastern Mindanao, the Philippines in December 2012. Our assessment indicates that the producer accuracy reaches 88.9% for debris and mud flows and 83.3% for windthrow, and user accuracy reaches 94% and 81%, respectively. The result indicates that the proposed methods have great potential for distinguishing the two effects. It also highlights the efficacy of integrating PPGIS with remote sensing, for image validation purposes and in practice to enhance local residents’ environmental consciousness for enhancing adaptive capacity in resource limited regions.
AB - The agricultural impacts of tropical cyclones remain the primary threat to livelihoods in Southeast Asia and Latin America. The impacts take two forms, one is windthrow, i.e. uprooted or snapped trees, caused by strong wind, and the other is hydrogeological effects from heavy precipitation. The empirical effects are different for the two forms. However, little previous research has been devoted to distinguishing the two effects to estimate agricultural losses, and even fewer have used moderate-resolution (10 m resolution) images. This study presents a methodological progression to address this deficiency. First, an object-based image analytical method distinguishes the two effects using Satellite Pour l’Observation de la Terre — 5 satellite images. Various object-based features are compared to acquire their spectral, textural, and geometric characteristics for the interpretation. Second, a public participation geographical information system (PPGIS) approach is developed that combines community empowerment and collaborative field survey to rebuild and represent ground truth during disasters for image validation. The method is applied to a case study of typhoon Bopha that struck Compostela Valley, eastern Mindanao, the Philippines in December 2012. Our assessment indicates that the producer accuracy reaches 88.9% for debris and mud flows and 83.3% for windthrow, and user accuracy reaches 94% and 81%, respectively. The result indicates that the proposed methods have great potential for distinguishing the two effects. It also highlights the efficacy of integrating PPGIS with remote sensing, for image validation purposes and in practice to enhance local residents’ environmental consciousness for enhancing adaptive capacity in resource limited regions.
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U2 - 10.1080/01431161.2017.1382741
DO - 10.1080/01431161.2017.1382741
M3 - Article
AN - SCOPUS:85048082380
SN - 0143-1161
VL - 39
SP - 131
EP - 148
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
IS - 1
ER -