The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W6-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W6-2021, 27–33, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-27-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W6-2021, 27–33, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-27-2021

  18 Nov 2021

18 Nov 2021

CLIMATE RISK VULNERABILITY ASSESSMENT OF THE MAJOR CROPS IN THE PROVINCE OF AGUSAN DEL NORTE, PHILIPPINES

A. G. Apdohan1,2, R. P. Varela3, and R. M. Balanay3 A. G. Apdohan et al.
  • 1College of Engineering and Geosciences, Caraga State University, Butuan City, Philippines
  • 2Center for Resource Assessment, Analytics and Emerging Technologies, Caraga State University, Butuan City, Philippines
  • 3College of Agriculture and Agri-Industries, Caraga State University, Butuan City, Philippines

Keywords: Climate Risk Vulnerability, GIS, MaxEnt, Sensitivity, Exposure, Adaptive Capacity

Abstract. Assessing an area's vulnerability can serve as an effective planning tool to increase resilience to climate-related hazards. This paper provides information on the most vulnerable municipalities to climate change impacts in the province of Agusan del Norte, Philippines. The assessment included in the geospatial analysis were physical, agro-ecological, and socio-economic indicators clustered under the components of exposure, sensitivity, and adaptive capacity. Using MaxEnt, modelling the suitability of crops due to changes in temperature and precipitation by the year 2050 determines the crops' sensitivity. A combination of natural hazards datasets was used to estimate the extent of exposure to each municipality within the province under pressure from climate and hydro-meteorological risks. An up-to-date database from the concerned local government units for adaptive capacity indicators was clustered into seven capitals: economic, natural, human, physical, social, anticipatory, and institutional. The total CRV model for rice, corn, and banana crops revealed that the municipalities identified as highly vulnerable due to their high exposure to climate hazards, the decreasing crops' suitability to climate variability, and low adaptive capacity.