Development of Spatial Model for Food Security Prediction Using Remote Sensing Data in West Java, Indonesia

The food crisis is a problem that the world will face. availability of growing areas continues to decrease with increase in demand result future. Good planning needed deal future crises. absence studies on development spatial models estimating an area’s status has made for handling suboptimal. This study aims predict security by integrating paddy fields environmental factors determine West Java Province. Food modeling done land cover, population, productivity, and identifying influence factors. cover prediction be developed using CA-Markov model. Meanwhile, identify factors, multivariable linear regression (MLR) was used from remote sensing observations. data are form NDDI (Normalized Difference Drought Index), NDVI Vegetation surface temperature (LST), soil moisture, precipitation, altitude, slopes. overall accuracy up 93%. From 2005, flow energy still able needs obtain surplus 6.103 Mcal. On other hand, 2030 not deficit 13,996,292.42 MLR results, seven affect productivity fields, determination coefficient reaching 50.6%. Thus, predicting production more specific if it integrates With this study, hoped can as material mitigating crises