Land suitability analysis for maize production in Indonesia using satellite remote sensing and GIS-based multicriteria decision support system

Abstract

Maize is one of the potential crops can help in regional food production with self-sufficiency of foods in the drought prone areas of East Java in Indonesia. The purpose of this research is to determine the lands that are suitable for sustainable maize production in some selected areas of East Java by using various spatial and remote sensing datasets. The methodology was divided into three stages: first, the Landsat 8 operational land imagery satellite datasets were processed to create layers for the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI) and land surface temperature. For the proposed multicriteria analysis, another seven criteria: distance from roads, distance from rivers, slope, land cover, elevation levels, soil types and rainfall, were considered. Second, a spatial analysis was performed to identify highly suitable areas for maize production using a geographical extent and multicriteria analysis. Third, the criteria were determined using land suitability information for a 5-year period. The land suitability analysis with equal weight showed that 70.8% of the land (136,663 ha) was highly suitable, 26.3% of the land (50,872 ha) was moderately suitable, and 2.8% of the land (5391 ha) was marginally suitable. On the other hand, expert knowledge was also considered using the analytical hierarchy process (AHP) and indicated that 64.9% of the land (125,216 ha) was highly suitable, 30.4% of the land (58,828 ha) was moderately suitable, and 4.5% (8603 ha) of the land was marginally suitable. The yield estimation was determined for the highly suitable areas with NDVI (R2 = 77.81%) and SAVI (R2 = 72.8%). The regression analysis was incorporated to predicted yield of maize. This research recommends that satellite remote sensing, GIS and AHP-based multicriteria analysis can be extended for agricultural extension services to select suitable lands for increasing maize production.