Water Soil Availability Prediction in Coffee Land Plantations with Remote Sensing

Abstract

Abstract The availability of soil water is the basis of plant growth, so its availability is important key for coffee plants growing in South Malang. Climate change makes the availability of water for these plants a complex problem because changing temperature and humidity. Remote sensing is a fast and cheap way to predict water availability in coffee plantations with large land areas and rapid climate change. The aims of this research to estimate water soil availability in coffee land plantations to meet plant water needs. The water content in coffee plantations can be estimated by combining the vegetation index values with a combination of Normalized Difference Vegetation Index (NDVI), Fractional Vegetation Cover (FVC), Land Surface Temperature (LST), and Land Surface Emissivity (LSE). The method used in this research is to make tentative maps obtained from overlays of all combining the vegetation index values. The selection of research locations is based on the area of the coffee plantation using the smallest pixel, with an area of 3.000.000 m square meters. Each location of the research location was carried out four times for sampling the soil moisture content. The results showed that the correlation value between water content and the estimation results had a correlation of 0.814, with a regression value of 0.663 and a probability value of 0.9226. This shows that it is possible to estimate the water content of coffee plantations using remote sensing made it easier for coffee farmers to take action based on actual conditions on the land.