Acreage and production estimation of mango orchards using Indian Remote Sensing (IRS) satellite data

Abstract

In order to exploit the potential of remote sensing in the field of horticulture, a study was initiated to estimate acreage and production of mango orchards using Indian Remote Sensing (IRS) satellite data. The data from linear imaging self scanning (LISS) II of IRS 1B and IRS 1C LISS III data covering the study area have been used. The boundary mask as well as sample segment approaches were tried for acreage estimation. Available yield data and meteorological and growth parameter data were collected to develop an agro-meteorological model. The study has clearly demonstrated the usefulness of LISS II and LISS III data for identifying and estimating mango orchard acreage. It was observed that use of LISS III is better compared to LISS II as the spatial resolution has improved the classification using maximum likelihood algorithm. The study also indicated that the condition of orchards could also be assessed to some extent. Total enumeration technique using summer season data gave very accurate acreage estimates of mango. The sampling approach is also good for mango orchard acreage estimation which provided almost the same accuracy as total enumeration technique but by saving about 6–8 times the analysis time and cost. Due to non-availability of reliable data at different levels, it was difficult to develop any regional level single yield model. However, it was observed that an agro-meteorological data-based model could be developed by collecting such data for 3–4 years in selected orchards.