Big Data Scheme from Remote Sensing Applications: Concluding Notes for Agriculture and Forestry Applications

Abstract

This chapter discusses the application of remote sensing perspective and how to develop the big data analytical platform for diversified land-use planning towards food and nutrition security, crop growth monitoring, yield forecasting, land suitability analysis, forest productivity and drought assessment for crops, vegetables, and fruits. The geospatial, mathematical, and logical modeling including multicriteria evaluation systems were conducted to determine the key outcomes of each chapter in this book have been lucidly discussed. Remote sensing and GIS-based systematic analysis are reported to indicate the biophysical and socioeconomic factors that bring sustainability in regional policy planning. The big data scheme for regional planning requires the high-density levels of data that ensures trustworthiness, authenticity, availability, and accountability of datasets. Furthermore, geospatial planning has the advantages of trustworthiness and authenticity in the intervention process to support the livelihoods of farmers during damages due to drought and flash floods. In regard to carbon stock analysis and forest loss assessment, ecological resource conservation is discussed referring to vegetation signatures derived from satellite imageries. Additionally, forest productivity assessment is explained based on carbon stock analysis to establish resilience in forest ecosystems.