Abstract
The advancement of remote sensing provides a new opportunity for a data analytical platform for robust decision-making based on near real-time datasets derived from satellites and unmanned aerial vehicles (UAVs). The spectral signature through passive and active remote sensing has the advantages of providing information on plant responses in low-, medium-, and high-resolution images with temporal variability and enables taking action for sustainable agriculture and forest resource management. Therefore, the aim of this review article is to find a new avenue for generating data management platforms in the field of agriculture and forestry. The advancement of satellite remote sensing technology has already been suggested to open the gateway to establishing big data analytical platforms through decision support systems. Specifically, this review paper highlights some appropriate and important applications of satellite and UAV-derived indices and algorithms to address the scope and application of geographic information systems (GISs) in the field of agriculture and forestry research. The analytical signatures of changes in vegetation and water storage in leaves and water bodies were analyzed and presented using different phenological properties, land use land cover (LULC) changes, and natural disaster damage assessments to support policy formations and the livelihoods of farmers. The remote sensing and GIS-based analytical datasets cover crop calendars and phenological changes from forest canopies that refer to productivity according to seasons. Seasonal variations in the productivity of crops and forests can ensure appropriate actions with resilience for the sustainable management of bioresources.
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Arab, S.T. et al. (2022). A Review of Remote Sensing Applications in Agriculture and Forestry to Establish Big Data Analytics. In: Ahamed, T. (eds) Remote Sensing Application. New Frontiers in Regional Science: Asian Perspectives, vol 59. Springer, Singapore. https://doi.org/10.1007/978-981-19-0213-0_1
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