Browsing by Author "Rahul Nigam"

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Geospatial technology in agroforestry: status, prospects, and constraints
(Springer, 2023) Prashant Sharma; Daulat Ram Bhardwaj; Manoj Kumar Singh; Rahul Nigam; Nazir A. Pala; Amit Kumar; Kamlesh Verma; Dhirender Kumar; Pankaj Thakur
Agroforestry has an indispensable role in food and livelihood security in addition to its capacity to combat the detrimental effects of climate change. However, agroforestry has not been properly promoted and exploited due to lack of precise extent, geographical distribution, and carbon sequestration (CS) assessment. The recent advent of geospatial technologies, as well as free availability of spatial data and software, can provide new insights into agroforestry resources assessment, decision-making, and policy development despite agroforestry’s small spatial extent, isolated nature, and higher structural and functional complexity of agroforestry. In this review, the existing application of geospatial technologies together with its constraints and limitations as well as the potential future application for agroforestry has been discussed. The review reveals that the application of optical remote sensing in agroforestry includes spatial extent mapping, production of tree species spectral signature, CS assessment, and suitability mapping. Simultaneously, the recent surge in the use of synthetic aperture radar in conjunction with algorithms based on vegetation photosynthesis and optical data enables a more accurate estimation of gross primary productivity at different scales. However, unmanned aerial vehicles equipped with sensors, such as multispectral, LiDAR, hyperspectral, and thermal, offer a considerably higher potential and accuracy than satellite-based datasets. In the future, the health monitoring of agroforestry systems can be a key concern that may be addressed by utilizing hyperspectral and thermal datasets to analyze plant biochemistry, chlorophyll fluorescence, and water stress. Additionally, current (GEDI, ECOSTRESS) and future space agency missions (BIOMASS, FLEX, NISAR, TRISHNA) have enormous potential to shed fresh light on agroforestry systems. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.