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Firoz Ahmad, Md Meraj Uddin and Laxmi Goparaju

Abstract

Agroforestry provides the foundation for climate-smart agriculture to withstand the extreme weather events. The aim of the present study was to identify the land of Samastipur, Bihar, India for agroforestry, based on GIS modeling concept utilizing various ancillary (soil fertility) and satellite data (DEM, wetness, NDVI and LULC) sets. This was achieved by integrating various thematic layers logically in GIS domain. Agroforestry suitability maps were generated for the Samastipur district of Bihar, India which showed 48.22 % as very high suitable, 22.83 % as high suitable, 23.32% as moderate suitable and 5.63% as low suitable. The cross evaluation of agroforestry suitability with LULC categories revealed that the 86.4 % (agriculture) and 30.2% (open area) of land fall into a very high agroforestry suitability category which provides the huge opportunity to harness agroforestry practices if utilized scientifically. Such analysis/results will certainly assist agroforestry policymakers and planner in the state of Bihar, India to implement and extend it to new areas. The potentiality of Remote Sensing and GIS can be exploited in accessing suitable land for agroforestry which will significantly help to rural poor people/farmers in ensuring food and ecological security, resilience in livelihoods.

Open access

Firoz Ahmad, Md Meraj Uddin and Laxmi Goparaju

Abstract

Geospatial evaluation of various datasets is extremely important because it gives a better comprehension of the past, present and future and can therefore be significantly utilized in effective decision making strategies. This study examined the relationships, using geospatial tools, between various diversified datasets such as land use/land cover (LULC), long term Normalized Difference Vegetation Index (NDVI) based changes, long term forest fire points, poverty percentage, tribal percentage, forest fire hotspots, climate change vulnerability, agricultural vulnerability and future (2030) climate change anomalies (RCP-6) of Jharkhand state, India, for a better understanding and knowledge of its vegetation health, LULC, poverty, tribal population and future climate change impact. The long term NDVI (1982-2006) evaluation revealed negative change trends in seven northwest districts of Jharkhand state, these were: Hazaribag, Ramgarh, Palamu, Lohardaga, Chatra, Garhwa and Latehar. The forests as well as the agriculture of these districts have lost their greenness during this period. The forest fire frequency events were found to be more pronounced in the land use/land cover of “tropical lowland forests, broadleaved, evergreen, <1000 m” category, and were roughly twice the intensity of the “tropical mixed deciduous and dry deciduous forests” category. In the nine districts of Jharkhand it was found that 40 % of the population was living below the poverty line which is around twice the national average. The highest poverty districts, in percentage, were: Garwah (53.93), Palamu (49.24), Latehar (47.99) and Chatra (46.2). The southwest and south of Jharkhand state shows a tribal population density of more than 40%. The climate change vulnerability was found to be highest in the district of Saraikela followed by Pashchim Singhbhum, whereas agricultural vulnerability was found to be highest in the district of Pashchim Singhbhum followed by Saraikela, Garhwa, Simdega, Latehar, Palamu and Lohardaga. The temperature anomalies prediction for the year 2030 shows an increasing trend in temperature with values of 0.8°C to 1°C in the state of Jharkhand. The highest increases were observed in the districts of Pashchim Singhbhum, Simdega and Saraikela. Based on these evaluations we can conclude that a few of the districts of Jharkhand, such as Pashchim Singhbhum, Garhwa, Palamu and Latehar need to be prioritized for development on an urgent basis. The outcomes of this study would certainly guide the policymakers to prepare more robust plans when keeping in mind the future climate change impacts for the prioritization of various districts of Jharkhand which suffer from extreme poverty, diminished livelihood and insignificant agricultural productivity for the betterment of the people of Jharkhand based on their adaptive capacity.