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Estimation of crop and forest biomass resources in a semi-arid region using satellite data and GIS

In India the demand of sustainable energy is growing at a fragmented level. The demand of rural electrification and economic growth requires high production of energy. Hence, the use of renewable energy may help to mitigate air pollution, and allow specific regenerative agriculture, waste, and forest biomass for producing the energy and achieving sustainable development goals. In the current work, we have selected a district of Maharashtra state of India as a case study and mapped the different land cover categories, and their estimated biomass. Based on this we have prepared the biomass thematic maps for the study area. These biomass maps have been prepared in the GIS environment and they displayed the biomass of crops, forests, and wastelands. The studied district has huge potential for agricultural biomass and can act as biofuel and biomass economies. These maps may play a crucial role in upgrading biomass sites focused on generating power from plants in the district Akola of Maharashtra, India.
- Zhejiang Ocean University China (People's Republic of)
- Zhejiang Ocean University China (People's Republic of)
- Sant Gadge Baba Amravati University India
- Mansoura University Egypt
- University of Allahabad India
Renewable energy, Agriculture (General), S1-972, Earth observing data sets, Mapping, Biomass
Renewable energy, Agriculture (General), S1-972, Earth observing data sets, Mapping, Biomass
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).38 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
