Geospatial technology has an enormous capacity to analyze large and diversified datasets for evaluating the hidden spatial relationship which provides a better comprehension of the subject and helps significantly in policymaking and planning future strategies. This study has examined the relationship among diversified remote sensing and GIS datasets such as GHG emission from cropland, rice cultivation area, agro-ecological region, Land use/ Land cover (LULC) categories, long-term NDVI (1982-2006) based negative changes, agriculture vulnerability, drought-prone area and future (2021, 2050) climate change anomalies (RCP-6) of India for better understanding and knowledge of the GHG emission scenario, vegetation health, LULC, agriculture vulnerability, and future climate change impact. The LULC analysis revealed that 49.6% (1 628 959 km2) of the geographical area was found to be under category ‘cropland’. The 32.5% of the total cropland areas are used for rice cultivation whereas around 76% of this rice cultivation area is producing high GHG emission (>1000 Mg CO2e/yr.). LULC categories ‘Cropland’ and ‘Plantation’ show the long-term (1982-2006) negative change equivalent to 19.7 and 70.2% respectively. Similarly, around 56% of LULC categories representing the forest show the long-term negative change whereas the maximum change (139 867 km2) was found in the category of ‘Deciduous Broadleaf Forest’. The 30.6% of the LULC category of ‘cropland’ falls in very high agriculture vulnerable areas whereas 31.7% of the same category falls in the drought-prone area. The significant increase in temperature and abrupt rainfall patterns were observed during Kharif and Rabi seasons in the future. Such variation of climate parameter in the future not only adversely affect the agriculture crop production but also the natural vegetation of India. The outcomes of the present study would support the policymakers of India to implement the climate-smart agriculture (CSA) and REDD+ on an urgent priority based on a proper evaluation of the socio-economic condition of the poor people. It will certainly help in the reduction of GHG emission, forest amelioration, will bring the resilience in livelihood and mitigate the poverty among the rural communities for the betterment of people.
Tag: GIS
Environment suitability mapping of livestock: A case study of Ethiopian indigenous sheep and goats
Demand for livestock products is increasing as climate volatility threatens animal productivity and welfare. Therefore, novel technologies and approaches to meet these challenges are required. Geo-informatics and geo-visualization can address a critical question in this endeavor -where can improved indigenous, newly developed and composite breeds be introduced while retaining optimal productivity and resilience to climatic and environmental volatility? Here, a case study of four and two Ethiopian indigenous breeds of sheep (Atsbi, Doyogena, Horro, Menz) and goats (Abergelle, Yabello), and geo-informatics based spatial analytics generating, for each breed, a suitability index map is presented. The analysis reveals overlapping and breed-specific enviro-geographic and ecological suitability niches. More than 51% of Ethiopia is unsuitable for the optimal performance of the six breeds. The proportions of unsuitable land are 64.84% (Menz), 53.44% (Horro), 76.98% (Doyogena), 83.53% (Atsbi), 82.37% (Abergelle) and 63.89% (Yabello). The suitable production range for the four sheep breeds show a slight overlap, but that of the two goat breeds did not. The goats are best suited to the drylands, but the niche for Abergelle is in the north, and that of Yabello is in the south of Ethiopia. The heatmaps suggest that the mean annual temperature and precipitation have the largest contribution in the classification of geographic areas into suitability classes. Our results provide insights for targeting location specific species- and breed-interventions, and with climate change trajectories and natural resource base abundance, will be a major criterion for building resilient livestock production systems. Furthermore, ecological suitability mapping can allow practitioners to evaluate potential geographic ranges for newly-developed, experimental, and improved livestock breeds to design sustainable and innovative agro-ecological solutions.
Biomass Carbon and Tree Cover Dynamics Assessment (2000–2010) on Agriculture Landscape in India: Geospatial Interpretation
This paper assesses the remote sensing datasets of biomass carbon on the agricultural landscape and their decadal change dynamics due to variation in tree cover dominance using geospatial technology in India. Remote sensing data showed that in the year 2000, 16.9% of all agricultural land (28.02 million hectares) in India had agroforestry land (at least 10% tree cover) which was further increased to 22.5% (37.30 million hectares) over 10 years (up to the year 2010). The total biomass carbon estimate in the year 2000 was found 1868.75 million tons of carbon (1.87 Pg C) over the Indian agriculture landscape (166 million hectares). Out of which approximately 1039 million tons (1.04 Pg C) of biomass carbon come from trees (with 55.7% contribution). Total biomass carbon loss between the periods of 2000 and 2010 was observed 31.19 million tons, whereas gain was 170.02 million tons. The decadal biomass carbon net gain was 138.83 million tons due to an increase in agroforestry land by 5.6% (9.27 million hectares). The mean biomass carbon in India increased from 11.29 to 12.13t C ha1 in 10 years, whereas the global mean increment is 20.4 to 21.4t C ha1 during the same base periods (Zomer et al in Sci Rep 6:29987, https://doi.org/10.1038/srep29987, 2016). Our analysis critically addressed one of the past research gaps of the biomass carbon-related findings in the agriculture landscape due to tree cover variation. Such understanding will assist significantly agroforestry decision-makers of India in enhancing future harmonized blueprint for agroforestry.
Potential of Agroforestry to Provide Wood Resources to Central Asia
Background: Agroforestry systems have the potential to provide timber and wood as a domestic raw material, as well as an additional source of income for rural populations. In Central Asia, tree windbreaks from mainly poplar trees have a long tradition, but were largely cut down as source for fuel wood after the disintegration of the Soviet Union. As Central Asia is a forest-poor region, restoration of tree windbreaks has the potential to provide timber and wood resources to that region. This study aimed to assess the potential of tree windbreaks to contribute to domestic timber and wood production. Methods: This study rests on a GIS-based analysis, in which tree lines (simulated by line shape files) were intersected with cropland area. The tree data to calculate timber and wood volumes stem from a dataset with 728 single trees from a relevant range of climatic conditions. Results: The potential annually available timber volumes from tree windbreaks with 500 m spacing are 2.9 million m3 for Central Asia as a whole and 1.5 million m3 for Uzbekistan alone, which is 5 times the current domestic roundwood production and imports of the country. Conclusions: tree windbreaks offer untapped potential to deliver wood resources domestically as a raw material for wood-based value chains.