Scaling-up agroforestry area in various forms is a scientific path towards achieving various sustainable development goals(SDGs),especially improving livelihood,reducing poverty,conserving environment and biodiversity...Scaling-up agroforestry area in various forms is a scientific path towards achieving various sustainable development goals(SDGs),especially improving livelihood,reducing poverty,conserving environment and biodiversity,and transforming climate change.In this study,the effort was made to investigate the land potentiality for agroforestry at the district level in Jharkhand State,India by applying geographic information system(GIS)modeling technology using climate(temperature and precipitation),topography(slope and elevation),ecology(percent tree cover and normalized difference vegetation index(NDVI)),and social economics(poverty rate and tribal dominance)factors.The results revealed that six districts of Jharkhand State had agroforestry potential greater than 60.00%.The highest agroforestry suitability was found in Simdega District(78.20%),followed by Pakur(76.25%),West Singhbhum(72.70%),Dumka(68.84%),Sahibganj(64.63%),and Godda(63.43%)districts.Additionally,we identified 513 out of 32,620 villages of Jharkhand State potentially suitable(agroforestry suitability≥80.00%)for agroforestry with the objective of life improvement among marginalized society.Under the outside forest area,8.58%of the total geographical land of Jharkhand State was wasteland,much of which was found suitable for agroforestry practices.The agroforestry setups in those wastelands can absorb 637 t carbon annually in long run and can provide direct economic benefits to the locals besides additional income for carbon emission reduction.This study concluded that Jharkhand State has plenty of high potential land for agroforestry,and adoption of agroforestry at the village level must be given high priority.This study could guide the nodal authorities to prepare appropriate strategies for scaling the tree cover in agroforestry systems in village-level landscape planning which needs policy attention and investment for achieving 9 out of the 17 SDGs.展开更多
Introduction: Despite serious interventions worldwide, malaria remains a significant cause of global morbidity and mortality. Malaria endemic zones are predominant in the poorest tropical regions of the world, especia...Introduction: Despite serious interventions worldwide, malaria remains a significant cause of global morbidity and mortality. Malaria endemic zones are predominant in the poorest tropical regions of the world, especially in continental Africa and South-Asia. Major Indian population reside in malaria endemic zones which are tribal dominated and inaccessible. Lack of suitable data, reporting and medical facilities in malaria vulnerable regions handicaps the decision makers in taking adequate steps. Natural resources were mapped to establish their possible linkage with malaria incidence and to delineate malaria hotspots using geo-spatial tools. Methods: Remote sensing data along with various ancillary data such as socio-economic (population in general, child population, tribal population, literacy), epidemiology (Malaria API and Pf cases) and environmental parameters (wetness, forest cover, rainfall, aspect, elevation, slope, drainage buffer, and breeding sites) were integrated on GIS platform using a designed weight matrix. Multi criteria evaluation was done to generate hotspot for effective monitoring of malaria incidences. Results: Various thematic layers were utilized for integrated mapping, and the final map depicted 59.1% of the study area is vulnerable to high to very high risk of malaria occurrence. Manoharpur Administrative Block consisted of 89% of its area under high to very high probability of malaria incidence and it needs to be prioritized first for preventing epidemic outbreak. Various village pockets were revealed for prioritizing it for focused intervention of malaria control measures. Conclusions: Geospatial technology can be potentially used to map in the field of vector-borne diseases including malaria. The maps produced enable easy update of information both spatially and temporally provide effortless accessibility of geo-referenced data to the policy makers to produce cost-effective measures for malaria control in the endemic regions.展开更多
基金the International Center for Research in Agroforestry(ICRAF)New Delhi Regional Centre for its motivation and support in conducting this study.
文摘Scaling-up agroforestry area in various forms is a scientific path towards achieving various sustainable development goals(SDGs),especially improving livelihood,reducing poverty,conserving environment and biodiversity,and transforming climate change.In this study,the effort was made to investigate the land potentiality for agroforestry at the district level in Jharkhand State,India by applying geographic information system(GIS)modeling technology using climate(temperature and precipitation),topography(slope and elevation),ecology(percent tree cover and normalized difference vegetation index(NDVI)),and social economics(poverty rate and tribal dominance)factors.The results revealed that six districts of Jharkhand State had agroforestry potential greater than 60.00%.The highest agroforestry suitability was found in Simdega District(78.20%),followed by Pakur(76.25%),West Singhbhum(72.70%),Dumka(68.84%),Sahibganj(64.63%),and Godda(63.43%)districts.Additionally,we identified 513 out of 32,620 villages of Jharkhand State potentially suitable(agroforestry suitability≥80.00%)for agroforestry with the objective of life improvement among marginalized society.Under the outside forest area,8.58%of the total geographical land of Jharkhand State was wasteland,much of which was found suitable for agroforestry practices.The agroforestry setups in those wastelands can absorb 637 t carbon annually in long run and can provide direct economic benefits to the locals besides additional income for carbon emission reduction.This study concluded that Jharkhand State has plenty of high potential land for agroforestry,and adoption of agroforestry at the village level must be given high priority.This study could guide the nodal authorities to prepare appropriate strategies for scaling the tree cover in agroforestry systems in village-level landscape planning which needs policy attention and investment for achieving 9 out of the 17 SDGs.
文摘Introduction: Despite serious interventions worldwide, malaria remains a significant cause of global morbidity and mortality. Malaria endemic zones are predominant in the poorest tropical regions of the world, especially in continental Africa and South-Asia. Major Indian population reside in malaria endemic zones which are tribal dominated and inaccessible. Lack of suitable data, reporting and medical facilities in malaria vulnerable regions handicaps the decision makers in taking adequate steps. Natural resources were mapped to establish their possible linkage with malaria incidence and to delineate malaria hotspots using geo-spatial tools. Methods: Remote sensing data along with various ancillary data such as socio-economic (population in general, child population, tribal population, literacy), epidemiology (Malaria API and Pf cases) and environmental parameters (wetness, forest cover, rainfall, aspect, elevation, slope, drainage buffer, and breeding sites) were integrated on GIS platform using a designed weight matrix. Multi criteria evaluation was done to generate hotspot for effective monitoring of malaria incidences. Results: Various thematic layers were utilized for integrated mapping, and the final map depicted 59.1% of the study area is vulnerable to high to very high risk of malaria occurrence. Manoharpur Administrative Block consisted of 89% of its area under high to very high probability of malaria incidence and it needs to be prioritized first for preventing epidemic outbreak. Various village pockets were revealed for prioritizing it for focused intervention of malaria control measures. Conclusions: Geospatial technology can be potentially used to map in the field of vector-borne diseases including malaria. The maps produced enable easy update of information both spatially and temporally provide effortless accessibility of geo-referenced data to the policy makers to produce cost-effective measures for malaria control in the endemic regions.
