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Displaying 896 - 900 of 1195Prioritization of Sub-watersheds in Khanapara–Bornihat Area of Assam–Meghalaya (India) Based on Land Use and Slope Analysis Using Remote Sensing and GIS
Improper utilization of natural resources without any conservation work is the prime cause of the watershed deterioration. Fast developmental activities and population pressure in the hills of Khanapara–Bornihat area near Guwahati city (about 10 km east of Guwahati) results rapid alteration of the land use/land cover in the recent times. This also causes the growth of land use over the unsuitable topography. As a result, there is a general degradation of the natural resources within the area.
Unfulfilled farmer expectations: the case of the Insect Resistant Maize for Africa (IRMA) project in Kenya
BACKGROUND: Maize is the most important staple food in Kenya; any reduction in production and yield therefore often becomes a national food security concern. To address the challenge posed by the maize stem borer, the Insect Resistant Maize for Africa (IRMA) agricultural biotechnology public-private partnership (PPP) project was launched in 1999. There were, however, pre-existing concerns regarding the use of genetic engineering in crop production and skepticism about private sector involvement.
Human activities directly alter watershed dissolved silica fluxes
Controls on chemical weathering, such as bedrock geology, runoff, and temperature, are considered to be the primary drivers of Si transport from the continents to the oceans. However, recent work has highlighted terrestrial vegetation as an important control over Si cycling. Here we show that at the regional scale (Southern New England, USA), land use/land cover (LULC) is an important variable controlling the net transport of Si from the land to the sea, accounting for at least 40% of dissolved Si (DSi) fluxes.
Exploring the Potential of Object Based Image Analysis for Mapping Urban Land Cover
The paper investigates the performance and potential of object based image analysis technique (OBIA) for land cover information extraction from high resolution satellite datasets. Efficiency of the technique has been assessed in different urban land cover situations using merged CARTOSAT-1 and IRS-P6 LISS-IV image subsets of Dehradun, India. Multi-scale iterative Nearest Neighbour classification has been applied. Classification results have been quantitatively evaluated.
Three distinct global estimates of historical land-cover change and land-use conversions for over 200 years
Earth’s land cover has been extensively transformed over time due to both human activities and natural causes. Previous global studies have focused on developing spatial and temporal patterns of dominant human land-use activities (e.g., cropland, pastureland, urban land, wood harvest). Process-based modeling studies adopt different strategies to estimate the changes in land cover by using these land-use data sets in combination with a potential vegetation map, and subsequently use this information for impact assessments.