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Displaying 496 - 500 of 1195Land leveling and changes in soil properties in paddy fields of Guilan province, Iran
The aim of this study was to evaluate the impacts of land leveling on some of soil properties. Land leveling as an effective strategy for paddy land management is one of the most important programs run by the Ministry of Jihad-Agriculture in Guilan province, northern part of Iran. Precise land leveling improves irrigation application, fertilization efficiency, and uniform soil moisture for germination. Also, it increases yields and cultivable lands and reduces delivery losses.
Automated Approach for Land Cover Classification Based on a Fuzzy Supervised Learning Framework
This paper proposes an automatic framework for land cover classification. In majority of published work by various researchers so far, most of the methods need manually mark the label of land cover types. In the proposed framework, all the information, like land cover types and their features, is defined as prior knowledge achieved from land use maps, topographic data, texture data, vegetation’s growth cycle and field data.
Land use/land cover classification of the vicinity of Lake Chad using NigeriaSat-1 and Landsat data
Lake Chad in Africa experienced severe droughts in the 1970s and 1980s and overexploitations of water resulting in a decline of water level in the Lake and surrounding rivers. Such droughts and overexploitation of water caused a significant change of land use and water management practices over the last 50� years. Understanding the change of land use and land cover is, therefore, crucial to understand disturbance of the water cycle around the Lake.
Prediction of Land Cover Change Using Markov and Cellular Automata Models: Case of Al-Ain, UAE, 1992-2030
The UAE has witnessed rapid urban development and economic growth in recent years. With its ambitious vision to become one of the advanced nations by 2021, planners and policy-makers need to know the most likely direction of future urban development. In this study, remotely sensed imagery coupled with cellular automata models were used to predict land cover in Al Ain, the second largest city in the Emirate of Abu Dhabi. Markov and cellular automata models were used for 1992 and 2006 to predict land cover in 2012.
alternative approach for delineating eco-sensitive zones around a wildlife sanctuary applying geospatial techniques
The dynamics, degradation, and conservation of forest ecosystems are matters of prime concerns worldwide at the present. Proper planning and management of a forest area are essentially needed to protect it from the grasp of burgeoning pressure of urban-industrial sprawl. Establishment of eco-sensitive zones (ESZs), which act as buffer areas around the core forests, is one of the key approaches towards achieving this goal.