Rapid and unplanned urbanization and haphazard infrastructure development causes pressure on the finite land resource and there is urgent need to preserve the arable land for food security. Land suitability analysis is a technique in which the land quality assessment is performed through interpretation of land properties for allocation of lands for particular use. The present paper attempts to conduct a land suitability analysis to determine the potential sites for agriculture land use in Sambhunath municipality of Saptari district. The criteria/ factors for the land suitability analysis were identified through literatures and modified in the local context through expert opinions and focus group discussions. The evaluation of agriculture land is accomplished using Analytic Hierarchy Process (AHP), Multi-Criteria Evaluation (MCE) and Geographic Information System (GIS). Agriculture suitability index was developed and optimized qualitatively through the strength, weakness, opportunity, and threat (SWOT) analysis. Finally, potential agriculture suitability index map is prepared. The analysis shows almost 3139 ha (29%) lands as 14 highly suitable and 3001 ha (28%) of moderately suitable agriculture land within the municipality. Almost all the suitable agriculture land is located at low land with flat terrain to gentle slope having high natural fertility and mainly in land capability classes I and II. The unsuitable and poorly suitable agriculture land is occupied in the undulating areas and hilly terrain of the Siwalik hill. The study found the GIS tool integrated with MCE-AHP useful in land suitability evaluation process and anticipated that it could act as the planning tool to allocate lands in land use planning for sustainable agricultural practices.
Dynamics of land use are closely related with society, development activities and environment. For the sustainable management of land resource of an area, land use may act as one of the elements of conflicts which could be resolved through land use planning ensuring equitable access and right of land to the owners. The present paper attempts to assess the land use for land use planning and infrastructure development through land evaluation including risk factors. Sambhunath municipality located within Saptari district of Nepal has been used as the study area to test the issues raised. Both qualitative and quantitative methods are used for data generation and analysis. Land use changes have been analyzed for the period 1986 to 2017. Potential land use zones have been identified through land suitability analysis using MCE-AHP and in relation to the risk factors such as flood, soil erosion, landslide, and fire. The infrastructure development plan has been allocated based on land use suitability index maps and planning guidelines. Land use projection have been made through Cellular Automata technique, and land use plans have been developed based on projected land use and optimized through SWOT analysis. Implementation strategy is developed based on legal framework to implement land use plan at local level. The land use change patterns are characterized by the increase of agriculture and built-up area and the decrease in areas under forest cover and water body simultaneously. Altogether 27 different criteria are identified and applied in land use suitability evaluation. Risk prone area is found mostly surrounding to the foot of Chure hill and along Khando river. Almost 46% of the total areas have been planned for future agriculture land use followed by residential, commercial, industrial and public uses which are 201 ha, 26 ha, 3ha, and 345 ha respectively. An implementation strategy has been devised to empower and enforcement for compliance of land use zone together with guidelines for outlined development activities.
Urban sprawl refers to the urbanization extent, which is mainly caused by population growth and large scale migration and it is a global phenomenon. In developing countries like Nepal, where the population growth and internal migration rate in urban area is high, it has posed serious implication on the resources of the region. Effective and efficient infrastructure planning of an urban environment require information related to the rate of urban growth along with its trend, pattern and extent of urban sprawl. The pattern and extent of urban sprawl is identified and modeled using remotely sensed data along with collateral data. RS and GIS are used to analyze and interpret the urban land use changes. Cellular Automate Markov (CA-Markov) process is used to urban sprawl modeling to identify possible pattern of sprawl and subsequently predict the nature of future sprawl Nepalese Journal on Geoinformatics -12, 2070 (2013AD): 50-56
Road network deals with the development of a comprehensive plan for construction and operation of transportation facilities. In order to develop efficient and better transport facility, it is necessary to have a proper road network. In sustainable road network planning, planners put into consideration factors like gradients or slope, land-use and geology with community and governmental interest. These different considerations make the planning process complex and generate confusion in the decision making process. The use of geographic information system (GIS) and multi-criteria analysis (MCA) has helped planners to reduce complexity and to achieve desired and more accurate results. MCA prevents the imposition of criteria limit and gives opportunity to decision makers to enter their own judgments. This provides a better communication among the community for creating a more open choice for analysis and possible changes if necessary. In this study, road network has been analyzed with optimal least cost path algorithm of spatial analysis in GIS using different ancillary data layers and each layer weight-scoring has been computed with MCA in spatial decision support system (SDSS). The optimal least cost path would provide the best option with certainty and considers a gradient, connected neighbors, thematic cost and surface distance in three dimensional spaces. The path gradient can be adjusted as per the requirements, depending upon the terrain conditions and possible to design a more realistic route automatically with appropriate parameters.Nepalese Journal on Geoinformatics -13, 2014, Page: 34-40
Building extraction in built-up area is of great interest for visualization, simulation and monitoring urban landscape which is used for town/city planning as well as regional planning. Building extraction in urban areas based on merely a single high resolution optical data is often hard to conduct and to improve quality of building detection with consistency, completeness and correctness. Optical images are one of the major sources of individual building extraction from orthoimage but most of these do not produce anticipated result especially to building’s shape and outlines in dense urban environment. Extraction of objects from InSAR images is a complicated phenomenon for interpretability due to side looking geometry and effects of layover, foreshortening, shadowing and multi bounce scattering. In this study, buildings and building blocks are extracted from fusion of optical and InSAR data using object oriented analysis (OOA) technique. The improvement of building footprint has done with rectangular fit for building hypothesis and building height from normalized digital surface model (nDSM) based on fuzzy membership function. The results of building extraction has found reasonably good and accurate in planned urban layouts. The quality of building extraction has highly dependent on settlement density, contrast and other image characteristics.Nepalese Journal on Geoinformatics -13, 2014, Page: 16-23
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.