Dar es Salaam is one of the fastest growing cities in East Africa, with a population of 4,364,541 whose annual growth rate is 4.5%. The population increase is mainly caused by rural to urban migration causing traffic ...Dar es Salaam is one of the fastest growing cities in East Africa, with a population of 4,364,541 whose annual growth rate is 4.5%. The population increase is mainly caused by rural to urban migration causing traffic congestion, unemployment, emerging of unplanned settlements, inadequate infrastructure, and social and housing services. In order to overcome these challenges there is an urgent need to establish and determine suitable locations of satellite towns to the outskirts of the central business district (CBD) to strengthen economic and social activities using reliable techniques. Selecting suitable locations of satellite towns has been determined by using distance from the CBD and population growth indicators. The limitations of using these indicators include unsuitable locations, which ultimately failed to attract economic growth in such areas. In this study, we introduce a new approach of selecting suitable location of satellite towns in fast growing cities. This approach uses Saaty Model and Geographic Information Systems techniques, whereby a pair wise comparison matrix, consistency index and consistency ratio are employed to determine suitable locations of satellite towns in Ubungo and Kinondoni Municipalities. Also, seven criteria were used to produce suitability maps for water, power line, road, communication line, elevation, slope and land use. The results obtained from this study show that about 5.31% of the area was classified as highly suitable, 29.82% as moderately suitable, 24.27% as marginally suitable and 40.6% permanently unsuitable. Locations of satellite towns determined using Saaty model was found to be on highly suitable areas whereas locations of satellite towns proposed by the Dar es Salaam master plan were located on marginally suitable areas. The study concludes that Saaty Model, if integrated with GIS, can be effectively used to determine suitable locations for satellite towns in urban areas.展开更多
With the introduction of powerful and high-speed personal computers, proficient techniques for infrastructure development and management have advanced, of which Geoinformatics technology is of great significance. An a...With the introduction of powerful and high-speed personal computers, proficient techniques for infrastructure development and management have advanced, of which Geoinformatics technology is of great significance. An attempt has been made for broad mapping and analysis of existing infrastructures in the context of planning scheme in Paschim Medinipur district, and to delineate the development zones of educational infrastructure facilities. The thematic layers considered in this study are infrastructure accessibility, type and condition of classroom and number of classroom allocated for the educational system at primary and upper primary level. Moran’s I statistics was used to estimate the spatial distribution of elementary infrastructure across the district. All these themes and their individual features were then assigned weights according to their relative importance in educational development and corresponding normalized weights were obtained based on the Saaty’s analytical hierarchy process. The thematic layers were finally integrated in GIS software based on multi-criteria approach to yield educational development infrastructure index. Moran’s I statistics shows girl’s toilet, electric and boundary wall facility within the district are clustered in pattern at primary level. At the upper primary level, only electric and computer facilities shows the clustered distribution across the district. However, four different zones have been delineated, namely ‘very good’, ‘good’, ‘moderate’ and ‘poor’. The block covered by very good elementary educational infrastructure facility is Daspur –I and Dantan –II at primary level and Keshiary block at upper primary level in Paschim Medinipur district. Finally, it is concluded that the Geoinformatics technology is very efficient and useful for the identification of infrastructure development.展开更多
Flooding is a natural event often associated with floodplain areas,characterised by large,sudden and significant rises in river water levels that drastically alters the surrounding landscape.The research employs ArcGI...Flooding is a natural event often associated with floodplain areas,characterised by large,sudden and significant rises in river water levels that drastically alters the surrounding landscape.The research employs ArcGIS tools,multi-criteria evaluation techniques and theMaximumEntropy(MaxEnt)model to assess flood hazard zones.The key physical elements of slope,elevation,rainfall,drainage density,land use,and soil types have been integrated to identify areas vulnerable to flooding.Overlay analysis has been used to construct zones specifically designated for flood hazards.Additionally,pairwise comparison using Saaty’s scale was employed to calculate the Eigenvector weights for each physical factor.A comparison of AUC values is estimated to find the most effective method for delineating flood hazard zones.TheMaxEnt model achieved an Area Under Curve(AUC)of 0.978,outperforming the Analytical hierarchy Process(AHP)model with an AUC of 0.967.The higher AUC indicates that the MaxEnt model is better at distinguishing between positive and negative occurrences.This could lead to more reliable predictions of the flood hazard zones.Overall,the higher AUC of the MaxEnt model suggests greater reliability and robustness.展开更多
文摘Dar es Salaam is one of the fastest growing cities in East Africa, with a population of 4,364,541 whose annual growth rate is 4.5%. The population increase is mainly caused by rural to urban migration causing traffic congestion, unemployment, emerging of unplanned settlements, inadequate infrastructure, and social and housing services. In order to overcome these challenges there is an urgent need to establish and determine suitable locations of satellite towns to the outskirts of the central business district (CBD) to strengthen economic and social activities using reliable techniques. Selecting suitable locations of satellite towns has been determined by using distance from the CBD and population growth indicators. The limitations of using these indicators include unsuitable locations, which ultimately failed to attract economic growth in such areas. In this study, we introduce a new approach of selecting suitable location of satellite towns in fast growing cities. This approach uses Saaty Model and Geographic Information Systems techniques, whereby a pair wise comparison matrix, consistency index and consistency ratio are employed to determine suitable locations of satellite towns in Ubungo and Kinondoni Municipalities. Also, seven criteria were used to produce suitability maps for water, power line, road, communication line, elevation, slope and land use. The results obtained from this study show that about 5.31% of the area was classified as highly suitable, 29.82% as moderately suitable, 24.27% as marginally suitable and 40.6% permanently unsuitable. Locations of satellite towns determined using Saaty model was found to be on highly suitable areas whereas locations of satellite towns proposed by the Dar es Salaam master plan were located on marginally suitable areas. The study concludes that Saaty Model, if integrated with GIS, can be effectively used to determine suitable locations for satellite towns in urban areas.
文摘With the introduction of powerful and high-speed personal computers, proficient techniques for infrastructure development and management have advanced, of which Geoinformatics technology is of great significance. An attempt has been made for broad mapping and analysis of existing infrastructures in the context of planning scheme in Paschim Medinipur district, and to delineate the development zones of educational infrastructure facilities. The thematic layers considered in this study are infrastructure accessibility, type and condition of classroom and number of classroom allocated for the educational system at primary and upper primary level. Moran’s I statistics was used to estimate the spatial distribution of elementary infrastructure across the district. All these themes and their individual features were then assigned weights according to their relative importance in educational development and corresponding normalized weights were obtained based on the Saaty’s analytical hierarchy process. The thematic layers were finally integrated in GIS software based on multi-criteria approach to yield educational development infrastructure index. Moran’s I statistics shows girl’s toilet, electric and boundary wall facility within the district are clustered in pattern at primary level. At the upper primary level, only electric and computer facilities shows the clustered distribution across the district. However, four different zones have been delineated, namely ‘very good’, ‘good’, ‘moderate’ and ‘poor’. The block covered by very good elementary educational infrastructure facility is Daspur –I and Dantan –II at primary level and Keshiary block at upper primary level in Paschim Medinipur district. Finally, it is concluded that the Geoinformatics technology is very efficient and useful for the identification of infrastructure development.
基金Lab facilities are supported by DST-FIST.The DST-FIST program,under the Department of Science and Technology,Government of India,provides financial assistance through the‘Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions’(FIST)scheme.
文摘Flooding is a natural event often associated with floodplain areas,characterised by large,sudden and significant rises in river water levels that drastically alters the surrounding landscape.The research employs ArcGIS tools,multi-criteria evaluation techniques and theMaximumEntropy(MaxEnt)model to assess flood hazard zones.The key physical elements of slope,elevation,rainfall,drainage density,land use,and soil types have been integrated to identify areas vulnerable to flooding.Overlay analysis has been used to construct zones specifically designated for flood hazards.Additionally,pairwise comparison using Saaty’s scale was employed to calculate the Eigenvector weights for each physical factor.A comparison of AUC values is estimated to find the most effective method for delineating flood hazard zones.TheMaxEnt model achieved an Area Under Curve(AUC)of 0.978,outperforming the Analytical hierarchy Process(AHP)model with an AUC of 0.967.The higher AUC indicates that the MaxEnt model is better at distinguishing between positive and negative occurrences.This could lead to more reliable predictions of the flood hazard zones.Overall,the higher AUC of the MaxEnt model suggests greater reliability and robustness.
