Urbanization posits the expression of urban expanse expansion due to population growth, rise in built-up areas, high population density and its correspondingly urban way of life. Unrestrained impetus of development an...Urbanization posits the expression of urban expanse expansion due to population growth, rise in built-up areas, high population density and its correspondingly urban way of life. Unrestrained impetus of development and land use land cover change (LULCC) portent several issues such as unlawful urban sprawl, loss of agricultural land, forest loss and other associated complications. This study analyzed the dynamics of urbanization and other LULCC in Ghana’s Greater Kumasi area via Landsat images (TM 1986, OLI 2013 and OLI 2023) using ERDAS Imagine, Idrisi and ArcGIS software. Implementing supervised classification technique, the Maximum Likelihood Classifier (MLC) procedure was employed to categories the study area into five LULC classes. Accuracy assessment undertaken on the resultant LULC maps was deemed very satisfactory. The results from 1986-2023 pointed to an upsurge in a built-up extent as of 8% to 41%, a decrease in Closed Forest from 9% to 4%, another decrease in Open Forests from 64% to 33%, a slight increase from 16% to 20% in farmlands and a stable level of water share. Further analysis indicated that the study area had undergone LULCC within the periods 1986-2013 and 2013-2023 at 60% and 37% respectively. The findings showed uncontrolled urban sprawling along major roads and forest loss as deforestation outside protected areas and degradation in protected forest. The monitoring of urbanization and other LULCC is important for local, and national governments and other bodies charged with the implementation of programs and policies that manage and utilize natural resources. Development adapts to mitigate the effect on the environment.展开更多
In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a ...In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.展开更多
An automatic approach is presented to track a wide screen in a multipurpose hall video scene. Once the screen is located, this system also generates the temporal rate of change by using the edge detection based method...An automatic approach is presented to track a wide screen in a multipurpose hall video scene. Once the screen is located, this system also generates the temporal rate of change by using the edge detection based method. Our approach adopts a scene segmentation algorithm that explores visual features （texture） and depth information to perform efficient screen localization. The cropped region which refers to the wide screen undergoes salient visual cues extraction to retrieve the emphasized changes required in rate-of- change computation. In addition to video document indexing and retrieval, this work can improve the machine vision capability in the behavior analysis and pattern recognition.展开更多
Ghana like all countries in Sub-Saharan region of Africa have long been undergoing intense land use land cover changes (LULCC) which have given rise to extensive forest loss (deforestation and degradation), loss of ar...Ghana like all countries in Sub-Saharan region of Africa have long been undergoing intense land use land cover changes (LULCC) which have given rise to extensive forest loss (deforestation and degradation), loss of arable land and land degradation. This study assessed the past LULCC in the Atwima Nwabiagya which contains the Barekese and Owabi Headworks) and the old Kumasi Local Assemblies’ areas in Ghana and projected the scenario in 2040 for business-as-usual (BAU). The synergies of satellite imagery of 1990, 2000, 2010 and 2020 were classified with an overall accuracy of 90%. Markov Cellular-Automata method was used to forecast the future LULC pattern after detecting main driving forces of LULCC. The findings showed an extensive increase in built up areas from 11% in 1990 to 39% in 2020 owing largely to 23% decrease in forest cover and 6% decrease in agricultural lands within the past 30 years (1990-2020). The projected LULC under the BAU scenario for 2040 showed built-up surge from 39% to 45% indicating additional forest loss from 43% in 2020 to 40% and decreasing agricultural land from 17% to 14%. The main driver for the LULCC is clearly anthropogenic driven as the human population in the study area keeps rising every censual year. This study exemplifies the fast-tracked forest loss, loss of arable land and challenges on ecosystem sustainability of the Barekese-Owabi-Kumasi landscape. The current and projected maps necessitate the apt implementation of suitable interventions such as reforestation, protection measures and policy decision in deliberate land use planning to mitigate further loss of forest cover and safeguard the Barekese and Owabi headworks.展开更多
文摘Urbanization posits the expression of urban expanse expansion due to population growth, rise in built-up areas, high population density and its correspondingly urban way of life. Unrestrained impetus of development and land use land cover change (LULCC) portent several issues such as unlawful urban sprawl, loss of agricultural land, forest loss and other associated complications. This study analyzed the dynamics of urbanization and other LULCC in Ghana’s Greater Kumasi area via Landsat images (TM 1986, OLI 2013 and OLI 2023) using ERDAS Imagine, Idrisi and ArcGIS software. Implementing supervised classification technique, the Maximum Likelihood Classifier (MLC) procedure was employed to categories the study area into five LULC classes. Accuracy assessment undertaken on the resultant LULC maps was deemed very satisfactory. The results from 1986-2023 pointed to an upsurge in a built-up extent as of 8% to 41%, a decrease in Closed Forest from 9% to 4%, another decrease in Open Forests from 64% to 33%, a slight increase from 16% to 20% in farmlands and a stable level of water share. Further analysis indicated that the study area had undergone LULCC within the periods 1986-2013 and 2013-2023 at 60% and 37% respectively. The findings showed uncontrolled urban sprawling along major roads and forest loss as deforestation outside protected areas and degradation in protected forest. The monitoring of urbanization and other LULCC is important for local, and national governments and other bodies charged with the implementation of programs and policies that manage and utilize natural resources. Development adapts to mitigate the effect on the environment.
基金supported by the National High Technology Research and Developmemt Program of China (No2007AA12Z162)the Program for New Century Excellent Talents in University, Ministry of Education (NoNCET-06-0476)the Jiangsu Provincial 333 Engineering for High Level Talents(No.BK2006505)
文摘In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.
文摘An automatic approach is presented to track a wide screen in a multipurpose hall video scene. Once the screen is located, this system also generates the temporal rate of change by using the edge detection based method. Our approach adopts a scene segmentation algorithm that explores visual features （texture） and depth information to perform efficient screen localization. The cropped region which refers to the wide screen undergoes salient visual cues extraction to retrieve the emphasized changes required in rate-of- change computation. In addition to video document indexing and retrieval, this work can improve the machine vision capability in the behavior analysis and pattern recognition.
文摘Ghana like all countries in Sub-Saharan region of Africa have long been undergoing intense land use land cover changes (LULCC) which have given rise to extensive forest loss (deforestation and degradation), loss of arable land and land degradation. This study assessed the past LULCC in the Atwima Nwabiagya which contains the Barekese and Owabi Headworks) and the old Kumasi Local Assemblies’ areas in Ghana and projected the scenario in 2040 for business-as-usual (BAU). The synergies of satellite imagery of 1990, 2000, 2010 and 2020 were classified with an overall accuracy of 90%. Markov Cellular-Automata method was used to forecast the future LULC pattern after detecting main driving forces of LULCC. The findings showed an extensive increase in built up areas from 11% in 1990 to 39% in 2020 owing largely to 23% decrease in forest cover and 6% decrease in agricultural lands within the past 30 years (1990-2020). The projected LULC under the BAU scenario for 2040 showed built-up surge from 39% to 45% indicating additional forest loss from 43% in 2020 to 40% and decreasing agricultural land from 17% to 14%. The main driver for the LULCC is clearly anthropogenic driven as the human population in the study area keeps rising every censual year. This study exemplifies the fast-tracked forest loss, loss of arable land and challenges on ecosystem sustainability of the Barekese-Owabi-Kumasi landscape. The current and projected maps necessitate the apt implementation of suitable interventions such as reforestation, protection measures and policy decision in deliberate land use planning to mitigate further loss of forest cover and safeguard the Barekese and Owabi headworks.
