Coupling of Cellular Automata Urban Growth Model and HEC-HMS to Predict Future Flood Extents in the Upper Klang Ampang Catchment

Urban areas in tropical regions have higher flood risks due to the more frequent occurrence of intense convective rainfalls. The rising urbanization process have caused more surfaces to be covered with impervious materials, resulting in increased runoff. Modelling urban growth and its impact on urban hydrology is essential to ensure informed decision in the sustainable management and planning of cities in developing country like Malaysia. The aim of this research is to develop an integrated system for simulating future flood extents by coupling flood and urban growth models for the Upper Klang Ampang catchment which includes Kuala Lumpur capital city. HEC-HMS was used for flood modelling while SLEUTH cellular automata model was employed to analyse urban growth in the catchment. The results indicate that using historical satellite images from 1990, 2000, 2010 and 2016 as input data layers along with slope, land use, hill shade, road and restricted area layers, a slight increase in urban growth from 2020 until 2050 is predicted which can cause the peak discharge to increase by about 11-15%. The integrated flood estimation-urban growth system can be used as an effective tool in urban planning and management for the city

Coupling of Cellular Automata Urban Growth Model and HEC-HMS to Predict Future Flood Extents in the Upper Klang Ampang Catchment

Urban areas in tropical regions have higher flood risks due to the more frequent occurrence of intense convective rainfalls. The rising urbanization process have caused more surfaces to be covered with impervious materials, resulting in increased runoff. Modelling urban growth and its impact on urban hydrology is essential to ensure informed decision in the sustainable management and planning of cities in developing country like Malaysia. The aim of this research is to develop an integrated system for simulating future flood extents by coupling flood and urban growth models for the Upper Klang Ampang catchment which includes Kuala Lumpur capital city. HEC-HMS was used for flood modelling while SLEUTH cellular automata model was employed to analyse urban growth in the catchment. The results indicate that using historical satellite images from 1990, 2000, 2010 and 2016 as input data layers along with slope, land use, hill shade, road and restricted area layers, a slight increase in urban growth from 2020 until 2050 is predicted which can cause the peak discharge to increase by about 11-15%. The integrated flood estimation-urban growth system can be used as an effective tool in urban planning and management for the city

Rapid Urban Growth in the Kathmandu Valley, Nepal: Monitoring Land Use Land Cover Dynamics of a Himalayan City with Landsat Imageries

abstract: The Kathmandu Valley of Nepal epitomizes the growing urbanization trend spreading across the Himalayan foothills. This metropolitan valley has experienced a significant transformation of its landscapes in the last four decades resulting in substantial land use and land cover (LULC) change; however, no major systematic analysis of the urbanization trend and LULC has been conducted on this valley since 2000. When considering the importance of using LULC change as a window to study the broader changes in socio-ecological systems of this valley, our study first detected LULC change trajectories of this valley using four Landsat images of the year 1989, 1999, 2009, and 2016, and then analyzed the detected change in the light of a set of proximate causes and factors driving those changes. A pixel-based hybrid classification (unsupervised followed by supervised) approach was employed to classify these images into five LULC categories and analyze the LULC trajectories detected from them. Our results show that urban area expanded up to 412% in last three decades and the most of this expansion occurred with the conversions of 31% agricultural land. The majority of the urban expansion happened during 1989–2009, and it is still growing along the major roads in a concentric pattern, significantly altering the cityscape of the valley. The centrality feature of Kathmandu valley and the massive surge in rural-to-urban migration are identified as the primary proximate causes of the fast expansion of built-up areas and rapid conversions of agricultural areas

Analysis of Landscape Composition and Configuration Based on LULC Change Modeling

Land cover changes threaten biodiversity by impacting the natural habitats and require careful and continuous assessment. The standard approach for assessing these changes is land cover modeling. The present study investigated the spatio-temporal changes in Land Use Land Cover (LULC) in the Gorgan River Basin (GRB) during the 1990–2020 period and predicted the changes by 2040. First, a change analysis employing satellite imagery from 1990 to 2020 was carried out. Then, the Multi-Layer Perceptron (MLP) technique was used to predict the transition potential. The accuracy rate, training RMS, and testing RMS of the artificial neural network, MLP, and the transition potential modeling were computed in order to evaluate the results. Utilizing projections for 2020, the prediction of land cover change was made. By contrasting the anticipated land cover map of 2020 with the actual land cover map of 2020, the accuracy of the model was evaluated. The LULC conditions in the future were predicted under two scenarios of the current change trend (scenario 1) and the ecological capability of the land (scenario 2) by 2040. Seven landscape metrics were considered, including Number of Patches, Patch Density, the Largest Patch Index, Edge Density, Land- scape Shape Index, Patch Area, and Area-Weighted Mean Shape Index. Based on the Cramer coefficient, the most critical factors affecting LULC change were elevation, distance from forest, and experimental probability of change. For the 1990–2020 period, the LULC change was shown to be influenced by deforestation, reduced rangeland, and expansion of agricultural and residential areas. Based on scenario 1, the area of forest, agriculture, and rangeland would face −0.8, 0.5, and 0.1% changes in the total area, respectively. In scenario 2, the area of forest, agriculture, and rangeland would change by 0.1, −1.3, and 1.3% of the total area, respectively. Landscape metrics results indicated the destructive trend of the landscape during the 1990–2020 period. For improving the natural condition of the GRB, it is suggested to prioritize different areas in need of regeneration due to inappropriate LULC changes and take preventive and protective measures where changes in LULC were predicted in the future, taking into account land management conditions (scenario 2)

Sustainable Urban Development: Bioregionalistic Vision for Small Towns

Cities and towns are the social constructs in regional settings. They physically manifest and exist as power centres through various layers of culture, economy, politics, and religion. There was a symbiotic relationship between the ‘setting’ and the ‘construct’ in the past. With time and advent of technology, haphazard developments led to degradation of ecological systems and have become a confronted affair. Global warming, its adverse effects and the constant references to the words ‘sustainability’ and ‘resilience’ pose questions on the existing planning models. Small towns experiencing a tremendous pressure of urbanisation and rich in natural resources, coherence and identity are fast changing. An indispensable change in the planning models is necessary to mitigate this existential crisis and condition the emerging urbanism in small towns sustainably. This paper unearths the role and possibilities of bioregional planning as a sustainable urban development paradigm and suggests few indicative parameters for envisioning bioregionalism in small towns

Application of Remote Sensing and Geographic Information System in Identification of Urban Growth nodes: A Case of Surat City, India

With the passage of time, the city's growth behavior will not change unless and until the government intervenes, and thus its identity will shift from monocentric to polycentric to meet the needs of citizens. As a result, this study is being conducted to identify emerging growth nodes within a selected area of Surat City, as well as their growth drivers over a 30-year period. Quantified built-up area within a patch size of 1km x 1km was used to compute patch density at five-year intervals from 1991 to 2021. In addition, the spatial changes that occurred within patches over the same time period were examined. Both analyses aid in determining the emerging growth nodes over a 30-year period. From 1991 to 2021, the city was driven by socioeconomic criteria such as land price, availability of good health and educational facilities, water and sewerage networks, fire stations, proximity factors such as proximity to major roads, bridges, bus stations, metro, railway stations, airport, environmental factors such as the development of riverfront and linear park, bio-diversity park, and government interventions in terms of Town Planning Schemes. This study thus aids urban planners and decision-makers in selecting which growth nodes to plan for new development and type of development, what to connect, and what to protect in the years to come

آشکارسازی تغییرات کاربری / پوشش اراضی شهر گنبد کاووس با استفاده از سنجش از دور

توجه به توسعه فیزیکی شهری پایدار، به عنوان یک ضرورت اساسی در برنامه‌های توسعه‌ی شهری، حاکی از اهمیت این موضوع در تقویت جبهه‌های فرهنگی، اجتماعی و کالبدی شهر می‌باشد. تغییرات پوشش سرزمین و توسعه شهرها سبب تخریب زیستگاه‌های طبیعی و کاهش تنوع زیستی شده است، یکی از روش‌های مورد استفاده برنامه‌ریزان جهت کنترل روند تغییرات پوشش سرزمین و کاربری اراضی، مدل‌سازی می‌باشد. این مطالعه با هدف مدل‌سازی تغییرات کاربری اراضی شهر گنبدکاووس با استفاده از LCM  انجام شد. آشکارسازی تغییرات کاربری اراضی با استفاده از تصاویر ماهواره لندست متعلق به سال‌های 1366، 1379، 1389 و 1393 انجام شد. مدل‌سازی نیروی انتقال با استفاده از پرسپترون چندلایه شبکه عصبی مصنوعی و 10 متغیر انجام پذیرفت. سپس با استفاده از مدل پیش‌بینی سخت و دوره واسنجی 1366 تا 1379 مدل‌سازی برای سال 1389 صورت گرفت و برای ارزیابی با نقشه واقعیت زمینی سال 1389 مورد مقایسه قرار گرفت، در پایان نیز با استفاده از دوره واسنجی 1379 تا 1389 پوشش سرزمین سال 1404 ،1419 و 1429پیش‌بینی شد. نتایج نشان می‌دهد در کل دوره مورد مطالعه به ترتیب 32/2858  کاربری شهری و 47/1106 اراضی آبی افزایش داشته و همچنین به ترتیب 77/2331 اراضی بایر و 5/2135 هکتار از وسعت اراضی دیم کاسته شده است. نتایج مدل‌سازی نیروی انتقال در اکثر زیرمدل‌ها صحت بالایی را نشان می‌دهد. نتایج مدل‌سازی با استفاده از زنجیره‌های مارکوف نشان داد که در سال‌های آتی شهر گنبدکاووس توسعه شدیدی خواهد داشت و اغلب به سمت شرق و جنوب خواهد بود، همچنین توسعه در سمت شمال و غرب نیز وجود دارد که در صورت عدم توجه باعث توسعه حاشیه‌نشینی خواهد شد