Identifying the Risk Areas and Urban Growth by ArcGIS-Tools

Abouelreesh is one of the most at risk areas in Aswan, Egypt, which suffers from storms, poor drainage, and flash flooding. These phenomena affect the urban areas and cause a lot of damage to buildings and infrastructure. Moreover, the potential for the further realization of dangerous situations increased when the urban areas of Abouelreesh extended towards the risk areas. In an effort to ameliorate the danger, two key issues for urban growth management were studied, namely: (i) estimations regarding the pace of urban sprawl, and (ii) the identification of urban areas located in regions that would be affected by flash floods. Analyzing these phenomena require a lot of data in order to obtain good results, but in our case, the official data or field data was limited so we tried to obtain it by accessing two kinds of free sources of satellite data. First, we used Arc GIS tools to analyze (digital elevation model (DEM)) files in order to study the watershed and better identify the risk area. Second, we studied historical imagery in Google Earth to determine the age of each urban block. The urban growth rate in the risk areas had risen to 63.31% in 2001. Urban growth in the case study area had been influenced by house sizes, because most people were looking to live in bigger houses. The aforementioned problem can be observed by considering the increasing average house sizes from 2001 until 2013, where, especially in risky areas, the average of house sizes had grown from 223 m2 in 2001 to 318 m2 in 2013. The findings from this study would be useful to urban planners and government officials in helping them to make informed decisions on urban development to benefit the community, especially those living in areas at risk from flash flooding from heavy rain events.

[1]  A. Wagner,et al.  URBAS: forecasting and management of flash floods in urban areas , 2009 .

[2]  Annemarie Müller Areas at risk - Concept and Methods for Urban Flood Risk Assessment: A Case Study of Santiago de Chile , 2012 .

[3]  H. M. Wood,et al.  The use of Earth observing satellites for hazard support , 2001, IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217).

[4]  David T. Potere,et al.  Horizontal Positional Accuracy of Google Earth's High-Resolution Imagery Archive , 2008, Sensors.

[5]  Sarah Taylor Lovell,et al.  Mapping public and private spaces of urban agriculture in Chicago through the analysis of high-resolution aerial images in Google Earth , 2012 .

[6]  Md. Sharif Imam Ibne Amir,et al.  Watershed delineation and cross-section extraction from DEM for flood modelling , 2014 .

[7]  Zdeneþk Má DETERMINATION OF TEXTURE OF TOPOGRAPHY FROM LARGE SCALE CONTOUR MAPS , 2001 .

[8]  Biswajeet Pradhan,et al.  Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery , 2011 .

[9]  David King,et al.  Recovery and resettlement following the 2011 flash flooding in the Lockyer Valley , 2014 .

[10]  M. Sangati Flash flood analysis and modelling in mountain regions , 2009 .

[11]  N. M. Noor,et al.  Determination of Spatial Factors in Measuring Urban Sprawl in Kuantan Using Remote Sensing and GIS , 2013 .

[12]  B. Pradhan Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing , 2010 .

[13]  Idowu Ajibade,et al.  Urban flooding in Lagos, Nigeria: Patterns of vulnerability and resilience among women , 2013 .

[14]  Deanne Bird,et al.  Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods , 2009 .

[15]  Takashi Nakamura,et al.  Mapping VHR Water Depth, Seabed and Land Cover Using Google Earth Data , 2014, ISPRS Int. J. Geo Inf..

[16]  R. Falconer,et al.  Modelling flash flood risk in urban areas , 2011 .

[17]  William Eadson Adapting Cities to Climate Change Understanding and Addressing the Development Challenges , 2011 .

[18]  S. Lindley,et al.  Probabilistic GIS-based method for delineation of urban flooding risk hotspots , 2014, Natural Hazards.

[19]  Abdel-Aziz Belal,et al.  Detecting urban growth using remote sensing and GIS techniques in Al Gharbiya governorate, Egypt , 2011 .

[20]  Da Wei R Mei De Men Te,et al.  Arc Hydro GIS for Water Resources , 2013 .

[21]  Robert J. Nicholls,et al.  Assessing the costs of adaptation to climate change: a review of the UNFCCC and other recent estimates , 2009 .

[22]  Sébastien Limet,et al.  Parallel Computing Flow Accumulation in Large Digital Elevation Models , 2011, ICCS.

[23]  Baolin Su,et al.  GIS Techniques for Watershed Delineation of SWAT Model in Plain Polders , 2011 .

[24]  T. Tingsanchali Urban flood disaster management , 2012 .

[25]  P. Fan,et al.  Measuring urban sprawl and its drivers in large Chinese cities: The case of Hangzhou , 2013 .

[26]  Nancy M. Trautmann,et al.  From Local to Global: A Birds-Eye View of Changing Landscapes , 2009 .

[27]  J. Lamond,et al.  Cities and Flooding: A Guide to Integrated Urban Flood Risk Management for the 21st Century , 2012 .

[28]  R. Risi,et al.  Meso-scale hazard zoning of potentially flood prone areas , 2015 .

[29]  Mukesh,et al.  Morphometric analysis of a Semi Urban Watershed, trans Yamuna, draining at Allahabad using Cartosat (DEM) data and GIS , 2014 .

[30]  Matthew L. Clark,et al.  Virtual Interpretation of Earth Web-Interface Tool (VIEW-IT) for Collecting Land-Use/Land-Cover Reference Data , 2011, Remote. Sens..

[31]  Lanlan Li,et al.  A Preprocessing Program for Hydrologic Model—A Case Study in the Wei River Basin , 2012 .