scholarly journals Analyzing the Spatiotemporal Uncertainty in Urbanization Predictions

2021 ◽  
Vol 13 (3) ◽  
pp. 512
Author(s):  
Jairo Alejandro Gómez ◽  
ChengHe Guan ◽  
Pratyush Tripathy ◽  
Juan Carlos Duque ◽  
Santiago Passos ◽  
...  
Keyword(s):  
Urban Growth ◽  
Geographical Information Systems ◽  
Growth Models ◽  
A Priori ◽  
Remote Sensing Data ◽  
Public Utility ◽  
Town Planning ◽  
Geographical Information ◽  
New Town ◽  
Spatiotemporal Uncertainty

With the availability of computational resources, geographical information systems, and remote sensing data, urban growth modeling has become a viable tool for predicting urbanization of cities and towns, regions, and nations around the world. This information allows policy makers, urban planners, environmental and civil organizations to make investments, design infrastructure, extend public utility networks, plan housing solutions, and mitigate adverse environmental impacts. Despite its importance, urban growth models often discard the spatiotemporal uncertainties in their prediction estimates. In this paper, we analyzed the uncertainty in the urban land predictions by comparing the outcomes of two different growth models, one based on a widely applied cellular automata model known as the SLEUTH CA and the other one based on a previously published machine learning framework. We selected these two models because they are complementary, the first is based on human knowledge and pre-defined and understandable policies while the second is more data-driven and might be less influenced by any a priori knowledge or bias. To test our methodology, we chose the cities of Jiaxing and Lishui in China because they are representative of new town planning policies and have different characteristics in terms of land extension, geographical conditions, growth rates, and economic drivers. We focused on the spatiotemporal uncertainty, understood as the inherent doubt in the predictions of where and when will a piece of land become urban, using the concepts of certainty area in space and certainty area in time. The proposed analyses in this paper aim to contribute to better urban planning exercises, and they can be extended to other cities worldwide.

scholarly journals Determination of Flood Hazard Zones Using Geographical Information Systems and Remote Sensing Techniques: A Case Study in Part Yenagoa Metropolis

2019 ◽  
pp. 1-9
Author(s):  
Eteh Desmond ◽  
Francis Emeka Egobueze ◽  
Francis Omonefe
Keyword(s):  
Remote Sensing ◽  
Geographical Information Systems ◽  
Flood Hazard ◽  
Environmental Law ◽  
Remote Sensing Data ◽  
Flood Management ◽  
Geographical Information ◽  
Flood Level ◽  
The Government ◽  
Srtm Data

Flood has been a serious hazard for the past decades in Nigeria at large. The incidence of 2012 and 2018 flood disaster in Yenagoa, Amassoma and other parts of the state have not been recover till date and the government is not consigned about the well been of the people. The major causes of the flood are attributed to increased rainfall and lack of drainages including dredging of rivers and disobeying of environmental law and infrastructure failure. Coastal Towns or communities are one of the most affected areas of flood and their farms and fishing implements were washed away by the floodwater in 2012 and 2018 in Bayelsa State. Flood management is needed for provision of time information so quick response can be done as soon as possible. Using SRTM data to produce digital elevation model and IDW Contour, the 3D model from ground data of Yenagoa metropolis using ArcGIS 10.6 to generate and analyze them. As a result of field survey, flood level calculation was made to classified flood hazard zones for migration, Agricultural Educational, and construction purpose such as land suitability. This was used in ascertaining the extent of the flooded area. The result reveals that an area of over 5.9888882km2 and riverine and coastal area is flooded, affecting more than 15 coastal and riverine communities. The finding also concludes that remote sensing data like SRTM data and Geospatial techniques seems effective in mapping and identifying areas prone to flooding. Therefore Remote sensing and Geospatial database should be established for proper flood mapping and the government should constantly dredge the area from time to time. 

ON THE MATABILITY OF POLYGONS

2008 ◽  
Vol 18 (05) ◽  
pp. 469-506
Author(s):  
GILL BAREQUET ◽  
AYA STEINER
Keyword(s):  
Information Systems ◽  
Medical Imaging ◽  
Surface Reconstruction ◽  
Geographical Information Systems ◽  
Piecewise Linear ◽  
A Priori ◽  
Sufficient Conditions ◽  
Geographical Information ◽  
Triangulated Surface ◽  
The Past

Interpolating a piecewise-linear triangulated surface between two polygons lying in parallel planes has attracted a lot of attention in the literature over the past three decades. This problem is the simplest variant of interpolation between parallel slices, which may contain multiple polygons with unrestricted geometries and/or topologies. Its solution has important applications to medical imaging, digitization of objects, geographical information systems, and more. Practically all currently-known methods for surface reconstruction from parallel slices assume a priori the existence of a non-self-intersecting triangulated surface defined over the vertices of the two polygons, which connects them. Gitlin et al. were the first to specify a nonmatable pair of polygons. In this paper we provide proof of the nonmatability of a “simpler” pair of polygons, which is less complex than the example given by Gitlin et al. Furthermore, we provide a family of polygon pairs with unbounded complexity, which we believe to be nonmatable. We also give a few sufficient conditions for polygon matability.

scholarly journals CONTRIBUTION OF GEOGRAPHICAL INFORMATION SYSTEMS TO THE IDENTIFICATION OF GOODS IMPACTED BY THE CONSTRUCTION OF THE YAOUNDÉ-NSIMALEN HIGHWAY: URBAN SECTION

2020 ◽  
pp. 353-359
Author(s):  
Eric Wilson TEGNO NGUEKAM ◽  
Bernard Foahom ◽  
Camille Kamtchoua Mbetjock
Keyword(s):  
Information Systems ◽  
Geographic Information Systems ◽  
Urban Area ◽  
Geographical Information Systems ◽  
Market Value ◽  
Public Utility ◽  
Geographical Information ◽  
Public Purpose ◽  
Practical Tool ◽  
Set Up

Cameroon through its Strategy for Growth and Employment (DSCE), has set up the construction of the Yaoundé-Nsimalen highway project. As part of the assessments of its potential effects on the environment, an ESIA was carried out, according to the framework law on the management of the environment. The acquisition of housing has resulted in an '' anarchic '' installation in the urban and peri-urban area. The construction of a highway as planned overlays on these facilities and poses a problem related to the liberation of spaces previously occupied. The purpose of this study is to identify, locate and classify the impacted goods by the highway construction project through Geographic Information Systems (GIS). Our methodology consisted first, making a satellite identification of the impacted goods, then a field campaign and finally a processing of the data collected. This study was also limited to the identification of two types of property, the buildings and parcels of land. Thus, it has been possible to distinguish and locate six categories of buildings, eight categories of parcels of land defined according to the Cameroon law No. 85/009 of 04 July 1985 on the expropriation for public purpose and the terms of compensation and according to Order No. 0082 / y. 15.1 / MNUH / D of November 20, 1987 laying down the bases for calculating the market value of buildings expropriated for reasons of public utility. The result of this study shows that mapping is a very practical tool for identifying and materializing the impacts that a project may have on components of environment. The GIS revealed a potential disappearance of 1502 building spread over 867 parcels of land.

scholarly journals Using building types and demographic data to improve our understanding and use of urban sprawl simulation

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Mojtaba Eslahi ◽  
Rani El Meouche ◽  
Anne Ruas
Keyword(s):  
Cellular Automata ◽  
Urban Growth ◽  
Urban Areas ◽  
Geographical Information Systems ◽  
Dynamic Models ◽  
Urban Expansion ◽  
Demographic Data ◽  
Population Data ◽  
Geographical Information ◽  
Sleuth Model

<p><strong>Abstract.</strong> Many studies, using various modeling approaches and simulation tools have been made in the field of urban growth. A multitude of models, with common or specific features, has been developed to reconstruct the spatial occupation and changes in land use. However, today most of urban growth techniques just use the historical geographic data such as urban, road and excluded maps to simulate the prospective urban maps. In this paper, adding buildings and population data as urban fabric factors, we define different urban growth simulation scenarios. Each simulation corresponds to policies that are more or less restrictive of space considering what these territories can accommodate as a type of building and as a global population.</p><p>Among the urban growth modeling techniques, dynamic models, those based on Cellular Automata (CA) are the most common for their applications in urban areas. CA can be integrated with Geographical Information Systems (GIS) to have a high spatial resolution model with computational efficiency. The SLEUTH model is one of the cellular automata models, which match the dynamic simulation of urban expansion and could be adapted to morphological model of the urban configuration and fabric.</p><p>Using the SLEUTH model, this paper provides different simulations that correspond to different land priorities and constraints. We used common data (such as topographic, buildings and demography data) to improve the realism of each simulation and their adequacy with the real world. The findings allow having different images of the city of tomorrow to choose and reflect on urban policies.</p>

scholarly journals USING GIS FOR DEVELOPING SUSTAINABLE URBAN GROWTH CASE KYRENIA REGION

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 263-268 ◽  
Author(s):  
C. Kara ◽  
N. Akçit
Keyword(s):  
Urban Development ◽  
Environmental Protection ◽  
Urban Growth ◽  
Geographical Information Systems ◽  
Planning Process ◽  
Central Zone ◽  
Geographical Information ◽  
Sustainable Urban Development ◽  
Soil Productivity ◽  
Multi Criteria Evaluation

<p><strong>Abstract.</strong> It is critical to develop urban layers for analysis sustainable urban development possibilities within planning process. Kyrenia Region has many physical, environmental or economic issues that may danger the growth possibilities in sustainable manner. From this point, this study uses different spatial layers such as slope, distance to roads, distance to central zone, vegetation, soil productivity, environmental protection zones, distance to open/green space, distance to education for supporting sustainable urban growth policies and define suitable areas for urban development within this perspective. The study tries to convert sustainable urban growth policies such as; compact growth, environmental protection, equal accessibility to basic services; into spatial layers and establish proper framework for multi criteria evaluation in Kyrenia Region within using geographical information systems. It shows suitability values for Kyrenia region and constraints zones at final section. It clearly presents the suitable areas for the sustainable urbanization and also unsuitable or risky areas for reducing the possible disasters and may happen in the future.</p>

scholarly journals INTEGRATION OF REMOTE SENSING DATA AND BASIC GEODATA AT DIFFERENT SCALE LEVELS FOR IMPROVED LAND USE ANALYSES

2015 ◽  
Vol XL-3/W3 ◽  
pp. 85-89 ◽  
Author(s):  
G. Waldhoff ◽  
S. Eichfuss ◽  
G. Bareth
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Resolution ◽  
Geographical Information Systems ◽  
High Spatial Resolution ◽  
Regional Scale ◽  
Remote Sensing Data ◽  
Geographical Information ◽  
Sensing Data ◽  
Very High Spatial Resolution

The classification of remote sensing data is a standard method to retrieve up-to-date land use data at various scales. However, through the incorporation of additional data using geographical information systems (GIS) land use analyses can be enriched significantly. In this regard, the Multi-Data Approach (MDA) for the integration of remote sensing classifications and official basic geodata for a regional scale as well as the achievable results are summarised. On this methodological basis, we investigate the enhancement of land use analyses at a very high spatial resolution by combining WorldView-2 remote sensing data and official cadastral data for Germany (the Automated Real Estate Map, ALK). Our first results show that manifold thematic information and the improved geometric delineation of land use classes can be gained even at a high spatial resolution.

scholarly journals Identification and mapping of soil erosion areas in the Blue Nile, Eastern Sudan using multispectral ASTER and MODIS satellite data and the SRTM elevation model

2010 ◽  
Vol 14 (7) ◽  
pp. 1167-1178 ◽  
Author(s):  
M. El Haj Tahir ◽  
A. Kääb ◽  
C.-Y. Xu
Keyword(s):  
Soil Erosion ◽  
Geographical Information Systems ◽  
Thermal Emission ◽  
Remote Sensing Data ◽  
Degradation Process ◽  
Geographical Information ◽  
Important Indicator ◽  
Blue Nile ◽  
Elevation Model ◽  
Eastern Sudan

Abstract. The area of the Upper Blue Nile in Eastern Sudan is considered prone to soil erosion which is an important indicator of the land degradation process. In this study, an erosion identification and mapping approach is developed based on adaptations to the regional characteristics of the study area and the availability of data. This approach is derived from fusion between remote sensing data and geographical information systems (GIS). The developed model is used to map the spatial distribution of soil erosion caused by the rains of 2006 using automatic classification of multispectral Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. Shuttle Radar Topography Mission (SRTM) digital elevation model is used to orthoproject ASTER data. A maximum likelihood classifier is trained with four classes, Gully, Flat_land, Mountain and Water and applied to images from March and December 2006. Validation is done with field data from December and January 2006/2007. The results allow the identification of erosion gullies and subsequent estimation of eroded area. Consequently, the results are up-scaled using Moderate Resolution Imaging Spectroradiometer (MODIS) products of the same dates. Because the selected study site is representative of the wider Blue Nile region, it is expected that the approach presented could be applied to larger areas.

scholarly journals Dynamics and forecasting of population growth and urban expansion in Srinagar City – A Geospatial Approach

2014 ◽  
Vol XL-8 ◽  
pp. 709-716 ◽  
Author(s):  
M. Farooq ◽  
M. Muslim
Keyword(s):  
Population Growth ◽  
Urban Sprawl ◽  
Urban Growth ◽  
Urban Areas ◽  
Geographical Information Systems ◽  
Urban Expansion ◽  
Geographical Information ◽  
Spatial And Temporal Variability ◽  
Jammu And Kashmir ◽  
Srinagar City

The urban areas of developing countries are densely populated and need the use of sophisticated monitoring systems, such as remote sensing and geographical information systems (GIS). The urban sprawl of a city is best understood by studying the dynamics of LULC change which can be easily generated by using sequential satellite images, required for the prediction of urban growth. Multivariate statistical techniques and regression models have been used to establish the relationship between the urban growth and its causative factors and for forecast of the population growth and urban expansion. In Srinagar city, one of the fastest growing metropolitan cities situated in Jammu and Kashmir State of India, sprawl is taking its toll on the natural resources at an alarming pace. The present study was carried over a period of 40 years (1971–2011), to understand the dynamics of spatial and temporal variability of urban sprawl. The results reveal that built-up area has increased by 585.08 % while as the population has increased by 214.75 %. The forecast showed an increase of 246.84 km<sup>2</sup> in built-up area which exceeds the overall carrying capacity of the city. The most common conversions were also evaluated.

Sign in / Sign up

Export Citation Format

Share Document