Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada

Faisal, Kamil; Shaker, Ahmed; Habbani, Suhaib

doi:10.3390/ijgi5030023

Cited by 13 publications

(18 citation statements)

References 20 publications

(30 reference statements)

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“…The reason for subtracting the DBI layer from the NDVI values is that built-up areas can be identified better [3,20,30]. Through this step, DBI values of green vegetation will decrease and the features with higher DBI values but lower NDVI values will be enhanced.…”

Section: Dry Built-up Indexmentioning

confidence: 99%

Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates

Rasul

Balzter

Ibrahim

et al. 2018

Land

166

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Arid and semi-arid regions have different spectral characteristics from other climatic regions. Therefore, appropriate remotely sensed indicators of land use and land cover types need to be defined for arid and semi-arid lands, as indices developed for other climatic regions may not give plausible results in arid and semi-arid regions. For instance, the normalized difference built-up index (NDBI) and normalized difference bareness index (NDBaI) are unable to distinguish between built-up areas and bare and dry soil that surrounds many cities in dry climates. This paper proposes the application of two newly developed indices, the dry built-up index (DBI) and dry bare-soil index (DBSI) to map built-up and bare areas in a dry climate from Landsat 8. The developed DBI and DBSI were applied to map urban areas and bare soil in the city of Erbil, Iraq. The results show an overall classification accuracy of 93% (κ = 0.86) and 92% (κ = 0.84) for DBI and DBSI, respectively. The results indicate the suitability of the proposed indices to discriminate between urban areas and bare soil in arid and semi-arid climates.

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Section: Dry Built-up Indexmentioning

confidence: 99%

Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates

Rasul

Balzter

Ibrahim

et al. 2018

Land

166

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show abstract

“…Chen et al [45] shows that land cover types can be represented by utilizing NDVI, NDWI and NDBI. Moreover, Faisal and Shaker [46,47] show that the built-up index derived from NDBI and NDVI could represent industrial areas within the city. Therefore, in UEQ studies, the higher NDBI/built-up values may be deemed to have a negative impact on the city.…”

Section: Normalized Difference Vegetation Index (Ndwi)mentioning

confidence: 99%

An Investigation of GIS Overlay and PCA Techniques for Urban Environmental Quality Assessment: A Case Study in Toronto, Ontario, Canada

Faisal

Shaker

2017

Sustainability

Self Cite

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Abstract:The United Nations estimates that the global population is going to be double in the coming 40 years, which may cause a negative impact on the environment and human life. Such an impact may instigate increased water demand, overuse of power, anthropogenic noise, etc. Thus, modelling the Urban Environmental Quality (UEQ) becomes indispensable for a better city planning and an efficient urban sprawl control. This study aims to investigate the ability of using remote sensing and Geographic Information System (GIS) techniques to model the UEQ with a case study in the city of Toronto via deriving different environmental, urban and socio-economic parameters. Remote sensing, GIS and census data were first obtained to derive environmental, urban and socio-economic parameters. Two techniques, GIS overlay and Principal Component Analysis (PCA), were used to integrate all of these environmental, urban and socio-economic parameters. Socio-economic parameters including family income, higher education and land value were used as a reference to assess the outcomes derived from the two integration methods. The outcomes were assessed through evaluating the relationship between the extracted UEQ results and the reference layers. Preliminary findings showed that the GIS overlay represents a better precision and accuracy (71% and 65%), respectively, comparing to the PCA technique. The outcomes of the research can serve as a generic indicator to help the authority for better city planning with consideration of all possible social, environmental and urban requirements or constraints.

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“…In particular, the Yangtze River Delta Urban Agglomeration (YRDUA), one of six typical mega-city regions found across the world, has reached the highest density and urbanization levels in China. Such rapid urbanization has spurred natural resource depletion and a series of ecological and environmental problems [7,8], e.g., quality deterioration, pollution of urban surface water, exacerbated urban heat island effects, and the degradation of ecosystem functioning [9,10]. Therefore, a timely and general analysis of urban expansion (e.g., expansion rates, expansion patterns, and expansion evaluations) is crucial to understanding the characteristics of for 1992 to 2010 and quantitatively evaluated the urbanization processes and expansion rates of 34 prefecture-level cities in northeastern China [41].…”

Section: Introductionmentioning

confidence: 99%

Expansion Analysis of Yangtze River Delta Urban Agglomeration Using DMSP/OLS Nighttime Light Imagery for 1993 to 2012

Zhang

Sun

et al. 2018

IJGI

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Abstract:Investigating the characteristics of urban expansion is helpful in managing the relationship between urbanization and the ecological and environmental issues related to sustainable development. The Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) collects visible and near-infrared light from the Earth's surface at night without moonlight. It generates effective time series data for mapping the dynamics of urban expansion. As a major urban agglomeration in the world, the Yangtze River Delta Urban Agglomeration (YRDUA) is an important intersection zone of both the "Belt and Road Initiative" and the "Yangtze River Economic Belt" in China. Therefore, this paper analyses urban expansion characteristics of the YRDUA for 1993-2012 from urban extents extracted from the DMSP/OLS for 1993, 1997, 2002, 2007, and 2012. First, calibration procedures are applied to DMSP/OLS data, including intercalibration, intra-annual composition, and inter-annual series correction procedures. Spatial extents are then extracted from the corrected DMSP/OLS data, and a threshold is determined via the spatial comparison method. Finally, three models are used to explore urban expansion characteristics of the YRDUA from expansion rates, expansion spatial patterns, and expansion evaluations. The results show that the urban expansion of the YRDUA occurred at an increasing rate from 1993-2007 and then declined after 2007 with the onset of the global financial crisis. The Suxichang and Ningbo metropolitan circles were seriously affected by the financial crisis, while the Hefei metropolitan circle was not. The urban expansion of the YRDUA moved from the northeast to the southwest over the 20-year period. Urban expansion involved internal infilling over the first 15 years and then evolved into external sprawl and suburbanization after 2007.

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Modeling the Relationship between the Gross Domestic Product and Built-Up Area Using Remote Sensing and GIS Data: A Case Study of Seven Major Cities in Canada

Cited by 13 publications

References 20 publications

Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates

Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates

An Investigation of GIS Overlay and PCA Techniques for Urban Environmental Quality Assessment: A Case Study in Toronto, Ontario, Canada

Expansion Analysis of Yangtze River Delta Urban Agglomeration Using DMSP/OLS Nighttime Light Imagery for 1993 to 2012

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