Simulating land use change in urban renewal areas: A case study in Hong Kong

Zheng, Huifeng; Shen, Geoffrey Qiping; Wang, Hao; Hong, Jiman

doi:10.1016/j.habitatint.2014.10.008

Cited by 168 publications

(80 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The overall accuracy values and the kappa values for the classified images of 1984, 2000 and 2015 were calculated. The kappa values for all LULC maps are greater than 0.90, which represents strong to perfect agreement (Zheng et al, 2015). Therefore, the classified LULC images were sufficiently accurate to conduct change analysis.…”

Section: Lulc Maps and Accuracy Assessmentmentioning

confidence: 82%

“…The accuracy assessment is consist of producer accuracy, user accuracy, overall accuracy and kappa value (Congalton & Green, 1999). Kappa value above 0.8 indicates strong-to-perfect agreement or accuracy between two maps (Zheng, Shen, Wang, & Hong, 2015). In this study, the accuracy of the classified LULC maps was assessed using 200 randomly selected validation points outside of the training sites.…”

Section: Image Pre-processing and Lulc Classificationmentioning

confidence: 99%

See 1 more Smart Citation

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Wang

Maduako

2018

European Journal of Remote Sensing

106

View full text Add to dashboard Cite

An accurate information on the amount and location of Land use and land cover (LULC) changes is necessary to develop and implement a sustainable-urban planning.This research investigates the potential of an integrated Multi-Layer Perceptron and Markov Chain Analysis (MLP-MCA) to map and accurately predict the future LULC change scenarios in Lagos Metropolitan Region of Nigeria. Multi-temporal LULC datasets derived from remotely sensed Landsat images from 1984, 2000 and 2015 were used for modeling, validation and prediction. Predicted LULC changes for 2030 and 2050 were performed based on the LULC map of 2015 using MLP-MCA method. The result reveals a significant expansion of built-up areas during the whole study period. Analysis of LULC distribution in Lagos metropolitan region shows that about 50% of urban land expansion happened beyond the administrative boundary of Lagos State during the period of 2000-2015. It is predicted that more than 75% of future urban growth will occur across the border of Lagos State, in the neighbouring Ogun State by 2050. These results imply that a strong and consistent collaboration between different states is crucial to establish an effective regional planning framework and ensure a proper planned growth of the metropolitan region.ARTICLE HISTORY

show abstract

Section: Lulc Maps and Accuracy Assessmentmentioning

confidence: 82%

Section: Image Pre-processing and Lulc Classificationmentioning

confidence: 99%

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Wang

Maduako

2018

European Journal of Remote Sensing

106

View full text Add to dashboard Cite

show abstract

“…In the comparison, the kappa value was calculated as 0,82. The obtained accuracy was assessed based on literature surveys [32,35,36] and the resolution and classification errors of satellite images used in the analyses and it was thought that the model accuracy was sufficient. Thus, the simulation performed for 2034 and the forecasts arising as the result of this simulation might provide important information for the future.…”

Section: Resultsmentioning

confidence: 99%

Modelling spatial changes in coastal areas of Samsun (Turkey) using a Cellular Automata-Markov Chain method

Öztürk

2017

Teh. vjesn.

View full text Add to dashboard Cite

Original scientific paper The evolution of cities over a specific time period and the determination of relevant trends are important to simulate for the proper development and planning of a city. In particular, coastal areas experience intense pressure from developers with respect to settlements, tourism, trade and industry, and built-up areas are being observed near coasts. The inability to direct development and control growth is destroying natural resources in coastal areas at a rapid pace. Thus, determining these trends is the key component for ensuring the protection of natural resources and planned growth. Because a complete estimation of urban expansion is not possible, likely changes can be determined using simulations. In this study, a 30-year urban expansion simulation was obtained using land use/land cover (LU/LC) data for 1987 and 2004 at Samsun (Turkey) coastal areas and using the Cellular AutomataMarkov Chain (CA-Markov) method. To verify the method, urban expansion simulation for the year 2014 was compared with real LU/LC data for the same year, and the kappa value was found to be 0,82. To determine LU/LC, Landsat TM/ETM+/OLI satellite images were used, and the analyses were realised in a geographic information system (GIS) environment. As a result of the study, the CA-Markov Chain approach integrated with GIS and remote sensing was shown to be effective in the study of urban growth dynamics. Using the simulation for the year 2034, probable urban expansion in the 2014-2034 period was estimated as approximately 3683 ha and the probable destructions of absolute agricultural lands, forests and pastures were predicted as approximately 968 ha, 228 ha and 24 ha, respectively. Keywords: cellular automata; GIS; Markov Chain; remote sensing; urban expansion Modeliranje prostornih promjena u priobalnim područjima Samsuna (Turska) primjenom metode Stanični automati-Markovljev lanacIzvorni znanstveni članak Promjene gradova kroz određeni vremenski period i određivanje relevantnih trendova važni su za simuliranje odgovarajućeg razvoja i planiranja grada. U priobalnim područjima naročito dolazi do izražaja intenzivni pritisak za izgradnjom, razvojem turizma, trgovine i industrije od strane velepoduzetnika, institucija i poduzeća koja se bave izgradnjom. Zbog nesposobnosti usmjeravanja razvoja i jačanja kontrole ubrzano dolazi do uništavanja prirodnih resursa u priobalnim područjima. Stoga je određivanje tih trendova ključno za osiguranje zaštite prirodnih resursa i planiranog razvoja. Budući da nije moguća potpuna procjena urbanog širenja, vjerojatne se promjene mogu odrediti simulacijama. U ovom se radu simulacija 30-godišnjeg urbanog širenja (2004-2034) dobila prema podacima o korištenju zemljišta/izgrađenosti zemljišta -land use/land cover (LU/LC) iz 1987 i 2004 za Samsun, priobalna područja Turske, uz primjenu metode Stanični automati-Markovljev lanac (CA-Markov). Kako bi se provjerila ta metoda, simulacija urbanog širenja za 2014. uspoređena je sa stvarnim LU/LC podacima za istu godinu te je dobivena kapp...

show abstract

“…Many studies show the usability of GIS and remote sensing applications as a support for local authorities (Adhvaryu, 2010;O'Looney, 1997;Zheng et al, 2015). To support local governments efficiently as well as spatial planners and other professionals being involved in planning processes and to reduce costs, our approach was to work with freely accessible data from remote sensing and public census data which were provided by the Statistics Bureau of Guangzhou Municipality.…”

Section: Methodological Approachmentioning

confidence: 99%

Growth Scenarios for the City of Guangzhou, China: Transferability and Confirmability

Lehner

Kraus

Wei

et al. 2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:This work deals with the development of urban growth scenarios and the prevision of the spatial distribution of built-up area and population for the urban area of the city of Guangzhou in China. Using freely-available data, including remotely sensed data as well as census data from the ground, expenditure of time and costs shall remain low. Guangzhou, one of the biggest cities within the Pearl River Delta, has faced an enormous economic and urban growth during the last three decades. Due to its economical and spatial characteristics it is a promising candidate for urban growth scenarios. The monitoring and prediction of urban growth comprises data of population and give them a spatial representation. The model, originally applied for the Indian city Ahmedabad, is used for urban growth scenarios. Therefore, transferability and confirmability of the model are evaluated. Challenges that may occur by transferring a model for urban growth from one region to another are discussed. With proposing the use of urban remote sensing and freely available data, urban planners shall be fitted with a comprehensible and simple tool to be able to contribute to the future challenge Smart Growth.

show abstract

Simulating land use change in urban renewal areas: A case study in Hong Kong

Cited by 168 publications

References 53 publications

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Spatio-temporal urban growth dynamics of Lagos Metropolitan Region of Nigeria based on Hybrid methods for LULC modeling and prediction

Modelling spatial changes in coastal areas of Samsun (Turkey) using a Cellular Automata-Markov Chain method

Growth Scenarios for the City of Guangzhou, China: Transferability and Confirmability

Contact Info

Product

Resources

About