Dynamic monitoring of land-use/land-cover change and urban expansion in Shenzhen using Landsat imagery from 1988 to 2015

ABSTRACT To analyse changes in human settlement in Shenzhen City during the past three decades, changes in land use/land cover (LULC) and urban expansion were investigated based on multi-temporal Landsat Thematic Mapper/Enhanced Thematic Mapper Plus/Operational Land Imager (TM/ETM+/OLI) images. Using C4.5-based AdaBoost, a hierarchical classification method was developed to extract specific classes with high accuracy by combining a specific number of base-classifier decisions. Along with a classification post-processing approach, the classification accuracy was greatly improved. The statistical analysis of LULC changes from 1988 to 2015 shows that built-up areas have increased 6.4-fold, whereas cultivated land and forest continually decreased because of rapid urbanization. Urban expansion driven by human activities has considerably affected the landscape change of Shenzhen. The urban-expansion pattern of Shenzhen is a mixture of three urban-expansion patterns. Among these patterns, traffic-driven urban expansion has been the main form of urban expansion for some time, especially in the Non-Special Economic Zone. In addition, by taking 8 to 10 year periods as time intervals, urban expansion in Shenzhen was divided into three stages: the early-age urbanization stage (1988–1996), the rapid urbanization stage (1996–2005), and the intensive urbanization stage (2005–2015). For different stages, the state of urban expansion is different. In long-term LULC dynamic monitoring and urban-expansion detection, it was possible to obtain 11 LULC maps, which took 2 to 4 years as a research interval. With regard to the short research periods, LULC changes and urban expansion were investigated in detail.

[1]  X. H,et al.  A new index for delineating built-up land features in satellite imagery , 2008 .

[2]  Jianguo Wu,et al.  Assessing urban sustainability of Chinese megacities: 35 years after the economic reform and open-door policy , 2016 .

[3]  Ujjwal Maulik,et al.  A Robust Multiple Classifier System for Pixel Classification of Remote Sensing Images , 2010, Fundam. Informaticae.

[4]  Yangbo Chen,et al.  Remote sensing imagery classification using AdaBoost with a weight vector (WV AdaBoost) , 2017 .

[5]  Paul E. Gessler,et al.  The application of ensemble techniques for land-cover classification in arid lands , 2015 .

[6]  Artur Nowakowski,et al.  Remote Sensing Data Binary Classification Using Boosting with Simple Classifiers , 2015, Acta Geophysica.

[7]  Limin Yang,et al.  Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance , 2002 .

[8]  Yuanzhi Zhang,et al.  Seasonal Change of Land-Use/Land-Cover (LULC) Detection Using MODIS Data in Rapid Urbanization Regions: A Case Study of the Pearl River Delta Region (China) , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[9]  Wen Cao,et al.  Monitoring urban land cover and vegetation change by multi-temporal remote sensing information , 2010 .

[10]  H. Liu.  Accuracy analysis of remote sensing change detection by rule-based rationality evaluation with post-classification comparison , 2003 .

[11]  Effects of urbanization on incidence of noncommunicable diseases , 2012 .

[12]  Mariana Belgiu,et al.  Random forest in remote sensing: A review of applications and future directions , 2016 .

[13]  A. Dewan,et al.  Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization , 2009 .

[14]  Feng Wu,et al.  Projection of the Spatially Explicit Land Use/Cover Changes in China, 2010–2100 , 2013 .

[15]  Yangbo Chen,et al.  Assessing the long-term impact of urbanization on run-off using a remote-sensing-supported hydrological model , 2015 .

[16]  Giles M. Foody,et al.  Mapping a specific class with an ensemble of classifiers , 2007 .

[17]  D. Weindorf,et al.  Monitoring land cover changes in a newly reclaimed area of Egypt using multi-temporal Landsat data. , 2010 .

[18]  Conghe Song,et al.  Long-term land cover dynamics by multi-temporal classification across the Landsat-5 record , 2013 .

[19]  Yang Hong,et al.  Actual evapotranspiration estimation for different land use and land cover in urban regions using Landsat 5 data , 2010 .

[20]  Shuguang Liu,et al.  Data concurrency is required for estimating urban heat island intensity. , 2016, Environmental pollution.

[21]  .M AderojuOlaide,et al.  Impacts of Urban Land use changes on flood events in Warri, Delta State Nigeria , 2014 .

[22]  H. S. Lim,et al.  Landsat data to evaluate urban expansion and determine land use/land cover changes in Penang Island, Malaysia , 2010 .

[23]  Jianping Wu,et al.  Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979–2009) in China , 2011, Environmental monitoring and assessment.

[24]  D. Koc-San,et al.  ANALYSIS OF RELATIONSHIP BETWEEN URBAN HEAT ISLAND EFFECT AND LAND USE/COVER TYPE USING LANDSAT 7 ETM+ AND LANDSAT 8 OLI IMAGES , 2016 .

[25]  Hanqiu Xu.  Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery , 2006 .

[26]  J. Marques,et al.  Relating landscape to stream nitrate-N levels in a coastal eastern-Atlantic watershed (Portugal) , 2016 .

[27]  D. King,et al.  Mapping forest growth and decline in a temperate mixed forest using temporal trend analysis of Landsat imagery, 1987–2010 , 2014 .

[28]  Manfred Ehlers,et al.  Application of SPOT data for regional growth analysis and local planning , 1990 .

[29]  J. Mas.  Monitoring land-cover changes: A comparison of change detection techniques , 1999 .

[30]  Athanassios I. Sfougaris,et al.  electing landscape metrics as indicators of spatial heterogeneity — A omparison among Greek landscapes , 2013 .

[31]  Hanqiu Xu,et al.  A remote sensing and GIS integrated study on urbanization with its impact on arable lands: Fuqing City, Fujian Province, China , 2000 .

[32]  Alberto García-Martín,et al.  The relationship between landscape patterns and human-caused fire occurrence in Spain , 2013 .

[33]  G. Fischer,et al.  Land-use and land-cover change. Science/research plan , 1995 .

[34]  Jinmu Choi,et al.  A hybrid approach to urban land use/cover mapping using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images , 2004 .

[35]  Antonio J. Plaza,et al.  Automatic Change Detection in High-Resolution Remote Sensing Images by Using a Multiple Classifier System and Spectral–Spatial Features , 2016, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[36]  M. Ng,et al.  The Role of Planning in the Development of Shenzhen, China: Rhetoric and Realities , 2004 .

[37]  T. Esch,et al.  New dimensions of urban landscapes: The spatio-temporal evolution from a polynuclei area to a mega-region based on remote sensing data , 2014 .

[38]  B. Pradhan,et al.  Multi-temporal landsat images based on eco-environmental change analysis in and around Chah Nimeh reservoir, Balochestan (Iran) , 2014, Environmental Earth Sciences.

[39]  Shixiao Yu,et al.  Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China , 2015, Environmental Monitoring and Assessment.

[40]  Robert Gilmore Pontius,et al.  Land transition estimates from erroneous maps , 2010 .

[41]  Claudia Gallikowski.  Agenda 21 , 1999 .

[42]  Xiaoping Liu,et al.  Aggregative model-based classifier ensemble for improving land-use/cover classification of Landsat TM Images , 2014 .

[43]  P. Gong,et al.  Application of satellite and GIS technologies for land-cover and land-use mapping at the rural-urban fringe : A case study , 1992 .

[44]  A. Nurwanda,et al.  Analysis of Land Cover Changes and Landscape Fragmentation in Batanghari Regency, Jambi Province☆ , 2016 .

[45]  Abduwasit Ghulam,et al.  Drivers of land cover and land use changes in St. Louis metropolitan area over the past 40 years characterized by remote sensing and census population data , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[46]  Youpeng Xu,et al.  Urban Rainwater Utilization and its Role in Mitigating Urban Waterlogging Problems—A Case Study in Nanjing, China , 2012, Water Resources Management.

[47]  W. Cohen,et al.  Landsat's Role in Ecological Applications of Remote Sensing , 2004 .

[48]  A. Huete.  A soil-adjusted vegetation index (SAVI) , 1988 .

[49]  Long Hualou.  Rural Housing Land Transition in China:Theory and Verification , 2006 .

[50]  Sergio M. Vicente-Serrano,et al.  Using landscape ecology to evaluate an alternative management scenario in abandoned Mediterranean mountain areas , 2006 .

[51]  Qihao Weng.  A remote sensing?GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China , 2001 .

[52]  Qingxi Tong,et al.  Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance , 2014 .

[53]  A. Noormets,et al.  Monthly land cover‐specific evapotranspiration models derived from global eddy flux measurements and remote sensing data , 2016 .