Built-up Area Change Research Articles

Towards a novel backdating strategy for creating built-up land time series data using contemporary spatial constraints

For retrospective land cover change analysis extending back in time earlier than approximately the year 2000, multispectral remote sensing data such as the Landsat archive are often the only available and systematically archived data source. However, the spatial resolution of such observations often impedes the change analysis of geographic phenomena that may occur at sub-pixel level, such as changes in built-up land. In such cases, the integration of these data products with increasingly available contemporary high resolution settlement data employed as spatial constraints can potentially mitigate this drawback. Little research has been done regarding the quantitative potential of such integrative approaches, often due to the lack of multi-temporal reference data about changes in built-up area at sufficient spatio-temporal granularity and extent. In this contribution, we present and evaluate a time-series based approach for built-up area change analysis using Landsat time series data, spatially constrained by contemporary building footprint data. We evaluate the potential of our approach using a highly accurate multi-temporal reference database of built-up areas created through integrating publicly available building footprint and cadastral data in selected regions of the United States of America.

Analysis and simulation of land cover changes and their impacts on land surface temperature in a lower Himalayan region

Rapid urbanization is changing the existing patterns of Land Use Land Cover (LULC) globally which is consequently increasing the Land Surface Temperature (LST) in many regions. Present study was focused on estimating the current and simulating the future LULC and LST trends in the alpine environment of lower Himalayan region of Pakistan. Past patterns of LULC and LST were identified through the Support Vector Machine (SVM) and multi-spectral Landsat satellite images during 1987–2017 data period. The Cellular automata (CA) model and Artificial Neural Network (ANN) were applied to simulate future (years 2032 and 2047) LULC and LST changes, respectively, using their past patterns. CA model was validated for the simulated and the estimated LULC for the year 2017 with an overall Kappa (K) value of 0.77 using validation modules in QGIS and IDRISI software. ANN method was validated by correlating the observed and simulated LST for the year 2017 with correlation coefficient (R) and Mean Square Error (MSE) values of 0.81 and 0.51, respectively. Results indicated a change in the LULC and LST for instance the built-up area was increased by 4.43% while agricultural area and bare soil were reduced by 2.74% and 4.42%, respectively, from 1987 to 2017. The analysis of LST for different LULC classes indicated that built-up area has highest temperature followed by barren, agriculture and vegetation surfaces. Simulation of future LULC and LST showed that the built-up area will be increased by 2.27% (in 2032) and 4.13% (in 2047) which led 42% (in 2032) and 60% (in 2047) of the study area as compared to 26% area (in 2017) to experience LST greater than 27 °C. A strong correlation between built-up area changes and LST was thus found signifying major challenge to urban planners mitigating the consequent of Urban Heat Island (UHI) phenomenon. It is suggested that future urban planning should focus on urban plantation to counter UHI phenomena in the region of lower Himalayas.

Modeling Polycentric Urbanization Using Multisource Big Geospatial Data

Understanding the dynamics of polycentric urbanization is important for urban studies and management. This paper proposes an analytical model that uses multisource big geospatial data to characterize such dynamics to facilitate policy making. There are four main steps: (1) main centers and subcenters are identified using spatial cluster analysis and geographically weighted regression (GWR) based on Visible Infrared Imaging Radiometer Suite (VIIRS)/NPP and social media check-in data; (2) the built-up areas are extracted by using Defense Meteorological Satellite Program—Operational Linescan System (DMSP/OLS) gradient images; (3) the economic corridors that connect the main center and subcenters are constructed using road network data from Open Street Map (OSM) with the least-cost distance method; and (4) the major urban development direction is identified by analyzing the changes in built-up areas within the economic corridors. The model is applied to three major cities in northeastern, central, and northwestern China (Shenyang, Wuhan, and Xi’an) from 1992 to 2012.

Analysis for Mapping of Built-Up Area Using Remotely Sensed Indices – A Case Study of Rajarhat Block in Barasat Sadar Sub-Division in West Bengal (India)

Abstract Present study investigated mapping and monitoring urban land areas from Landsat8 satellite data using remotely sensed indices. The normalized difference built-up index (NDBI), Enhanced Built-Up and Bareness Index (EBBI), Index-based built-up index (IBI), urban index (UI), normalized difference bareness index (NDBaI) were used to extract the built-up area. The NDBI was more effective at discriminating built-up areas and at increasing accuracy (overall accuracy of 76.45 % and kappa accuracy of 57 %) of the built-up density percentage than other remotely sensed indices. Evidence on built-up area change geographically would permit urban planner and decision makers to comprehend and appraise urban growth pattern in regards to land cover dynamics.

Assessment of Shoreline and Associated Landuse/Land cover Changes along Part of Lagos Coastline, Nigeria

Abstract The city of Lagos, Nigeria has undergone rapid increase in population due to economic and commercial activities. As a result of this, there has been a persistent change in Land use/Land cover (LULC) of the city and shoreline through the years. This observation necessitated the use of multi-temporal satellite data to characterize shoreline changes between 1984 and 2016. Therefore, the study attempts to determine the shoreline change during the study period and the coastal land use and land cover (LULC) of the study area. Satellite data was acquired andsubjected to some image processing techniques such as image enhancement, supervised classification, and shoreline extraction. The digital shoreline analysis system (DSAS) in ArcGIS environment was utilized to cast transects and calculate statistical parameters for the shoreline and spatial data used was Landsat TM, ETM and OLI for the years 1984, 1990, 2000, 2004 and 2016 respectively. The results indicate that LULC changes in builtup areas increases rapidly during the years (1984-2015) from 12.2 -36.2%, water bodies increased from (1984- 1990-2000) from 52%, 54%, 52% and reduces to 47.4% in the year 2015 while vegetation cover reduces drastically through the year range from 36%, 33%, 29%, 24% and 16%. A total of 1034 transects were generated with 100m spacing and the average rate of change was calculated for the 32 year period (1984-2016). The linear regression rate (LRR) shoreline result shows a mean of -0.59m/year where 73.1% of transect fall under erosion and 61.8% accretion respectively. The end point rate (EPR) and net shoreline movement (NSM) analysis revealed mean shoreline change of -0.57m/year and -18.1m/period respectively from 1984-2016. The EPR and NSM results both revealed that 231 transect or 22.3% experienced erosion, and 805 transect or 77.9% with accretion. It was observed that significant accretion rate recorded along most sections of the shorelines is attributed to beach nourishment activities.

Multiscale remote sensing of urbanization in Ho Chi Minh city, Vietnam - A focused study of the south

This study focuses on monitoring and mapping the urbanization process in the south of Ho Chi Minh City, Vietnam. Among the most vulnerable cities worldwide due to climate change, Ho Chi Minh city is experiencing the fast urbanization in last decades, especially in the south, a wetland area. The severe environmental impact such as flood has occurred more frequently implying the critical infrastructures development is far behind the expansion of newly built-up residences and hence, growing population. To what extent, the newly built-up areas have contributed to accelerating the environmental impacts in the context of climate change? The aim of this study is twofold. Firstly, we experiment three different levels of spatial resolution, sub-meter, 2.5 m and 10–15 m in mapping the landcover changes of a selected typical fast urbanization area in 2000–2010. With all about 80% classification accuracy achievement, we found that sub-meter resolution is the best for a reliable identification of land cover changes in such complex and fast-growing built-up areas whereas 2.5 m resolution is sufficient to identify the extent of built-up areas and 10–15 m is unsuitable. We also confirmed a consistent expansion, over 25%, of built-up area in our study area, using three different resolutions in spite of small differences in other landcover types. Secondly, in comparison of ground data, we revealed that most of the newly built-up areas in 2000–2010 were built on the higher land and no flood incident was recorded obviously. However, the nearby lowland experienced more floods due to the changes. A slight increase of sea level and the sinking of the city due to the groundwater extraction may also contribute to more flood incidents. Remote sensing proved to be effective in revealing the temporal urbanization and its possible consequences. However, a holistic approach to investigation needs to be developed to better understand the contribution of anthropogenic activities to environmental impacts in the climate change context.

Modeling the Spatio-temporal dynamics and evolution of land use and land cover (1984–2015) using remote sensing and GIS in Raya, Northern Ethiopia

This study models the spatio-temporal dynamics, patterns, and evolution of land use and land cover (LULC) (1984–2015) using remote sensing and GIS supported by in-suit measurements in Raya, Northern Ethiopia. Landsat thematic mapper (TM), and operational land imager (OLI) path 168/169 and row 051/52 were acquired from the United States Geological Survey Landsat archive. All necessary image pre-processing techniques were applied to remove the distortions due to sensors. Eight major LULC types based on a supervised image classification and maximum likelihood decision rule were identified. Post-classification change detection method was also applied to detect the dynamics in LULC. Significant change in forestland, shrub/bush land, built-up area, grassland, cropland, barren land, and floodplain areas were observed over the period 1984–2015. Considerable losses were observed in grasslands (36.9%), water body (8.7%), and floodplain areas (74.4%), while other LULC types increased. This explains why the study area is frequently affected by drought and other related disasters. An overall accuracy of 88.5, 86.5 and 90.5% were observed for the 1984, 1995 and 2015 LULC, respectively. The overall Kappa coefficient of 0.87, 0.85, and 0.90 were also observed for the same periods. Besides, the Pearson pairwise correlation matrix among the 1984–1995, 1995–2015 and 1984–2015 LULC shows positive and strong correlation (r = 0.916, r = 0.908, r = 0.914) at p < 0.005 significance level. Therefore, there is no much difference in identifying LULC types using TM and OLI products. This study is crucial to implement scientific land use policies and strategies in the study area.

Analysis of land cover/use changes using Landsat 5 TM data and indices.

Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.

Quantifying annual changes in built-up area in complex urban-rural landscapes from analyses of PALSAR and Landsat images

Built-up area supports human settlements and activities, and its spatial distribution and temporal dynamics have significant impacts on ecosystem services and global environment change. To date, most of urban remote sensing has generated the maps of impervious surfaces, and limited effort has been made to explicitly identify the area, location and density of built-up in the complex and fragmented landscapes based on the freely available datasets. In this study, we took the lower Yangtze River Delta (Landsat Path/Row: 118/038), China, where extensive urbanization and industrialization have occurred, as a case study site. We analyzed the structure and optical features of typical land cover types from (1) the HH and HV gamma-naught imagery from the Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), and (2) time series Landsat imagery. We proposed a pixel- and rule-based decision tree approach to identify and map built-up area at 30-m resolution from 2007 to 2010, using PALSAR HH gamma-naught and Landsat annual maximum Normalized Difference Vegetation Index (NDVImax). The accuracy assessment showed that the resultant annual maps of built-up had relatively high user (87–93%) and producer accuracies (91–95%) from 2007 to 2010. The built-up area was 2805km2 in 2010, about 16% of the total land area of the study site. The annual maps of built-up in 2007–2010 show relatively small changes in the urban core regions, but large outward expansion along the peri-urban regions. The average annual increase of built-up areas was about 80km2 per year from 2007 to 2010. Our annual maps of built-up in the lower Yangtze River Delta clearly complement the existing maps of impervious surfaces in the region. This study provides a promising new approach to identify and map built-up area, which is critical to investigate the interactions between human activities and ecosystem services in urban-rural systems.

Urban expansion and vegetation changes in Hangzhou Bay area using night-light data

Based on DMSP/OLS night-light data and MODIS NDVI data for 2000, 2007 and 2013, this paper studied on characteristics of urban expansion and vegetation changes in built-up areas with nighttime light threshold extraction and vegetation index analysis using remote sensing and GIS. Results showed that the threshold method could realize the effective extraction of urban land information. In general, the urban built-up area expanded along with Hangzhou Bay in V model, and there were three expansion patterns: polygon pattern, linear pattern and point pattern. Obvious spatio-temporal variations in different cities were found in the rate and the dynamic degree of urban expansion and the compactness of urban morphology. The whole study area showed a decreasing trend in the rate and the dynamic degree of urban expansion, while the average compactness of urban morphology declined after the rise. Vegetation conditions became better in built-up areas except Jiaxing in 2000-2007, but it became worse in all cities in 2007-2013. Urban expansion had a ne-gative effect on the vegetation change in built-up areas in 2000-2013.

Spatial evaluation of impacts of increase in impervious surface area on SCS-CN and runoff in Nagpur urban watersheds, India

The changing land use due to rapid urbanization has profound impact on the runoff in urban watersheds. The spatial analysis in urban watersheds is felt necessary for management of surface and subsurface water regimes. Significant increase in impervious zones was observed in Nagpur urban watersheds between 2000 and 2012 having impacts on runoff, and even flash floods were observed. This study presents spatial and temporal impacts of change in urban built-up area on curve number (CN) and runoff during the years 2000 and 2012. The study also analyzes effect of slope on CN values and shows that CN increases with slope. High-resolution satellite images were used to map impervious surface areas (ISAs) which show an increase of 0.9 to 34 % during 2000–2012. Spearman’s and Pearson’s coefficients have been generated to establish relationship between runoff, impervious surface areas, vegetation index, slope, and runoff coefficient. It has been hypothetically assumed that if 100, 50, and 25 % rooftop rainwater harvesting is considered, the estimated runoff reduces in 2012 as compared to the year 2000. The study suggests that increase in impervious areas within urban watersheds can be utilized for groundwater augmentation adopting rooftop rainwater-harvesting techniques and to prevent flash floods.

Urban Built-up Area Extraction and Change Detection of Adama Municipal Area using Time-Series Landsat Images

Urban built-up area information is required in various applications of land use planning and management. However, urban built-up area extraction from moderate spatial resolution Landsat time-series data is challenging because of significant intra-urban heterogeneity and spectral confusion between other landcover types. This paper proposes a technique to extract urban built-up area from time-series Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imageries and determines urban area changes between 1984 to 2015 of Adama Municipal Area of Ethiopia. The study selected three indices, the Enhanced Built-Up and Bareness Index (EBBI), Soil Adjusted Vegetation Index (SAVI) and Modified Normalized Difference Water Index (MNDWI), to represent three major urban land-use classes: built-up and barren/bare land, open waterbody, and vegetation, respectively. The built-up area was extracted by taking the difference between EBBI, SAVI and MNDWI to remove the vegetation and water noises, and the resulted index image was spectrally segmented to separate built-up area from the non-urban built-up lands. The derived index was used to map built-up area for 1984, 1995, 2005 and 2015 periods. The expansion of the built-up area has been revealed as a major change in the area when city area expanded substantially by 293% between 1984 to 2015 periods. The advantage of the method was to use almost the entire spectral range of Landsat imageries which cause less spectral confusion between land cover classes and hence resulted in higher accuracies compared to other indices. The method was effective and simple to implement, and can be used for built-up extraction in other areas.

Built-Up Area Change Analysis in Iasi City Using GIS

Abstract The study analyses the spatial and temporal changes occurred in the builtup area of Iași city and its surrounding areas using cartographic materials from different time periods. The paper aims to highlight the areas where the most significant changes took place by identifying the main evolution patterns, generated by certain natural or human-driven factors. The results of the study were achieved by using specific photo-interpretation methods of the available orthophotomaps form 2006 and 2012, mainly using the professional GIS softwares TNT Mips 7.2., ArcGIS 10.2 and Global Mapper 11. The changes have lead on the one hand to the conversion of the former industrial areas and thus, the urban regeneration, but also to the periurbanization phenomenon, with major functional and structural effects.

Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data

In 1986, the Government of Vietnam implemented free market reforms known as Doi Moi (renovation) that provided private ownership of farms and companies, and encouraged deregulation and foreign investment. Since then, the economy of Vietnam has achieved rapid growth in agricultural and industrial production, construction and housing, and exports and foreign investments, each of which have resulted in momentous landscape transformations. One of the most evident changes is urbanization and an accompanying loss of agricultural lands and open spaces. These rapid changes pose enormous challenges for local populations as well as planning authorities. Accurate and timely data on changes in built-up urban environments are essential for supporting sound urban development. In this study, we applied the Support Vector Machine classification (SVM) to multi-temporal stacks of Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images from 1993 to 2010 to quantify changes in built-up areas. The SVM classification algorithm produced a highly accurate map of land cover change with an overall accuracy of 95%. The study showed that most urban expansion occurred in the periods 2001–2006 and 2006–2010. The analysis was strengthened by the incorporation of population and other socio-economic data. This study provides state authorities a means to examine correlations between urban growth, spatial expansion, and other socio-economic factors in order to not only assess patterns of urban growth but also become aware of potential environmental, social, and economic problems.

Pengaruh Perubahan Penggunaan Lahan Sub DAS Rawapening terhadap Erosi dan Sedimentasi Danau Rawapening

Konferensi Nasional Danau Indonesia ( KNDI ) di Bali tahun 2009 menetapkan Danau Rawapening sebagai salah satu dari 15 ( lima belas ) danau/waduk yang memerlukan prioritas dalam pemulihan kerusakan danau di Indonesia. Alih fungsi lahan yang terjadi pada Sub DAS Rawapening memicu terjadinya peningkatan kerusakan lahan yang berimbas pada tingginya laju erosi dan s edimentasi di Danau Rawapening. Penelitian ini menggunakan pendekatan positivistik/kuantitatif dengan metode analisis yang digunakan adalah metode penelitian deskriptif yang menggambarkan variabel -variabel dan fenomena-fenomena yang terjadi. Hasil perhitungan erosi dan sedimentasi menunjukkan bahwa erosi dan sedimentasi di Danau Rawapening menurun dari tahun 1991, 2001 dan 2011. Hal ini dikarenakan ada beberapa faktor yang bersifat dinamis pada analisis yang dilakukan. Untuk melihat pengaruh perubahan penggunaan lahan terhadap erosi dan sedimentasi secara mendalam maka digunakan nilai erosivitas rata-rata sebesar 2.523,09. Hasil analisis menunjukkan bahwa penurunan luas lahan tegakan berbanding terbalik dengan laju erosi, jumlah erosi dan sedimentasi. Sedang kan luasan lahan terbangun berbanding lurus dengan laju erosi, jumlah erosi, dan sedimentasi. Perubahan penggunaan lahan yang menyebabkan kenaikan erosi terbesar adalah perubahan penggunaan lahan dengan tegakan menjadi lahan terbangun dan perubahan penggunaan lahan pertanian menjadi lahan terbangun.Kata kunci : perubahan penggunaan lahan, erosi, sedimentasi

Remote Sensing and Topographic Information in a GIS environment for Urban Growth and Change

Urbanization results in the expansion of administrative boundaries, mainly at the periphery, ultimately leading to changes in landcover. Agricultural land, naturally vegetated land, and other land types are converted into residential areas with a high density of constructs, such as transportation systems and housing. In urban regions of rapid growth and change, urban planners need regular information on up to date ground change. Amman (the capital of Jordan) is growing at unprecedented rates, creating extensive urban landscapes. Planners interact with these changes without having a global view of their impact. The use of aerial photographs and satellite images data combined with topographic information and field survey could provide effective information to develop urban change and growth inventory which could be explored towards producing a very important signature for the built-up area changes.

Change Detection of Land cover and Urban Heat Islands using Multi-Temporal Landsat Images, application in Tanta City, Egypt

The rapid urbanization coupled with tremendous growth in population and built-up areas in cities, lead to problems associated with global climate change impacts such as urban heat islands. The current study is concerned with mapping the dynamics of urban growth and the urban heat island (UHI) in Tanta city, Nile Delta, Egypt using remote sensing data and techniques. The thermal bands of five multi-temporal Landsat5 TM and Landsat7 ETM+ images covering Tanta city, Egypt acquired in summer season were analysed for the spatio-temporal identification and mapping of UHIs. First, Landsat multiple bands were used to classify the landcover and to detect the changes in built-up areas. Second, the thermal bands were used to retrieve the land surface temperature (LST) in the city and outskirts. Third, The urban heat islands (UHI) intensity was identified for each image and mapped using the mean temperature and standard deviation. Finally, a regression analysis was conducted to study the relationship between LST and green areas and built-up areas. The results revealed the enormous urban growth and reduction of the green areas in Tanta during the study periods. This was accompanied by an increase in urban heat islands intensity. The results revealed that the relationships between the percentage of built-up areas, green areas and the land surface temperature in the city.

Effects of Peri-Urban Land Use Changes on Forest Ecosystem Services: The Case of Settlements Surrounding Pugu and Kazimzumbwi Forest Reserves in Tanzania

Peri-urban settlements constitute foci of urban expansion in most cities of the developing world. They provide livelihood opportunities by exploiting adjacent resources such as forest products, land and water. Yet they constitute a conflicting zone of development whereby urban and rural livelihoods compete for space. This paper examines the effects of peri-urban land-use changes on forest ecosystem services from Pugu and Kazimzumbwi forest reserves. Land use changes were analysed using series aerial photographs of between 1975 and 2012. This was complemented with participatory resource mapping, focus group discussion and key informant interviews to identify and qualify changes in ecosystem services over the period of 37 years. Literature review was also used to capture non-spatial data. Results indicate that there has been tremendous change in built-up area surrounding the forest reserve. It increased from 608.78 hectares in 1975 to 4,933.51 hectares in 2012 representing an increase from 2.4 to 19.1 percent. The same trend pervaded residential and the reverse for open land uses. These changes have resulted into disappearance of ecosystem services (plant and animal species, honey and wax production, mushrooms and water resources). The remaining forest ecosystem services are likely to completely disappear in few years if protection and conservation measures will not be stepped up. Guided land use plans for all areas surrounding the forest reserves and decentralized forest management have been recommended to facilitate restoration of forest services.

Dynamics of Urban Growth in Semarang Metropolitan – Central Java: An Examination Based on Built-Up Area and Population Change

Representation of rapid urban growth followed by high rate of land conversion is clearly observed in the case of Semarang Metropolitan. Located in Java Island, this capital city has been performing as the largest urban area in the Central Java Province. This paper aims to examine urban growth pattern in Semarang Metropolitan by applying two main indicators, i.e., (1) additional built-up area 1972-2009 indicated as land conversion, and (2) population change between 1991-2008. Accordingly, distance is regard as an important parameter to further examine the emerging pattern based on the two indicators. Remote Sensing (RS) and Geographical Information System (GIS) were used to analyze satellite images and built-up area development from the different periods. The analyses result show that suburbanization has been taken place in Semarang Metropolitan. The emerging pattern is very common in Asian cities as it is very much similar with the pattern in view selected cities in the neighboring countries (Jakarta, Bangkok, Metro Manila).

Urban containment policies and urban growth

While there has been controversy over the negative and positive effects of urban containment policies (UCPs), little is known about their impact on urban growth with policy tightness. This paper empirically analyses UCP impacts on changes in population, employment, built-up areas, and housing values. A simultaneous equation model is estimated, with, as endogenous variables, the above changes at the city level. Both stringent containment policies (SCP), such as greenbelts and urban growth boundaries, and less stringent containment policies (LSCP), such as urban service areas, are found to have significant impacts on changes in population, employment, housing values, and city land area. SCPs have positive effects on changes in population and housing values twice as large as LSCPs, suggesting that SCPs more successfully accommodate new growth within growth boundaries and that housing values increase with the tightness of UCPs.