Detection of City Integration Processes in Rapidly Urbanizing Areas Based on Remote Sensing Imagery

Since China’s reform and development commenced, in the context of rapid urbanization and coordinated regional development, Chinese cities with a close geographic proximity and social ties have gradually formed an integrated city development model. As a new phenomenon in China’s urbanization process, existing research on China’s integrated cities mainly focuses on typical case studies, and most research has been limited to literature reviews and theoretical analyses. The growing application of remote sensing technology in urbanization research in recent years has provided new opportunities for the analysis of city integration. Therefore, based on multi-spectral Landsat-8 and nighttime light images (SNPP/VIIRS, Suomi National Polar-orbiting Platform/Visible Infrared Imaging Radiometer Suite), this paper selects four of the most representative integrated cities with different backgrounds in China to analyze the land-use conversion, plot light fluctuation, and light gravity center shift in the boundary zone between cities. The results show that (1) Guangfo has the highest level of integration and urban expansion is mainly concentrated in the south-central part of the boundary area; (2) Guanshen’s level of integration is second to Guangfo’s and is mainly concentrated in the west; (3) HuSu’s integration is still in the initial stage and its increase in light intensity lags behind the expansion of building land during the study period; (4) although the light intensity and building land area increased significantly during the study period in Xixian, the overall development level of Xixian still lagged behind coastal cities due to the restriction of its geographical location. Our application results expand the data sources for integrated city research and the obtained results can potentially support decision-making and planning in the process of urban development.

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Impact of Urbanization on Urban Heat Island Intensity in Major Districts of Bangladesh Using Remote Sensing and Geo-Spatial Tools

Climate ◽

10.3390/cli10010003 ◽

2022 ◽

Vol 10 (1) ◽

pp. 3

Author(s):

Md. Naimur Rahman ◽

Md. Rakib Hasan Rony ◽

Farhana Akter Jannat ◽

Subodh Chandra Pal ◽

Md. Saiful Islam ◽

...

Keyword(s):

Climate Change ◽

Remote Sensing ◽

Urban Heat Island ◽

Urban Expansion ◽

Winter Period ◽

Landsat 8 ◽

Heat Island ◽

Rapid Urbanization ◽

Urban Heat ◽

The Impact

Urbanization is closely associated with land use land cover (LULC) changes that correspond to land surface temperature (LST) variation and urban heat island (UHI) intensity. Major districts of Bangladesh have a large population base and commonly lack the resources to manage fast urbanization effects, so any rise in urban temperature influences the population both directly and indirectly. However, little is known about the impact of rapid urbanization on UHI intensity variations during the winter dry period in the major districts of Bangladesh. To this end, we aim to quantify spatiotemporal associations of UHI intensity during the winter period between 2000 and 2019 using remote-sensing and geo-spatial tools. Landsat-8 and Landsat-5 imageries of these major districts during the dry winter period from 2000 to 2020 were used for this purpose, with overall precision varying from 81% to 93%. The results of LULC classification and LST estimation showed the existence of multiple UHIs in all major districts, which showed upward trends, except for the Rajshahi and Rangpur districts. A substantial increase in urban expansion was observed in Barisal > 32%, Mymensingh > 18%, Dhaka > 17%, Chattogram > 14%, and Rangpur > 13%, while a significant decrease in built-up areas was noticed in Sylhet < −1.45% and Rajshahi < −3.72%. We found that large districts have greater UHIs than small districts. High UHI intensities were observed in Mymensingh > 10 °C, Chattogram > 9 °C, and Barisal > 8 °C compared to other districts due to dense population and unplanned urbanization. We identified higher LST (hotspots) zones in all districts to be increased with the urban expansion and bare land. The suburbanized strategy should prioritize the restraint of the high intensity of UHIs. A heterogeneous increase in UHI intensity over all seven districts was found, which might have potential implications for regional climate change. Our study findings will enable policymakers to reduce UHI and the climate change effect in the concerned districts.

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Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

Journal of Geographical Studies ◽

10.21523/gcj5.19030102 ◽

2020 ◽

Vol 3 (1) ◽

pp. 11-23 ◽

Cited By ~ 3

Author(s):

Abdulla Al Kafy ◽

Abdullah Al-Faisal ◽

Mohammad Mahmudul Hasan ◽

Md. Soumik Sikdar ◽

Mohammad Hasib Hasan Khan ◽

...

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Land Surface ◽

Agricultural Land ◽

Global Climate ◽

Urban Expansion ◽

Water Bodies ◽

Landsat 8 ◽

Lulc Changes ◽

The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

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Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽

10.3390/geosciences11080312 ◽

2021 ◽

Vol 11 (8) ◽

pp. 312

Author(s):

Barbara Wiatkowska ◽

Janusz Słodczyk ◽

Aleksandra Stokowska

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Satellite Imagery ◽

Urban Areas ◽

Agricultural Land ◽

Urban Expansion ◽

Landsat 8 ◽

Rate Of Increase ◽

Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

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Assessing the impact of arid area urbanization on flash floods using GIS, remote sensing, and HEC-HMS rainfall–runoff modeling

Hydrology Research ◽

10.2166/nh.2016.133 ◽

2016 ◽

Vol 47 (6) ◽

pp. 1142-1160 ◽

Cited By ~ 22

Author(s):

Mohamed El Alfy

Keyword(s):

Remote Sensing ◽

Hydrologic Modeling ◽

Integrated Approach ◽

Flash Floods ◽

Landsat 8 ◽

Arid Areas ◽

Rainfall Runoff ◽

Rapid Urbanization ◽

Runoff Modeling ◽

The Impact

This study uses an integrated approach, bringing together geographic information system (GIS), remote sensing, and rainfall–runoff modeling, to assess the urbanization impact on flash floods in arid areas. Runoff modeling was carried out as a function of the catchment characteristics and the maximum daily rainfall parameters. Land-use types were extracted from the supervised classification of SPOT-5 (2010) and Landsat-8 (2015) satellite images and were validated during field checks. Catchment morphometric characteristics were carried out using the correlated Topaz and Arc-Hydro tools. Maximum floods of the catchment were evaluated by coupling GIS and remote sensing with Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) hydrologic modeling. Peak discharges were estimated, and the abstraction losses were computed for different return periods. The model results were calibrated according to actual runoff event. The research shows that rapid urbanization adversely affects hydrological processes, since the sprawl on the alluvial channels is significant. This reduces infiltration into the underlying alluvium and increases runoff, leading to higher flood peaks and volumes even for short duration low intensity rainfall. To retain a considerable amount of water and sediments in these arid areas, construction of small dams at the fingertip channels at the outlet of the lower order sub-basins is recommended.

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Thermal Remote Sensing: A tool to Determine Temporal Land Surface Temperature in Hawassa City, Ethiopia

10.21203/rs.3.rs-63046/v1 ◽

2020 ◽

Author(s):

Mikias Biazen Molla

Keyword(s):

Remote Sensing ◽

Standard Deviation ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Urban Expansion ◽

Landsat 8 ◽

Landsat 8 Oli ◽

Thermal Remote Sensing ◽

The City

Abstract This investigation was conducted for the estimation of the temporal land surface temperature value using thermal remote sensing of Landsat-8 (OLI) Data in Hawassa City Administration, Ethiopia. Satellite datasets of Landsat-7 (ETM+) for 22nd March 2002 and Landsat-8 (OLI) of 22nd March 2019 were taken for this study. Different algorisms were used to estimate the Normalized Difference Vegetation Index threshold from the Red and Near-Infrared band and the ground earth's surface emissivity esteem is legitimately recovered from the thermal infrared by coordinating with the outcome got from MODIS information. The land use land cover map of the city was prepared with better accuracy using the on-screen classification technique. The spatial distribution of surface temperature of the city range from 6.62°C to 22.54°C with a mean of 14.58°C and a standard deviation of 11.25 in the year of march 22nd 2002. The LST result derived from Landsat 8 for March 22nd, 2019, ranges from 11.97°C to 35.5°C with a mean of 23.735 °C and a standard deviation of 16.64. In both years the higher LST values correspond to built-up/settlement and bare/open lands of the city; whereas, lower LST values were observed in vegetation (trees/woodlot, shrubs, and grass forested) area. Urban expansion (built-up area roads, and another impervious surface), decline in vegetation levels due to deforestation and increasing population density. Increasing an evergreen tree and green space coverage, design and develop city parks and rehabilitate the existing degraded natural environments are among the recommended strategy to reduce the rate of LST.

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Multi-Scenario Simulation for the Consequence of Urban Expansion on Carbon Storage: A Comparative Study in Central Asian Republics

Land ◽

10.3390/land10060608 ◽

2021 ◽

Vol 10 (6) ◽

pp. 608

Author(s):

Yang Chen ◽

Wenze Yue ◽

Xue Liu ◽

Linlin Zhang ◽

Ye’an Chen

Keyword(s):

Carbon Storage ◽

Agricultural Development ◽

Negative Impact ◽

Central City ◽

Urban Expansion ◽

Google Earth ◽

City Development ◽

Rapid Urbanization ◽

Central Asian ◽

Integrated Valuation

There is growing concern about the consequences of future urban expansion on carbon storage as our planet experiences rapid urbanization. While an increasing body of literature was focused on quantifying the carbon storage impact of future urban expansion across the globe, rare attempts were made from the comparative perspective on the same scale, particularly in Central Asia. In this study, Central Asian capitals, namely Ashkhabad, Bishkek, Dushanbe, Nur Sultan, and Tashkent, were used as cases. According to the potential impacts of BRI (Belt and Road Initiative) on urban expansion, baseline development scenario (BDS), cropland protection scenario (CPS), and ecological protection scenario (EPS) were defined. We then simulated the carbon storage impacts of urban expansion from 2019 to 2029 by using Google Earth Engine, the Future Land Use Simulation model, and the Integrated Valuation of Environmental Services and Tradeoffs model. We further explored the drivers for carbon storage impacts of future urban expansion in five capitals. The results reveal that Nur Sultan will experience carbon storage growth from 2019 to 2029 under all scenarios, while Ashkhabad, Bishkek, Dushanbe, and Tashkent will show a decreasing tendency. EPS and CPS will preserve the most carbon storage for Nur Sultan and the other four cities, respectively. The negative impact of future urban expansion on carbon storage will be evident in Ashkhabad, Bishkek, Dushanbe, and Tashkent, which will be relatively inapparent in Nur Sultan. The potential drivers for carbon storage consequences of future urban expansion include agricultural development in Bishkek, Dushanbe, and Tashkent, desert city development in Ashkhabad, and prioritized development of the central city and green development in Nur Sultan. We suggest that future urban development strategies for five capitals should be on the basis of differentiated characteristics and drivers for the carbon storage impacts of future urban expansion.

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Analyzing Urban Growth Pattern and Driving Factors Using Remote Sensing and GIS: A Case Study of Banepa Municipality, Nepal

Journal on Geoinformatics, Nepal ◽

10.3126/njg.v20i1.39471 ◽

2020 ◽

Vol 20 (1) ◽

pp. 9-18

Author(s):

Rabina Twayana ◽

Sijan Bhandari ◽

Reshma Shrestha

Keyword(s):

Remote Sensing ◽

Land Use ◽

Urban Growth ◽

Growth Pattern ◽

Agricultural Land ◽

Urban Expansion ◽

Urban Land ◽

Driving Factors ◽

Rapid Urbanization ◽

The Impact

Nepal is considered one of the rapidly urbanizing countries in south Asia. Most of the urbanization is dominated in large and medium cities i.e., metropolitan, sub-metropolitan, and municipalities. Remote Sensing and Geographic Information System (GIS) technologies in the sector of urban land governance are growing day by day due to their capability of mapping, analyzing, detecting changes, etc. The main aim of this paper is to analyze the urban growth pattern in Banepa Municipality during three decades (1992-2020) using freely available Landsat imageries and explore driving factors for change in the urban landscape using the AHP model. The Banepa municipality is taken as a study area as it is one of the growing urban municipalities in the context of Nepal. The supervised image classification was applied to classify the acquired satellite image data. The generated results from this study illustrate that urbanization is gradually increasing from 1992 to 2012 while, majority of the urban expansion happened during 2012-2020, and it is still growing rapidly along the major roads in a concentric pattern. This study also demonstrates the responsible driving factors for continuous urban growth during the study period. Analytical Hierarchy Process (AHP) was adopted to analyze the impact of drivers which reveals that, Internal migration (57%) is major drivers for change in urban dynamics whereas, commercialization (25%), population density (16%), and real estate business (5%) are other respective drivers for alteration of urban land inside the municipality. To prevent rapid urbanization in this municipality, the concerned authorities must take initiative for proper land use planning and its implementation on time. Recently, Nepal Government has endorsed Land Use Act 2019 for preventing the conversion of agricultural land into haphazard urban growth.

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Impacts of Large-Scale Groundwater Exploitation Based on Long-Term Evolution of Hydraulic Heads in Dhaka City, Bangladesh

Water ◽

10.3390/w13101357 ◽

2021 ◽

Vol 13 (10) ◽

pp. 1357

Author(s):

Mazeda Islam ◽

Marc Van Van Camp ◽

Delwar Hossain ◽

Md. Mizanur Rahman Sarker ◽

Shahina Khatun ◽

...

Keyword(s):

Large Scale ◽

Groundwater Resources ◽

Urban Expansion ◽

Public Works ◽

Dhaka City ◽

Rapid Urbanization ◽

Groundwater Exploitation ◽

South Central ◽

The City

Dhaka city has emerged as the fastest-growing megacity, having more than 20 million inhabitants, with a growth rate of 3.62%. Unplanned and rapid urbanization, coupled with exponential population growth, has significantly altered the groundwater dynamics in Dhaka city. This study concentrates on the evolution of long-term piezometric heads of the Upper Dupi Tila aquifer (UDA) and the Middle Dupi Tila aquifer (MDA) based on long-term hydrographs, piezometric maps and synthetic graphical overviews of piezometric trends. Due to over-exploitation, the piezometric level (PL) has declined deeper than −85 and −65 m PWD (Public Works Department reference datum) in UDA and MDA, respectively. The highest rate of decline was observed in the south-central to southeastern parts of the city both in UDA (4.0 m/year) and MDA (5.74 m/year). The results clearly show that the rates of decline in PL vary from 2.25 to 5.74 m/year in both aquifers of the city, and urban expansion has greatly affected the shape and extent of the depression cone over the past four decades. The magnitudes of the depression cones in both aquifers seem to pose a considerable threat to groundwater resources, indicating that the current exploitation is not sustainable at all.

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Use of Remotely Sensed Data to Enhance Estimation of Aboveground Biomass for the Dry Afromontane Forest in South-Central Ethiopia

Remote Sensing ◽

10.3390/rs12203335 ◽

2020 ◽

Vol 12 (20) ◽

pp. 3335

Author(s):

Habitamu Taddese ◽

Zerihun Asrat ◽

Ingunn Burud ◽

Terje Gobakken ◽

Hans Ole Ørka ◽

...

Keyword(s):

Remote Sensing ◽

Standard Deviation ◽

Aboveground Biomass ◽

Predictor Variable ◽

Landsat 8 ◽

Independent Variables ◽

Estimation Efficiency ◽

South Central ◽

Shortwave Infrared ◽

Sentinel 2

Periodic assessment of forest aboveground biomass (AGB) is essential to regulate the impacts of the changing climate. However, AGB estimation using field-based sample survey (FBSS) has limited precision due to cost and accessibility constraints. Fortunately, remote sensing technologies assist to improve AGB estimation precisions. Thus, this study assessed the role of remotely sensed (RS) data in improving the precision of AGB estimation in an Afromontane forest in south-central Ethiopia. The research objectives were to identify RS variables that are useful for estimating AGB and evaluate the extent of improvement in the precision of the remote sensing-assisted AGB estimates beyond the precision of a pure FBSS. Reference AGB data for model calibration and estimation were collected from 111 systematically distributed circular sample plots (SPs) of 1000 m2 area. Independent variables were derived from Landsat-8, Sentinel-2 and PlanetScope images acquired in January 2019. The area-weighted mean and standard deviation of the spectral reflectance, spectral index and texture (only for PlanetScope) variables were extracted for each SP. A maximum of two independent variables from each image type was fitted to a generalized linear model for AGB estimation using model-assisted estimators. The results of this study revealed that the Landsat-8 model with the predictor variable of shortwave infrared band reflectance and the PlanetScope model with the predictor variable of green band reflectance had estimation efficiency of 1.40 and 1.37, respectively. Similarly, the Sentinel-2 model, which had predictor variables of shortwave infrared reflectance and standard deviation of green leaf index, improved AGB estimation with the relative efficiency of 1.68. Utilizing freely available Sentinel-2 data seems to enhance the AGB estimation efficiency and reduce cost and extensive fieldwork in inaccessible areas.

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Extracting and overlaping geospatial informations from remote sensing to mapping genegal drought of Ninh Thuan province

Journal of Mining and Earth Sciences ◽

10.46326/jmes.2020.61(4).02 ◽

2020 ◽

Vol 61 (4) ◽

pp. 11-24

Author(s):

Thao Phuong Thi Do ◽

Chinh Mai Thi Duong ◽

Tai Anh Le ◽

Vinh Tuyet Thi Tran ◽

Ha Thu Thi Nguyen ◽

...

Keyword(s):

Remote Sensing ◽

Warning System ◽

Remote Sensing And Gis ◽

Landsat 8 ◽

Natural Phenomena ◽

Gis Technology ◽

Analytic Hierarchy ◽

South Central ◽

Hierarchy Process ◽

Very High

Drought is one of the natural phenomena that seriously affects to society in general as well as the lives of people in particular. Therefore, determining early drought is necessary. Remote sensing and GIS technology with extracting and overlaping tools which can assess the extent of drought from geospatial informations in a wide area. Experimental area is Ninh Thuan province, where drought often occur. Five indexes (TCI, VCI, SAVI, WWSVI, TVDI) are extracted from Landsat 8. The weights according to the level of influence is determine by Analytic Hierarchy Process (AHP). Results shows current drought in five levels: no drought; low; medium; high and very high, then compared with the drought warning system in the South-central region. The areas of Ninh Phuoc, Ninh Son and Phan Rang are higher drought phenomena at the time of dry season (accounting for about 60% of the total provincial area).

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