scholarly journals Tracking Urban Expansion Using Random Forests for the Classification of Landsat Imagery (1986–2015) and Predicting Urban/Built-Up Areas for 2025: A Study of the Kumasi Metropolis, Ghana

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 44
Author(s):  
Bernard Fosu Frimpong ◽  
Frank Molkenthin
Keyword(s):  
City Planning ◽  
Landsat Imagery ◽  
Urban Expansion ◽  
Satellite Image ◽  
Unique Contribution ◽  
Land Use Land Cover ◽  
Rapid Urbanization ◽  
Lulc Changes ◽  
Spatio Temporal

Kumasi is a nodal city and functions as the administrative and economic capital of the Ashanti region in Ghana. Rapid urbanization has been experienced inducing the transformation of various Land Use Land Cover (LULC) types into urban/built-up areas in Kumasi. This paper aims at tracking spatio-temporal LULC changes utilizing Landsat imagery from 1986, 2013 and 2015 of Kumasi. The unique contribution of this research is its focus on urban expansion analysis and the utilization of Random Forest (RF) Classifier for satellite image classification. Change detection, urban land modelling and urban expansion in the sub-metropolitan zones, buffers, density decay curve and correlation analysis were methodologies adopted for our study. The classifier yielded better accuracy compared to earlier works in Ghana. The evaluation of LULC changes indicated that urban/built-up areas are continually increasing at the expense of agricultural and forestlands. The urban/built-up areas occupied 4622.49 hectares (ha) (23.78%), 13,447.50 ha (69.18%) and 14,004.60 ha (72.05%) in 1986, 2013 and 2015, respectively of the 19,438 ha area of Kumasi. Projection indicated that urban/built-up areas will occupy 15,490 ha (79.70%) in 2025. The urban expansion was statistically significant. The results revealed the importance of spatial modeling for environmental management and city planning.

scholarly journals Spatiotemporal Influence of Land Use/Land Cover Change Dynamics on Surface Urban Heat Island: A Case Study of Abuja Metropolis, Nigeria

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Heat Islands ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.

scholarly journals Lane-Level Road Extraction from High-Resolution Optical Satellite Images

2019 ◽  
Vol 11 (22) ◽  
pp. 2672
Author(s):  
Jiguang Dai ◽  
Tingting Zhu ◽  
Yilei Zhang ◽  
Rongchen Ma ◽  
Wantong Li
Keyword(s):  
High Resolution ◽  
Rural Areas ◽  
Template Matching ◽  
City Planning ◽  
Urban Expansion ◽  
Satellite Image ◽  
Road Extraction ◽  
Urban And Rural Areas ◽  
Optical Satellite Images ◽  
Vehicle Management

High-quality updates of road information play an important role in smart city planning, sustainable urban expansion, vehicle management, urban planning, traffic navigation, public health and other fields. However, due to interference from road geometry and texture noise, it is difficult to avoid the decline of automation while accurately extracting roads. Therefore, we propose a high-resolution optical satellite image lane-level road extraction method. First, from the perspective of template matching and considering road characteristics and relevant semantic relations, an adaptive correction model, an MLSOH (multi-scale line segment orientation histogram) descriptor, a sector descriptor, and a multiangle beamlet descriptor are proposed to solve the interference from geometry and texture noise in road template matching and tracking. Second, based on refined lane-level tracking, single-lane and double-lane road-tracking modes are designed to extract single-lane and double-lane roads, respectively. In this paper, Pleiades satellite and GF-2 images are selected to set up different scenarios for urban and rural areas. Experiments are carried out on the phenomena that restrict road extraction, such as tree occlusion, building shadow occlusion, road bending, and road boundary blurring. Compared with other methods, the proposed method not only ensures the accuracy of lane-level road extraction but also greatly improves the automation of road extraction.

scholarly journals Spatio-temporal reasoning for the classification of satellite image time series

2012 ◽  
Vol 33 (13) ◽  
pp. 1805-1815 ◽  
Author(s):  
François Petitjean ◽  
Camille Kurtz ◽  
Nicolas Passat ◽  
Pierre Gançarski
Keyword(s):  
Time Series ◽  
Satellite Image ◽  
Temporal Reasoning ◽  
Spatio Temporal

scholarly journals Perkembangan Wilayah dan Perubahan Tutupan Lahan di Kabupaten Purwakarta sebagai Dampak dari Proses Konurbasi Jakarta-Bandung

2018 ◽  
Vol 2 (2) ◽  
pp. 195
Author(s):  
Alfin Murtadho ◽  
Siti Wulandari ◽  
Muhammad Wahid ◽  
Ernan Rustiadi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Regional Development ◽  
Land Cover Change ◽  
Urban Expansion ◽  
Satellite Image ◽  
Water Bodies ◽  
Urban Region ◽  
Land Use Land Cover ◽  
The Impact

<p class="ISI-Paragraf">Jabodetabek and Bandung Raya metropolitan region experienced an urban expansion phenomenon that caused the two metropolitan regions to become increasingly connected by a corridor and form a mega-urban region caused by the conurbation process. Purwakarta regency is one of the regions in Jakarta-Bandung corridor that experienced the impact of Jakarta-Bandung conurbation process. This study aims to analyze the level of regional development, to analyze land cover change that occurred, and to predict Purwakarta Regency land use/land cover in 2030. Regional development analysis is done by using the Scalogram method based on Potential Village data of year 2003 and 2014. Land cover change analysis is done through spatial analysis by overlaying land cover Landsat Satellite Image of year 2000 and 2015. Land use/land cover prediction in 2030 is conducted through spatial modelling of Cellular Automata Markov method. Purwakarta Regency experienced an increase in regional development within the period of 11 years (2003 to 2014), which is marked by a decrease in the percentage of the number of villages that are in hierarchy III and increase in the percentage of the number of villages that are in hierarchy II and I. In general, within 15 years (2000 to 2015) Purwakarta Regency has increasing number of built-up area and mixed gardens, meanwhile dry land, forest, paddy field, and water bodies tend to decrease. The results of CA Markov analysis show that the built-up area is predicted to continue to increase from 2000 to 2030, meanwhile paddy fields and water bodies will continue to decrease.</p>

scholarly journals SPATIO-TEMPORAL ANALYSIS AND MODELING OF URBAN GROWTH OF BIRATNAGAR CITY, NEPAL

2019 ◽  
Vol IV-5/W2 ◽  
pp. 97-102
Author(s):  
S. Shrestha
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Growth ◽  
Urban Expansion ◽  
Urban Change ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Spatial Metrics ◽  
Land Cover Map ◽  
Spatio Temporal

Abstract. Increasing land use land cover changes, especially urban growth has put a negative impact on biodiversity and ecological process. As a consequences, they are creating a major impact on the global climate change. There is a recent concern on the necessity of exploring the cause of urban growth with its prediction in future and consequences caused by this for sustainable development. This can be achieved by using multitemporal remote sensing imagery analysis, spatial metrics, and modeling. In this study, spatio-temporal urban change analysis and modeling were performed for Biratnagar City and its surrounding area in Nepal. Land use land cover map of 2004, 2010, and 2016 were prepared using Landsat TM imagery using supervised classification based on support vector machine classifier. Urban change dynamics, in term of quantity, and pattern was measured and analyzed using selected spatial metrics and using Shannon’s entropy index. The result showed that there is increasing trend of urban sprawl and showed infill characteristics of urban expansion. Projected land use land cover map of 2020 was modeled using cellular automata-based approach. The predictive power of the model was validated using kappa statistics. Spatial distribution of urban expansion in projected land use land cover map showed that there is increasing threat of urban expansion on agricultural land.

scholarly journals Influence of Land Use and Land Cover Change on Land surface temperature

2021 ◽  
Vol 283 ◽  
pp. 01038
Author(s):  
Jing Sun ◽  
Jing He
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Expansion ◽  
Rapid Urbanization ◽  
Lulc Changes ◽  
The Mean ◽  
The Relationship

The rapid urbanization process has recently led to significant land use and land cover (LULC) changes, thereby affecting the climate and the environment. The purpose of this study is to analyze the LULC changes in Hefei City, Anhui Province, and their relationship with land surface temperature (LST). To achieve this goal, multitemporal Landsat data were used to monitor the LULC and LST between 2005 and 2015. The study also used correlation analysis to analyze the relationship between LST, LULC, and other spectral indices (NDVI, NDBI, and NDWI). The results show that the built-up land has expanded significantly, transforming from 488.26 km2 in 2005 to 575.64 km2 in 2015. It further shows that the mean LST in Hefei city has increased from 284.0 K in 2005 to 285.86 K in 2015. The results also indicate that there is a positive correlation between LST and NDVI and NDBI, while there is a negative correlation between LST and NDWI. This means that urban expansion and reduced water bodies will lead to an increase in LST.

scholarly journals Spatio-Temporal Evaluation of Urban Growth of Zuru Metropolis, Nigeria

2021 ◽  
Vol 5 (2) ◽  
pp. 456-467
Author(s):  
Y.A. Maleeks ◽  
A.O. Aliyu ◽  
A. Bala ◽  
A.U. Isiaka ◽  
K.Z. Atta
Keyword(s):  
Population Growth ◽  
Urban Area ◽  
Urban Growth ◽  
Water Body ◽  
Anthropogenic Activities ◽  
Landsat Imagery ◽  
Urban Expansion ◽  
Population Increase ◽  
Urban Dynamics ◽  
Spatio Temporal

The pattern of development in a city is mostly governed by urban dynamics, with population increase being the primary driving force. Built-up cover is the most important predictor of urban expansion. Zuru metropolis in Kebbi State has witnessed remarkable developmental activities caused by human influences such as buildings, road constructions, and population growth for over decades. Urban growth was ascertained for a period of 30 years through the analysis of Landsat imagery of 1988, 1998, 2008 and 2018. The datasets were classified into five (5) land covers, namely, built-up, water body, rocky surface, vegetation, and others. Quantitative assessment of the urban growth was ascertained by computing post-classification LC dynamics and Land Consumption Rate/Land Absorption Coefficient (LCR/LAC). The results showed that the built-up cover (urban area) conspicuously increased with area of 693.35 ha, 728.74 ha, 5210.5 ha and 6845.75 ha respectively for the period of study (1988 – 2018). The increment in built-up area was indicative of population growth from 1988 to 2018. The study revealed that between 1988 to 2018 showed that built-up increased by 11.78%, while rocky surface and water body have shrunk by 16.44% and 0.02% respectively, which can be attributed to anthropogenic activities in which rocky surface and waterbody have been transformed into built-up cover. It further revealed that the urban area experienced crowdedness in the years 2008 and 2018 respectively due to high LCR values of 2.71% compared to LCR values of 0.0714% and 0.0558% in 1988 and 1998. Land transformation into urban area and spread of the population to the outskirts of the study area was prominent between 1998 and 2008 due to high LAC value of 0.0998. The study concluded that there was transformation of rocky surface and waterbody into urban area, which was caused by population growth, human and agricultural activities in Zuru metropolis.

scholarly journals Exploring the Dynamic Spatio-Temporal Correlations between PM2.5 Emissions from Different Sources and Urban Expansion in Beijing-Tianjin-Hebei Region

2021 ◽  
Vol 18 (2) ◽  
pp. 608
Author(s):  
Shen Zhao ◽  
Yong Xu
Keyword(s):  
Urban Areas ◽  
Energy Production ◽  
Urban Expansion ◽  
Transport Sector ◽  
Emission Data ◽  
Rapid Urbanization ◽  
Local Conditions ◽  
Spatio Temporal ◽  
Different Sources ◽  
Pm2.5 Emissions

Due to rapid urbanization globally more people live in urban areas and, simultaneously, more people are exposed to the threat of environmental pollution. Taking PM2.5 emission data as the intermediate link to explore the correlation between corresponding sectors behind various PM2.5 emission sources and urban expansion in the process of urbanization, and formulating effective policies, have become major issues. In this paper, based on long temporal coverage and high-quality nighttime light data seen from the top of the atmosphere and recently compiled PM2.5 emissions data from different sources (transportation, residential and commercial, industry, energy production, deforestation and wildfire, and agriculture), we built an advanced Bayesian spatio-temporal autoregressive model and a local regression model to quantitatively analyze the correlation between PM2.5 emissions from different sources and urban expansion in the Beijing-Tianjin-Hebei region. Our results suggest that the overall urban expansion in the study area maintained gradual growth from 1995 to 2014, with the fastest growth rate during 2005 to 2010; the urban expansion maintained a significant positive correlation with PM2.5 emissions from transportation, energy production, and industry; different anti-haze policies should be designated according to respective local conditions in Beijing, Tianjin, and Hebei provinces; and during the period of rapid urban expansion (2005–2010), the spatial correlations between PM2.5 emissions from different sources and urban expansion also changed, with the biggest change coming from the PM2.5 emissions from the transport sector.

scholarly journals Mapping and classification of crops using high resolution satellite image

2018 ◽  
Vol 10 (3) ◽  
pp. 818-825
Author(s):  
R Jagadeeswaran ◽  
A Poornima ◽  
R Kumaraperumal
Keyword(s):  
Land Cover ◽  
Tamil Nadu ◽  
Satellite Image ◽  
Unsupervised Classification ◽  
Land Use Land Cover ◽  
Multiple Cropping ◽  
Error Matrix ◽  
Hybrid Classification ◽  
Crop Area

In the present study an attempt was made to perform land use land cover classification at Level-III in order to discriminate and map individual crops. IRS Resources at 2 LISS IV sensor imagery (5.0 m spatial resolution) of September 2014 was utilized for the study. A hybrid classification approach of unsupervised classification followed by supervised classification was adopted to identify and map the crop area in Kodumudi block, Erode district of Tamil Nadu. Signature evaluation was carried out to study the class separability and through cross tabulation and the accuracy was assessed by error matrix. The signature separability analysis to classify various land cover classes indicated that the class viz., waterbody, settlement, sandy area and fallow land were better and for vegetation sub-classes viz., individual crops were poor, which means classification of individual crops was a challenge. The overall accuracy with three different algorithms varied from 56 to 65 per cent and this low accuracy was due to the problem in discriminating the tonal variation and spectral pattern of individual crops in the study area. Thus, classification of vegetation categories into individual crops using LISS IV data resulted in moderate classification accuracy in areas with multiple cropping.

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