scholarly journals Application of remote sensing and GIS for assessing the urbanization trend in Can Tho city

2018 ◽  
Vol 2 (1) ◽  
pp. 52-57
Author(s):  
Le Van Trung ◽  
Nguyen Nguyen Vu
Keyword(s):  
Remote Sensing ◽  
Urban Expansion ◽  
Impervious Surface ◽  
Remote Sensing And Gis ◽  
Growth Patterns ◽  
Landsat Images ◽  
Average Growth Rate ◽  
Average Growth ◽  
Multi Temporal ◽  
Can Tho City

This paper presents the method of integrating remote sensing and GIS to analyze the urbanization trend through the impervious surface change in Can Tho City. The impervious surface maps were created from the multi-temporal LandSat images in 1997, 2005, 2010, 2016 and were overlaid in GIS to extract the urban expansion from 1997 to 2016. The results showed the urban area of Can Tho increased from 1506,638 ha in 1997 to 5611,114 ha in 2016, average growth rate of 14,3%/year. The integration of remote sensing and GIS was found to be effective in monitoring and analyzing urban growth patterns.

Quantifying Urban Sprawl With Spatial Autocorrelation Techniques Using Multi-Temporal Satellite Data

2019 ◽  
pp. 1624-1644
Author(s):  
Gabriele Nolè ◽  
Rosa Lasaponara ◽  
Antonio Lanorte ◽  
Beniamino Murgante
Keyword(s):  
Remote Sensing ◽  
Spatial Autocorrelation ◽  
Urban Areas ◽  
Urban Expansion ◽  
Data Sets ◽  
Temporal Data ◽  
Landsat Images ◽  
Urban Settlements ◽  
Multi Temporal ◽  
Soil Consumption

This study deals with the use of satellite TM multi-temporal data coupled with statistical analyses to quantitatively estimate urban expansion and soil consumption for small towns in southern Italy. The investigated area is close to Bari and was selected because highly representative for Italian urban areas. To cope with the fact that small changes have to be captured and extracted from TM multi-temporal data sets, we adopted the use of spectral indices to emphasize occurring changes, and geospatial data analysis to reveal spatial patterns. Analyses have been carried out using global and local spatial autocorrelation, applied to multi-date NASA Landsat images acquired in 1999 and 2009 and available free of charge. Moreover, in this paper each step of data processing has been carried out using free or open source software tools, such as, operating system (Linux Ubuntu), GIS software (GRASS GIS and Quantum GIS) and software for statistical analysis of data (R). This aspect is very important, since it puts no limits and allows everybody to carry out spatial analyses on remote sensing data. This approach can be very useful to assess and map land cover change and soil degradation, even for small urbanized areas, as in the case of Italy, where recently an increasing number of devastating flash floods have been recorded. These events have been mainly linked to urban expansion and soil consumption and have caused loss of human lives along with enormous damages to urban settlements, bridges, roads, agricultural activities, etc. In these cases, remote sensing can provide reliable operational low cost tools to assess, quantify and map risk areas.

Quantifying Urban Sprawl with Spatial Autocorrelation Techniques using Multi-Temporal Satellite Data

2014 ◽  
Vol 5 (2) ◽  
pp. 19-37 ◽  
Author(s):  
Gabriele Nolè ◽  
Rosa Lasaponara ◽  
Antonio Lanorte ◽  
Beniamino Murgante
Keyword(s):  
Remote Sensing ◽  
Spatial Autocorrelation ◽  
Urban Areas ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Small Towns ◽  
Temporal Data ◽  
Landsat Images ◽  
Multi Temporal ◽  
Soil Consumption

This study deals with the use of satellite TM multi-temporal data coupled with statistical analyses to quantitatively estimate urban expansion and soil consumption for small towns in southern Italy. The investigated area is close to Bari and was selected because highly representative for Italian urban areas. To cope with the fact that small changes have to be captured and extracted from TM multi-temporal data sets, we adopted the use of spectral indices to emphasize occurring changes, and geospatial data analysis to reveal spatial patterns. Analyses have been carried out using global and local spatial autocorrelation, applied to multi-date NASA Landsat images acquired in 1999 and 2009 and available free of charge. Moreover, in this paper each step of data processing has been carried out using free or open source software tools, such as, operating system (Linux Ubuntu), GIS software (GRASS GIS and Quantum GIS) and software for statistical analysis of data (R). This aspect is very important, since it puts no limits and allows everybody to carry out spatial analyses on remote sensing data. This approach can be very useful to assess and map land cover change and soil degradation, even for small urbanized areas, as in the case of Italy, where recently an increasing number of devastating flash floods have been recorded. These events have been mainly linked to urban expansion and soil consumption and have caused loss of human lives along with enormous damages to urban settlements, bridges, roads, agricultural activities, etc. In these cases, remote sensing can provide reliable operational low cost tools to assess, quantify and map risk areas.

scholarly journals REMOTE SENSING AND GIS TECHNIQUES FOR URBAN GROWTH MONITORING OF BASARAH CITY

2011 ◽  
Vol 7 (1) ◽  
Author(s):  
Salah A. H. Saleh
Keyword(s):  
Economic Growth ◽  
Remote Sensing ◽  
Spatial Distribution ◽  
Urban Growth ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Expansion ◽  
Remote Sensing And Gis ◽  
Growth Patterns ◽  
Growth Monitoring

Basarah city has experienced a rapid urban expansion over the last decades dueto accelerated economic growth. This paper reports an investigation into the application ofthe integration of remote sensing and geographic information systems (GIS) for detectingurban built up growth for the period 1973 - 2002, and evaluate its impact on theenvironmental situation of Basarah city by analyzing the spatial distribution of urbanexpansion according to land cover types and normalized difference vegetation index(NDVI). The integration of remote sensing and GIS was found to be effective inmonitoring and analyzing urban growth patterns and in evaluating urbanization impact onsurface conditions of Baghdad area.

scholarly journals Rapid Urban Expansion and Its Implications on Geomorphology: A Remote Sensing and GIS Based Study

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
S. N. Mohapatra ◽  
Padmini Pani ◽  
Monika Sharma
Keyword(s):  
Remote Sensing ◽  
Growth Rate ◽  
Urban Growth ◽  
Anthropogenic Activities ◽  
Urban Expansion ◽  
Central India ◽  
Remote Sensing And Gis ◽  
Landsat Images ◽  
Geomorphic Features ◽  
The City

Topography, vegetation, climate, water table, and even the anthropogenic activities all are affected by urban growth through diverse mechanisms. The present study focuses on the implications of urban expansion on geomorphology in the historical city of Gwalior in central India. The expansion of urban area has been quantified by deriving data for four decades (1972–2013) from the Landsat images. The results show that the urban built-up area has increased by 08.48 sq. km during the first eighteen years (1972–1990) which has increased to 16.28 sq. km during the next sixteen years (1990–2006). The built-up area has gone up to 23.19 sq. km in the next seven years (2006–2013). Overall during the last 40 years the growth of the urban built-up is nearly three times of the built-up areas in 1972. The average decadal growth rate of population is 27.28 percent while that of built-up land is 36.29 percent. The construction activities have affected important geomorphic features such pediplain, buried pediplain, residual hills, and denudational hills. It was concluded that, instead of shortsighted urban development, proper measures should be taken in accordance with scientific planning for the urban expansion of the city in the future.

scholarly journals Characterizing urban expansion of Korla City and its spatial-temporal patterns using remote sensing and GIS methods

2017 ◽  
Vol 9 (3) ◽  
pp. 458-470 ◽  
Author(s):  
Bumairiyemu Maimaiti ◽  
Jianli Ding ◽  
Zibibula Simayi ◽  
Alimujiang Kasimu
Keyword(s):  
Remote Sensing ◽  
Urban Expansion ◽  
Temporal Patterns ◽  
Remote Sensing And Gis ◽  
Gis Methods ◽  
Korla City

scholarly journals Indication of Urban expansion of Gujranwala city (Pakistan) by Remote sensing and GIS

2019 ◽  
Vol 3 (1) ◽  
pp. 13-23
Author(s):  
Asad Aziz ◽  
Muhammad Anwar ◽  
Mehwish Rani ◽  
Shawaz Ahmad ◽  
Saqib Zaheer
Keyword(s):  
Remote Sensing ◽  
Urban Expansion ◽  
Remote Sensing And Gis

Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

2013 ◽  
pp. 228-244
Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Landscape Metrics ◽  
Landsat Images ◽  
Aerial Photos ◽  
Multi Temporal ◽  
Urban Rural ◽  
Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

Quantifying Urban Expansion Using Landsat Images and Landscape Metrics: A Case Study of the Halton Region, Ontario

GEOMATICA ◽  
2020 ◽  
Author(s):  
Liyuan Qing ◽  
Hasti A. Petrosian ◽  
Sarah N. Fatholahi ◽  
Michael A. Chapman ◽  
Jonathan Li
Keyword(s):  
Landscape Metrics ◽  
Urban Areas ◽  
Census Data ◽  
Urban Expansion ◽  
Landsat Images ◽  
Factors Affecting ◽  
Supervised Learning Algorithms ◽  
Dramatic Rise ◽  
Multi Temporal ◽  
Gis Software

Urbanization is considered as one of the main factors affecting global change. The Halton Region as part of the Great Toronto Area (GTA), is regarded as one of the fastest growing regions in Canada, generating 20% of national GDP. It is also one of the most desirable places for living and thriving business. This research attempts to assess the urban expansion in the Halton Region, Ontario, Canada from 1989 to 2019 using satellite images, analysis approaches and landscape metrics. Multi-temporal Landsat images, and the supervised learning algorithms in GIS software were used to explore the dynamic changes, and to classify the urban and non-urban areas. The temporal urban expansion in the Halton Region experienced a dramatic rise, and mainly occurred from the centre of the area. The analysis of landscape metrics based on different methods, including Land Use in Central Indiana (LUCI) model, Vegetation-Impervious Surface-soil (V-I-S) model, and the census data of Canada was carried out to understand the transition mode of the urbanization in the Halton Region. Also, the population growth in the centre of the Halton Region was considered as one of driven forces affecting urban expansion. The results showed that most of the landscape metrics rose between 1989 and 2019, indicating leapfrog pattern of urbanization occurred over the entire period. The contribution of this research is to evaluate the urbanization in the Halton Region, and give the city managers a clear mind to make appropriate decisions in further urban planning.

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