Urban agglomeration impact analysis using remote sensing and GIS techniques in Malegaon city, India

Poyil, Rohith P.; Misra, Anil Kumar

doi:10.1016/j.ijsbe.2015.02.006

Cited by 26 publications

(11 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Primary data were collected through household surveys, FGDs, in-depth interviews and site observation, while secondary data was obtained from Jimma city Municipality, and CSA of Ethiopia. The Landsat TM 1997 with 30 m × 30 m resolution and Aerial Photography (2007 and 2017 with 15 m × 15 m resolution) were used to detect the LULCC following (Poyil and Misra 2015;Shaw and Das 2018). Characteristics of the satellite data used in this study are summarized in Table 2.…”

Section: Data Source and Instrumentsmentioning

confidence: 99%

Exploiting temporal-spatial patterns of informal settlements using GIS and remote sensing technique: a case study of Jimma city, Southwestern Ethiopia

2019

View full text Add to dashboard Cite

Background: Temporal change detection of informal settlement was conducted using geographic information system and remote sensing in order to evaluate the land use land cover change (LULCC) in Jimma city, southwestern Ethiopia. We analyzed the LULCC since 1997 using Landsat imagery of 1997, and aerial photography of 2007 and 2017. Qualitative and quantitative data was also collected from city residents by using structured questionnaires focusing on peoples' perceptions to understand the pattern of informal settlements in the study area. Maximum likelihood supervised classification methods was employed to create the signature class of the five land cover classes: built up, vegetation, barren land, open land and agricultural land. Results:The results indicated that the informal settlement has been increased in the peripheries from 29% in 1997, 37% in 2007 and 41% in 2017. This study focuses on the continued transformation of various land uses into informal settlements, causing encroachment on agricultural and open land particularly in the city periphery. The unprecedented population growth and unplanned development activities in urban areas results in urban agglomeration, which increase the price of land market for construction. This implies that rapid population growth, shortage of formal housing and unaffordable cost of formal housing for urban dwellers contributed to informal settlements. Conclusions:Increasing urbanization and rapid population growth are often associated with the development of urban informal settlements. Informal settlements and urban informality are the common problems particularly in the periphery of Jimma city. These results can be used as a basis for informal settlement assessment in other cities in the country and beyond. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

show abstract

Section: Data Source and Instrumentsmentioning

confidence: 99%

Exploiting temporal-spatial patterns of informal settlements using GIS and remote sensing technique: a case study of Jimma city, Southwestern Ethiopia

2019

View full text Add to dashboard Cite

show abstract

“…As a result of rapid population growth and transition from rural to economical and industrial areas of development, urban expansion is widespread, specially, in the metropolitan areas of developing countries (Shi et al, 2009;Abubakr and Pradhan, 2016). This can be taken as a positive initiative (Fan, 1999), since people can afford more opportunities and resources to improve the standard of living in cities than they can in a village (Poyil and Misra, 2015). Urban expansion is, however, often associated with unplanned, uncoordinated and uncontrolled change (Noor and Rosni, 2013) and the intensified pressure on resources and natural environment influence the city space negatively (Dadras et al, 2015), particularly when the cities expand into the adjoining rural areas (Hegazy and Kaloop, 2015).…”

Section: Introductionmentioning

confidence: 99%

Identification and assessment of the driving forces for the use of urban green parks and their accessibility in Colombo, Sri Lanka, through analytical hierarchical processing

Pussella

Lin

2019

Geospat Health

View full text Add to dashboard Cite

Urban green parks perform a remarkable role for the physical, social and psychological wellbeing of the urban public by providing space for relaxation and recreation, directly influencing public health through mitigation of the urban heat impact, noise reduction and moderation of air and water pollution. An indicator-based approach on analytical hierarchical processing was used to identify and assess the driving forces for the utilization of urban green parks and their accessibility. Eight indicators: location, topography and geography, facility and services, safety and security, social and culture, ecology, demography, and weather and climate (further divided into 50 factors) were used in the study. Data were collected through a questionnaire survey in which 887 regular park users participated. A standardized study design was implemented to study and assess four urban green parks in the Colombo metropolitan district, Sri Lanka. The study identified park facilities and services as well as safety and security measures maintained by the park as the key factors of appeal, while location, ecology, topography and geography, including weather and climate, had a lower relative influence when selecting a park for recreation. Social, cultural and demographic factors appeared to be of the least interest. The study recommends park managers to assess their parks using this model to enhance the characteristics found to be the most important. It further suggests developing models also for other park types by considering which factors would have the highest relative influence in providing a better service for the regular park user.

show abstract

“…T HE problem of estimation of urban sprawl has been approached by classifying built-up pixels from satellite imagery with the help of various classification methodologies [1], [2], [3], [4]. In supervised classification algorithms using multi-spectral satellite images [5], information stored in different bands at pixel level is utilized as "features" to classify the pixel as "builtup" or "non built-up".…”

Section: Imentioning

confidence: 99%

Development of new Index based supervised algorithm for separation of Built-Up and River Sand pixels from Landsat7 imagery : Comparison of performance with SVM

Mukherjee¹,

Ramachandran²

2020

Preprint

View full text Add to dashboard Cite

While classifying "built-up" pixels from satellite imagery, both machine learning & index based algorithms often misclassify "river sand" pixels as "built-up" ones due to the similarity in their spectral profiles. With the help of the spectral reflectance information in BLUE & GREEN bands of Landsat satellite imagery, this study has introduced a new index BRSSI (Built-Up & River Sand Separation Index) that efficiently reduce the misclassification between these two classes. The classification performance of the proposed index along with the same of Support Vector Machine (SVM) classifier have been reported for 3 study sites from different geographic locations across India. The results shows that average overall accuracy, F1 score and kappa (κ) coefficient for the developed index corresponding to selected study regions are 0.9763, 0.9767 & 0.9527 respectively. Though it has been noticed that SVM performs marginally better than BRSSI, it requires tuning of the parameters for optimum classification performance compared to BRSSI which is not only easy to implement but also computationally inexpensive. Also, visual representation of the classified images for entire study sites using additional filter of BRSSI ensures significant reduction of misclassification of "river sand" pixels as "built-up" class.

show abstract

Urban agglomeration impact analysis using remote sensing and GIS techniques in Malegaon city, India

Cited by 26 publications

References 17 publications

Exploiting temporal-spatial patterns of informal settlements using GIS and remote sensing technique: a case study of Jimma city, Southwestern Ethiopia

Exploiting temporal-spatial patterns of informal settlements using GIS and remote sensing technique: a case study of Jimma city, Southwestern Ethiopia

Identification and assessment of the driving forces for the use of urban green parks and their accessibility in Colombo, Sri Lanka, through analytical hierarchical processing

Development of new Index based supervised algorithm for separation of Built-Up and River Sand pixels from Landsat7 imagery : Comparison of performance with SVM

Contact Info

Product

Resources

About