Spatiotemporal Analysis of Land Use / Land Cover in Swat, Pakistan Using Supervised Classification in Remote Sensing: 2000 to 2015

Arif, Hania; Talib, Bushra; Shahzad, Muhammad; Mehmood, Syed Amer; Batool, Hafsa; Naeem, Kashif; Batool, Saira; Nasir, Jawad; Shafiq, Muhammad

doi:10.46660/ijeeg.vol11.iss2.2020.450

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…The data were downloaded from the U.S. Geological Survey (USGS) website, https://earthexplorer.usgs.gov/ in the WGS84 coordinate system, and all the bands were combined using a layer stacking method in ERDAS Imagine software. Later, [14,[20][21][22] to classify the land cover area surrounding the campus. The satellite imageries were subset and classified into nine (9) types of land-cover within 5 km and 10 km offset from the boundary of UiTMCPP Permatang Pauh campus.…”

Section: Methodsmentioning

confidence: 99%

The impact of UiTM Cawangan Pulau Pinang Permatang Pauh campus on urban development in Central Seberang Perai District

Othman

Bakhari

Mahmood

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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Universiti Teknologi MARA (UiTM) is regarded as one of the largest higher education institutions (HEIs) in Malaysia. Significantly, HEIs are increasingly seen as catalysts for development, with substantial contribution not only as providers of education and research but also as an active role in developing their economic, social and cultural surroundings. Thus, it is thought the existence of HEIs particularly UiTM as key players in global development, alongside being significant contributors to local urban areas’ development. UiTM Cawangan Pulau Pinang (UiTMCPP) was first established in June 1996 at a temporary site in Permatang Pasir as the university’s eleventh campus. In August 2003, UiTMCPP relocates to a permanent campus in Jalan Permatang Pauh. The main purpose of this study is to determine the influence of the UiTMCPP Permatang Pauh campus on the local area’s urban expansion. In this study, multi-temporal satellite imageries, Landsat Thematic Mapper (TM) in three different years (1999, 2009, and 2019) was processed by Geographic Information System (GIS) and remote sensing techniques to distinguish the spatial expansion of urbanisation in Central Seberang Perai District. Further analysis on data collection using the quantitative and qualitative approach were performed to determine the actual impact of urbanisation on the communities. Results show that the percentage of developed area increased from 51.2% (1999) to 68.6% (2019) within a 5 km radius, and from 29.0% (1999) to 45.6% (2019) within a 10 km radius, according to the urban development map. Although the establishment and existence of the UiTMCPP Permatang Pauh campus can be considered one of the area’s development catalysts, several adjacent educational institutions also contribute to the growth of the region near the UiTM campus.

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Section: Methodsmentioning

confidence: 99%

The impact of UiTM Cawangan Pulau Pinang Permatang Pauh campus on urban development in Central Seberang Perai District

Othman

Bakhari

Mahmood

et al. 2022

IOP Conf. Ser.: Earth Environ. Sci.

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“…In this forest ecoregion, 21 studies were conducted [44][45][46][47][48]53,[56][57][58][59][60]67,68,70,73,88,89,91,94,95,100]. This is the forest ecoregion in which the largest number of studies were conducted.…”

Section: Western Himalayan Subalpine Conifer Forestsmentioning

confidence: 99%

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

Ahmad

Gilani

et al. 2021

Forests

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This paper synthesizes research studies on spatial forest assessment and mapping using remote sensing data and techniques in Pakistan. The synthesis states that 73 peer-reviewed research articles were published in the past 28 years (1993–2021). Out of all studies, three were conducted in Azad Jammu & Kashmir, one in Balochistan, three in Gilgit-Baltistan, twelve in Islamabad Capital Territory, thirty-one in Khyber Pakhtunkhwa, six in Punjab, ten in Sindh, and the remaining seven studies were conducted on national/regional scales. This review discusses the remote sensing classification methods, algorithms, published papers' citations, limitations, and challenges of forest mapping in Pakistan. The literature review suggested that the supervised image classification method and maximum likelihood classifier were among the most frequently used image classification and classification algorithms. The review also compared studies before and after the 18th constitutional amendment in Pakistan. Very few studies were conducted before this constitutional amendment, while a steep increase was observed afterward. The image classification accuracies of published papers were also assessed on local, regional, and national scales. The spatial forest assessment and mapping in Pakistan were evaluated only once using active remote sensing data (i.e., SAR). Advanced satellite imageries, the latest tools, and techniques need to be incorporated for forest mapping in Pakistan to facilitate forest stakeholders in managing the forests and undertaking national projects like UN’s REDD+ effectively.

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Spatiotemporal Analysis of Land Use / Land Cover in Swat, Pakistan Using Supervised Classification in Remote Sensing: 2000 to 2015

Cited by 2 publications

References 9 publications

The impact of UiTM Cawangan Pulau Pinang Permatang Pauh campus on urban development in Central Seberang Perai District

The impact of UiTM Cawangan Pulau Pinang Permatang Pauh campus on urban development in Central Seberang Perai District

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

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