Remotely sensed image interpretation for assessment of land use land cover changes and settlement impact on allocated irrigation water in Multan, Pakistan

Naeem, Maira; Farid, Hafiz Umar; Madni, Muhammad Arbaz; Ahsen, Rameez; Khan, Zahid Mehmood; Dilshad, Aqsa; Shahzad, Huzaifa

doi:10.1007/s10661-021-09732-5

Cited by 11 publications

(8 citation statements)

References 59 publications

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“…Apart from this, population density, demand for forest resources, land usage, and distance from human settlements are other major factors of deforestation [30,31,49]. Being a country of the Global South, Pakistan's population growth and the expansion of settlements in mountainous forest areas have resulted in unparalleled rates of vegetation degradation [40,[55][56][57]. Moreover, the increasing human population has led to causeless deforestation and is a significant driver of land use change in the investigated area and worldwide [4,5,8,21,22,37,52].…”

Section: Introductionmentioning

confidence: 99%

Environmental Risk Assessment in the Hindu Kush Himalayan Mountains of Northern Pakistan: Palas Valley, Kohistan

et al. 2022

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Forest cover in the Hindu Kush Himalayan (HKH) mountains of northern Pakistan has changed dramatically due to community dynamics such as population growth, household dynamics, and intensive economic activity for people’s livelihoods. Demographic development is one of the major factors influencing forest cover change in a previously sparsely populated environment. An abrupt upsurge in population exerts adverse effects on the local natural resources, specifically forests. The present research shows an increase in population from 1980 to 2017, the development of human settlements, and a long-term decline in forest cover. This study was conducted in the Palas valley in the HKH mountains using GIS and remote sensing (RS) technology. Analysis of the changes between 1980, 2000, and 2017 was done using ArcGIS and the maximum likelihood algorithm for supervised classification of Landsat MSS TM ETM+ and Sentinel 2A satellite images. We used Euclidean distances and buffer analysis techniques to identify that most changes occurred within 1 to 3 km of the settlement’s proximity in each period. We also found changes in forest cover to be much greater near settlements than elsewhere in the study area. According to the findings of the study, population explosion and other socio-economic factors have imposed excessive pressure on vegetation cover, resulting in the loss of 17,076 ha of forests in the remote Palas valley.

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Section: Introductionmentioning

confidence: 99%

Environmental Risk Assessment in the Hindu Kush Himalayan Mountains of Northern Pakistan: Palas Valley, Kohistan

et al. 2022

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“…However, several articles have described the use of supervised classification to detect land cover changes, including in Tirupati, India [95]; Egypt's western Nile delta [56]; and South America [78]. Recently, Naeem et al [67] and Hussain et al [70] successfully identified LULC changes and NDVI estimation in Southern Punjab using the districts of Multan, Lodhran, and Vehari. Our study used 16 districts (Figure 1) of Southern Punjab to examine more accurate LULC changes and vegetation.…”

Section: Discussionmentioning

confidence: 99%

“…The classification accuracy of satellite images can be assessed by calculating overall accuracy and Kappa Coefficient (K). The overall accuracy can be determined by estimating user and producer accuracy [67,70]. User accuracy is used to quantify the probability that a classified pixel matches the land cover class of its actual geographical position.…”

Section: Accuracy Assessmentmentioning

confidence: 99%

“…Hussain [66] determined LULC changes in Lodhran, Multan, and Vehari districts using Landsat satellite images. Naeem et al [67] examined LULC detection in the Multan district from 1990 to 2020. The studies of Hussain et al [68] and Hussain et al [30] evaluated LULC patterns in Lodhran and Multan districts, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…Hussain et al [70] recently determined LULC changes in two districts (Multan and Vehari) of South Punjab. Additionally, several researchers conducted an accuracy assessment and used the Kappa coefficient to analyze the findings produced from the satellite images [67,70].…”

Section: Introductionmentioning

confidence: 99%

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Land Use/Land Cover Change Detection and NDVI Estimation in Pakistan’s Southern Punjab Province

Raza

Syed

et al. 2023

Sustainability

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Land use/land cover (LULC) changes are among the most significant human-caused global variations affecting the natural environment and ecosystems. Pakistan’s LULC patterns have undergone huge changes since the 1900s, with no clear mitigation plan. This paper aims to determine LULC and normalized difference vegetation index (NDVI) changes as well as their causes in Pakistan’s Southern Punjab province over four different periods (2000, 2007, 2014, and 2021). Landsat-based images of 30 m × 30 m spatial resolution were used to detect LULC changes, while NDVI dynamics were calculated using Modis Product MOD13Q1 (Tiles: h24 v5, h24 v6) at a resolution of 250 m. The iterative self-organizing (ISO) cluster method (object meta-clustering using the minimal distance center approach) was used to quantify the LULC changes in this research because of its straightforward approach that requires minimal human intervention. The accuracy assessment and the Kappa coefficient were calculated to assess the efficacy of results derived from LULC changes. Our findings revealed considerable changes in settlements, forests, and barren land in Southern Punjab. Compared to 2000, while forest cover had reduced by 31.03%, settlement had increased by 14.52% in 2021. Similarly, forest land had rapidly been converted into barren land. For example, barren land had increased by 12.87% in 2021 compared to 2000. The analysis showed that forests were reduced by 31.03%, while settlements and barren land increased by 14.52% and 12.87%, respectively, over the twenty year period in Southern Punjab. The forest area had decreased to 4.36% by 2021. It shows that 31.03% of forest land had been converted to urban land, barren ground, and farmland. Land that was formerly utilized for vegetation had been converted into urban land due to the expansion of infrastructure and the commercial sector in Southern Punjab. Consequently, proper monitoring of LULC changes is required. Furthermore, relevant agencies, governments, and policymakers must focus on land management development. Finally, the current study provides an overall scenario of how LULC trends are evolving over the study region, which aids in land use planning and management.

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Water Resources and Irrigation Management Using GIS and Remote Sensing Techniques: Case of Multan District (Pakistan)

Raza,

Khaliq,

et al. 2023

Springer Hydrogeology

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Remotely sensed image interpretation for assessment of land use land cover changes and settlement impact on allocated irrigation water in Multan, Pakistan

Cited by 11 publications

References 59 publications

Environmental Risk Assessment in the Hindu Kush Himalayan Mountains of Northern Pakistan: Palas Valley, Kohistan

Environmental Risk Assessment in the Hindu Kush Himalayan Mountains of Northern Pakistan: Palas Valley, Kohistan

Land Use/Land Cover Change Detection and NDVI Estimation in Pakistan’s Southern Punjab Province

Water Resources and Irrigation Management Using GIS and Remote Sensing Techniques: Case of Multan District (Pakistan)

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