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Land Use/Land Cover Change Detection and NDVI Estimation in Pakistan’s Southern Punjab Province
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 dif...
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Published in: | Sustainability 2023-02, Vol.15 (4), p.3572 |
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description | 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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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.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su15043572</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agricultural land ; Agricultural research ; Agriculture ; Barren lands ; Change detection ; Classification ; Climate change ; Clustering ; Earth resources technology satellites ; Ecosystems ; Floods ; Forests ; Geographic information systems ; Geospatial data ; Land cover ; Land management ; Land use ; Land use management ; Land use planning ; Landsat ; Landsat satellites ; Mitigation ; Natural resources ; Normalized difference vegetative index ; Pakistan ; Planning ; Remote sensing ; Rivers ; Satellite imagery ; Sensors ; Spatial discrimination ; Spatial resolution ; Trends ; Vegetation</subject><ispartof>Sustainability, 2023-02, Vol.15 (4), p.3572</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c368t-fe01937ff86a9d2e11fa84b180796dbc94bb04bde37b2c7d97f4fa723f62b60d3</citedby><cites>FETCH-LOGICAL-c368t-fe01937ff86a9d2e11fa84b180796dbc94bb04bde37b2c7d97f4fa723f62b60d3</cites><orcidid>0000-0002-7833-9253 ; 0000-0001-9035-3990 ; 0000-0002-5506-9502 ; 0000-0002-5617-9375 ; 0000-0002-3771-9380 ; 0000-0001-9207-5779 ; 0000-0001-9421-0807 ; 0000-0002-6224-9050</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2779688569/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2779688569?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25752,27923,27924,37011,38515,43894,44589,74283,74997</link.rule.ids></links><search><creatorcontrib>Hu, Yongguang</creatorcontrib><creatorcontrib>Raza, Ali</creatorcontrib><creatorcontrib>Syed, Neyha Rubab</creatorcontrib><creatorcontrib>Acharki, Siham</creatorcontrib><creatorcontrib>Ray, Ram L</creatorcontrib><creatorcontrib>Hussain, Sajjad</creatorcontrib><creatorcontrib>Dehghanisanij, Hossein</creatorcontrib><creatorcontrib>Zubair, Muhammad</creatorcontrib><creatorcontrib>Elbeltagi, Ahmed</creatorcontrib><title>Land Use/Land Cover Change Detection and NDVI Estimation in Pakistan’s Southern Punjab Province</title><title>Sustainability</title><description>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. 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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. 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subjects | Agricultural land Agricultural research Agriculture Barren lands Change detection Classification Climate change Clustering Earth resources technology satellites Ecosystems Floods Forests Geographic information systems Geospatial data Land cover Land management Land use Land use management Land use planning Landsat Landsat satellites Mitigation Natural resources Normalized difference vegetative index Pakistan Planning Remote sensing Rivers Satellite imagery Sensors Spatial discrimination Spatial resolution Trends Vegetation |
title | Land Use/Land Cover Change Detection and NDVI Estimation in Pakistan’s Southern Punjab Province |
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