Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/112818
DC Field | Value | Language |
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dc.contributor | Department of Land Surveying and Geo-Informatics | - |
dc.creator | Raza, D | - |
dc.creator | Shu, H | - |
dc.creator | Ehsan, M | - |
dc.creator | Fan, H | - |
dc.creator | Abdelrahman, K | - |
dc.creator | Aslam, H | - |
dc.creator | Quddoos, A | - |
dc.creator | Aslam, RW | - |
dc.creator | Nazeer, M | - |
dc.creator | Fnais, MS | - |
dc.creator | Sardar, A | - |
dc.date.accessioned | 2025-05-09T00:55:08Z | - |
dc.date.available | 2025-05-09T00:55:08Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/112818 | - |
dc.language.iso | en | en_US |
dc.publisher | Cogent OA | en_US |
dc.rights | © 2025 the Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group | en_US |
dc.rights | this is an open Access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/), which permits unre-stricted use, distribution, and reproduction in any medium, provided the original work is properly cited. the terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. | en_US |
dc.rights | The following publication Raza, D., Shu, H., Ehsan, M., Fan, H., Abdelrahman, K., Aslam, H., … Sardar, A. (2025). Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability. Cogent Food & Agriculture, 11(1) is available at https://doi.org/10.1080/23311932.2024.2448597. | en_US |
dc.subject | 2SFCa | en_US |
dc.subject | Agriculture | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Sustainable development goal | en_US |
dc.subject | Wheat demand | en_US |
dc.title | Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 11 | - |
dc.identifier.issue | 1 | - |
dc.identifier.doi | 10.1080/23311932.2024.2448597 | - |
dcterms.abstract | Accurate insights into the spatial distribution of cultivated areas, land use for effective agricultural management, and improvement of food security planning, especially in developing countries. Therefore, this study examined the impact of land changes and population growth on agricultural land and wheat crop productivity. First, by incorporating more than three decades of satellite data (1990–2022) and different Landsat missions with machine learning algorithms, high-confidence classes were defined for different land features, including cropland. Second, the wheat grown area was identified using the cropland extraction based wheat acreage assessment method (CLE-WAAM). Third, population dynamics were examined by applying an exponential growth model to forecast population growth and predict food demand. These findings necessitate the integrated methodological development for wheat demand and supply mechanisms using the two-step floating catchment area (2SFCA) approach for a more thorough analysis of socioeconomic developments. The results revealed that the cropland area was transformed into non-cropland, with a percentage of 8.01. A 79% rise in the population occured between 1990 and 2022, with a projected increase of 112% by 2030. Specifically, the wheat cultivation area decreased by 28%, despite stagnant parameters observed since 2000. The proposed method contributes efficiently to the United Nations’ sustainable development goal (02: Zero Hunger) using satellite, geospatial, and statistical data integration. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Cogent food & agriculture, 2025, v. 11, no. 1, 2448597 | - |
dcterms.isPartOf | Cogent food & agriculture | - |
dcterms.issued | 2025 | - |
dc.identifier.scopus | 2-s2.0-85214942753 | - |
dc.identifier.eissn | 2331-1932 | - |
dc.identifier.artn | 2448597 | - |
dc.description.validate | 202505 bcch | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | The Major program of the national natural Science Foundation of China (no. 42394065); the Special Fund of the State laboratory of information engineering in Surveying, Mapping and remote Sensing, Wuhan University; the researchers Supporting project number (RSP2025R351), King Saud University, Riyadh, Saudi Arabia | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Raza_Evaluation_Agriculture_Land.pdf | 32.63 MB | Adobe PDF | View/Open |
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