{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T21:49:29Z","timestamp":1773006569631,"version":"3.50.1"},"reference-count":28,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"vor","delay-in-days":13,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Transactions in GIS"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Deforestation is a significant contributor to global greenhouse gas emissions, underscoring the need for effective forest conservation and management strategies. Developing such strategies requires a thorough understanding of the primary drivers of forest loss. However, the complexity of these factors, combined with the requisite skill set for accurate identification, poses considerable challenges for data collection. This study introduces a novel deep learning\u2010based approach, termed Deep Transformation Forest Detection (DTFD), which utilizes vision transformers equipped with a self\u2010attention mechanism. This innovative method enhances the modeling of contextual and spatial relationships in satellite imagery while facilitating efficient processing without relying on convolutions. This capability is particularly beneficial for heterogeneous and binary classification tasks. The self\u2010attention mechanism allows for the assignment of varying weights to input data, thereby improving the identification of areas at risk of deforestation adjacent to forested regions. The results achieved by DTFD demonstrate exceptional performance compared to state\u2010of\u2010the\u2010art methods across multiple datasets. Notably, the findings reveal significant changes in forest cover and environmental dynamics, with DTFD attaining superior metrics, including accuracy (95.64%), precision (95.55%),\n                    <jats:italic>F<\/jats:italic>\n                    1 score (93.74%), recall (94.83%), and Intersection over Union (IoU) (94.31%). This research contributes to the monitoring of climate change impacts, rapid urbanization, and natural disasters, with a specific emphasis on urban forests and their interactions with urban environmental changes.\n                  <\/jats:p>","DOI":"10.1111\/tgis.70150","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T15:02:19Z","timestamp":1763132539000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["<scp>DTFD<\/scp>\n                    : A Transformer Approach for High\u2010Resolution Satellite Image Forest Change Detection"],"prefix":"10.1111","volume":"29","author":[{"given":"Gaganpreet","family":"Kaur","sequence":"first","affiliation":[{"name":"Lovely Professional University  Phagwara India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6323-2683","authenticated-orcid":false,"given":"Yasir","family":"Afaq","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering SRM University\u2010AP  Amaravati India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1080\/07038992.2021.2010036"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-024-03127-2"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2021.112741"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs14194694"},{"key":"e_1_2_9_6_1","volume-title":"Global Forest Resources Assessment 2020\u2014Key Findings","author":"FAO","year":"2020"},{"key":"e_1_2_9_7_1","first-page":"1","article-title":"Change Detection on Remote Sensing Images Using Dual\u2010Branch Multilevel Intertemporal Network","volume":"61","author":"Feng Y.","year":"2023","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"issue":"1","key":"e_1_2_9_8_1","first-page":"113","article-title":"Multi\u2010Temporal Forest Cover Change Detection in the Metchie\u2010Ngoum Protection Forest Reserve, West Region of Cameroon","volume":"23","author":"Fokeng R. M.","year":"2020","journal-title":"Egyptian Journal of Remote Sensing and Space Sciences"},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs11171976"},{"key":"e_1_2_9_10_1","unstructured":"Howard A. G. M.Zhu B.Chen et\u00a0al.2017.Mobilenets: Efficient Convolutional Neural Networks for Mobile Vision ApplicationsarXiv preprint arXiv:1704.04861."},{"key":"e_1_2_9_11_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2022.3188636","article-title":"Forest\u2010CD: Forest Change Detection Network Based on VHR Images","volume":"19","author":"Jiang J.","year":"2022","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"e_1_2_9_12_1","doi-asserted-by":"publisher","DOI":"10.1111\/tgis.13133"},{"key":"e_1_2_9_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12145-022-00885-6"},{"key":"e_1_2_9_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs14246362"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-023-14331-2"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2024.114195"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrs.2019.02.001"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s40068-020-0163-z"},{"key":"e_1_2_9_19_1","doi-asserted-by":"publisher","DOI":"10.11591\/ijai.v11.i3.pp930-938"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.3390\/f11040398"},{"key":"e_1_2_9_21_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs16071269"},{"key":"e_1_2_9_22_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs14040816"},{"key":"e_1_2_9_23_1","doi-asserted-by":"publisher","DOI":"10.3390\/su141912321"},{"key":"e_1_2_9_24_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11760-024-03140-1"},{"key":"e_1_2_9_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10661-023-11360-0"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.3390\/su12093925"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2019.2918840"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2021.10.015"},{"key":"e_1_2_9_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICIVC.2018.8492747"}],"container-title":["Transactions in GIS"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/tgis.70150","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/tgis.70150","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/tgis.70150","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T19:35:13Z","timestamp":1772998513000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/tgis.70150"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":28,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["10.1111\/tgis.70150"],"URL":"https:\/\/doi.org\/10.1111\/tgis.70150","archive":["Portico"],"relation":{},"ISSN":["1361-1682","1467-9671"],"issn-type":[{"value":"1361-1682","type":"print"},{"value":"1467-9671","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11]]},"assertion":[{"value":"2024-08-23","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-30","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-11-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70150"}}