{"title":"Land-cover changes and deforestation drivers in the forest landscape of Banmauk township in the Sagaing Region of upper Myanmar","authors":"Tin Hnaung Aye, S. Shibata","doi":"10.1080/13416979.2023.2185185","DOIUrl":null,"url":null,"abstract":"ABSTRACT This study focused on the extent of land-cover changes and prediction of probable factors in deforestation based on changes observed from 2000 to 2021 in the forest landscape of Banmauk Township in Myanmar’s Sagaing Region. Landsat 7 ETM+ and Landsat 8 OLI satellite imagery were used to identify seven land-cover classes via supervised random tree classification, and binary logistic regression analysis was used to predict the potential for biophysical and locational factors to affect deforestation. A stratified random sampling method was used to assess the accuracy of the classified maps and to estimate the areas. The study revealed that dense forest coverage decreased from 45.65% in 2000 to 29.01% in 2021, while open forest areas increased from 49.33% to 54.51%. Mining areas exhibited a considerable increase from 0.37% to 5.35%, while settlement and barren/scrub land areas increased from 0.16% to 0.51% and 1.71% to 7.70%, respectively. Agricultural areas slightly increased from 2.11% to 2.33%, while water areas remained almost the same at around 0.60%. Post-classification change detection analysis showed that deforestation occurred mainly through converting forest land to mining and barren/scrub land. The study indicated that lower altitudes and road accessibility are significantly associated with the potential for deforestation.","PeriodicalId":15839,"journal":{"name":"Journal of Forest Research","volume":"28 1","pages":"231 - 239"},"PeriodicalIF":1.3000,"publicationDate":"2023-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Forest Research","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/13416979.2023.2185185","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT This study focused on the extent of land-cover changes and prediction of probable factors in deforestation based on changes observed from 2000 to 2021 in the forest landscape of Banmauk Township in Myanmar’s Sagaing Region. Landsat 7 ETM+ and Landsat 8 OLI satellite imagery were used to identify seven land-cover classes via supervised random tree classification, and binary logistic regression analysis was used to predict the potential for biophysical and locational factors to affect deforestation. A stratified random sampling method was used to assess the accuracy of the classified maps and to estimate the areas. The study revealed that dense forest coverage decreased from 45.65% in 2000 to 29.01% in 2021, while open forest areas increased from 49.33% to 54.51%. Mining areas exhibited a considerable increase from 0.37% to 5.35%, while settlement and barren/scrub land areas increased from 0.16% to 0.51% and 1.71% to 7.70%, respectively. Agricultural areas slightly increased from 2.11% to 2.33%, while water areas remained almost the same at around 0.60%. Post-classification change detection analysis showed that deforestation occurred mainly through converting forest land to mining and barren/scrub land. The study indicated that lower altitudes and road accessibility are significantly associated with the potential for deforestation.
期刊介绍:
Journal of Forest Research publishes original articles, reviews, and short communications. It covers all aspects of forest research, both basic and applied, with the aim of encouraging international communication between scientists in different fields who share a common interest in forest science.