F. A. Dangbo, O. Gardi, K. Adjonou, A. K. D. Hlovor, J. Blaser, K. Kokou
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The estimated overall accuracy of the forest cover change map is 88.7%. In the study area, the forest area was estimated at 246’915 ha in 1991, 232’741 ha in 2003 and 230’390 ha in 2018. The gross forest loss has increased from 182.5 ha/year in the first period 1991-2003 to 187.47 ha/year in the second period 2003-2018. The corresponding net annual forest loss (incl. regeneration) rates are 0.5% in the first period and 0.1% in the second period. The decrease of the net annual forest loss rate in the second period is attributed to an increase in forest regeneration. This study can be considered as a reproducible approach to map forest-cover change and can support policy approaches towards reducing emissions from deforestation and degradation (REDD+). \n \n Key words: Forest loss, forest gain, multi-date, Landsat, random forest, Togo.","PeriodicalId":267383,"journal":{"name":"Journal of Horticulture and Forestry","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An analytical assessment of forest cover changes over the last 30 Years in the semi-deciduous forest zone of Togo\",\"authors\":\"F. A. Dangbo, O. Gardi, K. Adjonou, A. K. D. Hlovor, J. Blaser, K. Kokou\",\"doi\":\"10.5897/JHF2020.0631\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Understanding dynamics of forest cover is important to monitor change in forest area. 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The gross forest loss has increased from 182.5 ha/year in the first period 1991-2003 to 187.47 ha/year in the second period 2003-2018. The corresponding net annual forest loss (incl. regeneration) rates are 0.5% in the first period and 0.1% in the second period. The decrease of the net annual forest loss rate in the second period is attributed to an increase in forest regeneration. 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引用次数: 2
摘要
了解森林覆盖动态变化对监测森林面积变化具有重要意义。本研究的目的是发展一种方法,以评估具有高度空间复杂性和时间变化的景观中的森林覆盖变化,从而能够产生可靠的监测信息。森林覆盖变化图是使用时间序列Landsat图像、谷歌Earth的高分辨率图像、免费软件R和QGIS制作的。在603’972 ha范围内,以30 m空间分辨率绘制了完整的森林覆盖变化图。通过5000个随机采样点的照片解译,以及谷歌Earth (Quickbird) 2018年的高分辨率图像和2018年、1991年和2003年的Landsat卫星图像,验证了这一结果。估算森林覆盖变化图的总体精度为88.7%。研究区森林面积1991年为246’915 ha, 2003年为232’741 ha, 2018年为230’390 ha。森林损失总量从1991-2003年第一期的182.5公顷/年增加到2003-2018年第二期的187.47公顷/年。相应的森林年净损失率(包括更新)在第一个时期为0.5%,在第二个时期为0.1%。第二阶段森林年净损失率的下降是由于森林更新的增加。这项研究可以被认为是绘制森林覆盖变化地图的一种可重复的方法,可以支持减少森林砍伐和退化造成的排放(REDD+)的政策方法。关键词:森林损失,森林收益,多数据,Landsat,随机森林,多哥
An analytical assessment of forest cover changes over the last 30 Years in the semi-deciduous forest zone of Togo
Understanding dynamics of forest cover is important to monitor change in forest area. The objective of the present study is to develop an approach for assessing forest cover changes in landscapes with high spatial complexity and temporal variation that can allow the generation of robust monitoring information. The forest-cover change maps were produced using time-series of Landsat images, high resolution images from Google Earth, free software R and QGIS. A complete map of forest cover change at 30 m spatial resolution was produced over 603'972 ha. The result was validated by photo-interpretation of 5000 randomly sampled points and on the basis of high-resolution images available in Google Earth (Quickbird) for the year 2018 and Landsat satellite images for the year 2018, 1991 and 2003. The estimated overall accuracy of the forest cover change map is 88.7%. In the study area, the forest area was estimated at 246’915 ha in 1991, 232’741 ha in 2003 and 230’390 ha in 2018. The gross forest loss has increased from 182.5 ha/year in the first period 1991-2003 to 187.47 ha/year in the second period 2003-2018. The corresponding net annual forest loss (incl. regeneration) rates are 0.5% in the first period and 0.1% in the second period. The decrease of the net annual forest loss rate in the second period is attributed to an increase in forest regeneration. This study can be considered as a reproducible approach to map forest-cover change and can support policy approaches towards reducing emissions from deforestation and degradation (REDD+).
Key words: Forest loss, forest gain, multi-date, Landsat, random forest, Togo.