Bamboo mapping of Ethiopia, Kenya and Uganda for the year 2016 using multi-temporal Landsat imagery

被引:41
作者
Zhao, Yuanyuan [1 ]
Feng, Duole [1 ]
Jayaraman, Durai [2 ]
Belay, Daniel [3 ]
Sebrala, Heiru [3 ]
Ngugi, John [4 ]
Maina, Eunice [5 ]
Akombo, Rose [5 ]
Otuoma, John [4 ]
Mutyaba, Joseph [6 ]
Kissa, Sam [6 ]
Qi, Shuhua [7 ]
Assefa, Fiker [2 ]
Oduor, Nellie Mugure [2 ]
Ndawula, Andrew Kalema [2 ]
Li, Yanxia [2 ]
Gong, Peng [1 ,8 ]
机构
[1] Tsinghua Univ, Dept Earth Syst Sci, Key Lab Earth Syst Modeling, Minist Educ, Beijing 100084, Peoples R China
[2] Int Network Bamboo & Rattan, Beijing 100102, Peoples R China
[3] Minist Environm Forest & Climate Change, Addis Ababa 12760, Ethiopia
[4] Kenya Forestry Res Inst, Nairobi 2041200200, Kenya
[5] Kenya Forest Serv, Nairobi 3051300100, Kenya
[6] Natl Forestry Author, Kampala 70863, Uganda
[7] Jiangxi Normal Univ, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Jiangxi, Peoples R China
[8] Joint Ctr Global Change Studies, Beijing 100875, Peoples R China
关键词
East Africa; Bamboo; Multi-temporal; Landsat; CLOUD SHADOW; FOREST; COVER; CLASSIFICATION; UNDERSTORY; EXPANSION; DYNAMICS;
D O I
10.1016/j.jag.2017.11.008
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Mapping the spatial distribution of bamboo in East Africa is necessary for biodiversity conservation, resource management and policy making for rural poverty reduction. In this study, we produced a contemporary bamboo cover map of Ethiopia, Kenya and Uganda for the year 2016 using multi-temporal Landsat imagery series at 30 m spatial resolution. This is the first bamboo map generated using remotely sensed data for these three East African countries that possess most of the African bamboo resource. The producer's and user's accuracies of bamboos are 79.2% and 84.0%, respectively. The hotspots with large amounts of bamboo were identified and the area of bamboo coverage for each region was estimated according to the map. The seasonal growth status of two typical bamboo zones (one highland bamboo and one lowland bamboo) were analyzed and the multi-temporal imagery proved to be useful in differentiating bamboo from other vegetation classes. The images acquired in September to February are less contaminated by clouds and shadows, and the image series cover the dying back process of lowland bamboo, which were helpful for bamboo identification in East Africa.
引用
收藏
页码:116 / 125
页数:10
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