干旱区生态环境知识资源中心(Arid): Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data

Arid

DOI	10.3390/rs11222633
	Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data
	Wessels, Konrad 1,2; Mathieu, Renaud 3,4,5; Knox, Nichola 6; Main, Russell 4,5; Naidoo, Laven 4,5; Steenkamp, Karen 2
通讯作者	Wessels, Konrad
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2019
卷号	11 期号:22
英文摘要	Namibia is a very arid country, which has experienced significant bush encroachment and associated decreased livestock productivity. Therefore, it is essential to monitor bush encroachment and widespread debushing activities, including selective bush thinning and complete bush clearing. The aim of study was to develop a system to map and monitor fractional woody cover (FWC) at national scales (50 m and 75 m resolution) using Synthetic Aperture Radar (SAR) satellite data (Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) global mosaics, 2009, 2010, 2015, 2016) and ancillary variables (mean annual precipitation-MAP, elevation), with machine learning models that were trained with diverse airborne Light Detection and Ranging (LiDAR) data sets (244,032 ha, 2008-2014). When only the SAR variables were used, an average R-2 of 0.65 (RSME = 0.16) was attained. Adding either elevation or MAP, or both ancillary variables, increased the mean R-2 to 0.75 (RSME = 0.13), and 0.79 (RSME = 0.12). The inclusion of MAP addressed the overestimation of FWC in very arid areas, but resulted in anomalies in the form of sharp gradients in FWC along a MAP contour which were most likely caused by to the geographic distribution of the LiDAR training data. Additional targeted LiDAR acquisitions could address this issue. This was the first attempt to produce SAR-derived FWC maps for Namibia and the maps contain substantially more detailed spatial information on woody vegetation structure than existing national maps. During the seven-year study period the Shrubland-Woodland Mosaic was the only vegetation structural class that exhibited a regional net gain in FWC of more than 0.2 across 9% (11,906 km(2)) of its area that may potentially be attributed to bush encroachment. FWC change maps provided regional insights and detailed local patterns related to debushing and regrowth that can inform national rangeland policies and debushing programs.
英文关键词	Namibia bush encroachment ALOS PALSAR woody cover LiDAR tree shrub
类型	Article
语种	英语
国家	USA ; South Africa ; Philippines ; Namibia
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000502284300038
WOS关键词	AFRICAN SAVANNAS ; BUSH ENCROACHMENT ; LAND DEGRADATION ; FOREST BIOMASS ; RADAR ; QUEENSLAND ; RAINFALL ; SAR ; MAP ; BACKSCATTER
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
EI主题词	2019-11-02
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/310732
作者单位	1.George Mason Univ, Geog & GeoInformat Sci, 4400 Univ Dr,MSN 6C3, Fairfax, VA 22030 USA; 2.CSIR, Remote Sensing Res Unit, Earth Observat Sci & Informat Technol, Meraka Inst, ZA-0001 Pretoria, South Africa; 3.IRRI, Sustainable Impact Platform, Geospatial Sci & Modelling, Los Banos 4031, Philippines; 4.CSIR, Nat Resources & Environm, Ecosyst Earth Observat, ZA-0001 Pretoria, South Africa; 5.Univ Pretoria, Dept Geog Geomat & Meteorol, ZA-0001 Pretoria, South Africa; 6.Namibia Univ Sci & Technol, Dept Geospatial Sci & Technol, Windhoek, Namibia
推荐引用方式 GB/T 7714	Wessels, Konrad,Mathieu, Renaud,Knox, Nichola,et al. Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data[J],2019,11(22).
APA	Wessels, Konrad,Mathieu, Renaud,Knox, Nichola,Main, Russell,Naidoo, Laven,&Steenkamp, Karen.(2019).Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data.REMOTE SENSING,11(22).
MLA	Wessels, Konrad,et al."Mapping and Monitoring Fractional Woody Vegetation Cover in the Arid Savannas of Namibia Using LiDAR Training Data, Machine Learning, and ALOS PALSAR Data".REMOTE SENSING 11.22(2019).