Evaluating the capability of Landsat 8 OLI and SPOT 6 for discriminating invasive alien species in the African Savanna landscape

被引:46
作者
Kganyago, Mahlatse [1 ,2 ]
Odindi, John [1 ]
Adjorlolo, Clement [1 ,2 ]
Mhangara, Paidamoyo [2 ]
机构
[1] Univ KwaZulu Natal, Sch Agr Earth & Environm Sci, P Bag X01, ZA-3209 Pietermaritzburg, South Africa
[2] South African Natl Space Agcy, Earth Observat, Enterprise Bldg,Mark Shuttleworth St, ZA-0001 Pretoria, South Africa
关键词
Invasive alien plants; Landsat; 8; OLI; SPOT; 6; Support vector machine; Parthenium hysterophorus; PARTHENIUM PARTHENIUM-HYSTEROPHORUS; SUPPORT VECTOR MACHINES; HYPERSPECTRAL IMAGERY; SPATIAL-RESOLUTION; CLASSIFICATION; ECOLOGY; PATTERN; TREE; SVM; BIOGEOGRAPHY;
D O I
10.1016/j.jag.2017.12.008
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Globally, there is paucity of accurate information on the spatial distribution and patch sizes of Invasive Alien Plants (IAPs) species. Such information is needed to aid optimisation of control mechanisms to prevent further spread of IAPs and minimize their impacts. Recent studies have shown the capability of very high spatial (< 1 m) and spectral resolution (< 10 nm) data for discriminating vegetation species. However, very high spatial resolution may introduce significant intra-species spectral variability and result in reduced mapping accuracy, while higher spectral resolution data are commonly limited to smaller areas, are costly and computationally expensive. Alternatively, medium and high spatial resolution data are available at low or no cost and have limitedly been evaluated for their potential in determining invasion patterns relevant for invasion ecology and aiding effective IAPs management. In this study medium and high resolution datasets from Landsat Operational Land Imager (OLI) and SPOT 6 sensors respectively, were evaluated for mapping the distribution and patch sizes of IAP, Parthenium hysterophorus in the savannah landscapes of KwaZulu-Natal, South Africa. Support Vector Machines (SVM) classifier was used for classification of both datasets. Results indicated that SPOT 6 had a higher overall accuracy (86%) than OLI (83%) in mapping P. hysterophorus. The study found larger distributions and patch sizes in OLI than in SPOT 6 as a result of possible P. hysterophorus expansion due to temporal differences between images and coarser pixels were insufficient to delineate gaps inside larger patches. On the other hand, SPOT 6 showed better capabilities of delineating gaps and boundaries of patches, hence had better estimates of distribution and patch sizes. Overall, the study showed that OLI may be suitable for mapping well-established patches for the purpose of large scale monitoring, while SPOT 6 can be used for mapping small patches and prioritising them for eradication to prevent further spread at a landscape scale.
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页码:10 / 19
页数:10
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