Volta

Mapping Lantana camara and Leucaena leucocephala in Protected Areas of Pakistan: A Geo-Spatial Approach

Unknown authors · 2023
hash_id: e2d9342e3b7295bd37931cefd4eedb10cf760e65ed0a01b2b1c836a132aa71bf · DOI: 10.3390/rs15041020

Invasive alien plants are considered as one of the major causes of loss of native biodiversity around the world. Remote sensing provides an opportunity to identify and map native and invasive species using accurate spectral information. The current study was aimed to evaluate PlanetScope (3 m) and Sentinel (10 m) datasets for mapping the distribution of native and invasive species in two protected areas in Pakistan, using machine learning (ML) algorithms. The multispectral data were analysed with the following four ML algorithms (classifiers)—random forest (RF), Gaussian mixture model (GMM), k-nearest neighbour (KNN), and support vector machine (SVM)—to classify two invasive species, Lantana camara L. (common lantana) and Leucaena leucocephala L. The (Ipil-ipil) Dzetsaka plugin of QGIS was used to map …

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Cited by (2)

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