Over the last few years, deep learning (DL) techniques have gained popularity and have
become the new standard for data processing in remote sensing analysis. Deep learning …

Detecting and map** the occurrence, spatial distribution and abundance of Alien Invasive
Plants (AIPs) have recently gained substantial attention, globally. This work, therefore …

Invasive and expansive plant species are considered a threat to natural biodiversity
because of their high adaptability and low habitat requirements. Species investigated in this …

Hyperspectral images possess a continuous and analogous spectral nature, enabling the
classification of distinctive information by analyzing the subtle variations between adjacent …

This study investigates the utility of an off-the-shelf, consumer-grade unmanned aerial
vehicle (UAV) for invasive species map** in a lacustrine fringe environment. Specifically …

Reliable distribution maps are crucial for the management of invasive plant species. An
alternative to traditional field surveys is the use of remote sensing data, which allows …

Detecting and map** plant invaders using hyperspectral remote sensing is necessary in
mitigating the extensive ecologic and economic damage these alien plants induce on our …

The accurate detection and map** of plant invasions is important for an effective weed
management strategy in forest plantations. In this study, the utility of WorldView-2 was …

Solanum mauritianum is a highly destructive and resourceful plant invader, resulting in
severe economic and ecological damage. Detecting and map** the spatial distribution of …

In this paper, a fast and robust self-representation (FRSR) method is proposed to select a
proper band subset from hyperspectral imagery (HSI). The FRSR assumes the separability …