K-means and alternative clustering methods in modern power systems

SM Miraftabzadeh, CG Colombo, M Longo… - Ieee …, 2023 - ieeexplore.ieee.org
As power systems evolve by integrating renewable energy sources, distributed generation,
and electric vehicles, the complexity of managing these systems increases. With the …

Ocean water quality monitoring using remote sensing techniques: A review

F Mohseni, F Saba, SM Mirmazloumi, M Amani… - Marine environmental …, 2022 - Elsevier
Abstract Ocean Water Quality (OWQ) monitoring provides insights into the quality of water in
marine and near-shore environments. OWQ measurements can contain the physical …

Challenges and limitations of remote sensing applications in northern peatlands: present and future prospects

AYA Abdelmajeed, R Juszczak - Remote Sensing, 2024 - mdpi.com
This systematic literature review (SLR) provides a comprehensive overview of remote
sensing (RS) applications in northern peatlands from 2017 to 2022, utilising various …

[HTML][HTML] Remote sensing and machine learning tools to support wetland monitoring: A meta-analysis of three decades of research

H Jafarzadeh, M Mahdianpari, EW Gill, B Brisco… - Remote Sensing, 2022 - mdpi.com
Despite their importance to ecosystem services, wetlands are threatened by pollution and
development. Over the last few decades, a growing number of wetland studies employed …

[HTML][HTML] Wetland map** in great lakes using Sentinel-1/2 time-series imagery and DEM data in Google Earth Engine

F Mohseni, M Amani, P Mohammadpour, M Kakooei… - Remote Sensing, 2023 - mdpi.com
The Great Lakes (GL) wetlands support a variety of rare and endangered animal and plant
species. Thus, wetlands in this region should be mapped and monitored using advanced …

Probabilistic coastal wetland map** with integration of optical, SAR and hydro-geomorphic data through stacking ensemble machine learning model

P Prasad, VJ Loveson, M Kotha - Ecological Informatics, 2023 - Elsevier
The present study focuses on preparing the wetland map using earth observation data and
applying a novel ensemble model. Eight advanced machine learning algorithms were …

Comparing Pixel-and Object-Based Approaches for Classifying Multispectral Drone Imagery of a Salt Marsh Restoration and Reference Site

GS Norris, A LaRocque, B Leblon, MA Barbeau… - Remote Sensing, 2024 - mdpi.com
Monitoring salt marshes with remote sensing is necessary to evaluate their state and
restoration. Determining appropriate techniques for this can be overwhelming. Our study …

Using UAV multispectral photography to discriminate plant species in a seep wetland of the Fynbos Biome

K Musungu, T Dube, J Smit, M Shoko - Wetlands Ecology and …, 2024 - Springer
Wetlands harbour a wide range of vital ecosystems. Hence, map** wetlands is essential
to conserving the ecosystems that depend on them. However, the physical nature of …

[HTML][HTML] Effects of multi-growth periods UAV images on classifying karst wetland vegetation communities using object-based optimization stacking algorithm

Y Zhang, B Fu, X Sun, H Yao, S Zhang, Y Wu… - Remote Sensing, 2023 - mdpi.com
Combining machine learning algorithms with multi-temporal remote sensing data for fine
classification of wetland vegetation has received wide attention from researchers. However …

Application of remote sensing data in large-scale monitoring of wetlands

SS Shinkarenko, SA Bartalev - Cosmic Research, 2024 - Springer
The present review examines existing technologies for map** wetland ecosystems (WEs)
based on remote sensing data. WEs are the most valuable ecosystems with a high …