UAV-based forest health monitoring: A systematic review

S Ecke, J Dempewolf, J Frey, A Schwaller, E Endres… - Remote Sensing, 2022 - mdpi.com
In recent years, technological advances have led to the increasing use of unmanned aerial
vehicles (UAVs) for forestry applications. One emerging field for drone application is forest …

A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops

N Amarasingam, ASA Salgadoe, K Powell… - Remote Sensing …, 2022 - Elsevier
Recent advancements in the application of unmanned aerial vehicles (UAVs) based remote
sensing (RS) in precision agricultural practices have been critical in enhancing crop health …

Comparison of random forest, k-nearest neighbor, and support vector machine classifiers for land cover classification using Sentinel-2 imagery

P Thanh Noi, M Kappas - Sensors, 2017 - mdpi.com
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-
Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost …

Improving above ground biomass estimates of Southern Africa dryland forests by combining Sentinel-1 SAR and Sentinel-2 multispectral imagery

RM David, NJ Rosser, DNM Donoghue - Remote Sensing of Environment, 2022 - Elsevier
Having the ability to make accurate assessments of above ground biomass (AGB) at high
spatial resolution is invaluable for the management of dryland forest resources in areas at …

[HTML][HTML] Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

JP Dash, MS Watt, GD Pearse, M Heaphy… - ISPRS Journal of …, 2017 - Elsevier
Research into remote sensing tools for monitoring physiological stress caused by biotic and
abiotic factors is critical for maintaining healthy and highly-productive plantation forests …

Advanced multi-sensor optical remote sensing for urban land use and land cover classification: Outcome of the 2018 IEEE GRSS data fusion contest

Y Xu, B Du, L Zhang, D Cerra, M Pato… - IEEE Journal of …, 2019 - ieeexplore.ieee.org
This paper presents the scientific outcomes of the 2018 Data Fusion Contest organized by
the Image Analysis and Data Fusion Technical Committee of the IEEE Geoscience and …

Landsat-8 vs. Sentinel-2: examining the added value of sentinel-2's red-edge bands to land-use and land-cover mapping in Burkina Faso

G Forkuor, K Dimobe, I Serme… - GIScience & remote …, 2018 - Taylor & Francis
The availability of freely available moderate-to-high spatial resolution (10–30 m) satellite
imagery received a major boost with the recent launch of the Sentinel-2 sensor by the …

Vineyard water status estimation using multispectral imagery from an UAV platform and machine learning algorithms for irrigation scheduling management

M Romero, Y Luo, B Su, S Fuentes - Computers and electronics in …, 2018 - Elsevier
Remote sensing can provide a fast and reliable alternative for traditional in situ water status
measurement in vineyards. Several vegetation indices (VIs) derived from aerial multispectral …

Urban tree species classification using a WorldView-2/3 and LiDAR data fusion approach and deep learning

S Hartling, V Sagan, P Sidike, M Maimaitijiang… - Sensors, 2019 - mdpi.com
Urban areas feature complex and heterogeneous land covers which create challenging
issues for tree species classification. The increased availability of high spatial resolution …

Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral imagery

A Narmilan, F Gonzalez, ASA Salgadoe… - Remote Sensing, 2022 - mdpi.com
The use of satellite-based Remote Sensing (RS) is a well-developed field of research. RS
techniques have been successfully utilized to evaluate the chlorophyll content for the …