A review of UAV platforms, sensors, and applications for monitoring of sugarcane crops
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 …
sensing (RS) in precision agricultural practices have been critical in enhancing crop health …
[HTML][HTML] Predicting canopy chlorophyll content in sugarcane crops using machine learning algorithms and spectral vegetation indices derived from UAV multispectral …
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 …
techniques have been successfully utilized to evaluate the chlorophyll content for the …
[HTML][HTML] Detection of white leaf disease in sugarcane using machine learning techniques over UAV multispectral images
Sugarcane white leaf phytoplasma (white leaf disease) in sugarcane crops is caused by a
phytoplasma transmitted by leafhopper vectors. White leaf disease (WLD) occurs …
phytoplasma transmitted by leafhopper vectors. White leaf disease (WLD) occurs …
[HTML][HTML] Mapping seasonal leaf nutrients of mangrove with sentinel-2 images and XGBoost method
Monitoring the seasonal leaf nutrients of mangrove forests helps one to understand the
dynamics of carbon (C) sequestration and to diagnose the availability and limitation of …
dynamics of carbon (C) sequestration and to diagnose the availability and limitation of …
[HTML][HTML] Autonomous detection of mouse-ear hawkweed using drones, multispectral imagery and supervised machine learning
Hawkweeds (Pilosella spp.) have become a severe and rapidly invading weed in pasture
lands and forest meadows of New Zealand. Detection of hawkweed infestations is essential …
lands and forest meadows of New Zealand. Detection of hawkweed infestations is essential …
[HTML][HTML] Estimating aboveground biomass of two different forest types in myanmar from sentinel-2 data with machine learning and geostatistical algorithms
P Wai, H Su, M Li - Remote Sensing, 2022 - mdpi.com
The accurate estimation of spatially explicit forest aboveground biomass (AGB) provides an
essential basis for sustainable forest management and carbon sequestration accounting …
essential basis for sustainable forest management and carbon sequestration accounting …
[HTML][HTML] Comparative analysis of remote sensing and geo-statistical techniques to quantify forest biomass
Accurately characterizing carbon stock is vital for reporting carbon emissions from forest
ecosystems. We studied the estimation of biomass using Sentinel-2 remote sensing data in …
ecosystems. We studied the estimation of biomass using Sentinel-2 remote sensing data in …
[HTML][HTML] CPR Algorithm—A new interpolation methodology and QGIS plugin for Colour Pattern Regression between aerial images and raster maps
P Blanco-Gómez, C Amurrio-Garcia… - SoftwareX, 2023 - Elsevier
Abstract The Colour Pattern Regression (CPR) algorithm complement for QGIS is presented
for determining and quantifying the relationship between aerial images and raster maps …
for determining and quantifying the relationship between aerial images and raster maps …
[HTML][HTML] The role of remote sensing in tropical grassland nutrient estimation: a review
AM Arogoundade, O Mutanga, J Odindi… - Environmental Monitoring …, 2023 - Springer
The carbon (C) and nitrogen (N) ratio is a key indicator of nutrient utilization and limitations
in rangelands. To understand the distribution of herbivores and grazing patterns, information …
in rangelands. To understand the distribution of herbivores and grazing patterns, information …
[HTML][HTML] Use of remotely sensed data to enhance estimation of aboveground biomass for the dry Afromontane forest in South-Central Ethiopia
Periodic assessment of forest aboveground biomass (AGB) is essential to regulate the
impacts of the changing climate. However, AGB estimation using field-based sample survey …
impacts of the changing climate. However, AGB estimation using field-based sample survey …