Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data

L Han, G Yang, H Dai, B Xu, H Yang, H Feng, Z Li… - Plant methods, 2019 - Springer
Background Above-ground biomass (AGB) is a basic agronomic parameter for field
investigation and is frequently used to indicate crop growth status, the effects of agricultural …

[HTML][HTML] Soil organic carbon and texture retrieving and map** using proximal, airborne and Sentinel-2 spectral imaging

A Gholizadeh, D Žižala, M Saberioon… - Remote Sensing of …, 2018 - Elsevier
Abstract Soil Organic Carbon (SOC) is a useful representative of soil fertility and an essential
parameter in controlling the dynamics of various agrochemicals in soil. Soil texture is also …

[HTML][HTML] Corn grain yield estimation from vegetation indices, canopy cover, plant density, and a neural network using multispectral and RGB images acquired with …

H García-Martínez, H Flores-Magdaleno… - Agriculture, 2020 - mdpi.com
Corn yields vary spatially and temporally in the plots as a result of weather, altitude, variety,
plant density, available water, nutrients, and planting date; these are the main factors that …

[HTML][HTML] Comparing deep learning and shallow learning for large-scale wetland classification in Alberta, Canada

ER DeLancey, JF Simms, M Mahdianpari, B Brisco… - Remote Sensing, 2019 - mdpi.com
Advances in machine learning have changed many fields of study and it has also drawn
attention in a variety of remote sensing applications. In particular, deep convolutional neural …

Individual tree crown segmentation and classification of 13 tree species using airborne hyperspectral data

J Maschler, C Atzberger, M Immitzer - Remote Sensing, 2018 - mdpi.com
Knowledge of the distribution of tree species within a forest is key for multiple economic and
ecological applications. This information is traditionally acquired through time-consuming …

[HTML][HTML] Assessment analysis of flood susceptibility in tropical desert area: a case study of Yemen

AR Al-Aizari, YA Al-Masnay, A Aydda, J Zhang… - Remote Sensing, 2022 - mdpi.com
Flooding is one of the catastrophic natural hazards worldwide that can easily cause
devastating effects on human life and property. Remote sensing devices are becoming …

A systematic review on the application of UAV-based thermal remote sensing for assessing and monitoring crop water status in crop farming systems

HS Ndlovu, J Odindi, M Sibanda… - International Journal of …, 2024 - Taylor & Francis
The accurate assessment and monitoring of crop water status is a critical component of
precision agriculture. Over the recent decade, unmanned aerial vehicles (UAVs) integrated …

[HTML][HTML] Map** forest fire risk—a case study in Galicia (Spain)

A Novo, N Fariñas-Álvarez, J Martínez-Sánchez… - Remote Sensing, 2020 - mdpi.com
The optimization of forest management in roadsides is a necessary task in terms of wildfire
prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk …

[HTML][HTML] Map** and monitoring of biomass and grazing in pasture with an unmanned aerial system

A Michez, P Lejeune, S Bauwens, AAL Herinaina… - Remote Sensing, 2019 - mdpi.com
The tools available to farmers to manage grazed pastures and adjust forage demand to
grass growth are generally rather static. Unmanned aerial systems (UASs) are interesting …

Map** terrestrial oil spill impact using machine learning random forest and Landsat 8 OLI imagery: A case site within the Niger Delta region of Nigeria

MS Ozigis, JD Kaduk, CH Jarvis - Environmental Science and Pollution …, 2019 - Springer
Terrestrial oil pollution is one of the major causes of ecological damage within the Niger
Delta region of Nigeria and has caused a considerable loss of mangroves and arable …