[HTML][HTML] A review of spectral indices for mangrove remote sensing

TV Tran, R Reef, X Zhu - Remote Sensing, 2022 - mdpi.com
Mangrove ecosystems provide critical goods and ecosystem services to coastal
communities and contribute to climate change mitigation. Over four decades, remote …

A comprehensive review of high throughput phenoty** and machine learning for plant stress phenoty**

T Gill, SK Gill, DK Saini, Y Chopra, JP de Koff… - Phenomics, 2022 - Springer
During the last decade, there has been rapid adoption of ground and aerial platforms with
multiple sensors for phenoty** various biotic and abiotic stresses throughout the …

A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research

D Montero, C Aybar, MD Mahecha, F Martinuzzi… - Scientific Data, 2023 - nature.com
Spectral Indices derived from multispectral remote sensing products are extensively used to
monitor Earth system dynamics (eg vegetation dynamics, water bodies, fire regimes). The …

Significant remote sensing vegetation indices: A review of developments and applications

J Xue, B Su - Journal of sensors, 2017 - Wiley Online Library
Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and
effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor …

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 …

Predicting grain yield in rice using multi-temporal vegetation indices from UAV-based multispectral and digital imagery

X Zhou, HB Zheng, XQ Xu, JY He, XK Ge, X Yao… - ISPRS Journal of …, 2017 - Elsevier
Timely and non-destructive assessment of crop yield is an essential part of agricultural
remote sensing (RS). The development of unmanned aerial vehicles (UAVs) has provided a …

[HTML][HTML] Forestry remote sensing from unmanned aerial vehicles: A review focusing on the data, processing and potentialities

N Guimarães, L Pádua, P Marques, N Silva, E Peres… - Remote Sensing, 2020 - mdpi.com
Currently, climate change poses a global threat, which may compromise the sustainability of
agriculture, forestry and other land surface systems. In a changing world scenario, the …

[HTML][HTML] Wheat yellow rust monitoring by learning from multispectral UAV aerial imagery

J Su, C Liu, M Coombes, X Hu, C Wang, X Xu… - … and electronics in …, 2018 - Elsevier
The use of a low-cost five-band multispectral camera (RedEdge, MicaSense, USA) and a
low-altitude airborne platform is investigated for the detection of plant stress caused by …

Vegetation index weighted canopy volume model (CVMVI) for soybean biomass estimation from unmanned aerial system-based RGB imagery

M Maimaitijiang, V Sagan, P Sidike… - ISPRS journal of …, 2019 - Elsevier
Crop biomass estimation with high accuracy at low-cost is valuable for precision agriculture
and high-throughput phenoty**. Recent technological advances in Unmanned Aerial …

[HTML][HTML] Assessing the detectability of European spruce bark beetle green attack in multispectral drone images with high spatial-and temporal resolutions

L Huo, E Lindberg, J Bohlin, HJ Persson - Remote Sensing of Environment, 2023 - Elsevier
Detecting disease-or insect-infested forests as early as possible is a classic application of
remote sensing. Under conditions of climate change and global warming, outbreaks of the …