Remote sensing of grassland production and management—A review

S Reinermann, S Asam, C Kuenzer - Remote Sensing, 2020 - mdpi.com
Grasslands cover one third of the earth's terrestrial surface and are mainly used for livestock
production. The usage type, use intensity and condition of grasslands are often unclear …

Evaluation of the PROSAIL model capabilities for future hyperspectral model environments: A review study

K Berger, C Atzberger, M Danner, G D'Urso, W Mauser… - Remote Sensing, 2018 - mdpi.com
Upcoming satellite hyperspectral sensors require powerful and robust methodologies for
making optimum use of the rich spectral data. This paper reviews the widely applied coupled …

Estimation of crop growth parameters using UAV-based hyperspectral remote sensing data

H Tao, H Feng, L Xu, M Miao, H Long, J Yue, Z Li… - Sensors, 2020 - mdpi.com
Above-ground biomass (AGB) and the leaf area index (LAI) are important indicators for the
assessment of crop growth, and are therefore important for agricultural management …

The superiority of the normalized difference phenology index (NDPI) for estimating grassland aboveground fresh biomass

D Xu, C Wang, J Chen, M Shen, B Shen, R Yan… - Remote Sensing of …, 2021 - Elsevier
Accurate monitoring of grassland aboveground fresh biomass (called AGB in the study) and
its spatial-temporal dynamics is indispensable for sustainable grassland management. The …

A comparison of crop parameters estimation using images from UAV-mounted snapshot hyperspectral sensor and high-definition digital camera

J Yue, H Feng, X **, H Yuan, Z Li, C Zhou, G Yang… - Remote Sensing, 2018 - mdpi.com
Timely and accurate estimates of crop parameters are crucial for agriculture management.
Unmanned aerial vehicles (UAVs) carrying sophisticated cameras are very pertinent for this …

Estimating natural grassland biomass by vegetation indices using Sentinel 2 remote sensing data

M Guerini Filho, TM Kuplich… - International Journal of …, 2020 - Taylor & Francis
Estimation of natural grassland biomass was carried out in a region located in the Brazilian
Pampa, using field and remote sensing data and statistical models. The study was …

Predicting plant biomass and species richness in temperate grasslands across regions, time, and land management with remote sensing and deep learning

J Muro, A Linstädter, P Magdon, S Wöllauer… - Remote Sensing of …, 2022 - Elsevier
Spatial predictions of biomass production and biodiversity at regional scale in grasslands
are critical to evaluate the effects of management practices across environmental gradients …

[HTML][HTML] Global fuel moisture content map** from MODIS

X Quan, M Yebra, D Riaño, B He, G Lai, X Liu - International Journal of …, 2021 - Elsevier
Fuel moisture content (FMC) of live vegetation is a crucial wildfire risk and spread rate driver.
This study presents the first daily FMC product at a global scale and 500 m pixel resolution …

A hybrid model to predict nitrogen concentration in heterogeneous grassland using field spectroscopy

MH Dehghan-Shoar, AA Orsi, RR Pullanagari… - Remote Sensing of …, 2023 - Elsevier
Field spectroscopy is a rapid and non-destructive tool used for the estimation of nitrogen
concentration (N%) of vegetation. Empirical and physically-based models are widely used …

Comparison of winter wheat yield estimation based on near-surface hyperspectral and UAV hyperspectral remote sensing data

H Feng, H Tao, Y Fan, Y Liu, Z Li, G Yang, C Zhao - Remote Sensing, 2022 - mdpi.com
Crop yields are important for food security and people's living standards, and it is therefore
very important to predict the yield in a timely manner. This study used different vegetation …