An overview of global leaf area index (LAI): Methods, products, validation, and applications

H Fang, F Baret, S Plummer… - Reviews of …, 2019 - Wiley Online Library
Leaf area index (LAI) is a critical vegetation structural variable and is essential in the
feedback of vegetation to the climate system. The advancement of the global Earth …

[HTML][HTML] Global data sets of vegetation leaf area index (LAI) 3g and fraction of photosynthetically active radiation (FPAR) 3g derived from global inventory modeling …

Z Zhu, J Bi, Y Pan, S Ganguly, A Anav, L Xu… - Remote sensing, 2013 - mdpi.com
Long-term global data sets of vegetation Leaf Area Index (LAI) and Fraction of
Photosynthetically Active Radiation absorbed by vegetation (FPAR) are critical to monitoring …

Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance

Z **ao, S Liang, J Wang, Y **ang… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Leaf area index (LAI) is an important vegetation biophysical variable and has been widely
used for crop growth monitoring and yield estimation, land-surface process simulation, and …

Evaluation of MODIS LAI/FPAR product collection 6. Part 2: Validation and intercomparison

K Yan, T Park, G Yan, Z Liu, B Yang, C Chen… - Remote Sensing, 2016 - mdpi.com
The aim of this paper is to assess the latest version of the MODIS LAI/FPAR product
(MOD15A2H), namely Collection 6 (C6). We comprehensively evaluate this product through …

GEOV1: LAI, FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part 2: Validation and intercomparison with …

F Camacho, J Cernicharo, R Lacaze, F Baret… - Remote Sensing of …, 2013 - Elsevier
This paper describes the scientific validation of the first version of global biophysical
products (ie, leaf area index, fraction of absorbed photosynthetically active radiation and …

Using linear regression, random forests, and support vector machine with unmanned aerial vehicle multispectral images to predict canopy nitrogen weight in corn

H Lee, J Wang, B Leblon - Remote Sensing, 2020 - mdpi.com
The optimization of crop nitrogen fertilization to accurately predict and match the nitrogen (N)
supply to the crop N demand is the subject of intense research due to the environmental and …

Validation and intercomparison of global Leaf Area Index products derived from remote sensing data

S Garrigues, R Lacaze, F Baret… - Journal of …, 2008 - Wiley Online Library
This study investigates the performances of four major global Leaf Area Index (LAI) products
at 1/11.2° spatial sampling and a monthly time step: ECOCLIMAP climatology …

[HTML][HTML] Estimating fractional cover of tundra vegetation at multiple scales using unmanned aerial systems and optical satellite data

H Riihimäki, M Luoto, J Heiskanen - Remote Sensing of Environment, 2019 - Elsevier
Fractional cover of green vegetation (FCover) is a key variable when observing Arctic
vegetation under a changing climate. Vegetation changes over large areas are traditionally …

[HTML][HTML] How can UAV bridge the gap between ground and satellite observations for quantifying the biomass of desert shrub community?

P Mao, J Ding, B Jiang, L Qin, GY Qiu - ISPRS Journal of Photogrammetry …, 2022 - Elsevier
Accurate estimation of the shrub above-ground biomass (AGB) is an essential basis for
determining carbon storage and monitoring desertification risk in arid ecosystems. However …

Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests

SG Leblanc, JM Chen, R Fernandes… - Agricultural and Forest …, 2005 - Elsevier
The retrieval of canopy architectural parameters using off-the-shelf digital cameras with fish-
eye lens is investigated. The technique used takes advantage of the sensor's linear …