Short-term changes of leaf area index, light transmission, and gap in a temperate mixed deciduous forest ecosystem in Bartın, Turkey

This study examines light competition between aspen and spruce during the sequence of aspen development. Leaf area index and light transmission were measured or estimated for aspen stands from 2 to 125 years old. Light transmission was lowest at 15-25 years, and in some stands, transmission was less than 5% of above-canopy light. Hypothetical aspen stands with various stem configurations and heights were developed, and positions were identified that would meet or fail Alberta free-to-grow (FTG) standards. Light transmission was estimated at each position with the MIXLIGHT forest light simulator. Positions in canopy gaps or at the northern sides of canopy gaps had higher light. In general, however, there was little difference in available light between positions that met or failed FTG criteria. Stand density and size of aspen trees appears to be a better index to predict light transmission and spruce success in juvenile aspen stands than current FTG criteria. Key words: competition, free to grow, hardwood, spruce, light

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Seasonal changes of leaf area index (LAI) in a tropical deciduous forest in west Mexico

Forest Ecology and Management ◽

10.1016/0378-1127(94)03485-f ◽

1995 ◽

Vol 74 (1-3) ◽

pp. 171-180 ◽

Cited By ~ 83

Author(s):

JoséManuel Maass ◽

James M. Vose ◽

Wayne T. Swank ◽

Angelina Martínez-Yrízar

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Seasonal Changes ◽

Deciduous Forest ◽

Tropical Deciduous Forest ◽

Area Index ◽

West Mexico

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Erratum to “Comparative analysis of IKONOS, SPOT, and ETM+ data leaf area index estimation in temperature coniferous and deciduous forest stands” [Remote Sensing of Environment 102 (2006) 161–175]

Remote Sensing of Environment ◽

10.1016/j.rse.2006.05.001 ◽

2006 ◽

Vol 103 (4) ◽

pp. 497 ◽

Cited By ~ 1

Author(s):

Kamel Soudani ◽

Christopher François ◽

Guerric le Maire ◽

Valérie Le Dantec ◽

Eric Dufrêne

Keyword(s):

Remote Sensing ◽

Comparative Analysis ◽

Leaf Area Index ◽

Leaf Area ◽

Deciduous Forest ◽

Forest Stands ◽

Area Index ◽

Index Estimation

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Estimation of Biomass and Leaf Area Index in the Western Ghats Forest Ecosystem by the Integrated Analysis of Hyperspectral Data and Space Borne LiDAR Data

Journal of Geography Environment and Earth Science International ◽

10.9734/jgeesi/2019/v19i430090 ◽

2019 ◽

pp. 1-12

Author(s):

Indu Indirabai ◽

M. V. Harindranathan Nair ◽

Jaishanker R. Nair ◽

Rama Rao Nidamanuri

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Forest Ecosystem ◽

Western Ghats ◽

Hyperspectral Data ◽

Spectral Information ◽

Lidar Data ◽

Biophysical Parameters ◽

Area Index ◽

The Western Ghats

The Western Ghats regions of India are characterised by highly complex and biodiverse forest ecosystem with heterogeneous tree species. The integration of LiDAR data with multispectral remote sensing has limitations in the case of spectral information abundance. The objective of this study was to undertake biophysical characterisation in the Western Ghats regions of India by the integration of GLAS ICESat data and AVIRIS-NG hyperspectral data. The methodology of the study includes pre-processing of the hyperspectral and ICESat GLAS data followed by the integration of the two data sets based on pixel based fusion strategy in order to estimate the biophysical parameters of forests. Biomass was estimated by Support Vector Regression method. The structural characteristics extracted from the LiDAR data are integrated with spectral characteristics from the AVIRIS NG imagery based on the pixel level so that biophysical characteristics including canopy height, biomass, Leaf Area Index are estimated. The integrated product on further analysis revealed the applicability of this approach to extract more spectral information and forest parameters. The key findings of the study include biophysical parameters both structural as well as abundant spectral information can be retrieved successfully by the methodology used which have strong correlation with the in situ measurements. The study concluded that biophysical parameters including Leaf Area Index, biomass and canopy height can be effectively estimated by the integration of AVIRIS-NG imagery and GLAS data, which cannot be possible when used independently. It is recommended to have continuous retrieval of LiDAR foot prints instead of discrete, to make modelling of the biophysical parameters a little more effective.

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Temporal disparity in leaf chlorophyll content and leaf area index across a growing season in a temperate deciduous forest

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2014.06.005 ◽

2014 ◽

Vol 33 ◽

pp. 312-320 ◽

Cited By ~ 26

Author(s):

H. Croft ◽

J.M. Chen ◽

Y. Zhang

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Chlorophyll Content ◽

Deciduous Forest ◽

Growing Season ◽

Temperate Deciduous Forest ◽

Area Index ◽

Leaf Chlorophyll ◽

Temperate Deciduous ◽

Temporal Disparity

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Evaluation of understory LAI estimation methodologies over forest ecosystem ICOS sites across Europe

10.5194/egusphere-egu2020-6674 ◽

2020 ◽

Author(s):

Jan-Peter George ◽

Jan Pisek ◽

Keyword(s):

Remote Sensing ◽

Leaf Area Index ◽

Leaf Area ◽

Forest Ecosystem ◽

Remote Sensing Data ◽

Ecosystem Functions ◽

Area Index ◽

Fractional Cover ◽

Semi Empirical

Leaf area index (i.e. one-half the total green leaf area per unit of horizontal ground surface area) is a crucial parameter in carbon balancing and modeling. Forest overstory and understory layers differ in carbon and water cycle regimes and phenology, as well as in ecosystem functions. Separate retrievals of leaf area index (LAI) for these two layers would help to improve modeling forest biogeochemical cycles, evaluating forest ecosystem functions and also remote sensing of forest canopies by inversion of canopy reflectance models. The aim of this study is to compare currently available understory LAI assessment methodologies over a diverse set of greenhouse gas measurement sites distributed along a wide latitudinal and elevational gradient across Europe. This will help to quantify &#160;the fraction of the canopy LAI which is represented by understory, since this is still the major source of uncertainty in global LAI products derived from remote sensing data. For this, we took ground photos as well as in-situ reflectance measurements of the understory vegetation at 30 ICOS (Integration Carbon Observation System) sites distributed across 10 countries in Europe. The data were analyzed by means of three conceptually different methods for LAI estimation and comprised purely empirical (fractional cover), semi-empirical (in-situ NDVI linked to the radiative transfer model FLiES), and purely deterministic (Four-scale geometrical optical model) approaches. Finally, our results are compared with global forest understory LAI maps derived from remote sensing data at 1 km resolution (Liu et al. 2017). While we found some agreement among the three methods (e.g. Pearson-correlation between empirical and semi-empirical = 0.63), we also identified sources that are particularly prone to error inclusion such as inaccurate assessment of fractional cover from ground photos. Relationships between understory LAI and long-term climate variables were weak and suggested that understory LAI at the ICOS sites is probably more strongly determined by microclimatic conditions.Liu Y. et al. (2017): Separating overstory and understory leaf area indices for global needleleaf and deciduous broadleaf forests by fusion of MODIS and MISR data. Biogeosciences 14: 1093-1110.

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