GLOBAL LEAF AREA INDEX DATA FROM FIELD MEASUREMENTS, 1932-2000

2001 ◽  
Author(s):  
G. P. ASNER ◽  
S. T. GOWER ◽  
J. M. O. SCURLOCK
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Field Measurements ◽  
Area Index ◽  
Index Data

scholarly journals An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI

2008 ◽  
Vol 35 (10) ◽  
pp. 1070 ◽  
Author(s):  
Sigfredo Fuentes ◽  
Anthony R. Palmer ◽  
Daniel Taylor ◽  
Melanie Zeppel ◽  
Rhys Whitley ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Gap Analysis ◽  
Digital Camera ◽  
Field Measurements ◽  
Accurate Estimation ◽  
Image Capture ◽  
Area Index ◽  
Modis Lai ◽  
Matlab Programming

Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional–structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAIM (LAIM = 1.009 – 0.0066 LAID; R2 = 0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI = 0.9591 LAID – 0.2371; R2 = 0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI = 1.0296 LAIe + 0.3468; R2 = 0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers.

scholarly journals Spatial Heterogeneity of Leaf Area Index (LAI) and Its Temporal Course on Arable Land: Combining Field Measurements, Remote Sensing and Simulation in a Comprehensive Data Analysis Approach (CDAA)

PLoS ONE ◽  
2016 ◽  
Vol 11 (7) ◽  
pp. e0158451 ◽  
Author(s):  
Tim G. Reichenau ◽  
Wolfgang Korres ◽  
Carsten Montzka ◽  
Peter Fiener ◽  
Florian Wilken ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Spatial Heterogeneity ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Arable Land ◽  
Field Measurements ◽  
Analysis Approach ◽  
Area Index ◽  
Temporal Course

scholarly journals Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements

2021 ◽  
Vol 14 ◽  
pp. 9372-9382
Author(s):  
Bowen Song ◽  
Liangyun Liu ◽  
Jingjing Zhao ◽  
Xidong Chen ◽  
Helin Zhang ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Field Measurements ◽  
Area Index ◽  
Coarse Resolution

scholarly journals Observed Vegetation Greening and Its Relationships with Cropland Changes and Climate in China

Land ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 274
Author(s):  
Yuzhen Zhang ◽  
Shunlin Liang ◽  
Zhiqiang Xiao
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Boosted Regression Trees ◽  
Trend Detection ◽  
Area Index ◽  
Vegetation Greenness ◽  
Detection Algorithms ◽  
Index Data

Chinese croplands have changed considerably over the past decades, but their impacts on the environment remain underexplored. Meanwhile, understanding the contributions of human activities to vegetation greenness has been attracting more attention but still needs to be improved. To address both issues, this study explored vegetation greening and its relationships with Chinese cropland changes and climate. Greenness trends were first identified from the normalized difference vegetation index and leaf area index from 1982–2015 using three trend detection algorithms. Boosted regression trees were then performed to explore underlying relationships between vegetation greening and cropland and climate predictors. The results showed the widespread greening in Chinese croplands but large discrepancies in greenness trends characterized by different metrics. Annual greenness trends in most Chinese croplands were more likely nonlinearly associated with climate compared with cropland changes, while cropland percentage only predominantly contributed to vegetation greening in the Sichuan Basin and its surrounding regions with leaf area index data and, in the Northeast China Plain, with vegetation index data. Results highlight both the differences in vegetation greenness using different indicators and further impacts on the nonlinear relationships with cropland and climate, which have been largely ignored in previous studies.

Effect of check dams on riparian vegetation cover: A multiscale approach based on field measurements and satellite images for Leaf Area Index assessment

2019 ◽  
Vol 657 ◽  
pp. 827-838 ◽  
Author(s):  
Giovanni Francesco Ricci ◽  
Giovanni Romano ◽  
Vincenzo Leronni ◽  
Francesco Gentile
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Vegetation Cover ◽  
Riparian Vegetation ◽  
Satellite Images ◽  
Field Measurements ◽  
Multiscale Approach ◽  
Area Index ◽  
Check Dams

Evaluation of the observation operator Jacobian for leaf area index data assimilation with an extended Kalman filter

2010 ◽  
Vol 115 (D9) ◽  
Author(s):  
Christoph Rüdiger ◽  
Clément Albergel ◽  
Jean-François Mahfouf ◽  
Jean-Christophe Calvet ◽  
Jeffrey P. Walker
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Extended Kalman Filter ◽  
Area Index ◽  
Observation Operator ◽  
Index Data

Integration of Landsat ETM+ Data with Field Measurements for Mapping Leaf Area Index in the Grasslands of Central Kazakhstan

2009 ◽  
Vol 46 (2) ◽  
pp. 212-231 ◽  
Author(s):  
P. A. Propastin ◽  
M. Kappas
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Field Measurements ◽  
Area Index

scholarly journals Analysis of a multiyear global vegetation leaf area index data set

2002 ◽  
Vol 107 (D22) ◽  
Author(s):  
Wolfgang Buermann
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Data Set ◽  
Area Index ◽  
Index Data ◽  
Global Vegetation

Evaluation of the Utility of Satellite-Based Vegetation Leaf Area Index Data for Climate Simulations

2001 ◽  
Vol 14 (17) ◽  
pp. 3536-3550 ◽  
Author(s):  
Wolfgang Buermann ◽  
Jiarui Dong ◽  
Xubin Zeng ◽  
Ranga B. Myneni ◽  
Robert E. Dickinson
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Area Index ◽  
Index Data ◽  
Climate Simulations
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