Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta

2003 ◽  
Vol 29 (3) ◽  
pp. 411-427 ◽  
Author(s):  
R J Hall ◽  
D P Davidson ◽  
D R Peddle
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Rocky Mountain ◽  
Mountain Forest ◽  
Forest Stands ◽  
Area Index ◽  
Remote Estimation

Measuring effective leaf area index, foliage profile, and stand height in New England forest stands using a full-waveform ground-based lidar

2011 ◽  
Vol 115 (11) ◽  
pp. 2954-2964 ◽  
Author(s):  
Feng Zhao ◽  
Xiaoyuan Yang ◽  
Mitchell A. Schull ◽  
Miguel O. Román-Colón ◽  
Tian Yao ◽  
...  
Keyword(s):  
New England ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Forest Stands ◽  
Area Index ◽  
Full Waveform ◽  
Ground Based Lidar ◽  
Stand Height ◽  
Effective Leaf Area Index

scholarly journals Remote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data

2018 ◽  
Vol 75 (1) ◽  
Author(s):  
Xiaojun Xu ◽  
Huaqiang Du ◽  
Guomo Zhou ◽  
Fangjie Mao ◽  
Xuejian Li ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Chlorophyll Content ◽  
Moso Bamboo ◽  
Phyllostachys Edulis ◽  
Area Index ◽  
Remote Estimation ◽  
Reflectance Data

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]

2006 ◽  
Vol 103 (4) ◽  
pp. 497 ◽  
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

scholarly journals Estimation of Leaf Area Index in a Mountain Forest of Central Japan with a 30-m Spatial Resolution Based on Landsat Operational Land Imager Imagery: An Application of a Simple Model for Seasonal Monitoring

2018 ◽  
Vol 10 (2) ◽  
pp. 179 ◽  
Author(s):  
Irina Melnikova ◽  
Yoshio Awaya ◽  
Taku Saitoh ◽  
Hiroyuki Muraoka ◽  
Takahiro Sasai
Keyword(s):  
Simple Model ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Spatial Resolution ◽  
Mountain Forest ◽  
Central Japan ◽  
Area Index ◽  
Seasonal Monitoring

scholarly journals Remote estimation of leaf area index and green leaf biomass in maize canopies

2003 ◽  
Vol 30 (5) ◽  
pp. n/a-n/a ◽  
Author(s):  
Anatoly A. Gitelson ◽  
Andrés Viña ◽  
Timothy J. Arkebauer ◽  
Donald C. Rundquist ◽  
Galina Keydan ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Green Leaf ◽  
Leaf Biomass ◽  
Area Index ◽  
Remote Estimation

scholarly journals Improving remote estimation of winter crops gross ecosystem production by inclusion of leaf area index in a spectral model

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5613 ◽  
Author(s):  
Radosław Juszczak ◽  
Bogna Uździcka ◽  
Marcin Stróżecki ◽  
Karolina Sakowska
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Spring Barley ◽  
Crop Productivity ◽  
Climatic Conditions ◽  
Area Index ◽  
Gross Ecosystem Production ◽  
Ecosystem Production ◽  
Winter Crops ◽  
Remote Estimation

The hysteresis of the seasonal relationships between vegetation indices (VIs) and gross ecosystem production (GEP) results in differences between these relationships during vegetative and reproductive phases of plant development cycle and may limit their applicability for estimation of croplands productivity over the entire season. To mitigate this problem and to increase the accuracy of remote sensing-based models for GEP estimation we developed a simple empirical model where greenness-related VIs are multiplied by the leaf area index (LAI). The product of this multiplication has the same seasonality as GEP, and specifically for vegetative periods of winter crops, it allowed the accuracy of GEP estimations to increase and resulted in a significant reduction of the hysteresis of VIs vs. GEP. Our objective was to test the multiyear relationships between VIs and daily GEP in order to develop more general models maintaining reliable performance when applied to years characterized by different climatic conditions. The general model parametrized with NDVI and LAI product allowed to estimate daily GEP of winter and spring crops with an error smaller than 14%, and the rate of GEP over- (for spring barley) or underestimation (for winter crops and potato) was smaller than 25%. The proposed approach may increase the accuracy of crop productivity estimation when greenness VIs are saturating early in the growing season.

scholarly journals Estimation of forest leaf area index from SPOT imagery using NDVI distribution over forest stands

2006 ◽  
Vol 27 (5) ◽  
pp. 885-902 ◽  
Author(s):  
H. Davi ◽  
K. Soudani ◽  
T. Deckx ◽  
E. Dufrene ◽  
V. Le Dantec ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Forest Stands ◽  
Area Index ◽  
Spot Imagery
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