Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurements of height and crown dimensions

Abstract A series of paired plots was installed in loblolly pine plantations at 42 locations in Georgia's Piedmont and Alabama's Piedmont and Coastal Plain. One plot of each pair had all competing vegetation eliminated. The other plot was left as an uncontrolled check. Locations were stratified over two age classes (5-9 and 12-16 yr old) and three slope positions (top, midslope, and bottom). Analysis of 33 surviving locations 8 yr after treatment revealed a positive treatment effect for both individual tree (dbh and total height) and stand characteristics (basal area per acre, total volume per acre, and merchantable volume per acre). There was no difference in volume response between age classes. Slope position was not significant for the individual tree variables, but was significant for the stand variables, with midslopes responding most positively followed by bottom and then top slope positions. Over all locations, the average treatment response was approximately ½ cord/ac/yr. Economic analyses indicate that the magnitude of the response will be economical for many stumpage prices, particularly on midslope and bottom slope positions, in plantations where access and species composition make herbicide spraying possible. South J. Appl. For. 20(4):188-192.

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Modeling individual tree growth for juvenile loblolly pine plantations

Forest Ecology and Management ◽

10.1016/s0378-1127(96)03851-0 ◽

1996 ◽

Vol 89 (1-3) ◽

pp. 157-172 ◽

Cited By ~ 17

Author(s):

Shaoang Zhang ◽

Harold E. Burkhart ◽

Ralph L. Amateis

Keyword(s):

Loblolly Pine ◽

Tree Growth ◽

Pine Plantations ◽

Individual Tree ◽

Individual Tree Growth

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Predictions of individual-tree and whole-stand attributes for loblolly pine plantations

Forest Ecology and Management ◽

10.1016/j.foreco.2006.09.019 ◽

2006 ◽

Vol 236 (2-3) ◽

pp. 342-347 ◽

Cited By ~ 22

Author(s):

Quang V. Cao

Keyword(s):

Loblolly Pine ◽

Pine Plantations ◽

Individual Tree ◽

Stand Attributes

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Crown structure and growth efficiency of red spruce in uneven-aged, mixed-species stands in Maine

Canadian Journal of Forest Research ◽

10.1139/x98-093 ◽

1998 ◽

Vol 28 (8) ◽

pp. 1233-1240 ◽

Cited By ~ 35

Author(s):

Douglas A Maguire ◽

John C Brissette ◽

Lianhong Gu

Keyword(s):

Leaf Area ◽

Volume Growth ◽

Growth Efficiency ◽

Tree Size ◽

Red Spruce ◽

Stem Volume ◽

Mixed Species ◽

Individual Tree ◽

South Central ◽

Tree Leaf

Several hypotheses about the relationships among individual tree growth, tree leaf area, and relative tree size or position were tested with red spruce (Picea rubens Sarg.) growing in uneven-aged, mixed-species forests of south-central Maine, U.S.A. Based on data from 65 sample trees, predictive models were developed to (i)estimate the amount of foliage held by individual trees from sapwood cross-sectional area and (ii)define the relationship between stem volume growth and three variables: total foliage area, relative position in the stand, and the degree of past suppression. A model that included variables representing tree size (or relative social position) and degree of past suppression (live branch whorls per unit crown length) indicated that stem volume growth first increased but later decreased over leaf area when other variables were held constant. Growth efficiency declined with increasing tree leaf area, although greater height and diameter enhanced growth efficiency and greater past suppression diminished growth efficiency. The decline in growth efficiency with greater leaf area likely is attributable to one or several of the factors previously identified as contributing to growth declines in mature, even-aged stands.

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A Model to Estimate Leaf Area Index in Loblolly Pine Plantations Using Landsat 5 and 7 Images

Remote Sensing ◽

10.3390/rs13061140 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1140

Author(s):

Stephen M. Kinane ◽

Cristian R. Montes ◽

Timothy J. Albaugh ◽

Deepak R. Mishra

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Loblolly Pine ◽

Vegetation Indices ◽

Pine Plantations ◽

Estimation Model ◽

Moisture Index ◽

Modeling Framework ◽

Area Index ◽

Extensive Evaluation

Vegetation indices calculated from remotely sensed satellite imagery are commonly used within empirically derived models to estimate leaf area index in loblolly pine plantations in the southeastern United States. The data used to parameterize the models typically come with observation errors, resulting in biased parameters. The objective of this study was to quantify and reduce the effects of observation errors on a leaf area index (LAI) estimation model using imagery from Landsat 5 TM and 7 ETM+ and over 1500 multitemporal measurements from a Li-Cor 2000 Plant Canopy Analyzer. Study data comes from a 16 quarter 1 ha plot with 1667 trees per hectare (2 m × 3 m spacing) fertilization and irrigation research site with re-measurements taken between 1992 and 2004. Using error-in-variable methods, we evaluated multiple vegetation indices, calculated errors associated with their observations, and corrected for them in the modeling process. We found that the normalized difference moisture index provided the best correlation with below canopy LAI measurements (76.4%). A nonlinear model that accounts for the nutritional status of the stand was found to provide the best estimates of LAI, with a root mean square error of 0.418. The analysis in this research provides a more extensive evaluation of common vegetation indices used to estimate LAI in loblolly pine plantations and a modeling framework that extends beyond the typical linear model. The proposed model provides a simple to use form allowing forest practitioners to evaluate LAI development and its uncertainty in historic pine plantations in a spatial and temporal context.

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Predicted leaf area growth and foliage efficiency of loblolly pine plantations

Forest Ecology and Management ◽

10.1016/s0378-1127(97)00022-4 ◽

1997 ◽

Vol 95 (2) ◽

pp. 109-115 ◽

Cited By ~ 5

Author(s):

Kunjin Shi ◽

Quang V Cao

Keyword(s):

Leaf Area ◽

Loblolly Pine ◽

Pine Plantations ◽

Area Growth ◽

Leaf Area Growth

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Using multispectral satellite imagery to estimate leaf area and response to silvicultural treatments in loblolly pine stands

Canadian Journal of Forest Research ◽

10.1139/x06-030 ◽

2006 ◽

Vol 36 (6) ◽

pp. 1587-1596 ◽

Cited By ~ 13

Author(s):

Francisco J Flores ◽

H Lee Allen ◽

Heather M Cheshire ◽

Jerry M Davis ◽

Montserrat Fuentes ◽

...

Keyword(s):

Leaf Area ◽

Loblolly Pine ◽

Vegetation Index ◽

Remote Sensing Data ◽

Pine Plantations ◽

Area Index ◽

Silvicultural Treatments ◽

Multispectral Satellite Imagery ◽

Landsat 7 ◽

Simple Ratio

The relationship between leaf area index (LAI) of loblolly pine plantations and the broadband simple ratio (SR) vegetation index calculated from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data was examined. An equation was derived to estimate LAI from readily available Landsat 7 ETM+ data. The equation developed to predict LAI with Landsat 7 ETM+ data was tested with ground LAI measurements taken in 12 plots. The root mean square error of prediction was 0.29, an error of approximately 14% in prediction. The ability of Landsat 7 ETM+ data to consistently estimate SR over time was tested using two scenes acquired on different dates during the winter (December to early March). Comparison between the two images on a pixel-by-pixel basis showed that approximately 96% of the pixels had a difference of <0.5 units of SR (approximately 0.3 units of LAI). When the comparison was made on a stand-by-stand basis (average stand SR), a maximum difference of 0.2 units of SR (approximately 0.12 units of LAI) was found. These results suggest that stand LAI of loblolly pine plantations can be accurately estimated from readily available remote sensing data and provide an opportunity to apply the findings from ecophysiological studies in field plots to forest management decisions at an operational scale.

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Leaf Area of Overstory and Understory in Pine Plantations in the Flatwoods

Southern Journal of Applied Forestry ◽

10.1093/sjaf/34.4.154 ◽

2010 ◽

Vol 34 (4) ◽

pp. 154-160 ◽

Cited By ~ 7

Author(s):

Alicia Peduzzi ◽

H. Lee Allen ◽

Randolph H. Wynne

Keyword(s):

Leaf Area ◽

Loblolly Pine ◽

Vegetation Index ◽

Landsat Imagery ◽

Vegetation Indices ◽

Slash Pine ◽

Pine Plantations ◽

Site Factors ◽

Biophysical Parameters ◽

Area Index

Abstract Leaf area index (LAI) was measured in summer and winter for the overstory and understory in 7- and 10-year-old loblolly and slash pine plantations on poorly drained, somewhat poorly drained, and moderately well-drained soils. LAI and vegetation indices (simple ratio [SR], normalized difference vegetation index [NDVI], vegetation index, and enhanced vegetation index) were also calculated using Landsat imagery. LAI values observed for the overstory were low in most of the plots (around 2 m2 m−2 in slash pine and around 3 m2 m−2 in loblolly pine), whereas the understory LAI was very high (around 2 m2 m−2), which can be attributed to the lack of canopy closure observed in all plots. No significant differences were found in the understory LAI values across soil drainage classes. Total LAI (overstory LAI plus understory LAI) values were weakly correlated with the vegetation indices. The LAI values estimated using Landsat data were typically half of the values estimated on the ground. Significant correlations were observed between the vegetation indices (SR and NDVI) and stand and site factors, suggesting that the satellite-derived indices were more related to the stand biophysical parameters than to in situ LAI estimates.

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Landsat 8 Based Leaf Area Index Estimation in Loblolly Pine Plantations

Forests ◽

10.3390/f10030222 ◽

2019 ◽

Vol 10 (3) ◽

pp. 222 ◽

Cited By ~ 6

Author(s):

Christine Blinn ◽

Matthew House ◽

Randolph Wynne ◽

Valerie Thomas ◽

Thomas Fox ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Loblolly Pine ◽

Empirical Model ◽

Vegetation Indices ◽

Pine Plantations ◽

Landsat 8 ◽

Surface Reflectance ◽

Area Index ◽

The Impact

Leaf area index (LAI) is an important biophysical parameter used to monitor, model, and manage loblolly pine plantations across the southeastern United States. Landsat provides forest scientists and managers the ability to obtain accurate and timely LAI estimates. The objective of this study was to investigate the relationship between loblolly pine LAI measured in situ (at both leaf area minimum and maximum through two growing seasons at two geographically disparate study areas) and vegetation indices calculated using data from Landsat 7 (ETM+) and Landsat 8 (OLI). Sub-objectives included examination of the impact of georegistration accuracy, comparison of top-of-atmosphere and surface reflectance, development of a new empirical model for the species and region, and comparison of the new empirical model with the current operational standard. Permanent plots for the collection of ground LAI measurements were established at two locations near Appomattox, Virginia and Tuscaloosa, Alabama in 2013 and 2014, respectively. Each plot is thirty by thirty meters in size and is located at least thirty meters from a stand boundary. Plot LAI measurements were collected twice a year using the LI-COR LAI-2200 Plant Canopy Analyzer. Ground measurements were used as dependent variables in ordinary least squares regressions with ETM+ and OLI-derived vegetation indices. We conclude that accurately-located ground LAI estimates at minimum and maximum LAI in loblolly pine stands can be combined and modeled with Landsat-derived vegetation indices using surface reflectance, particularly simple ratio (SR) and normalized difference moisture index (NDMI), across sites and sensors. The best resulting model (LAI = −0.00212 + 0.3329SR) appears not to saturate through an LAI of 5 and is an improvement over the current operational standard for loblolly pine monitoring, modeling, and management in this ecologically and economically important region.

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