Source: VIRGINIA POLYTECHNIC INSTITUTE submitted to NRP
AN INTEGRATED APPROACH TO MODEL FOREST THREE-DIMENSIONAL CANOPY ARCHITECTURE, LEAF PHYSIOLOGY, AND CARBON EXCHANGE
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
MCINTIRE-STENNIS
Reporting Frequency
Annual
Accession No.
0219864
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Oct 1, 2009
Project End Date
Sep 30, 2014
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
VIRGINIA POLYTECHNIC INSTITUTE
(N/A)
BLACKSBURG,VA 24061
Performing Department
Forest Resources and Environmental Conservation
Non Technical Summary
Global carbon modeling efforts require assumptions and oversimplifications that contribute to a large amount of uncertainty with predictions of ecosystem response to climate change. Models are weakened by the oversimplification of processes such as the interaction of sunlight with the forest canopy and the effects on photosynthesis. It is essential to develop a deeper understanding of the relationships between canopy physiology, the shortwave radiation regime within canopies, and carbon exchange. This study has four primary objectives that will improve our understanding of these relationships. Specifically the objectives are to: 1) Characterize changing forest structure and physiological properties due to latitude and species composition; 2) Determine, according to tree species, the relationships between photosynthesis, canopy biochemistry (i.e., the amount of chlorophyll and nitrogen in the leaves), canopy structure (the size and shapes of tree assemblages), and the vertical light profile; 3) Model how efficiently light is captured by the canopy for photosynthesis and the resulting effects on respiration, according to micrometeorological conditions, respiration, forest canopy structure, and foliar biochemistry; and 4) Assess improvements to models by comparing results to flux tower estimates and estimates derived from coarse-resolution (remote-sensing-based) national/global models. Data collection will include intensive field sampling efforts combined with remote sensing data acquisition at selected ecosystems. This will complement extensive on-going measurement efforts that are already established as part of the Canadian Carbon Program, AmeriFlux, and the North American Carbon Program. Statistical analysis will be used to determine the relationships between field measured variables. Cutting-edge remote sensing analysis techniques will be used to derive maps of variables related to ecosystem photosynthesis. These maps will be used as parameterize models of carbon exchange which will be driven by meteorological information. We anticipate improved understanding of carbon exchange across the landscape for our boreal and temperate sites and more accurate carbon modeling capabilities as a result of this research.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1230613107020%
1230613207010%
1237210107010%
1237210207010%
2050613107010%
2050613207010%
2057210107020%
2057210207010%
Knowledge Area
205 - Plant Management Systems; 123 - Management and Sustainability of Forest Resources;

Subject Of Investigation
7210 - Remote sensing equipment and technology; 0613 - Mixed conifer-broadleaf forests;

Field Of Science
2070 - Meteorology and climatology; 1070 - Ecology;
Goals / Objectives
The purpose of this study is to examine relationships between the three-dimensional (3-D) structure of the forest canopy, its shortwave radiation regime, and forest ecosystem photosynthesis and carbon exchange. This will be achieved through the following objectives and hypotheses: 1.) Characterize the spatial variability of canopy foliar biochemistry, canopy structure, and the fraction of photosynthetically active radiation absorbed by the canopy (FPAR) for selected boreal and temperate forest ecosystems where micrometeorological flux towers have been previously established. Hypothesis 1: For localized areas, the spatial variability of canopy chlorophyll concentration will vary according to species and canopy height and density. 2.)Determine, according to tree species, how leaf photosynthesis characteristics are influenced by foliar biochemistry, canopy structure, and the vertical light profile. Hypothesis 2: For a given species (under similar environmental conditions), canopy height-density and canopy chlorophyll concentration are directly related to FPAR and other leaf photosynthesis characteristics (e.g., the maximum rate of potential electron transport (Jmax), maximum rate of carboxylation (Vcmax), and light use efficiency). 3. Model light use efficiency (LUE), gross ecosystem productivity (GEP), and net ecosystem productivity (NEP) based on micrometeorological conditions, respiration, forest canopy structure, and foliar biochemistry. Hypothesis 3: There is a direct, inverse relationship between forest canopy height and density and NEP. 4. Assess improvements to models by comparing NEP and GEP from our model with flux tower estimates and estimates derived from coarse resolution (remote sensing-based) national/global models. Hypothesis 4: The influence of the vertical light profile on photosynthetic capacity is more pronounced in temperate forests than in boreal forests.
Project Methods
This work will require field visitations to measure the spatial variability of photosynthesis parameters and leaf biochemistry (leaf chlorophyll a, chlorophyll b, carotenoids, and nitrogen content) for several trees of each species. Multiple leaf samples will be collected from the tops of trees in the sunlit portion of the canopy to enable correlation to remotely sensed observations (e.g., Zarco-Tejada et al. 2001, O'Neill et al. 2002, Thomas et al. 2008). Field measurements will be repeated at strategic intervals (before, during, and after leaf-out, monthly during the summer, and during senescence) over the first 3 years of the study. The dates of these field campaigns will correspond to the collection dates for satellite hyperspectral imagery (Hyperion), as well as for Landsat and MODIS data (both Landsat and MODIS are collected and archived automatically). Discrete airborne lidar data and hyperspectral data will be (or already has been) collected over the sites. We will characterize the spatial variability of canopy physiology at the sites by first determining "units" with statistically separable biochemical signatures. Once these units are derived, they will be used in conjunction with lidar and hyperspectral remote sensing data to map the variability of canopy biochemistry across the entire study area. Spatial variability of FPAR: The spatial variability of FPAR within the flux tower footprints will be measured with a portable system of below-canopy PAR sensors that will be deployed at each site to capture a range of sunlight conditions. FPAR can then be estimated by comparing the below-canopy PAR values to the above-canopy PAR data collected at each flux tower (e.g. Thomas et al. 2006a). Statistical analysis will quantify the relationships between foliar biochemistry (chlorophyll and nitrogen), FPAR, and photosynthesis parameters. Maps of foliar biochemistry and photosynthesis parameters across the landscape will be generated that can be directly incorporated into Farquhar-based process models of photosynthesis. At a minimum, our work will enable 1) better parameterization of satellite-based process models driven by solar radiation, FPAR, light use efficiency or foliar biochemistry (such as the C-Fix model and PnET-CN discussed in the preliminary results) and 2) landscape application of simple empirical Farquhar-based models of photosynthesis driven by Vcmax and leaf nitrogen. Therefore, C-Fix, PnET-CN, and an empirical model will be run and compared to flux tower results by averaging the results within a superimposed footprint model for each time period. Comparisons will be made at 3-day, 10-day, monthly, and annual time scales.

Progress 10/01/09 to 09/30/14

Outputs
Target Audience: Target audience includes the broader scientific community, forestry professionals, and university students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Teaching efforts include a sophomore class called Forests, Society, and Climate which was taught to more than 60 students in the Spring of 2014. Other teaching included a PhD level class entitled Hyperspectral Remote Sensing for Natural Resources which covered the theory of imaging spectroscopy for plant physiology and other vegetation applications (Fall 2013). Additionally, FOR 1004 Digital Planet was designed and co-taught by V. Thomas and Randy Wynne in Fall 2013. This class is designed to introduce students to geospatial technologies around us, including how we interact with the environment and each other. Topics include the role of location-based services, global positioning systems, geographic information systems, remote sensing, virtual globes and web based mapping for environmental applications. Services in the area of counseling and tutoring occurred through the mentorship of graduate students in the Department of Forest Resources and Environmental Conservation and in the PhD in Geospatial and Environmental Analysis Program at Virginia Tech, as well as a new Interdisciplinary PhD Program in Remote Sensing. In the 2013-2014 year, the PIs were the major advisors for 5 PhD candidates and 1 masters student in these programs. How have the results been disseminated to communities of interest? Products in the 2013-2014 academic year include a completed PhD degree by N. Kayastha. This candidate was awarded the Oustanding PhD Student for the Department of Forest Resources and Environmental Conservation for 2013-2014. This work, and the on-going work of current graduate students, has been disseminated primarily at regional and national conferences, and reached an audience of more than 100 professional and academic people. The conference presentations are listed as follows: Stein, B., V.A. Thomas, L. Lorentz, and B. Strahm, 2014. "Predicting macronutrient concentrations from leaf reflectance in Loblolly Pine across multiple spatial scales". ASPRS 2014 Annual Conference. March 23-28, 2014. Louisville, Kentucky, USA. K. Correll, V. Thomas, and B. Strahm, 2014. "Stable Isotope Mapping at the Canopy Level in a Southern Peidmont Forest." ASPRS 2014 Annual Conference. March 23-28, 2014. Louisville, Kentucky, USA. Hwang, W.H., E.P. Wiseman, V.A. Thomas, 2014. "Tree Shade Produced by Various Tree Planting Configurations under Different Seasons and Geographic Latitudes. American Association of Geographers (AAG) Annual Conference, Tampa Bay, FL, April 8-12, 2014. Ranjith Gopalakrishnan, Valerie A. Thomas, John Coulston, Randolph H. Wynne. "Producing a canopy height map over a large region using heterogeneous lidar datasets." Virginia Tech Office of GIS and Remote Sensing (OGIS) Annual Research Symposium, April 4, 2014, Blacksburg, VA. Katie Correll, B. Strahm, and V. Thomas. "Mapping stable nitrogen isotopes using hyperspectral imagery." Virginia Tech Office of GIS and Remote Sensing (OGIS) Annual Research Symposium, April 4, 2014, Blacksburg, VA. Ling Yu, S. Ball, C. Blinn, K. Moeltner, S. Peery, V.A. Thomas, and R.H. Wynne. "Crowds for Clouds: Using an Internet Workforce to Interpret Clouds in Satellite Images." Virginia Tech Office of GIS and Remote Sensing (OGIS) Annual Research Symposium, April 4, 2014, Blacksburg, VA. Wu, Yl-J., V. A. Thomas, and R.D. Oliver, 2014. "Investigating Forest Conversion Across Several Scales of Urbanization in the Eastern United States". Virginia Tech Office of GIS and Remote Sensing (OGIS) Annual Research Symposium, April 4, 2014, Blacksburg, VA. Wu, Yl-J., V. A. Thomas, and R.D. Oliver, 2013. "Investigating Forest Conversion to Development Across Several Scales of Urbanization in the Eastern United States". 68th Annual Meeting of the Southeastern Division of the Association of American Geographers, Nov-24-26, 2013, Roanoke, VA. What do you plan to do during the next reporting period to accomplish the goals? Nothing Reported

Impacts
What was accomplished under these goals? Effective monitoring and modeling of forest health, productivity, and disturbance requires the use of remote sensing technology and algorithms. Most regional and global models of forest processes (e.g., net primary productivity) are weakened by oversimplification of processes and the inability to obtain reliable frequent measurements over large geographic extents. Two major questions have emerged to be critical areas of investigation in the fields of remote sensing and global monitoring of forest ecosystems. The first question is: How does forest structure relate to canopy physiology, and what drives changes in these relationships across geographic and environmental gradients? In other words, what controls forest productivity and how will forests respond to existing and future pressures? The second major question, which has rapidly emerged over the last several years is: How do we handle "Big Data" in the field of remote sensing to gain new insights into ecosystem function and disturbance? We have been approaching the first of these questions through the synergistic use of field data and two cutting-edge remote sensing technologies: light detection and ranging (lidar) and hyperspectral sensors. Simply described, lidar technology provides data that describes the three dimensional shape of objects encountered by its laser. We use these data to characterize various aspects of the physical the geometry of the forest, including the microtopography of the forest floor, canopy height, crown and stem density, leaf area, and other inventory-type measurements. In addition, we look at the light regime within the canopy, for functional questions related to canopy productivity. We use hyperspectral remote sensing to examine the reflection of sunlight off the canopy at many different wavelengths, which provides insight into canopy biochemistry, foliar isotopes, photosynthesis, stress, and other physiological indicators (e.g., Gokkaya et al. 2013, Stein et al. 2014). The second research question (big data) parallels similar issues in many other scientific fields that have emerged due to a number of converging factors including rapidly developing national and global environmental challenges, changes in technology, the compilation of many long-term sensor networks, and the general trend toward freely accessible massive multi-temporal remote sensing datasets, particularly the Landsat series. We are developing new computational approaches and techniques to better integrate big remote sensing data with field data for the assessment of forest coverage and disturbance (e.g., Brooks et al. 2014). Among numerous other findings, we have developed methods of detecting potential nutrient deficiencies that may limit the productivity of loblolly pine. Partial Least Squares Regression models have been found to perform well at the regional scale, with R2 values for nitrogen, phosphorus, potassium, calcium, and magnesium of 0.81, 0.70, 0.68, 0.42, and 0.51, respectively (Stein et al. 2013). Similarly, we have scaled models of chlorophyll from leaf to satellite in boreal ecosystems, both over time and space across multiple sensors (Gokkaya et al. 2013). Finally, we have developed 'big data' techniques that enable us to process and mine the historic and current archive of Landsat satellite imagery. We developed a harmonic regression approach to 'fill in' data gaps caused by weather disturbances and lapses in continuous cover. We then use residuals from harmonic regression over years of Landsat data, in conjunction with statistical quality control charts, to signal subtle disturbances in vegetative cover (Brooks et al. 2014).

Publications

  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Gokkaya, K., V. Thomas, H. McCaughey, and P. Treitz,. 2013. Testing the robustness of predictive models for chlorophyll generated from spaceborn imaging spectroscopy data for a mixedwood boreal forest canopy. International Journal of Remote Sensing, 35:1, 218-233.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Brooks, E.B., R.H. Wynne, V.A. Thomas, C.E. Blinn, and J.W. Coulston, 2014. On-the-fly massively multitemporal change detection using statistical quality control charts and Landsat data. IEEE Transactions on Geoscience and Remote Sensing, 52(6): 3316-3332.
  • Type: Journal Articles Status: Published Year Published: 2014 Citation: Stein, B., V.A. Thomas, L.J. Lorentz, and B.D. Strahm, 2014. Predicting macronutrient concentrations from loblolly pine leaf reflectance across local and regional scales, GIScience & Remote Sensing, 51:3, 269-287.
  • Type: Journal Articles Status: Awaiting Publication Year Published: 2014 Citation: 3. Gokkaya, K.*, V. Thomas, T. Noland, H. McCaughey, I Morrison, and P. Treitz, 2014 (in press). Mapping continuous forest type variation by means of correlating remotely sensed metrics to canopy nitrogen to phosphorus ratio in a boreal mixedwood forest. Applied Vegetation Science, Accepted May 25, 2014.


Progress 10/01/12 to 09/30/13

Outputs
Target Audience: Target audience includes the broader scientific community, foresty professionals, and university students. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided? Teaching effortsinclude a sophomore class called Forests, Society, and Climate which was taught to more than 30 students in the Spring of 2013. Other teaching included a PhD level class entitled Forestry Lidar Applications which covered the theory and applied use of lidar for forest and other natural resources (Fall 2012). Services in the area of counseling and tutoring occurred through the mentorship of graduate students in the Department of Forest Resources and Environmental Conservation and in the PhD in Geospatial and Environmental Analysis Program at Virginia Tech, as well as a new Interdisciplinary PhD Program in Remote Sensing. In the 2012-2013 year, the PIs were the major advisors for 6 PhD candidates and 3 masters students in these programs. How have the results been disseminated to communities of interest? Products in the 2012-2013 academic year include a completed MS degree by L. Lorentz an and a PhD awarded to E. Brooks. These two dissertations, and the on-going work of current graduate students, were disseminated primarily at national conferences, and reached an audience of more than 100 professional and academic people. The conference presentations are listed as follows. Quirino, V., R.H. Wynne, C. Huang, and V.A. Thomas, 2013. Evaluating three different remote sensing alternatives for estimating age of even-aged Loblolly pine stands located in Virginia, USA. SilviLaser 2013. Beijing, China, Oct. 9-11, 2013. Gopalakrishnan, R., J. Coulston, V.A. Thomas, and R.H. Wynne, 2013. Efficacy of using heterogeneous Lidar datasets in generating a tree height map, over a large region. SilviLaser 2013. Beijing, China, Oct. 9-11, 2013. Awadallab, M., A. Abbott, V.A. Thomas, R.H. Wynne, and R. Nelson, 2013. Estimating Forest Canopy Height and Biophysical Parameters Using Photon-counting Laser Altimetry. Silvilaser 2013. Beijing, China, Oct. 9-11, 2013. Brooks, E.B., R.H. Wynne, V.A. Thomas, C.E. Blinn, J.W. Coulston, P.J. Radtke, and C.E. Woodcock, 2013. Forest disturbance detection using harmonic regression and quality control charts on Landsat data. 79th Annual Meeting of the American Society for Photogrammetry and Remote Sensing, Baltimore, Maryland, March 24?28. Quirino, V.F., R.H. Wynne, H.E. Burkhart, and V.A. Thomas, 2013. Estimating age of even?aged loblolly pine plots from GeoSAR and Landsat ETM+ data. 79th Annual Meeting of the American Society for Photogrammetry and Remote Sensing, Baltimore, Maryland, March 24?28. Lorentz, L., V.A. Thomas, and B.D. Strahm, 2013. Hyperspectral prediction of foliar isotopic nitrogen, 79th ASPRS Annual Conference, Baltimore, MD, March 24-28, 2013. Lorentz, L., B.D. Strahm, and V.A. Thomas, 2013. Investigating the use of nitrogen stable isotopes to predict fertilizer growth response in loblolly pine, 17th Biennial Southern Silvicultural Research Conference, Shreveport, LA, March 5-7, 2013. Brooks, E.B., J.W. Coulston, R.H. Wynne, and V.A. Thomas, 2013. Improving the precision of dynamic forest parameter estimates using Landsat. 15th Annual OGIS Symposium, Blacksburg, Virginia, April 19, 2013. Gopalakrishnan, R., R. Wynne, and V. Thomas, 2013. Efficacy of using heterogeneous LIDAR datasets in generating a tree height map, over a large region, 15th Annual OGIS Symposium, Blacksburg, Virginia, April 19, 2013. Gopalakrishnan, R., R. Wynne, and V. Thomas. "Efficacy of using heterogeneous LIDAR datasets in generating a tree height map, over a large region”. PINEMAP Annual Meeting, Athens, Georgia, April 24?25, 2013. Quirino, V.F., R.H. Wynne, H.E. Burkhart, and V.A. Thomas, 2012. Using small-footprint, discrete return LiDAR to obtain stand level age of loblolly pine in central Virginia, USA, AGUFallMeeting, San Francisco, California, December 3?7. What do you plan to do during the next reporting period to accomplish the goals? We plan to continue moving forward in our ongoing efforts, which will include teaching, research, graduate student advising, presenting at conferences and publishing in scientific journals.

Impacts
What was accomplished under these goals? Outcomes from the 2012-2013 academic year include advancements in knowledge that can be used for future management (i.e., change in knowledge and, potentially, change in actions). The changes in knowledge include a new understanding of the impacts of land management decisions on ecosystem biodiversity in Virginia, as well as improved understanding between the relationships between forest structure (i.e., height, biomass, crown architecture), foliar macronutrients and canopy photosynthesis. This includes the development of improved remote-sensing based techniques to predict these variables. These techniques can be used to study nutrient status and carbon exchange for boreal mixed wood forests under varying forest management regimes, environmental conditions, and disturbances. All of these results have been published in peer-reviewed journals or in conference presentations (see above).

Publications

  • Type: Journal Articles Status: Accepted Year Published: 2013 Citation: Brooks, E.B.*, R.H. Wynne, V.A. Thomas, C.E. Blinn, and J.W. Coulston, 2013, in press. On-the-fly massively multitemporal change detection using statistical quality control charts and Landsat data. IEEE Transactions on Geoscience and Remote Sensing, DOI 10.1109/TGRS.2013.2272545.
  • Type: Journal Articles Status: Awaiting Publication Year Published: 2013 Citation: Gokkaya, K.*, V. Thomas, H. McCaughey, and P. Treitz,. 2013, in press. Testing the robustness of predictive models for chlorophyll generated from spaceborn imaging spectroscopy data for a mixedwood boreal forest canopy. International Journal of Remote Sensing, Accepted June 16, 2013.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Banskota, A.*, R.H. Wynne, V.A. Thomas, S.P. Servin, N. Kayastha, J.P. Gastellu-Etchegorry, and P.A. Townsend, 2013. Investigating the utility of wavelet transforms for inverting a 3-D radiative transfer model using hyperspectral data to retrieve forest LAI. Remote Sensing, 5: 2639-2659.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Kim, D., V. Thomas, J. Olson, M. Williams, and N. Clements, 2013. Statistical Trend and Change Point Analysis of Land Cover Change Patterns in East Africa. International Journal of Remote Sensing, 34(19): 6636-6650.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Banskota, A.*, R.H. Wynne, S.P. Serbin, N. Kayastha, V.A. Thomas, and P.A. Townsend, 2013. Utility of the Wavelet transform for LAI estimation using hyperspectral data. Photogrammetric Engineering & Remote Sensing, 79: 653-662.
  • Type: Journal Articles Status: Published Year Published: 2013 Citation: Kayastha, N.*, V. Thomas, J. Galbraith, and A. Banskota, 2012. Monitoring Wetland Change Using Inter-Annual Landsat Time-Series Data. Wetlands, 32(6): 1149-1162.
  • Type: Journal Articles Status: Published Year Published: 2012 Citation: Peduzzi, A.*, R.H. Wynne, V.A. Thomas, R.F. Nelson, J.J. Reis and M. Sanford, 2012. Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests. Remote Sensing, 4(6): 1758-1780.
  • Type: Journal Articles Status: Published Year Published: 2012 Citation: Brooks, E.B.*, V.A. Thomas, R.H. Wynne, and J.W. Coulston, 2012. Fitting the multitemporal curve: a fourier series approach to the missing data problem in remote sensing analysis. IEEE Transactions on Geoscience and Remote Sensing, 50(9): 3340-3353.


Progress 10/01/11 to 09/30/12

Outputs
OUTPUTS: Teaching Activities included a sophomore class at Virginia Tech, entitled Forests, Society, & Climate, which discussed the importance of global forests to society, their role in the carbon cycle, their importance for global biodiversity, and their links to climate. This course was taught to 24 undergraduate students in the Spring of 2012. Other teaching included a PhD level class entitled Hyperspectral Remote Sensing of Natural Resources, which covered topics including the physiology of the canopy, foliar biochemistry, and canopy processes, as well as the ability to predict these processes using remote sensing (Fall 2011). Services in the area of counseling and tutoring occurred through the mentorship of graduate students in the Department of Forest Resources and Environmental Conservation and in the PhD in Geospatial and Environmental Analysis Program at Virginia Tech. In the 2010-2011 year, the PIs were the major advisors for 6 PhD candidates and 2 masters students in these programs. Products in the 2011-2012 academic year include a completed MS degree by B. Stein, listed below, which was awarded the Outstanding MS Award by the College of Natural Resources and Environment at Virginia Tech. In addition, a PhD was awarded to K. Gokkaya, listed below. These two dissertations were disseminated primarily at national conferences, and reached an audience of more than 100 professional and academic people. The conference presentations are listed as follows. 1) Stein, B., Thomas, V. and D. Stauffer. 2012. Application of Geospatial Data to Wildlife Biodiversity Forecasts with Changing Land Use. American Society of Photogrammetry and Remote Sensing Annual Conference. March 19-23. Sacramento, CA.2) Stein, B., Thomas, V. and D. Stauffer. 2012. Assessing the Relationship Between Landscape Fragmentation and Wildlife Biodiversity in Virginia Ecoregions. Association of American Geographers. Feb. 24-28. New York, NY. 3)Gokkaya, K., Thomas, V., Noland, T., McCaughey, H., Treitz, P., and Morrison, I. 2012. Canopy pigment concentration estimation by spaceborne imaging spectroscopy in a boreal forest. American Society for Photogrammetry and Remote Sensing Annual Conference, Sacramento, CA, 19-23 March, 2012. PARTICIPANTS: Nothing significant to report during this reporting period. TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Outcomes from the 2011-2012 academic year include advancements in knowledge that can be used for future management (i.e., change in knowledge and, potentially, change in actions). The changes in knowledge include a new understanding of the impacts of land management decisions on ecosystem biodiversity in Virginia, as well as improved understanding between the relationships between forest structure (i.e., height, biomass, crown architecture), foliar macronutrients and canopy photosynthesis. This includes the development of improved remote-sensing based techniques to predict these variables. These techniques can be used to study nutrient status and carbon exchange for boreal mixedwood forests under varying forest management regimes, environmental conditions, and disturbances. All of these results have been published in peer-reviewed journals or in conference presentations (see above).

Publications

  • Kayastha, N., V. Thomas, J. Galbraith, 2012 (in press). Monitoring Wetland Change Using Inter-Annual Landsat Time-Series Data. Wetlands. Volume 32, Issue 6, pp 1149-116
  • Peduzzi, A., R.H. Wynne, V.A. Thomas, R.F. Nelson, J.J. Reis and M. Sanford, 2012. Combined Use of Airborne Lidar and DBInSAR Data to Estimate LAI in Temperate Mixed Forests. Remote Sensing, 4(6): 1758-1780.
  • Brooks, E.B., V.A. Thomas, R.H. Wynne, and J.W. Coulston, 2012. Fitting the multitemporal curve: a fourier series approach to the missing data problem in remote sensing analysis. IEEE Transactions on Geoscience and Remote Sensing. Volume 50, Issue 9, pp 3340 - 3353.
  • Peduzzi, A., R.H. Wynne, T.R. Fox, R.F. Nelson, and V.A. Thomas. 2012. Estimating leaf area index in intensively managed pine plantations using airborne laser scanning data. Forest Ecology and Management, 270: 54-65.
  • Stein, B. 2012. The relationship between wildlife biodiversity and landscape characteristics in Virginia. MS Thesis, Virginia Tech.
  • Gokkaya, K. 2012. The dissertation was entitled Prediction of Foliar Biochemistry in a Boreal Forest Canopy Using Imaging Spectroscopy and LiDAR Data. PhD Dissertation, Virginia Tech.
  • McCall, D.S, V.A. Thomas, and L. Lorentz, 2012. Early Detection of Stress on Annual Bluegrass on Putting Greens. Journal of the Virginia Turfgrass Council, May/June 2012.


Progress 10/01/10 to 09/30/11

Outputs
OUTPUTS: Services in the area of counseling and tutoring occurred through the mentorship of graduate students in the Department of Forest Resources and Environmental Conservation and in the PhD in Geospatial and Environmental Analysis Program at Virginia Tech. In the 2010-2011 year, the PIs were the major advisors for 9 PhD candidates and 2 masters students in these programs. Products in the 2010-2011 academic year include improved predictive modeling for foliar macronutrients, based on lidar and hyperspectral remote sensing. Specifically, models have been developed that can be applied in boreal mixedwood forest canopies for canopy nitrogen (N), phosphorus (P), the N:P ratio, magnesium, calcium, and potassium. In addition, relationships between these macronutrients and parameters of photosynthesis were modeled. These maps were presented at six institutional, national and international conferences (see below), and reached an audience of more than 100 professional and academic people. Dissemination of the work occurred primarily through presentations at conferences and through publications. The conference presentations are listed as follows. 1) Gokkaya, K., V. Thomas, T. Noland, R.H. Wynne, J.H. McCaughey, I. Morrison, and P.M. Treitz, 2011. Testing the temporal robustness of predictive Models for Forest Canopy Biochemistry Estimation. Poster presentation at the Virginia Tech GIS and Remote Sensing Research Symposium. Blacksburg, VA, April 8, 2011. 2) Brooks, E., V.A. Thomas, and R.H. Wynne, 2011. Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis. Poster presentation at the Virginia Tech GIS and Remote Sensing Research Symposium. Blacksburg, VA, April 8, 2011. 3) Brooks, E., V.A. Thomas, and R.H. Wynne, 2011. Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis. Oral presentation at the 3rd Annual FREC Graduate Research Symposium, Blacksburg, VA, April 8, 2011. 4) V. Thomas, M. Khomik, K. Gokkaya, J.H. McCaughey, A. Arain, and P. Treitz, 2011. Leaf and Canopy Physiology: Synergistic Use of Field Data and Remote Sensing. Presented at the Virginia Tech GIS and Remote Sensing Research Symposium. Blacksburg, VA, April 8, 2011. 5) Quirino, V., R.H. Wynne, J.R. Seiler, and V.A. Thomas.2011. Can soil respiration be estimated using remote sensing 77th Annual Meeting of the American Society for Photogrammetry and Remote Sensing, Milwaukee, Wisconsin, May 1-5. 6) Brooks, E., V.A. Thomas, and R.H. Wynne, 2011. Fitting the Multitemporal Curve: A Fourier Series Approach to the Missing Data Problem in Remote Sensing Analysis. Oral presentation at the 77th Annual Meeting of the American Society for Photogrammetry and Remote Sensing, Milwaukee, Wisconsin, May 1-5. PARTICIPANTS: Valerie Thomas, Assistant Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech. Randy Wynne, Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech. Collaborators: Paul Treitz, Head and Professor, Department of Geography, Queen's University, Kingston, ON, Canada Harry McCaughey, Professor, Department of Geography, Queen's Unversity, Kingston, ON, Canada Tom Noland, Ontario Forest Research Institute, Ontario Ministry of Natural Resources, Sault Ste. Marie, Canada TARGET AUDIENCES: The target audience is primarily scientists and forest resource managers. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Outcomes from the 2010-2011 academic year include advancements in knowledge that can be used for future management (i.e., change in knowledge and, potentially, change in actions). The changes in knowledge include a new understanding of foliar macronutrients and canopy photosynthesis. This includes the development of improved remote-sensing based techniques to predict these variables. These techniques can be used to study nutrient status and carbon exchance for boreal mixedwood forests under varying forest management regimes, environmental conditions, and disturbances. All of these results have been published in peer-reviewed journals or in conference presentations (see above).

Publications

  • Thomas, V., T. Noland, J.H. McCaughey, and P. Treitz (2011). Leaf area and clumping indices for a boreal mixedwood forest: lidar and hyperspectral models. International Journal of Remote Sensing, in press.
  • Thomas, V. (2011). Chapter 20. Hyperspectral remote sensing for forest management. In P.S. Thenkabail, J.G. Lyon, and A. Huete, editors, Hyperspectral Remote Sensing of Vegetation, Taylor and Francis, pages 469-487.


Progress 10/01/09 to 09/30/10

Outputs
OUTPUTS: Teaching Activities included the development of a new course taught in the spring of 2010. This course was entitled: Forests, Society, & Climate and discussed the importance of global forests to society, their role in the carbon cycle, their importance for global biodiversity, and their links to climate. This course was taught to 46 undergraduate students at Virginia Tech. In addition a 4 hour teaching seminar was offered in June of 2010 to an audience of community college teachers (approximately 40 people). This teaching seminar provided an introduction to lidar remote sensing. Teaching Products for this activity included the provision of slides and course notes on a DVD to this audience. Services in the area of counseling and tutoring occurred through the mentorship of graduate students in the Department of Forest Resources and Environmental Conservation and in the PhD in Geospatial and Environmental Analysis Program at Virginia Tech. The PIs are the major advisors for 9 PhD candidates in these programs. Products in the 2009-2010 academic year include the developed predictive models for leaf area and canopy clumping, as well as forest foliar nutrients, based on lidar and hyperspectral remote sensing. Specifically, models have been developed that can be applied in boreal mixedwood forest canopies for canopy nitrogen (N), phosphorus (P), the N:P ratio, magnesium, calcium, and potassium. These models have been applied to remote sensing data to create maps of these nutrients across boreal mixedwood canopies in northern Ontario, Canada. These maps were presented at six national and international conferences (see below), and reached an audience of more than 100 professional and academic people. Dissemination of the work occurred primarily through presentations at conferences and through publications. The conference presentations are listed as follows. Gokkaya, K., Thomas, V., Noland, T., Wynne, R., McCaughey, H., Morrison, I., and Treitz, P. 2009. Prediction of Foliar Biochemistry Using Canopy Reflectance and Structure Information. 30th Canadian Symposium on Remote Sensing. 22-25 June, 2009. Lethbridge, AB, Canada. Kayastha, N. and V. Thomas, 2009. Exploring approaches to extracting lidar points for LAI estimation. Presented at the Silvilaser 2009 in College Station, Texas. Kayastha, N. and V. Thomas, 2010. Exploring approaches to extracting lidar points for LAI estimation. Presented at the annual symposium of the Office of Geographic Information Systems and Remote Sensing, Virginia Tech. Award 3rd prize. V. Thomas, M. Khomik, J.H. McCaughey, A. Arain, and P. Treitz (2010) Leaf and Canopy Physiology: Synergistic Use of Field Measurements, Radiative Transfer Modeling, and Lidar-Hyperspectral Remote Sensing. Presented at the Canadian Remote Sensing Symposium, Prairie Summit in June 2010. Thomas, V., T. Noland, J.H. McCaughey, and P. Treitz. 2009. Lidar-hyperspectral analysis to examine leaf area index, clumping, and canopy biochemistry in a boreal mixedwood environment. Presented at the ASPRS 2009 Annual Conference, March 9-13, 2009. Baltimore, Maryland. PARTICIPANTS: Valerie Thomas, Assistant Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech. Randy Wynne, Professor, Department of Forest Resources and Environmental Conservation, Virginia Tech. Collaborators: Paul Treitz, Head and Professor, Department of Geography, Queen's University, Kingston, ON, Canada Harry McCaughey, Professor, Department of Geography, Queen's Unversity, Kingston, ON, Canada Tom Noland, Ontario Forest Research Institute, Ontario Ministry of Natural Resources, Sault Ste. Marie, Canada TARGET AUDIENCES: The target audience is primarily scientists and forest resource managers. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Outcomes from the 2009-2010 academic year include advancements in knowledge that can be used for future management (i.e., change in knowledge and, potentially, change in actions). The changes in knowledge include a new understanding of forest leaf area, clumping, and nutrient status according to boreal species. This includes the develop of new remote-sensing based techniques to predict these variables. These techniques can be used to study leaf area, clumping, and nutrient status for boreal mixedwood forests under varying forest management regimes, environmental conditions, and disturbances. All of these results have been published in peer-reviewed journals or in conference presentations (see above).

Publications

  • Treitz, P.M., V. Thomas, P.J. Zarco-Tejada, P. Gong, and P.J. Curran (2010). ASPRS Monograph - Hyperspectral Remote Sensing for Forestry. ASPRS Monograph Series, ISBN 1-57083-093-2, 107 pages.
  • Thomas, V., T. Noland, J.H. McCaughey, and P. Treitz (2010, in press). Leaf area and clumping indices for a boreal mixedwood forest: lidar and hyperspectral models. Submitted to the International Journal of Remote Sensing on Dec. 28, 2009.
  • Thomas, V., J.H. McCaughey, P. Treitz, D.A. Finch, T. Noland, T., and L. Rich, 2009. Spatial modelling of photosynthesis for a boreal mixedwood forest by integrating micrometeorological, lidar and hyperspectral remote sensing data. Agriculture and Forest Meteorology, 149:639-654.
  • Phillips RD, Blinn CE, Watson LT, et al. 2009. An Adaptive Noise-Filtering Algorithm for AVIRIS Data With Implications for Classification Accuracy, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Volume: 47 Issue: 9 Special Issue: Sp. Iss. SI Pages: 3168-3179 Published: SEP 2009
  • Pantaleoni E, Wynne RH, Galbraith JM, et al. 2009. Mapping wetlands using ASTER data: a comparison between classification trees and logistic regression. INTERNATIONAL JOURNAL OF REMOTE SENSING Volume: 30 Issue: 13 Pages: 3423-3440 Published: 2009
  • Pantaleoni E, Wynne RH, Galbraith JM, et al. 2009. A logit model for predicting wetland location using ASTER and GIS,INTERNATIONAL JOURNAL OF REMOTE SENSING Volume: 30 Issue: 9 Pages: 2215-2236 Published: 2009
  • Phillips RD, Watson LT, Wynne RH, et al. 2009. Feature reduction using a singular value decomposition for the iterative guided spectral class rejection hybrid classifier, ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING Volume: 64 Issue: 1 Pages: 107-116 Published: JAN 2009