B33N:
Monitoring Forest Structure, Productivity, and Change at the Intersection of Forest Modeling, Remote Sensing, and Field Measurements Posters


Submit an Abstract to this Session


Session ID#: 50945

Session Description:
Characterization and monitoring of forest productivity, structure, and composition are crucial for understanding current and future forest conditions and carbon stocks. Recent strides in the capabilities of remote sensing products and upgrades in computing power offer a new synergy with high-resolution forest models. When used in conjunction with fine-scale remote sensing measurements of forest characteristics, forest models provide a deeper understanding of the state of the forest through time. This remote sensing-modeling interface allows for more accurate estimates of forest biophysical parameters, updated forest allometric equations, improved remote sensing calibration algorithms, as well as increased confidence in modeling predictions. We seek studies that integrate high-resolution forest models with remote sensing observations to improve estimates of current ecosystem dynamics and state, including studies that predict forest response to environmental change.
Primary Convener:  Adrianna Foster, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Convener:  Amanda Hildt Armstrong, Universities Space Research Association, Columbia, MD, United States
Primary Liaison:  Adrianna Foster, NASA Goddard Space Flight Center, Greenbelt, MD, United States
Chairs:  Adrianna Foster, University of Virginia Main Campus, Charlottesville, United States and Amanda Hildt Armstrong, Universities Space Research Association, Columbia, MD, United States
OSPA Liaison:  Amanda Hildt Armstrong, Universities Space Research Association, Columbia, MD, United States
Index Terms:

0439 Ecosystems, structure and dynamics [BIOGEOSCIENCES]
0466 Modeling [BIOGEOSCIENCES]
0480 Remote sensing [BIOGEOSCIENCES]
1630 Impacts of global change [GLOBAL CHANGE]

Abstracts Submitted to this Session:

A Multi-scaled analysis of Forest Structure using Individual-Based Modeling in a Costa Rican Rainforest (394349)
Rico Fischer1, Amanda Hildt Armstrong2, Batuhan Osmanoglu3, Guoqing Sun4, Jon Ranson4 and Andreas Huth5, (1)Helmholtz Centre for Environmental Research - UFZ, Department of Ecological Modelling, Leipzig, Germany, (2)Universities Space Research Association, Columbia, MD, United States, (3)NASA Goddard Space Flight Center, Greenbelt, United States, (4)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (5)Helmholtz Centre for Environmental Research–UFZ, Department of Ecological Modelling, Leipzig, Germany
The Forest Resilience Threshold Experiment (FoRTE): An ecosystem experiment examining disturbance severity-production interactions (436166)
Lisa Haber1, Christopher Michael Gough2, Ben P Bond-Lamberty3 and Jeff Atkins1, (1)Virginia Commonwealth University, Biology, Richmond, United States, (2)Virginia Commonwealth University, Biology, Richmond, VA, United States, (3)Pacific Northwest National Laboratory, Joint Global Change Research Institute, Richland, WA, United States
Simulating Biological Disturbances Under Changing Climates: A Forest Dynamic Landscape Modeling Approach (459312)
Shengwu Duan1, Hong S. He2, Wen J. Wang2, Jacob S Fraser2 and Martin Spetich3, (1)University of Missouri-Columbia, School of Natural Resources, Columbia, MO, United States, (2)University of Missouri Columbia, School of Natural Resources, Columbia, MO, United States, (3)USDA Forest Service Southern Research Station, Hot Springs, AR, United States
Using Convolutional Network to Identify Tree Species Related to Forest Disturbance in a Neotropical Forest with very high resolution multispectral images (391437)
Fabien Hubert Wagner1, Alber Sanchez2, Yuliya Tarabalka3, Rodolfo G Lotte2, Matheus P Ferreira2, Marcos PM Aidar4, Manuel Gloor5, Oliver L. Phillips5 and Luiz Aragao6, (1)University of California Los Angeles, Los Angeles, United States, (2)INPE National Institute for Space Research, DSR, Sao Jose dos Campos, Brazil, (3)INRIA, Sophia Antipolis, France, (4)Institute of Botany, Department of Plant Physiology and Biochemistry, São Paulo, Brazil, (5)University of Leeds, School of Geography, Leeds, United Kingdom, (6)INPE National Institute for Space Research, Remote Sensing Division, Sao Jose dos Campos, Brazil
Multiscale Characterization of Tropical Forest Structure Integrating SAR Remote Sensing, Drone Mapping, and Microclimate Analysis (438044)
Derek Tesser, The Graduate Center, City University of New York, Earth and Environmental Sciences, New York, United States, Nick Steiner, The City College of New York, Earth and Atmospheric Science, New York, United States and Kyle C McDonald, City University of New York - City College, Earth and Atmospheric Sciences, New York, United States
Deep Images require Deep Learning: A Pixel-Based Convolutional Neural Network Classifier can Accurately Identify Tree Species Using Imaging Spectroscopy (364871)
Geoffrey A Fricker, California Polytechnic State University San Luis Obispo, San Luis Obispo, CA, United States, Janet Franklin, University of California, Riverside, Department of Botany and Plant Sciences, Riverside, CA, United States, Malcolm North, USDA Forest Service, Davis, CA, United States, Frank W Davis, La Kretz Research Center, Sedgwick Reserve, UC Santa Barbara, Santa Barbara, United States, Nicolas Synes, One Degree North, Manhattan Beach, CA, United States and Jeffrey A Wolf, Columbia University of New York, Palisades, NY, United States
Use of Time Series LiDAR to Quantify Stand Biomass Response to Fertilization at Larger Spatial Scales in Coastal Douglas-fir Forests. (447849)
John A Trofymow1,2, Jason Kelley1, Juha Metsaranta3 and Cosmin Filipescu4, (1)Natural Resources Canada, Canadian Forest Service, Victoria, BC, Canada, (2)University of Victoria, Biology, Victoria, BC, Canada, (3)Natural Resources Canada - Canadian Forest Service, Northern Forestry Centre, Edmonton, AB, Canada, (4)Natural Resources Canada - Canadian Forest Service, Canadian Wood Fibre Centre, Victoria, BC, Canada
LiDAR Based Classification of Forest Structures in Conifer-dominated Ecosystems in the Black Forest National Park (Germany) (430609)
Cyrus Samimi1, Florian Lang2, Sönke Birk3, Christoph Dreiser3 and Stefanie Gärtner3, (1)Faculty of Biology, Chemistry, and Earth Sciences, Research Group of Climatology, University of Bayreuth, Universitätsstraße 30, 95440 Bayreuth, Germany., Bayreuth, Germany, (2)University of Bayreuth, Bayreuth, Germany, (3)Black Forest National Park, Seebach, Germany
Individual Tree Mapping from LiDAR point clouds based on topological tools (419336)
Xin Xu, University of Maryland College Park, Department of Geographical Sciences, College Park, MD, United States, Federico Iuricich, Clemson University, School of Computing, College of Engineering, Computing and Applied Science, Clemson, United States and Leila De Floriani, University of Maryland College Park, Department of Geographical Sciences, College Park, United States
Retrieving gap fraction, clumping index, and leaf angle distribution for leaf area index estimations of deciduous trees from terrestrial LiDAR data (354186)
Tianyu Hu1, Yumei Li1, Yanjun Su2, Shichao Jin1 and Qinghua Guo3, (1)Institute of Botany, Chinese Academy of Sciences, Beijing, China, (2)Institute of Botany, Chinese Academy of Sciences, State Key Laboratory of Vegetation and Environmental Change, Beijing, China, (3)Peking University, Beijing, China
CONNECTING SATELLITE BASED SPECTRAL MODELLING APPROACH AND FOREST INVENTORY TO MODEL BIOMASS AND CARBON STOCKS IN NATURAL AND PLANTED FOREST OVER PART OF SEMI ARID ZONE, INDIA (434275)
Swati Uniyal, Andhra University, Visakhapatnam, India, Sarnam Singh, Indian Institute of Remote Sensing, Dehradun, India and Sitiraju Srinivasa Rao, RRSC- W National Remote Sensing center, ISRO, Jodhpur, India
Does tree diversity in North American forests influence carbon and water fluxes between ecosystems and the atmosphere? (456977)
Scott V Ollinger, University of New Hampshire, Earth Systems Research Center, Durham, United States, Andrew Ouimette, University of New Hampshire, Department of Natural Resources and the Environment, Durham, United States, Rebecca Sanders-DeMott, Boston University, Boston, MA, United States, Bobby H Braswell Jr, Indigo Ag, Boston, United States, Jingfeng Xiao, University of New Hampshire, Institute for the Study of Earth, Oceans, and Space, Earth Systems Research Center, Durham, United States and Lucie C Lepine, University of New Hampshire, Earth Systems Research Center, Durham, NH, United States

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