|Mila Alvarez||The State of Americas Forests: An Interactive Guide||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The State of Americas Forests is a website that tells a story of consumption and conservation, of conflict and collaboration. But most of all, it is a story of regrowth, renewal, and abundance. This online multimedia guide presents a comprehensive overview of Americas forests, the many ecosystem services they provide to society, and challenges that threaten forests. It offers a graphical view of authoritative data from the FIA Program and many other public and private sources.||State of Americas Forests is an online multimedia guide that puts authoritative information related to our nation´s forests in the hands of the public and professionals in intuitive ways. Exploratory maps, graphs, charts and videos help users to better understand the importance of forests as a source of clean water, clean air, human wellbeing, biodiversity, recreation, products, economic development, and many other benefits and services.
The website alerts of the many challenges that threaten forests existence and health, and undermine the many ecosystem services they provide to society, and particularly, to rural, forest-dependent communities. A careful analysis of wildfire, insect and disease outbreaks, invasive species, species at risk of extinction, housing development, forest fragmentation, and drought shows the degree of vulnerability forests face today and how one threat often compounds another.
Users also can explore trends over time, conditions defining our forest landscapes, the stewardship embraced throughout the different regions, and strategies adopted to conserve and protect a resource that blankets fully one-third of our landscape.
Visit State of Americas Forests at www.usaforests.org.
|Michael Bell||The Critical Loads Mapper Tool: Mapping FIA tree and lichen responses to air pollution for management applications||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Critical Loads Mapper tool (CL Mapper) is a joint project supported by the Environmental Protection Agency (EPA), USDA Forest Service (USFS), and the National Park Service (NPS) to make information more accessible on effects from atmospheric deposition of nitrogen (N) and sulfur (S). The CL Mapper is an interactive mapping tool that enables decision makers, researchers, and the public to easily access information for the coterminous U.S. on: 1) atmospheric deposition of N and S (estimates through time are provided for several different air quality models), 2) critical loads for terrestrial and aquatic ecosystems (from the National Atmospheric Deposition Program's National Critical Loads Database), and 3) critical load exceedances (defined as the deposition minus the critical load).|
|Erik Berg||Volume equations for planted Paulownia grown in unmanaged stands in the Southern Appalachians||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Three combined-species stem volume models were developed for three Paulownia species as functions of 1) DBH squared, 2) the product DBH squared and total height and 3) the product diameter ground line squared and total height. Parameterized equations generally aligned with those developed for Paulownia species in China. Results of our study provide managers information on productivity of three species of Paulownia that can be used for estimating plantation yields.||Little is known of the individual tree volumes of planted Paulownia left unmanaged until harvest in the southeastern United States. We sought to remedy this lack of information needed by land managers to make informed decisions by characterizing individual tree volumes of planted P. elongata, P. fortunei, and P. tomentosa in the cool-moist environment of the southern Appalachian Mountains. Three combined-species stem volume models were developed as functions of 1) DBH squared, 2) the product DBH squared and total height and 3) the product diameter ground line squared and total height. Parameterized equations generally aligned with those developed for Paulownia species in China. Results of our study provide managers information on Paulownia tree volumes that can be used for estimating plantation yields.|
|Mike Boyle||Leveraging Visual Analytics for Data-Driven Customer-Focused Decision Making||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||In every governmental agency, data is a strategic asset. For USDA, becoming a facts-based, data-driven, customer-focused organization is a top priority. To help realize this goal, USDA is leveraging Tableau as a visual analytics departmental standard to analyze, visualize, and share information to make fact-based, customer-focused decisions.|
Building on last years CXO Dashboard effort, the USDA Data Analytics Center of Excellence has partnered with mission areas, including Forest Service, to stand up dashboards to improve program effectiveness, availability and expenditure of resources, customer distribution and needs, customer service, and highlight key indicators of risk.
The initial twelve dashboards at Forest Service used existing datasets to build visualizations for Recreation, Fire, Hazardous Fuels, Engineering, Timber, Watershed, NEPA, Grants and Agreements, Budget and Safety. The dashboards use robust analytical tools and data visualizations to summarize and present information and support executive decision-making.
|Greg Brunner||Development and delivery of raster forest inventory data products and decision support tools using FIA field plots, dense time series of Landsat imagery, and Esri ArcGIS Enterprise in the AWS Cloud||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||NEED - TY Wilson has be asked|
|Jesse Caputo||The National Woodland Owner Survey (NWOS) Dashboard and Custom Reporting Tool||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The NWOS Data Visualization Tool is being built using the R Shiny platform, an open-source tool for creating interactive data dashboards and visualization tools that integrate fully with the R language, as well as with CSS and HTML. In order to maintain data security and avoid disclosure issues, the tool will not interact with any raw data. Instead, the tool will be built around pre-calculated arrays containing estimates for many (ultimately most) permutations of question, population, and domain||The official estimates resulting from the previous cycle (2011-2013) of the National Woodland Owner Survey (NWOS) resulted in almost two thousand pages, with many tens of thousands of individual estimates. These tables were published electronically as a USDA Forest Service General Technical Report comprising dozens of individual files. Although static documents have an important place in any data dissemination strategy, these formats are not the most intuitive or accessible for many users of public data. Since public utility is one of the primary justifications for public investment in data, it is important to seek to do better. In the current NWOS cycle, we intend on once again releasing a comprehensive publication containing tables of estimates for states, regions, and the country as a whole. In addition, however, we plan on providing a dynamic, interactive tool for accessing plots and tables of estimates across the populations, domains, and questions of the NWOS. Here we present an early version of this tool (using R Shiny), with an emphasis on univariate statistics. Future iterations of the tool will include functionality for cross-tabulations as well as custom data reporting, building off of the current NWOS Table Maker.|
|Brian Clough||Model-assisted, pixel level inventories for regional management planning: an application of SilviaTerra Basemap||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||This presentation introduces SilviaTerra Basemap, a pixel-level model assisted inventory product that is based on FIA and remote sensing datasets. To demonstrate the utility of our approach for regional management planning, we use Basemap information to map the distribution of mixed conifer forest and associated risk of bark beetle outbreak in the Carson National Forest, New Mexico, USA.||Using FIA data to guide management decisions at local to regional scales requires computational systems that are capable of predicting forest composition at fine resolution. Collaborating with Microsoft's AI for Earth program in 2018 and 2019, SilviaTerra has developed Basemap, a pixel-level data product based on FIA and remote sensing data that carries the forest attributes necessary to estimate forest populations at any scale. To demonstrate its utility for guiding management decisions, we use Basemap to derive the distribution of mixed conifer forests and associated risk for bark beetle outbreak in the Carson National Forest, New Mexico, USA. While the core of the data product is a suite of predictive models, we make use of model-assisted inventory methods to ensure top level consistency with large area estimates from FIA data. This feature makes Basemap highly scalable, and allows it to accommodate general attribution of a variety of derived variables (e.g., volume, biomass, wildlife habitat quality, etc.) within the FIA inventory framework. In addition to demonstrating its potential, planned future improvements to improve the accuracy and precision of the data will be discussed.|
|Jason Cooper||One Click for Timber Products Output data and a table generator built with Tableau.||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Southern Timber Product Output (TPO) Group has developed new TPO digital engagement tools which include the One-Click TPO Factsheets and the TPO Core Tables Generator. The One-Click TPO application allows users to view the most recent TPO survey summary data by state by using an interactive map interface. TPO Core Tables Generator populates ten core TPO tables for viewing once users select a state of interest from an interactive map interface. Both digital products will allow customers access to TPO data in a timelier manner with visual tables and charts customized by the user.|
|Sarah Crow||Forests in Focus: Assess Risk, Identify Opportunities, Make an Impact||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Forest in Focus (FF) is an innovative new platform to identify risk in forest product supply chains and provide opportunities for achieving positive conservation impacts through the engagement of family forest owners. Currently under development, Forests in Focus is a powerful data tool that gives users the business intelligence to help define, measure, and communicate their commitment to sustainable forest management to consumers, shareholders, and other stakeholders.||Forests in Focus provides a brand new view into woodbaskets with a dynamic, landscape-scale assessment of risk that offers insights to help verify responsible sourcing of wood fiber as well as identifying opportunities to invest in conservation impact through engagement of family forest owners. The American Forest Foundation (AFF) and GreenBlue have partnered with leaders at Forest Inventory and Analysis (FIA), Esri and NatureServe to develop an innovative interactive online dashboard to provide easy access to critical sustainability understanding and insight. With funding and partnership of a suite of companies including McDonald's, Mars, Staples, Georgia-Pacific, Domtar, Weyerhaeuser, WestRock and others, Forests in Focus represents a practical and powerful leveraging of FIA data and talent.|
|Mansfield Fisher||Spatial and Temporal Trends of Forest Type Transitions in the US Southeast||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Land use change literature focused on the US South demonstrates that increased returns to forestland leads to forest acreage expansion. Previous work links increased wood pellet demand with forest management intensification, the objective of this study is to analyze the relationship between expanding industrial plantation acreage and forest type transitions. Using data from the FIA Program, we look at forest type transitions temporally and spatially across the US South.||Land use change literature focused on the US South demonstrates that increased returns to forestland ultimately leads to forest acreage expansion. However, there is substantially less work on the relationship between forest rents and the expansion or contraction of specific forest types. Expanding on previous work linking increased wood pellet demand with forest management intensification, the objective of this study is to analyze the relationship between expanding industrial plantation acreage and forest type transitions. Using data from the Forest Inventory and Analysis Program, we look at forest type transitions temporally and spatially across the US South. Building forest type transition matrices based on state and intrastate-regions allows us to understand which forest types are experiencing the highest levels of intensification. Ongoing research is being performed to determine the statistical significance of spatial and temporal trends of forest type conversions. Developing a better understanding of which types of natural systems are being converted to plantations, and understanding the factors driving these conversions, will enable a more comprehensive analysis of the impact of expanding wood pellet demand.|
|Tracey Frescino||FIESTA!||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||FIESTA (Forest Inventory ESTimation and Analysis) is an open-source, R estimation package designed to efficiently process and translate multi-scale resource data to information. It provides a flexible platform to accommodate unique research questions such as on-the-fly estimation over user-defined polygons. It enables use of auxiliary data from a wide variety of remote sensing instruments and allows FIA to make use of statistical advances in areas such as model-assisted and small area estimation||Come to the party! This will be a lively demonstration of FIESTA (Forest Inventory ESTimation and Analysis) which is an open-source, R estimation package designed to efficiently process and translate multi-scale resource data to information. FIESTA was developed to support current available FIA tools such as EVALIDator. It provides a flexible platform to accommodate unique research questions such as on-the-fly estimation over user-defined polygons. It enables the use of auxiliary data from a wide variety of remote sensing instruments. It also allows FIA to make use of statistical advances in areas such as model-assisted, model-based and small area estimation. In this live demo, we provide an overview of the package, demonstrate complex spatial manipulations, illustrate estimation options for applications on National Forest Systems lands, and show options for creating rapid response estimates for disturbance events. Visitors will get a sense of how FIESTAs flexible, open-source strategy allows for accessibility, adaptability, and integration with other R packages and other software platforms -- helping bridge the gap between science and FIA production. Early visitors will have the opportunity to win prizes, so dont be late!|
|James Garner||Forests of Southern New England 2017 Digital Report||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||NRS FIA has adapted its quinquennial comprehensive forest status and trends report from a traditional printed layout into a suite of interconnected applications integrating the next generation of ArcGIS Online (AGOL) story maps with AGOL and Tableau dashboards. This dynamic presentation platform enables the user interact with and explore the maps, charts, and dashboards included in the report, along with an entire network of supporting information available in related websites and applications,||NRS FIA has adapted its quinquennial comprehensive forest status and trends report from a traditional printed layout into a suite of interconnected applications integrating the next generation of ArcGIS Online (AGOL) story maps with AGOL and Tableau dashboards. This dynamic presentation platform enables the user interact with and explore the maps, charts, and dashboards included in the report, along with an entire network of supporting information available in related websites and applications, all within the same browser window.|
|Andrew Hait||Census Bureau Data Dashboards||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||An overview of both the demographic and business data available from the US Census Bureau and how forest industry researchers and others can use the information in their work. We will also explore various Census data platforms that include these data, including the Census API that makes it easier for web site and software developers to access these data. One of these platforms, Census Business Builder, makes it easier for users who are unfamiliar with Census data products to access the key information they need via an interactive, cloud-based tool. Real-life use cases will be explored, using both the Small Business and Regional Analyst Editions of CBB.|
|Salma Huque||Forestry Data Science: Classification and Estimation||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||We explored alternatives to the current existing vegetation type variable's classification created by the USDA's LANDFIRE program using k-means clustering. We also investigated the underestimation issues of the out-of-bag mean squared error in random forest models using longitudinal data. We demonstrated this underestimation in a simulation incorporating remote-sensing data and satellite imagery from Daggett County, UT and offered solutions for using random forests with longitudinal data.||In this poster, we will present the findings of a forestry data science undergraduate research experience. This opportunity was a joint venture between FIA, Reed College, and Swarthmore College. We explored alternatives to the current existing vegetation type (EVT) classification method created by the USDA's LANDFIRE program. We used k-means clustering to create two new classification schemes that grouped EVT according to four key response variables. FIA can apply this scheme to improve existing estimators that rely on auxiliary data, such as the post-stratified estimator. We also investigated the underestimation of the predicted mean squared error of a random forest model when estimated by the out-of-bag mean squared error of a model built using longitudinal data. We demonstrated this underestimation in a simulation incorporating remote-sensing data and satellite imagery from Daggett County, UT. Finally, we offer potential solutions and best practices for using random forests with longitudinal data. These findings have implications for how FIA approaches classification and regression in their estimation methods.|
|Scott Jones||A Novel Approach to Using FIA Data in the Assessment of Biodiversity||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The use of FIA data in the assessment of biological diversity is associated with improvements to the indicators of the Conservation of Biological Diversity which is Criterion 1 of the Montreal Process Criteria and Indicator framework for forest sustainability. It is part of a larger effort focusing on further development of the entire criteria and indicator framework to make it more useful to managers, address smaller jurisdictions/landscapes that nations and to use existing data.||There have been many state of the forest reports and Forest Action Plan landscape assessments that have used the indicators of the Montreal Process for the Conservation of Biological Diversity and all attempts have produced less than useful results that also don't compare across time periods of assessment. A new approach is proposed using readily available FIA data sets for forest unit type (Community Diversity) and tree species type (Species Diversity) which allow for the calculation of Simpson's Diversity Index and a measure of evenness for forest communities and tree species. This approach allows for easy cross-period comparison, the identification of trends and eliminates the weakness of using only species richness. The approach also uses a new way of looking at Genetic Diversity using the categories of leading edge species, trailing edge species and herbaceous plant outlier species in addition to threatened and endangered species.|
|Kasey Legaard||The Maine ForEST (Forest Ecosystem Status and Trends) App: Data and tools to support landscape planning and forest risk analysis in real time||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Maine ForEST (Forest Ecosystem Status and Trends) App was developed to support risk analysis and landscape planning during an upcoming outbreak of the eastern spruce budworm. The ForEST App delivers up-to-date spatial information on key timber and non-timber resources through an intuitive web interface that includes visualization and summary analysis tools. Our intent is to enhance decision support by simplifying the delivery of valuable information to Maines diverse forest stakeholders.||The southern expansion of an ongoing outbreak of eastern spruce budworm is without question a leading threat to Maine's forest economy. In principle, timber loss to defoliation can be mitigated by early harvesting of vulnerable trees, application of insecticides, or salvage logging of infested trees. In practice, mitigation incurs economic, ecological, and social costs. Reducing the costs and enhancing the benefits of management decisions will require knowledge of both timber and non-timber resources, and their vulnerabilities. The Maine ForEST (Forest Ecosystem Status and Trends) App is a web mapping application that delivers high-value geospatial data relevant to budworm risk analysis and landscape planning through a user-friendly interface. Accurate and up-to-date spatial information on forest resources of high interest is provided through state-of-the-art machine learning methods applied to multispectral satellite imagery and FIA data. Visualization and summary analysis tools distill the complexity of forest landscape conditions into key pieces of information with minimal user effort. Our intent is to provide decision support to Maines diverse forest stakeholders throughout the next budworm outbreak.|
|Sarah Maebius||Post-Stratification and Variance Estimation in Forestry Data Science||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||We compared the relative efficiencies of FIA-IW's current post-stratification scheme with five other post-stratification schemes that stratify by groups including auxiliary data for three other variables: biomass, forest probability, and tree canopy cover. We also evaluated the performance of several model-assisted estimators for variance of the mean estimate of ndvi values for Daggett County under a systematic sample.||This poster presents the culmination of undergraduate research focused on the field of forestry data science. The experience combined efforts of representatives from FIA, Reed College, and Swarthmore College. For data collected under a systematic sampling design, we investigated the impacts of estimating the variance of a mean estimator using the standard FIA estimator, which assumes the systematic design can be approximated by a simple random sampling design and we tested out variance estimators that account for spatial autocorrelation. Conducting a simulation study, which involved taking many systematic samples from ndvi values in Daggett County, we concluded that the standard method of variance estimation could lead to biased approximations.
For another project, we explored new post-stratification schemes for FIA-IW. With access to auxiliary data, we proposed five schemes stratifying by levels of biomass, forest probability, and tree canopy cover. We concluded that a stratification scheme based on forest probability separated into four strata improves precision over FIAs current method of post-stratifying by forested and non-forested areas.
|Dacia Meneguzzo||Tree resources of the Great Plains interactive map viewer||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Statewide high-resolution (1-m) datasets of tree cover have been created and published for Kansas and Nebraska. Having such detailed spatial information about tree cover provides opportunities to create value-added products that quantify the ecosystem services provided by trees outside forests. In this digital presentation, the user can view these fine-scale geospatial products that describe the location, extent, and services provided by these important tree resources.||Windbreaks and narrow riparian corridors are an undercounted tree resource particularly in agricultural landscapes. Existing geospatial datasets developed using 30-m Landsat data often prone to high rates of commission errors because these features are generally small relative to the pixel size. To address this challenge, the Forest Inventory and Analysis program and the USDA National Agroforestry Center have partnered to develop methodologies for mapping tree cover using high-resolution 1-m NAIP imagery. In this showcase, we will take the user on a tour highlighting the prevalence and diversity of trees outside forests in Nebraska and Kansas. Digital datasets have been created in partnership with the Kansas Forest Service and the University of Nebraska-Lincoln. Using ArcGIS Online, this map application will allow the user to view the high resolution datasets as well as other readily available layers which can be useful for quantifying ecosystem functions of these trees. The detailed spatial products represent the potential for scalable and consistent monitoring of these tree resources across the agricultural areas prevalent in the central United States.|
|Scott Pugh||APPLYING THE TIMBER PRODUCT OUTPUT (TPO) EXPLORER DASHBOARD WITH THE TPO SURVEY OF THE FOREST INVENTORY & ANALYSIS PROGRAM||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The TPO Explorer is an online dashboard for investigating the current status and trends of timber harvest and roundwood use across the United States. Dashboard users can analyze and download TPO data by interacting with tables, graphs and maps. The data are from nationally consistent tables still in development and supplied by the TPO Survey Program. After finalizing the tables, the dashboard will be available as one of the new national TPO reporting tools.||The TPO Explorer is an online dashboard for investigating the current status and trends of timber harvest and roundwood use across the United States. Dashboard users can analyze and download TPO data by interacting with tables, graphs and maps. Views can be exported in various formats. The data are from nationally consistent tables still in development and originate from historic periodic and recent annual mill surveys of the TPO Survey Program. The program tracks the size and location of mills, the volume of roundwood product received, use of roundwood, and the disposition of mill and logging residue. The program is working toward achieving national consistency in data collection, processing and reporting tools. After finalizing the tables, the dashboard will be available as one of the new national TPO reporting tools.|
|Tracy Roof||Demonstrating the use of the Design and Analysis Toolkit for Inventory and Monitoring (DATIM) primarily using ATIM and SIT modules.||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Design and Analysis Toolkit for Inventory and Monitoring (DATIM) is a collection of applications and tools for inventory and planning purposes. This digital engagement will demonstrate DATIM focusing on ATIM and the Spatial Intersection Tool (SIT).||ATIM and EVALIDator are integrated to provide access to new estimates and allows users to run reports using the latest FIADB data. The SIT tool provides a streamlined user interface to allow users to generate new attributes using their own spatial data and will soon allow authorized users to securely intersect against real plot coordinates. DATIMs report management tool allows users to edit and share their existing reports. This digital engagement will present these new features within DATIM.
The Toolkit consists of :
(ATIM) Analysis Tool for Inventory and Monitoring
(DTIM) Design Tool for Inventory and Monitoring
(SIT) Spatial Intersection Tool
(DCS) DATIM Compilation System
|Ernesto Rubio-Camacho||Multilevel tree height models for the Mexican NFI: An alternative for data imputation and prediction||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The aim of this study is to contribute to Mexico's NFI through the generation of a unique model for predicting the height of pine trees. For this purpose, we used 150,649 pairs of tree height-diameter data from Mexicos NFI; Three classical models were fitted throughout non-linear mixed effects approximation. The best was the Näslund model with AIC = 647279, RMSE = 1.83 and R2 = 0.88. This is the first model fitted at national scale in Mexico and it is proposed a tool for the Mexican NFI.||Tree height is used to calculate a variety of parameters such as volume, biomass and site index. However, estimating tree height is time-consuming, labor-intensive and prone to measurement errors, especially in national forest inventories (NFI). The aim of this study is to contribute to Mexico's NFI through the generation of a unique model for predicting the height of pine trees. For this purpose, we used 150,649 pairs of tree height-diameter data from 6,334 plots of Mexicos NFI database (2009-14). Three classical models, i) Näslund, ii) Curtis and iii) Schumacher were fitted throughout non-linear mixed effects approximation, using the plot as random effect. The parameters were estimated via restricted maximum likelihood (REML), while Aike's Information Criterion (AIC), root mean squared error (RMSE) and coefficient of determination R2 were used for ranking purposes. The best was the Näslund model with AIC = 647279, RMSE = 1.83 and R2 = 0.88. These results are consistent with similar studies in other countries. This is the first model fitted at national scale in Mexico, using the plot as source of random-effects for Pinus and it is proposed as a new tool for the Mexican NFI, representing an alternative for database management.|
|Karen Schleeweis||FIA and LANDFIRE 15 Years of Partnership||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||More than 15 years ago the need was recognized for national breath, locally relevant geospatial data to support Wildland Fire Decision Support. The LANDFIRE project was created to fill this need and FIA plot data and expertise has been critical to helping the LANDFIRE project meet its mission. This story map will guide its audience through a multi-media experience on this partnership, LANDFIRE data and applications over parts of the National Forest System.||More than 15 years ago the need was recognized for national breath, locally relevant geospatial data to support Wildland Fire Decision Support. The LANDFIRE project was created to fill this need and FIA plot data and expertise has been critical to helping the LANDFIRE project meet its mission. This story map will guide its audience through a multi-media experience to understand how FIA has helped support national LANDFIRE vegetation and structure mapping, how the project data supports fire decision management community and other ecological applications and how FIA partners, such as national forests are meeting planning needs by using LANDFIRE maps.|
|John Shaw||Using FIA Data in the Forest Vegetation Simulator||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||This digital engagement session is designed to provide a basic overview of FVS and its capabilities, and to illustrate a few of the many ways that FIA data can be used. It is a companion to the regular program presentation A New Source for FIA Data Suitable for Use in the Forest Vegetation Simulator.||The Forest Vegetation Simulator (FVS), maintained by the U.S. Forest Service Forest Management Service Center, is the primary tool for stand projection within the Forest Service, but FVS is widely used in other federal and state agencies, academia, and private consulting. The return of FVS-ready FIA data to the FIA Datamart begins a new period of easy access to FIA plot data for use in FVS, and new opportunities for use of projected FIA data in state reports and other analyses. This digital engagement session is designed to provide a basic overview of FVS and its capabilities, and to illustrate a few of the many ways that FIA data can be used. This Digital Engagement Session is a companion to the regular program presentation A New Source for FIA Data Suitable for Use in the Forest Vegetation Simulator.|
|Douglas Stevenson||The Plague of the Edge Zone - New correction method for area, individual tree probability and statistical distortion of cruises created by the presence of edge plots.||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||A look at mathematics and computations of forest inventory plots that fall in or near the edge zone. Edge plots may violate homoscedasticity and independence, two conditions necessary for successful measurement. Double Meridian Distance provides a new way to correct for reduced plot area. Use of a computer allows the forester/cruiser to make the proper measurements while in the field. Plot area, individual- tree sampling probability and statistics of "ghost trees" are examined.||Inventory plots overlapping a stand boundary create size, probability and statistical problems plaguing foresters. Double Meridian Distance allows a correction factor to be calculated for the smaller (net) plot area. A zigzagging stand boundary is used as a reflection surface to determine individual tree weights for the Mirage Method. Both techniques are applied to curving stand boundaries such as roads and rivers. The method works on plots with any number of sides up to infinity. The methods are computationally intensive and require programming and a computational device to use in the field.
Trees in the edge strip have a reduced sampling probability which invalidates homoscedasticity; edge plots cannot be moved or deleted, but must be corrected instead. A process similar to the mirage method can be used to compute corrections on a tree-by-tree basis.
Ghost trees created by the Mirage Method and as a result of applying correction factors are not real trees. They do not contribute to degrees of freedom. Cruise statistics are distorted by their presence and must be corrected.
Correction methods will be reviewed and illustrated using a PowerPoint presentation and/or a printed poster presentation.
|Sergio Villela Gaytán||National inventory plots as random effects help explain the crown plasticity of mangroves||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||We contribute to the knowledge of mangrove ecosystems on the NFI of México using information from 74 plots to construct a multiple linear mixed effects model, the covariates were the diameter of the tree and the total height, while the random effects were the plots. The final mixed model had a cAIC = 7386.6 RMSE = 1,141 of and R2 = 0.66. In conclusion, mixed effects models become a useful tool not only for prediction but also to explain ecological processes.||We contribute to the knowledge of mangrove ecosystems through the Mexican National Forest Inventory information through building a model for prediction the crown width of mangroves using mixed effects models. We used information of 74 plots to build a multiple linear mixed effects model, the covariates were tree diameter and total height, while the random effects were the plots. The parameters were estimated via REML and AIC, the root mean squared error and the coefficient of determination R2 to evaluate the model. The mixed model was tested against the regular linear model through the Likelihood Ratio Test in order to assess the influence of the random effects. The random effects help explain the crown variation of mangroves. The results of the comparative procedures showed a better behaviour of the mixed model (x2(1) = 1424, p < 0.0001). The final mixed model had a cAIC=7386.6 RMSE = 1.141 of and R2 = 0.66. In conclusion, the mixed effects models become a useful tool not only for prediction but also to explain the ecological processes that influence the structure of the mangrove in response to changes in time that may be related to the effect of storms, changes in land use or the long-term effects of climate change.|
|Christopher Woodall||Monitoring a Future of Burning Forests: Combining a FIA fuel inventory dashboard with real-time fuel moisture measurements||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||Given an expected future of increased tree mortality and rising temperatures, it is expected that forest fire hazards will increase. In order to meet expected future resource management and wildfire fighting needs, a FIA down woody materials data dashboard was combined with emerging data from a real-time fuel moisture monitoring sensor network to enable user exploration of sub-diurnal forest wildfire hazards.||The FIA program conducts an annual inventory of Down Woody Materials (DWM) across the United States which enables creation of a spatial data dashboard of fuel attributes. Such National Fire Danger Rating System fuel attributes includes the mass of fine and coarse woody debris, otherwise defined as 1-hr to 1,000-hr fuels. Beyond fuel loading estimates, another vital component of estimating the probability of fuel ignition at any location is the air temperature and fuel moisture. In order to create a more temporally and spatially resolved estimate of wildfire hazards, a FIA DWM fuels dashboard was combined with real-time fuel moisture measurements from a sensor network to explore the opportunities and remaining hurdles towards creating such a real-time wildfire hazard digital tool for the wildfire community.|
|Rebekah Zehnder||Southern Timber Supply Analysis: Forest Inventory Data for All||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||The Southern Timber Supply Analysis web application summarizes USDA Forest Service Forest Inventory and Analysis (FIA) data for a user-defined supply area. The easy-to-use application produces estimates of the amount of timberland and standing timber, growth, and removals within a user-specified distance or trucking time of a site of interest in the U.S. South. Southern Timber Supply Analysis broadens delivery of FIA data, simplifying the process of examining forest inventory and sustainability.||The Southern Timber Supply Analysis web application summarizes USDA Forest Service Forest Inventory and Analysis (FIA) data for a user-defined supply area. The application produces estimates of the amount of timberland and standing timber, growth, and removals within a user-specified distance (50, 75, or 100 miles) or trucking time (1, 1.5, or 2 hours) of the users site of interest in the U.S. South. The analysis can be filtered by state and ownership, and timber quantities can be displayed by volume or by green weight. The results can be downloaded in a PDF report. The application also contains pre-made statewide reports available for download.
Designed specifically for ease of use, Southern Timber Supply Analysis simplifies the process of examining forest inventory levels and sustainability within a custom area. It presents the results equivalent to running numerous EVALIDator queries in a matter of seconds, with very little effort required by the user. The information available through Southern Timber Supply Analysis will support economic development, conservation and sustainability efforts, and state forestry agencies and associations.
|Rebekah Zehnder||My Citys Trees: Delivering Information from Urban FIA Data||Tuesday-evening||5a||Smokey-Mezzanine||Digital Engagement - Hands-On Session||My Citys Trees delivers Urban FIA data to a broad audience in a user-friendly interface, making the complex database accessible to average users. The information presented in the application provides a basis for strengthening urban forest management and advocacy efforts by empowering city government, non-profit organizations, and consultants with valuable data that is easy to access and understand.||My Citys Trees delivers Urban FIA data to a broad audience in a user-friendly interface, making the complex database accessible to average users. The use of themes to break down city-wide estimates into selected areas of the city remains a main feature of My Citys Trees. Themes, such as ecoregions, watersheds, or income level, are selected independently for each city to reflect local resource issues. Available estimates include tree counts, carbon storage, energy savings, and more.
The web application received some major updates in 2019, including improved functionality and additional features as well as data for more cities. Information on the status of Urban FIA in participating cities is available on the map. The revamped app has better reporting capability users are now able to produce a full report or one-page summary for their area in PDF format and share it directly from the application. Estimates now include breakdowns by diameter class and land use in addition to ownership. Data for San Diego and San Antonio are now available along with Austin and Houston data. The 2019 release of My Citys Trees is designed to work seamlessly across devices of all sizes, from smart phones to desktops.