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Examination Of Imputation Methods To Estimate Status And Change Of Forest Attributes From Paneled Inventory Data
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Book Synopsis Examination of Imputation Methods to Estimate Status and Change of Forest Attributes from Paneled Inventory Data by : Bianca N. I. Eskelson
Download or read book Examination of Imputation Methods to Estimate Status and Change of Forest Attributes from Paneled Inventory Data written by Bianca N. I. Eskelson and published by . This book was released on 2009 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Forest Inventory and Analysis (FIA) program conducts an annual inventory throughout the United States. In the western United States, 10% of all plots (one panel) are measured annually, and a moving average is used for estimating current condition and change of forest attributes while alternative methods are sought in all regions of the United States. This dissertation explored alternatives to the moving average in the Pacific Northwest using Current Vegetation Survey data collected in Oregon and Washington. Several nearest neighbor imputation methods were examined for their suitability to update plot-level forest attributes (basal area/ha, stems/ha, volume/ha, biomass/ha) to the current point in time. The results were compared to estimates obtained using a moving average and a weighted moving average. In terms of bias and accuracy, the weighted moving average performed better than the moving average. When the most recent measurements of the variables of interest were used as ancillary data, randomForest imputation outperformed both the moving average and the weighted moving average. For estimating current basal area/ha, stems/ha, volume/ha, and biomass/ha, tree-level imputation outperformed plot-level imputation. The difference in bias and accuracy between tree- and plot-level imputation was more pronounced when the variables of interest were summarized by species groups. Nearest neighbor imputation methods were also investigated for estimating mean annual change in selected forest attributes. The imputed mean annual change was used to update unmeasured panels to the current point in time. In terms of bias and accuracy, the resulting estimates of current basal area/ha, stems/ha, volume/ha, and biomass/ha outperformed the results obtained using plot-level imputation. Information on hard to estimate forest attributes such as cavity tree and snag abundance are important for wildlife management plans. Using FIA data collected in Washington, Oregon, and California, nearest neighbor imputation approaches and negative binomial regression models were examined for their suitability in estimating cavity tree and snag abundance. The negative binomial models were preferred to the nearest neighbor imputation approaches.
Book Synopsis Annual Design-based Estimation for the Annualized Inventories of Forest Inventory and Analysis by : Hans T. Schreuder
Download or read book Annual Design-based Estimation for the Annualized Inventories of Forest Inventory and Analysis written by Hans T. Schreuder and published by . This book was released on 2000 with total page 8 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Estimation and Prediction for Natural Resources Public Data by : Hans T. Schreuder
Download or read book Data Estimation and Prediction for Natural Resources Public Data written by Hans T. Schreuder and published by . This book was released on 1998 with total page 6 pages. Available in PDF, EPUB and Kindle. Book excerpt: A key product of both Forest Inventory and Analysis (FIA) of the USDA Forest Service and the Natural Resources Inventory (NRI) of the Natural Resources Conservation Service is a scientific data base that should be defensible in court. Multiple imputation procedures (MIPs) have been proposed both for missing value estimation and prediction of non-remeasured cells in annualized forest inventories such as the Southern Annual Forest Inventory System (SAFIS). MIPs generate clean-looking data bases that are easily used but hide a serious weakness: under different assumptions made by reasonable people, very different data bases and conclusions can be generated. A MIP is an interesting idea for prediction but should only be used for analyses by users, not for filling in data in a public data base. Simple illustrations are given to make our points. To maintain a defensible data base, FIA and NRI should only provide algorithms to facilitate user-generated data for prediction of non-remeasured cells. Users, not FIA and NRI, should be responsible for generating data bases that utilize these algorithms or other algorithms of their choosing, incorporating assumptions that they are willing to make. But they should be encouraged to work with FIA and NRI personnel in utilizing such algorithms.
Book Synopsis Application of an Imputation Method for Geospatial Inventory of Forest Structural Attributes Across Multiple Spatial Scales in the Lake States, U.S.A by : Ram K. Deo
Download or read book Application of an Imputation Method for Geospatial Inventory of Forest Structural Attributes Across Multiple Spatial Scales in the Lake States, U.S.A written by Ram K. Deo and published by . This book was released on 2014 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.
Book Synopsis Small area estimation in forest inventories: New needs, methods, and tools by : Barry Wilson
Download or read book Small area estimation in forest inventories: New needs, methods, and tools written by Barry Wilson and published by Frontiers Media SA. This book was released on 2023-04-17 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Pacific Northwest Research Station (Portland, Or.). Forest Inventory & Analysis Publisher : ISBN 13 : Total Pages :12 pages Book Rating :4.:/5 (319 download)
Book Synopsis Forest Inventory & Analysis by : Pacific Northwest Research Station (Portland, Or.). Forest Inventory & Analysis
Download or read book Forest Inventory & Analysis written by Pacific Northwest Research Station (Portland, Or.). Forest Inventory & Analysis and published by . This book was released on 2003 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Overview of Forest Inventory and Analysis Estimation Procedures in the Eastern United States by : Richard A. Birdsey
Download or read book An Overview of Forest Inventory and Analysis Estimation Procedures in the Eastern United States written by Richard A. Birdsey and published by . This book was released on 1992 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Unlocking the Forest Inventory and Analysis Database by : Hunter Stanke
Download or read book Unlocking the Forest Inventory and Analysis Database written by Hunter Stanke and published by . This book was released on 2020 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forest Inventory and Analysis (FIA) is a US Department of Agriculture Forest Service program that aims to monitor changes in forests across the US. FIA hosts one of the largest ecological datasets in the world, though its complexity limits access for many potential users. rFIA is an R package designed to simplify the estimation of forest attributes using data collected by the FIA Program. Specifically, rFIA improves access to the spatio-temporal estimation capacity of the FIA Database via space-time indexed summaries of forest variables within user-defined population boundaries. The package implements multiple design-based estimators, and has been validated against official estimates and sampling errors produced by the FIA Program. The package has been made open-source is freely available for download from the Comprehensive R Archive Network.In recent decades, forests of the western US have experienced unprecedented change in climate and forest disturbance regimes, and widespread shifts in forest composition, structure, and function are expected in response. However, large-scale, comprehensive assessments of tree population performance have yet to be conducted in the region. We develop an index of forest population performance based on repeated censuses of field plots, and apply this index to assess the status of the most abundant tree species in the western US. Our study provides empirical evidence to suggest tree species in the western US are exhibiting strong divergence in population performance, with over half (70%) of species experiencing range-wide population decline. We found spatial variation in population performance across the ranges of all species, indicating range shifts are already underway. Our results further indicate that species decline can seldom be attributed to a single forest disturbance agent, highlighting the importance of considering multiple risks factors in broad-scale forest management.
Book Synopsis Forest Analytics with R by : Andrew P. Robinson
Download or read book Forest Analytics with R written by Andrew P. Robinson and published by Springer Science & Business Media. This book was released on 2010-11-05 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forest Analytics with R combines practical, down-to-earth forestry data analysis and solutions to real forest management challenges with state-of-the-art statistical and data-handling functionality. The authors adopt a problem-driven approach, in which statistical and mathematical tools are introduced in the context of the forestry problem that they can help to resolve. All the tools are introduced in the context of real forestry datasets, which provide compelling examples of practical applications. The modeling challenges covered within the book include imputation and interpolation for spatial data, fitting probability density functions to tree measurement data using maximum likelihood, fitting allometric functions using both linear and non-linear least-squares regression, and fitting growth models using both linear and non-linear mixed-effects modeling. The coverage also includes deploying and using forest growth models written in compiled languages, analysis of natural resources and forestry inventory data, and forest estate planning and optimization using linear programming. The book would be ideal for a one-semester class in forest biometrics or applied statistics for natural resources management. The text assumes no programming background, some introductory statistics, and very basic applied mathematics.
Book Synopsis Advanced Methods for 3-D Forest Characterization and Mapping from Lidar Remote Sensing Data by : Carlos Alberto Silva
Download or read book Advanced Methods for 3-D Forest Characterization and Mapping from Lidar Remote Sensing Data written by Carlos Alberto Silva and published by . This book was released on 2018 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and spatially explicit measurements of forest attributes are critical for sustainable forest management and for ecological and environmental protection. Airborne Light Detection and Ranging (lidar) systems have become the dominant remote sensing technique for forest inventory, mainly because this technology can quickly provide highly accurate and spatially detailed information about forest attributes across entire landscapes. This dissertation is focused on developing and assessing novel and advanced methods for three dimensional (3-D) forest characterization. Specifically, I map canopy structural attributes of individual trees, as well as forests at the plot and landscape levels in both natural and industrial plantation forests using lidar remote sensing data. Chapter 1 develops a novel framework to automatically detect individual trees and evaluates the efficacy of k-nearest neighbor (k-NN) imputation models for estimating tree attributes in longleaf pine (Pinus palustris Mill.) forests. Although basal area estimation accuracy was poor because of the longleaf pine growth habit, individual tree locations, height and volume were estimated with high accuracy, especially in low-canopy-cover conditions. The root mean square distance (RMSD) for tree-level height, basal area, and volume were 2.96%, 58.62%, and 8.19%, respectively. Chapter 2 presents a methodology for predicting stem total and assortment volumes in industrial loblolly pine (Pinus taeda L.) forest plantations using lidar data as inputs to random forest models. When compared to reference forest inventory data, the accuracy of plot-level forest total and assortment volumes was high; the root mean square error (RMSE) of total, commercial and pulp volume estimates were 7.83%, 7.71% and 8.63%, respectively. Chapter 3 evaluates the impacts of airborne lidar pulse density on estimating aboveground biomass (AGB) stocks and changes in a selectively logged tropical forest. Estimates of AGB change at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg ̇ha−1 when pulse density decreased from 12 to 0.2 pulses ̇m−2. The effects of pulse density were more pronounced in areas of steep slope, but when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and subsequent AGB stocks and change estimates did not exceed 20 Mg ̇ha−1. Chapter 4 presents a comparison of airborne small-footprint (SF) and large-footprint (LF) lidar retrievals of ground elevation, vegetation height and biomass across a successional tropical forest gradient in central Gabon. The comparison of the two sensors shows that LF lidar waveforms are equivalent to simulated waveforms from SF lidar for retrieving ground elevation (RMSE=0.5 m, bias=0.29 m) and maximum forest height (RMSE=2.99 m; bias=0.24 m). Comparison of gridded LF lidar height with ground plots showed that an unbiased estimate of aboveground biomass at 1-ha can be achieved with a sufficient number of large footprints (> 3). Lastly, Appendix A presents an open source R package for airborne lidar visualization and processing for forestry applications.
Book Synopsis Sampling Techniques for Forest Inventories by : Daniel Mandallaz
Download or read book Sampling Techniques for Forest Inventories written by Daniel Mandallaz and published by CRC Press. This book was released on 2007-10-26 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sound forest management planning requires cost-efficient approaches to optimally utilize given resources. Emphasizing the mathematical and statistical features of forest sampling to assess classical dendrometrical quantities, Sampling Techniques for Forest Inventories presents the statistical concepts and tools needed to conduct a modern for
Book Synopsis Proceedings of the Fourth Annual Forest Inventory and Analysis Symposium by :
Download or read book Proceedings of the Fourth Annual Forest Inventory and Analysis Symposium written by and published by . This book was released on 2005 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fresh ideas, perspectives, and protocols associated with forest inventory and analysis surveys by :
Download or read book Fresh ideas, perspectives, and protocols associated with forest inventory and analysis surveys written by and published by . This book was released on 2003 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sampling and Estimation Documentation for the Enhanced Forest Inventory and Analysis Program: 2022 by :
Download or read book Sampling and Estimation Documentation for the Enhanced Forest Inventory and Analysis Program: 2022 written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Forest Inventory and Analysis (FIA) program of the Forest Service, an Agency of the U.S. Department of Agriculture, provides what is arguably the most valuable forest resource dataset in the United States. These data are the basis for numerous inquiries across a wide range of forest-related attributes at various spatial and temporal scales. While user-friendly analytical tools are publicly available to facilitate the use of the data without expert knowledge, there is a need for detailed documentation of the underlying sampling and estimation procedures. The audience for this information entails the entire spectrum of both internal and external FIA data consumers. This document clarifies some aspects of existing documentation, provides the sampling and estimation methods used for key program areas including Urban FIA, National Woodland Owner Survey, Timber Products Output, and Carbon, and provides an examination of burgeoning estimation topics relevant to the FIA program and its users. A broad overview is provided on several advanced estimation approaches of particular interest to the FIA community. While the exposition for each topic is necessarily coarse, links to more detailed research and informational material are provided for readers desiring to further study a specific area of interest.
Book Synopsis Comparison and Analysis of Small Area Estimation Methods for Improving Estimates of Selected Forest Attributes by : Michael E. Goerndt
Download or read book Comparison and Analysis of Small Area Estimation Methods for Improving Estimates of Selected Forest Attributes written by Michael E. Goerndt and published by . This book was released on 2010 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the most common practices regarding estimation of forest attributes is the partitioning of large forested subpopulations into smaller areas of interest to coincide with specific objectives of present and future forest management. New estimators are needed to improve estimation of selected forest attributes in small areas where the existing sample is insufficient to obtain precise estimates. This dissertation assessed the strength of light detection and ranging (LiDAR) as auxiliary information for estimating plot-level forest attributes (trees/ha, basal area/ha, volume/ha, quadratic mean diameter, Lorey's height) using intensity and nonintensity area-level LiDAR metrics and single tree remote sensing (STRS). LiDAR intensity metrics were useful for increasing precision for trees/ha. With the exception of Lorey's height, STRS did not significantly improve precision for most of the attributes. Small area estimation (SAE) techniques were assessed for precision and bias in estimating stand-level forest attributes (trees/ha, basal area/ha, volume/ha, quadratic mean diameter, mean height of 100 largest trees/ha) assuming a localized subpopulation using LiDAR auxiliary information. Selected estimation methods included area-level regression-based composite estimators and indirect estimators based on synthetic prediction and nearest neighbor imputation. The composite estimators produced lower bias and higher precision than synthetic prediction and imputation. The traditional composite estimator outperformed empirical best linear unbiased prediction for bias but not for precision. SAE methods were compared for precision and bias in estimating county-level forest attributes (trees/ha, basal area/ha, volume/ha, quadratic mean diameter, mean height of 100 largest trees/ha) assuming a regional subpopulation using Landsat auxiliary information. Selected estimation methods included unit-level mixed regression-based indirect and composite estimators, and imputation-based indirect and composite estimators. The indirect and composite estimators based on linear mixed effects models generally outperformed those based on imputation. The composite estimators performed the best in terms of bias for all attributes.
Book Synopsis Guidance for Forest Management and Landscape Ecology Applications of Recent Gradient Nearest Neighbor Imputation Maps in California, Oregon, and Washington by :
Download or read book Guidance for Forest Management and Landscape Ecology Applications of Recent Gradient Nearest Neighbor Imputation Maps in California, Oregon, and Washington written by and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many forest landscape ecology and ecological monitoring projects, forest structure and composition data availability at the correct scale are often limiting factors, motivating the development of map products based on remote sensing. Gradient nearest neighbor (GNN) imputation is a flexible framework for generating multivariate, annual, wall-to-wall maps of forest structure and composition for landscape, regional, and national applications. This report provides guidance on the appropriate use of forest structure and composition maps generated from satellite imagery, physical environment, and forest inventory data using the GNN modeling and mapping framework. We describe the GNN modeling and mapping framework associated with the generation and delivery of updated maps in 2020 (GNN-2020) that provide forest attribute status and trend data from 1986 to 2017. In relation to the GNN-2020 map data, we describe (1) the accuracy assessment reporting that accompanies all maps, (2) basic concepts regarding the strength of relationships between forest attributes and the geospatial predictor variables used in mapping, (3) the role of the number of nearest neighbors in map accuracy, (4) factors affecting the appropriate spatial and temporal scales for using the maps, (5) the types of changes in forest attributes that can be reasonably assessed with the maps, and (6) the challenges in creating categorical or classified maps based on the GNN-2020 data. Our goal is to provide enough background and guidance to use GNN products appropriately and effectively.
Book Synopsis An Analysis of the Compatibility of Forest Inventory and Analysis Data (U.S. Forest Service) as Input to Wildlife Habitat Relationship Models by : Barry R. Noon
Download or read book An Analysis of the Compatibility of Forest Inventory and Analysis Data (U.S. Forest Service) as Input to Wildlife Habitat Relationship Models written by Barry R. Noon and published by . This book was released on 1984 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
