scholarly journals Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1364
Author(s):  
Andrew J. Lister ◽  
Hans Andersen ◽  
Tracey Frescino ◽  
Demetrios Gatziolis ◽  
Sean Healey ◽  
...  
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Natural Resource ◽  
Forest Inventory ◽  
The United States ◽  
National Forest ◽  
Forest Inventories ◽  
National Forest Inventories ◽  
Sampling Statistics

Globally, forests are a crucial natural resource, and their sound management is critical for human and ecosystem health and well-being. Efforts to manage forests depend upon reliable data on the status of and trends in forest resources. When these data come from well-designed natural resource monitoring (NRM) systems, decision makers can make science-informed decisions. National forest inventories (NFIs) are a cornerstone of NRM systems, but require capacity and skills to implement. Efficiencies can be gained by incorporating auxiliary information derived from remote sensing (RS) into ground-based forest inventories. However, it can be difficult for countries embarking on NFI development to choose among the various RS integration options, and to develop a harmonized vision of how NFI and RS data can work together to meet monitoring needs. The NFI of the United States, which has been conducted by the USDA Forest Service’s (USFS) Forest Inventory and Analysis (FIA) program for nearly a century, uses RS technology extensively. Here we review the history of the use of RS in FIA, beginning with general background on NFI, FIA, and sampling statistics, followed by a description of the evolution of RS technology usage, beginning with paper aerial photography and ending with present day applications and future directions. The goal of this review is to offer FIA’s experience with NFI-RS integration as a case study for other countries wishing to improve the efficiency of their NFI programs.

scholarly journals Using Landsat Imagery to Assess Burn Severity of National Forest Inventory Plots

2021 ◽  
Vol 13 (10) ◽  
pp. 1935
Author(s):  
Flavie Pelletier ◽  
Bianca N.I. Eskelson ◽  
Vicente J. Monleon ◽  
Yi-Chin Tseng
Keyword(s):  
United States ◽  
Forest Inventory ◽  
Landsat Imagery ◽  
The United States ◽  
Remotely Sensed ◽  
National Forest Inventory ◽  
Burn Severity ◽  
National Forest ◽  
Remotely Sensed Data ◽  
National Inventory

As the frequency and size of wildfires increase, accurate assessment of burn severity is essential for understanding fire effects and evaluating post-fire vegetation impacts. Remotely-sensed imagery allows for rapid assessment of burn severity, but it also needs to be field validated. Permanent forest inventory plots can provide burn severity information for the field validation of remotely-sensed burn severity metrics, although there is often a mismatch between the size and shape of the inventory plot and the resolution of the rasterized images. For this study, we used two distinct datasets: (1) ground-based inventory data from the United States national forest inventory to calculate ground-based burn severity; and (2) remotely-sensed data from the Monitoring Trends in Burn Severity (MTBS) database to calculate different remotely-sensed burn severity metrics based on six weighting scenarios. Our goals were to test which MTBS metric would best align with the burn severity of national inventory plots observed on the ground, and to identify the superior weighting scenarios to extract pixel values from a raster image in order to match burn severity of the national inventory plots. We fitted logistic and ordinal regression models to predict the ground-based burn severity from the remotely-sensed burn severity averaged from six weighting scenarios. Among the weighting scenarios, two scenarios assigned weights to pixels based on the area of a pixel that intersected any parts of a national inventory plot. Based on our analysis, 9-pixel weighted averages of the Relative differenced Normalized Burn Ratio (RdNBR) values best predicted the ground-based burn severity of national inventory plots. Finally, the pixel specific weights that we present can be used to link other Landsat-derived remote sensing metrics with United States forest inventory plots.

Applications of the United States Forest Inventory and Analysis dataset: a review and future directions

2018 ◽  
Vol 48 (11) ◽  
pp. 1251-1268 ◽  
Author(s):  
Wade T. Tinkham ◽  
Patrick R. Mahoney ◽  
Andrew T. Hudak ◽  
Grant M. Domke ◽  
Mike J. Falkowski ◽  
...  
Keyword(s):  
United States ◽  
Forest Inventory ◽  
The United States ◽  
National Forest Inventory ◽  
Forest Resources ◽  
Climate Impacts ◽  
Permanent Plots ◽  
National Forest ◽  
Forest Inventory And Analysis ◽  
Research Areas

The United States Forest Inventory and Analysis (FIA) program has been monitoring national forest resources in the United States for over 80 years; presented here is a synthesis of research applications for FIA data. A review of over 180 publications that directly utilize FIA data is broken down into broad categories of application and further organized by methodologies and niche research areas. The FIA program provides the most comprehensive forest database currently available, with permanent plots distributed across all forested lands and ownerships in the United States and plot histories dating back to the early 1930s. While the data can be incredibly powerful, users need to understand the spatial resolution of ground-based plots and the nature of the FIA plot coordinate system must be applied correctly. As the need for accurate assessments of national forest resources continues to be a global priority, particularly related to carbon dynamics and climate impacts, such national forest inventories will continue to be an important source of information on the status of and trends in these ecosystems. The advantages and limitations of FIA’s national forest inventory data are highlighted, and suggestions for further expansion of the FIA program are provided.

scholarly journals A century of national forest inventories – informing past, present and future decisions

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Johannes Breidenbach ◽  
Ronald E. McRoberts ◽  
Iciar Alberdi ◽  
Clara Antón-Fernández ◽  
Erkki Tomppo
Keyword(s):  
Forest Inventory ◽  
Policy Making ◽  
Terrestrial Ecosystems ◽  
National Forest Inventory ◽  
100Th Anniversary ◽  
Future Research ◽  
National Forest ◽  
Forest Inventories ◽  
National Forest Inventories ◽  
Over Exploitation

AbstractIn 2019, 100 years had elapsed since the first National Forest Inventory (NFI) was established in Norway. Motivated by a fear of over-exploitation of timber resources, NFIs today enable informed policy making by providing data vital to decision support at international, national, regional, and local scales. This Collection of articles celebrates the 100th anniversary of NFIs with a description of past, present, and future research aiming at improving the monitoring of forest and other terrestrial ecosystems.

Strategies to compensate for the effects of nonresponse on forest carbon baseline estimates from the national forest inventory of the United States

2014 ◽  
Vol 315 ◽  
pp. 112-120 ◽  
Author(s):  
Grant M. Domke ◽  
Christopher W. Woodall ◽  
Brian F. Walters ◽  
Ronald E. McRoberts ◽  
Mark A. Hatfield
Keyword(s):  
United States ◽  
Forest Inventory ◽  
The United States ◽  
National Forest Inventory ◽  
Forest Carbon ◽  
National Forest

Forest Inventories in the United States and Canada

1987 ◽  
Vol 63 (6) ◽  
pp. 431-434
Author(s):  
Hans T. Schreuder ◽  
G. M. Bonnor
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Classification System ◽  
The United States ◽  
Land Classification ◽  
Exchange Of Information ◽  
Forest Inventories ◽  
The U.S

Canadian and United States (U.S.) extensive forest inventories are contrasted. The Canadians have had more experience in mapping and remote sensing; the U.S., in collecting, handling, and reporting change data. Development of common standards, terms, and definitions, as well as a common forest and land classification system, would facilitate cooperation and exchange of information.

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