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

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 monito...

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Main Authors: Andrew J. Lister, Hans Andersen, Tracey Frescino, Demetrios Gatziolis, Sean Healey, Linda S. Heath, Greg C. Liknes, Ronald McRoberts, Gretchen G. Moisen, Mark Nelson, Rachel Riemann, Karen Schleeweis, Todd A. Schroeder, James Westfall, B. Tyler Wilson
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/11/12/1364
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spelling doaj-0219d8342e05464f9b9ac29450b60bfc2020-12-20T00:00:18ZengMDPI AGForests1999-49072020-12-01111364136410.3390/f11121364Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest InventoryAndrew J. Lister0Hans Andersen1Tracey Frescino2Demetrios Gatziolis3Sean Healey4Linda S. Heath5Greg C. Liknes6Ronald McRoberts7Gretchen G. Moisen8Mark Nelson9Rachel Riemann10Karen Schleeweis11Todd A. Schroeder12James Westfall13B. Tyler Wilson14USDA Forest Service, Northern Research Station, York, PA 27410, USAUSDA Forest Service, Pacific Northwest Research Station, Portland, OR 97205, USAUSDA Forest Service, Rocky Mountain Research Station, Ogden, UT 84401, USAUSDA Forest Service, Pacific Northwest Research Station, Portland, OR 97205, USAUSDA Forest Service, Rocky Mountain Research Station, Ogden, UT 84401, USAUSDA Forest Service, Washington Office, Washington, DC 20250, USAUSDA Forest Service, Northern Research Station, York, PA 27410, USAUSDA Forest Service, Northern Research Station, York, PA 27410, USAUSDA Forest Service, Rocky Mountain Research Station, Ogden, UT 84401, USAUSDA Forest Service, Northern Research Station, York, PA 27410, USAUSDA Forest Service, Northern Research Station, York, PA 27410, USAUSDA Forest Service, Rocky Mountain Research Station, Ogden, UT 84401, USAUSDA Forest Service, Southern Research Station, Knoxville, TN 37919, USAUSDA Forest Service, Northern Research Station, York, PA 27410, USAUSDA Forest Service, Northern Research Station, York, PA 27410, USAGlobally, 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 requires 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.https://www.mdpi.com/1999-4907/11/12/1364national forest inventoryforest monitoringremote sensingforest samplinginventory efficiencyForest Inventory and Analysis
collection DOAJ
language English
format Article
sources DOAJ
author Andrew J. Lister
Hans Andersen
Tracey Frescino
Demetrios Gatziolis
Sean Healey
Linda S. Heath
Greg C. Liknes
Ronald McRoberts
Gretchen G. Moisen
Mark Nelson
Rachel Riemann
Karen Schleeweis
Todd A. Schroeder
James Westfall
B. Tyler Wilson
spellingShingle Andrew J. Lister
Hans Andersen
Tracey Frescino
Demetrios Gatziolis
Sean Healey
Linda S. Heath
Greg C. Liknes
Ronald McRoberts
Gretchen G. Moisen
Mark Nelson
Rachel Riemann
Karen Schleeweis
Todd A. Schroeder
James Westfall
B. Tyler Wilson
Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
Forests
national forest inventory
forest monitoring
remote sensing
forest sampling
inventory efficiency
Forest Inventory and Analysis
author_facet Andrew J. Lister
Hans Andersen
Tracey Frescino
Demetrios Gatziolis
Sean Healey
Linda S. Heath
Greg C. Liknes
Ronald McRoberts
Gretchen G. Moisen
Mark Nelson
Rachel Riemann
Karen Schleeweis
Todd A. Schroeder
James Westfall
B. Tyler Wilson
author_sort Andrew J. Lister
title Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
title_short Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
title_full Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
title_fullStr Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
title_full_unstemmed Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
title_sort use of remote sensing data to improve the efficiency of national forest inventories: a case study from the united states national forest inventory
publisher MDPI AG
series Forests
issn 1999-4907
publishDate 2020-12-01
description 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 requires 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.
topic national forest inventory
forest monitoring
remote sensing
forest sampling
inventory efficiency
Forest Inventory and Analysis
url https://www.mdpi.com/1999-4907/11/12/1364
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