Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager

Savage, Shannon L.; Lawrence, Rick L.; Squires, John R.; Holbrook, Joseph D.; Olson, Lucretia E.; Braaten, Justin D.; Cohen, Warren B.

doi:10.3390/f9040157

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Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager

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Department of Land Resources & Environmental Sciences, Montana State University, PO Box 173120, Bozeman, MT 59717, USA

USDA Forest Service, Rocky Mountain Research Station, 800 E. Beckwith, Missoula, MT 59801, USA

College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, 104 CEOAS Administration Building, Corvallis, OR 97331, USA

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USDA Forest Service, Pacific Northwest Research Station, 3200 SW Jefferson Way, Corvallis, OR 97331, USA

Author to whom correspondence should be addressed.

Forests 2018, 9(4), 157; https://doi.org/10.3390/f9040157

Received: 15 February 2018 / Revised: 15 March 2018 / Accepted: 19 March 2018 / Published: 21 March 2018

(This article belongs to the Special Issue New Application based on Advanced Remote Sensing Data in Forests and Wood Land Areas)

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Abstract

There is a pressing need to map changes in forest structure from the earliest time period possible given forest management policies and accelerated disturbances from climate change. The availability of Landsat data from over four decades helps researchers study an ecologically meaningful length of time. Forest structure is most often mapped utilizing lidar data, however these data are prohibitively expensive and cover a narrow temporal window relative to the Landsat archive. Here we describe a technique to use the entire length of the Landsat archive from Multispectral Scanner to Operational Land Imager (M2O) to produce three novel outcomes: (1) we used the M2O dataset and standard change vector analysis methods to classify annual forest structure in northwestern Montana from 1972 to 2015, (2) we improved the accuracy of each yearly forest structure classification by applying temporal continuity rules to the whole time series, with final accuracies ranging from 97% to 68% respectively for two and six-category classifications, and (3) we demonstrated the importance of pre-1984 Landsat data for long-term change studies. As the Landsat program continues to acquire Earth imagery into the foreseeable future, time series analyses that aid in classifying forest structure accurately will be key to the success of any land management changes in the future. View Full-Text

Keywords: remote sensing; forest structure classification; Landsat satellite imagery; time series; change vector analysis; temporal continuity

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MDPI and ACS Style

Savage, S.L.; Lawrence, R.L.; Squires, J.R.; Holbrook, J.D.; Olson, L.E.; Braaten, J.D.; Cohen, W.B. Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager. Forests 2018, 9, 157. https://doi.org/10.3390/f9040157

AMA Style

Savage SL, Lawrence RL, Squires JR, Holbrook JD, Olson LE, Braaten JD, Cohen WB. Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager. Forests. 2018; 9(4):157. https://doi.org/10.3390/f9040157

Chicago/Turabian Style

Savage, Shannon L., Rick L. Lawrence, John R. Squires, Joseph D. Holbrook, Lucretia E. Olson, Justin D. Braaten, and Warren B. Cohen. 2018. "Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager" Forests 9, no. 4: 157. https://doi.org/10.3390/f9040157

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Shifts in Forest Structure in Northwest Montana from 1972 to 2015 Using the Landsat Archive from Multispectral Scanner to Operational Land Imager

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