An Object-Based Approach to Map Young Forest and Shrubland Vegetation Based on Multi-Source Remote Sensing Data

An Object-Based Approach to Map Young Forest and Shrubland Vegetation Based on Multi-Source Remote Sensing Data

Many remote sensing studies have individually addressed afforestation, forest disturbance and forest regeneration, and considered land use history. However, no single study has simultaneously addressed all of these components that collectively constitute successional stages and pathways of young for...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 14; no. 5; p. 1091
Main Authors: Rittenhouse, Chadwick D., Berlin, Elana H., Mikle, Nathaniel, Qiu, Shi, Riordan, Dustin, Zhu, Zhe
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-03-2022
Subjects:
Afforestation
Agriculture
Carbon sequestration
Classification
continuous change detection and classification
Ecological studies
Environmental protection
forest disturbance
Forest management
forest succession
Forests
Height
Hydrology
Image resolution
Land cover
Land use
Landsat
Landsat time series
LiDAR
Regeneration
Remote sensing
Sensors
Shrublands
Temperate forests
Trees
Vegetation
Wildlife conservation
England
United Kingdom > UK
United States > US
Connecticut
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Summary:Many remote sensing studies have individually addressed afforestation, forest disturbance and forest regeneration, and considered land use history. However, no single study has simultaneously addressed all of these components that collectively constitute successional stages and pathways of young forest and shrubland at large spatial extents. Our goal was to develop a multi-source, object-based approach that utilized the strengths of Landsat (large spatial extent with good temporal coverage), LiDAR (vegetation height and vertical structure), and aerial imagery (high resolution) to map young forest and shrubland vegetation in a temperate forest. Further, we defined young forest and shrubland vegetation types in terms of vegetation height and structure, to better distinguish them in remote sensing for ecological studies. The multi-source, object-based approach provided an area-adjusted estimate of 42,945 ha of young forest and shrubland vegetation in Connecticut with overall map accuracy of 88.2% (95% CI 2.3%), of which 20,953 ha occurred in complexes ≥2 ha in size. Young forest and shrubland vegetation constituted 3.3% of Connecticut’s total land cover and 6.3% of forest cover as of 2018. Although the 2018 estimates are consistent with those of the past 20 years, concerted efforts are needed to restore, maintain, or manage young forest and shrubland vegetation in Connecticut.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14051091