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Article

Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery

1
Department of Earth System Science and Policy, University of North Dakota, Grand Forks, ND 58202, USA
2
Department of Geography and GISc, University of North Dakota, Grand Forks, ND 58202, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(3), 218; https://doi.org/10.3390/rs11030218
Received: 29 November 2018 / Revised: 17 January 2019 / Accepted: 17 January 2019 / Published: 22 January 2019
Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. As trees age and reach their lifespan limits, renovations should have taken place with new trees being planted. However, in recent years, the rate of tree removal is thought to exceed the rate of replanting, which can result in a net loss of shelterbelts. Through manual digitization and geographic object-based image analysis (GEOBIA), we mapped shelterbelt densities in the Grand Forks County using historical and contemporary aerial photography, and estimated actual changes in density over 54 years. Our results showed a doubling in shelterbelt densities from 1962 to 2014, with an increase of 6402 m2/km2 over the 52 years (or 123 m2/km2/year). From 2014 to 2016, we measured 1,040,178 m2 of shelterbelt areas removed from the county, creating a density loss of −157 m2/km2/year. The total change over two years was relatively small compared with that seen over the previous 52 years. However, the fact that the rate of shelterbelt planting has slowed, and more removal is occurring, should be of concern for an increased risk of wind erosion, similar to that experienced in Midwestern U.S. during the 1930s. The reduction of shelterbelt density is likely related to changes in farming practices and a decline in the Conservation Reserve Program, resulting from the increased returns of growing other row crops. To encourage shelterbelt planting as a conservation practice, additional guidelines and financial support should be considered to balance the tradeoff between soil erosion and agricultural intensification. View Full-Text
Keywords: geographic object-based image analysis; shelterbelts; Conservation Reserve Program geographic object-based image analysis; shelterbelts; Conservation Reserve Program
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MDPI and ACS Style

Burke, M.W.V.; Rundquist, B.C.; Zheng, H. Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery. Remote Sens. 2019, 11, 218. https://doi.org/10.3390/rs11030218

AMA Style

Burke MWV, Rundquist BC, Zheng H. Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery. Remote Sensing. 2019; 11(3):218. https://doi.org/10.3390/rs11030218

Chicago/Turabian Style

Burke, Morgen W.V., Bradley C. Rundquist, and Haochi Zheng. 2019. "Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery" Remote Sensing 11, no. 3: 218. https://doi.org/10.3390/rs11030218

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