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Letter

Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data

1
College of Forestry, Nanjing Forestry University, Nanjing 210037, China
2
Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
3
U.S. Geological Survey, Menlo Park, CA 94025, USA
4
U.S. Geological Survey, Reston, VA 20192, USA
5
U.S. Geological Survey, Seattle, WA 98402, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(7), 1126; https://doi.org/10.3390/rs12071126
Received: 24 February 2020 / Revised: 15 March 2020 / Accepted: 31 March 2020 / Published: 2 April 2020
(This article belongs to the Special Issue Remote Sensing of Land–Atmosphere Interactions)
Quantifying land-use and land-cover change (LULCC) effects on carbon sources and sinks has been very challenging because of the availability and quality of LULCC data. As the largest estuary in the United States, Chesapeake Bay is a rapidly changing region and is affected by human activities. A new annual land-use and land-cover (LULC) data product developed by the U.S. Geological Survey Land Change Monitoring and Analysis Program (LCMAP) from 2001 to 2011 was analyzed for transitions between agricultural land, developed land, grassland, forest land and wetland. The Land Use and Carbon Scenario Simulator was used to simulate effects of LULCC and ecosystem disturbance in the south of the Chesapeake Bay Watershed (CBW) on carbon storage and fluxes, with carbon parameters derived from the Integrated Biosphere Simulator. We found that during the study period: (1) areas of forest land, disturbed land, agricultural land and wetland decreased by 90, 82, 57, and 65 km2, respectively, but developed lands gained 293 km2 (29 km2 annually); (2) total ecosystem carbon stock in the CBW increased by 13 Tg C from 2001 to 2011, mainly due to carbon sequestration of the forest ecosystem; (3) carbon loss was primarily attributed to urbanization (0.224 Tg C·yr−1) and agricultural expansion (0.046 Tg C·yr−1); and (4) estimated carbon emissions and harvest wood products were greater when estimated with the annual LULC input. We conclude that a dense time series of LULCC, such as that of the LCMAP program, may provide a more accurate accounting of the effects of land use change on ecosystem carbon, which is critical to understanding long-term ecosystem carbon dynamics. View Full-Text
Keywords: land-use and land-cover change; carbon stock; carbon emission; LUCAS; LCMAP land-use and land-cover change; carbon stock; carbon emission; LUCAS; LCMAP
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MDPI and ACS Style

Diao, J.; Liu, J.; Zhu, Z.; Li, M.; Sleeter, B.M. Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data. Remote Sens. 2020, 12, 1126. https://doi.org/10.3390/rs12071126

AMA Style

Diao J, Liu J, Zhu Z, Li M, Sleeter BM. Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data. Remote Sensing. 2020; 12(7):1126. https://doi.org/10.3390/rs12071126

Chicago/Turabian Style

Diao, Jiaojiao, Jinxun Liu, Zhiliang Zhu, Mingshi Li, and Benjamin M. Sleeter. 2020. "Substantially Greater Carbon Emissions Estimated Based on Annual Land-Use Transition Data" Remote Sensing 12, no. 7: 1126. https://doi.org/10.3390/rs12071126

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