IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing · 2021 · 12 citations · 44 references
EngineeringLand UseForestryLand CoverLand DegradationChange AnalysisEarth ScienceSocial SciencesClimate ChangeGeographyRemote Sensing-based EstimatesForest Health MonitoringEarth Observation DataLand Cover MapDeforestationReforestationRemote SensingSichuan ProvinceForest InventoryRemote Sensing Technologies
Forests have significant impacts on the global carbon cycle, hydrological processes, and biodiversity. Driven by socioeconomic developments, forests experienced drastic changes since the mid-20th century in China. Although declassified spy satellite and other Earth observation satellite data offer remote sensing technologies for mapping these long-term changes, challenges remain unsolved for applications of large volumes of historical data. This study uses long-term satellite observations, including declassified satellite data in the 1960s and Landsat products since the 1970s to monitor the decadal changes. A semi-automated method was developed for the rapid registration of declassified images with reference to Landsat data. The method was applied to quantify the forest cover (FC) in Sichuan Province (excluding Chongqing), China. Combined with a Landsat-based FC change product, it revealed that the FC in Sichuan declined rapidly by 38% from the 1960s to 2005. The FC was estimated to be 45.19 ± 1.62% in the 1960s and 38.98 ± 2.06% in 1975, but it rapidly decreased to 28.91 ± 2.07% in 1990 and 27.87 ± 2.14% by 2005. Supplemented with the official statistics, the FC in Sichuan was reported to increase to 38.03% by 2018. Although differences between the remote sensing-based estimates and the statistics were observed, they highlight the challenges in reconstructing historical land use changes for carbon and other studies. The drastic loss of forests before 1990 and the stabilizing afterward reflects the changes in forest policies, which transitioned from serving timber products to forest conservations.
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