Spatio-Temporal Dynamics in Grasslands Using the Landsat Archive

LAND(2023)

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摘要
Grasslands are an important biotope in Europe, not only because they are widespread, but also because they provide valuable ecosystem services. The ecological value of a grassland parcel is directly proportional to the number of uninterrupted years of grassland cover. However, the area of long-term grassland (i.e., grassland of 5 years or older) is decreasing, limiting its ability to provide ecosystem services. To prevent the further disappearance of long-term grasslands, Europe developed an agricultural policy instrument in 2003 to protect grasslands of 5 years or older. Nature policy instruments aim to protect grasslands that have existed for more than 10 years to support their high environmental value. However, there is currently no multi-annual information on the location and age of grasslands at a high spatial and temporal resolution, which makes it difficult to assess the effectiveness of the current grassland protection regulations. Multi-annual satellite-based land cover classification can provide a solution for grassland area and age monitoring, which we tested by producing a series of Landsat-based land cover classification maps from 2005 to 2019 for the region of Flanders, Belgium. Historical land cover classification maps proved useful for evaluating past and present planning and policy to ensure grassland conservation, linking spatial and temporal changes in the area of long-term grasslands with policy changes and landscape dynamics. We were able to locate grasslands that were grassland between 2005 and 2014 but were converted to arable land between 2015 and 2019, identify the year in which these grasslands were converted to arable land, and demonstrate regional differences in the conservation of long-term grassland aged 5-9 years and 10 years or more. Long-term grassland aged 10 years or more disappeared faster in urban than in rural areas in Flanders between 2014 and 2019. Our study shows that multi-annual high-resolution satellite imagery provides objective and quantitative information on long-term grassland to support climate, agricultural, environmental, and nature policies.
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关键词
grassland,Landsat,land cover,permanent grasslands,historical grasslands,land cover classification,LULCC,cover dynamics,policy,random forest,hidden Markov model
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