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Enhancing the SDG 15.3.1 land-cover transition matrix using multidecadal vegetation indicators

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Figshare2026-03-11 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Enhancing_the_SDG_15_3_1_land-cover_transition_matrix_using_multidecadal_vegetation_indicators/31641902
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Sustainable Development Goal (SDG) 15.3.1, ‘Proportion of degraded land,’ assesses land degradation using three core sub-indicators: land productivity, land cover (LC), and soil organic carbon. The LC sub-indicator evaluates global trends through a transition matrix defined in the UNCCD Good Practice Guidance (GPG), classifying land cover changes as degradation, improvement, or stability. However, this approach does not capture intra-class transitions (e.g. changes occurring within the same LC class), potentially overlooking relevant degradation or improvement processes. To address this limitation, we expanded the original 7-class transition matrix by incorporating 44 CORINE Land Cover (CLC) detailed level-three classes, integrating biophysically weighted MODIS NDVI data (2000–2018). This enhanced framework enabled the detection of intra-class changes amounting to 1.06% (artificial), 0.96% (agricultural), 7.32% (natural), and 0.03% (wetland/water bodies). Notably, within the natural class (CLC 3) 8.53% of the area exhibited improvement, 14.9% degradation, and 76.5% stability. The workflow of the analysis using the 44 CORINE CLC detailed level-three classes for the year 2000 and 2018, the monthly NDVI were obtained from Google Earth engine (GEE) and cumulative averages computed, a percentile raking was then used quartiles to split the distribution into four equal parts (25%, 50%, 75%, and 100%) to reduce the number of CLC detailed level-three classes into a LC type. The ranking of the LC types was taken from the good Practice guidance (GPGs).
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2026-03-11
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