30 Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel using Landsat Timeseries
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https://zenodo.org/record/4013391
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30m resolution historically consistent land cover and cover fraction maps over the Sudano-Sahel for the period 1986-2015. These land cover / cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification / regression model, while historical consistency is achieved using the Hidden Markov Model.
Validated land cover / cover fraction maps covering the full Sudano-Sahel are provided for 2015 (2015_Sahel.zip), while historical maps are available for four focus areas. The extent of the areas are displayed in 11_study_area.jpeg
Each of the zip files contains 14 GeoTIFF files for the respective period and area:
Landsat_LC30_epochYYYY_AREA_bare-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_crops-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_DataDensityIndicator.tif [# overpasses that are used as input for the creation of the maps for this region / epoch]
Landsat_LC30_epochYYYY_AREA_discrete-classification-HMM.tif [temporally cleaned discrete classification map using the Hidden Markov Model; legend see below]
Landsat_LC30_epochYYYY_AREA_discrete-classification.tif [original discrete classification map; legend see below]
Landsat_LC30_epochYYYY_AREA_forest-type-layer.tif [legend see below]
Landsat_LC30_epochYYYY_AREA_grass-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_moss-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_shrub-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_snow-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_tree-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_urban-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_water-permanent-coverfraction-layer.tif [0-100%]
Landsat_LC30_epochYYYY_AREA_water-seasonal-coverfraction-layer.tif [0-100%]
Discrete classification legend:
0: Unknown. No or not enough satellite data available.
20: Shrubs. Woody perennial plants with persistent and woody stems and without any defined main stem being less than 5 m tall. The shrub foliage can be either evergreen or deciduous.
30: Herbaceous vegetation. Plants without persistent stem or shoots above ground and lacking definite firm structure. Tree and shrub cover is less than 10 %.
40: Cultivated and managed vegetation / agriculture. Lands covered with temporary crops followed by harvest and a bare soil period (e.g., single and multiple cropping systems). Note that perennial woody crops will be classified as the appropriate forest or shrub land cover type.
50: Urban / built up. Land covered by buildings and other man-made structures.
60: Bare / sparse vegetation. Lands with exposed soil, sand, or rocks and never has more than 10 % vegetated cover during any time of the year.
70: Snow and ice. Lands under snow or ice cover throughout the year.
80: Permanent water bodies. Lakes, reservoirs, and rivers. Can be either fresh or salt-water bodies.
90: Herbaceous wetland. Lands with a permanent mixture of water and herbaceous or woody vegetation. The vegetation can be present in either salt, brackish, or fresh water.
100: Moss and lichen.
111: Closed forest, evergreen needle leaf. Tree canopy >70 %, almost all needle leaf trees remain green all year. Canopy is never without green foliage.
112: Closed forest, evergreen broad leaf. Tree canopy >70 %, almost all broadleaf trees remain green year round. Canopy is never without green foliage.
113: Closed forest, deciduous needle leaf. Tree canopy >70 %, consists of seasonal needle leaf tree communities with an annual cycle of leaf-on and leaf-off periods.
114: Closed forest, deciduous broad leaf. Tree canopy >70 %, consists of seasonal broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.
115: Closed forest, mixed.
116: Closed forest, not matching any of the other definitions.
121: Open forest, evergreen needle leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, almost all needle leaf trees remain green all year. Canopy is never without green foliage.
122:Open forest, evergreen broad leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, almost all broadleaf trees remain green year round. Canopy is never without green foliage.
123: Open forest, deciduous needle leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, consists of seasonal needle leaf tree communities with an annual cycle of leaf-on and leaf-off periods.
124: Open forest, deciduous broad leaf. Top layer- trees 15-70 % and second layer- mixed of shrubs and grassland, consists of seasonal broadleaf tree communities with an annual cycle of leaf-on and leaf-off periods.
125: Open forest, mixed.
126: Open forest, not matching any of the other definitions.
200: Oceans, seas. Can be either fresh or salt-water bodies.
Forest type legend:
0: Unknown
1: Evergreen needle leaf
2: Evergreen broad leaf
3: Deciduous needle leaf
4: Deciduous broad leaf
5: Mix of forest types
More detail on the classification algorithm and the resulting maps can be found in the accompanying paper:
Souverijns, N.; Buchhorn, M.; Horion, S.; Fensholt, R.; Verbeeck, H.; Verbesselt, J.; Herold, M.; Tsendbazar, N.-E.; Bernardino, P.N.; Somers, B.; Van De Kerchove, R. Thirty Years of Land Cover and Fraction Cover Changes over the Sudano-Sahel Using Landsat Time Series. Remote Sens. 2020, 12, 3817. https://doi.org/10.3390/rs12223817
Please note that a quality layer is available for each of the historical areas / periods (Landsat_LC30_epochYYYY_AREA_DataDensityIndicator.tif). In case a value of 4 or lower is achieved here, the discrete land cover classification / cover fraction for this period / area is highly uncertain. Take this into account when analysing the maps. Furthermore, take note that there is a large difference between the temporally cleaned (Landsat_LC30_epochYYYY_AREA_discrete-classification-HMM.tif) and original discrete land cover classification (Landsat_LC30_epochYYYY_AREA_discrete-classification.tif). We recommend to use the temporally cleaned version in combination with the quality layer.
创建时间:
2024-07-19



