Input dataset for gap filling and land-cover mapping using eumap Library - 2000 to 2020
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://zenodo.org/record/4058225
下载链接
链接失效反馈官方服务:
资源简介:
Benchmark dataset containing slope, elevation, Landsat temporal composites and night light raster layers, and the training samples (LUCAS and CORINE samples compilation) to map the land-cover in different areas of the European Union-EU.
The slope and elevation refers to Digital Terrain Model for Continental Europe, and the night light images are from VNP46A1 product (VIIRS/NPP Daily Gridded Day Night Band 500m). The temporal composites were based on GLAD Landsat ARD, considering the 4 seasons and 3 percentiles per season (25, 50 and 75), for 6 spectral (blue, green, red, NIR, SWIR1, SWIR2) and 1 thermal band, resulting at end in 88 Landsat composites per year. The images for each season were selected using the same calendar dates for all period:
Winter: December 2 of previous year until March 20 of current year
Spring: March 21 until June 24 of current year
Summer: June 25 until September 12 of current year
Fall: September 13 until December 1 of current year
The temporal composites were generated to Sentinel-2 L2A for 2018, 2019 and 2020, using the same approach (4 seasons x 3 percentiles x 6 spectral bands).
The benchmark areas were selected according to the EU tiling system, which consists of 7,042 regular tiles with 30 x 30 km. The dataset uses the ETRS89-extended / LAEA Europe as spatial reference system (EPSG:3035), and all the raster layers have 1,000 x 1,000 pixels and 30m of spatial resolution.
For all the EU the training samples will have 32 land-cover classes, varying according to the benchmark area:
111: Urban fabric
122: Road and rail networks and associated land
123: Port areas
124: Airports
131: Mineral extraction sites
132: Dump sites
133: Construction sites
141: Green urban areas
211: Non-irrigated arable land
212: Permanently irrigated arable land
213: Rice fields
221: Vineyards
222: Fruit trees and berry plantations
223: Olive groves
231: Pastures
311: Broad-leaved forest
312: Coniferous forest
321: Natural grasslands
322: Moors and heathland
323: Sclerophyllous vegetation
324: Transitional woodland-shrub
331: Beaches, dunes, sands
332: Bare rocks
333: Sparsely vegetated areas
334: Burnt areas
335: Glaciers and perpetual snow
411: Inland wetlands
421: Maritime wetlands
511: Water courses
512: Water bodies
521: Coastal lagoons
522: Estuaries
523: Sea and ocean
The gap filling validation data was generated by creating a mask of all nodata pixels (gaps) for each temporal composite, and then transposing that mask. All valid pixels covered by the transposed nodata mask are considered validation pixels. This method was chosen to retain the diversity of spatiotemporal nodata patterns that occur in the data. Each gap filling validation file contains 3 directory:
raw: original temporal composite
validation: transposed data
filled_tmwm8: the best gap filling method that was tested
See the eumap library for more information about the gapfiling approach and land-cover mapping using this dataset.
创建时间:
2024-07-19



