DOI: 10.5281/zenodo.4311598
title: Input dataset for gap filling and land-cover mapping using eumap Library - 2000 to 2020

description: 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.
description: This work has received funding from the European Union's the Innovation and Networks Executive Agency (INEA) under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).