This dataset provides monthly maximum Land Surface Temperature (LST) values over Europe, derived from 1-km AVHRR observations. The data is generated by DLR and provided in the framework of the TIMELINE project. LST values are retrieved using physically-based split- and mono-window algorithms and corrected for atmospheric influences and surface emissivity. Only cloud-free observations with sensor view angles below 50 degrees are used. Due to reliance on infrared observations, data may be limited under persistent cloud cover. To ensure temporal consistency across sensors and overpass times, an orbit drift correction method was applied. This method harmonizes LST values to a fixed reference time of 13:00 local solar time, approximating the daily maximum temperature. The dataset is gridded in a 1-km LAEA ETRS89 projection. The product is provided in four tiles, covering the extent of the European Environmental Agency (EEA) reference grid, which includes the area from 900 000 m East and 900 000m North to 7 400 000m East and 5 500 000m North. The TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long-Term Dynamics In our Natural Environment) project, led by the German Remote Sensing Data Center (DFD) of the German Aerospace Center (DLR), focuses on generating a consistent, multi-decadal time series derived from NOAA and Metop AVHRR data. Spanning more than 40 years from the early 1980s to the present this dataset covers Europe and North Africa. TIMELINE establishes an operational environment for the systematic reprocessing of AVHRR raw data into Level 1b, Level 2, and Level 3 geoinformation products at 1.1 km spatial resolution. These products maintain uniform standards in format, projection, and spatial coverage. The dataset includes a comprehensive suite of land and atmospheric parameters such as atmospherically corrected surface reflectance, NDVI, snow cover, fire hotspots, burnt area, land and sea surface temperatures, and various cloud physical properties (e.g., cloud top temperature). By combining traditional and innovative remote sensing products with robust processing algorithms and state-of-the-art validation techniques, TIMELINE provides a unique, high-quality dataset for global change research.

Indian Remote Sensing satellites (IRS) are a series of Earth Observation satellites, built, launched and maintained by Indian Space Research Organisation. The IRS series provides many remote sensing services to India and international ground stations. With 5 m resolution and products covering areas up to 70 km x 70 km IRS PAN data provide a cost effective solution for mapping tasks up to 1:25'000 scale.

The FireBIRD mission consists of two small satellites, TET-1 and BIROS. Together, the two satellites are on an Earth observation mission that aims to detect forest fires, or high-temperature events, from space. The new infrared system provides high-quality data that is capable of measuring the spread of the fire and the amount of heat generated with great accuracy very early on - almost in real time - meaning that FireBIRD can serve as an early warning system. The data acquired from this Earth observation mission can also be used as a basis for scientific climate research. In addition to the main payload of the cameras, further experiments have been planned for developing the technology on board the small satellites. Further information can be found on the following website: http://www.dlr.de/firebird/en/ and in the FireBIRD brochure available at: http://www.dlr.de/firebird/en/Portaldata/79/Resources/dokumente/FireBIRD_Broschuere_HighRes_v3_english.pdf

The TimeScan product is based on the fully-automated analysis of comprehensive time-series acquisitions of Landsat data. Based on a user-specified definition of the required period of time, the region of interest and – optionally – the maximum cloud cover, the TimeScan processor starts with the collection of all available Landsat scenes that meet the user specification. Next, for each single scene masking of clouds, haze and shadow is conducted using the Fmask algorithm. Then, a total of 6 indices is calculated for those pixels of each single scene that have not been masked in the prior step. The set of indices includes the Normalized Difference Vegetation Index (NDVI), the Built-up Index (BI), the Modified Normalized Difference Water Index (MNDWI), the Normalized Difference Band-5 / Band-7 (ND57), the Normalized Difference Band-4 / Band-3 (ND43), and the Normalized Difference Band-3 / Band-2 (ND32). Finally, the TimeScan product is generated by calculating the temporal statistics (minimum, maximum, mean, standard deviation, mean slope) for each index over the defined period of time. Hence, in case of the defined 6 indices chosen, the TimeScan product will include a total of 30 bands (5 statistical features per index). As an additional band a quality layer is added which shows for each pixel the number of valid values (meaning times with no cloud/haze or shadow cover) that have been included in the statistics calculation.

The global TanDEM-X High-Resolution Coastline Product was developed by the German Remote Sensing Data Center (DFD) at the German Aerospace Center (DLR) as part of the TanDEM-X Mission and the HydroSHEDS v2.0 project. It is a global vector dataset that outlines the boundary between terrestrial and marine environments at a resolution of 10 meters. Between 2010 and 2015, the TanDEM-X mission acquired a complete coverage of the Earth's landmass, resulting in a global digital elevation model (DEM). Since the TanDEM-X coastline is derived from the TanDEM-X dataset, it provides an optimal fit for improving the DEM. Additionally, the TanDEM-X coastline is a key component in the derivation of hydrographic data within the HydroSHEDS v2.0 project, where it defines the outer boundary of watersheds and river networks. To meet hydrological requirements and to ensure global consistency, the TanDEM-X coastline was extracted automatically in a first step and subsequently manually verified and refined. Since the coastline is a mapping feature located in the coastal zone, its position is a function of the source data, the method used to identify the coastline, the time of acquisition, and the purpose of mapping.

The World Settlement Footprint (WSF) 3D provides detailed quantification of the average height, total volume, total area and the fraction of buildings at 90 m resolution at a global scale. It is generated using a modified version of the World Settlement Footprint human settlements mask derived from Sentinel-1 and Sentinel-2 satellite imagery in combination with digital elevation data and radar imagery collected by the TanDEM-X mission. The framework includes three basic workflows: i) the estimation of the mean building height based on an analysis of height differences along potential building edges, ii) the determination of building fraction and total building area within each 90 m cell, and iii) the combination of the height information and building area in order to determine the average height and total built-up volume at 90 m gridding. In addition, global height information on skyscrapers and high-rise buildings provided by the Emporis database is integrated into the processing framework, to improve the WSF 3D Building Height and subsequently the Building Volume Layer. A comprehensive validation campaign has been performed to assess the accuracy of the dataset quantitatively by using VHR 3D building models from 19 globally distributed regions (~86,000 km2) as reference data. The WSF 3D standard layers are provided in the format of Lempel-Ziv-Welch (LZW)-compressed GeoTiff files, with each file - or image tile - covering an area of 1 x 1 ° geographical lat/lon at a geometric resolution of 2.8 arcsec (~ 90 m at the equator). Following the system established by the TDX-DEM mission, the latitude resolution is decreased in multiple steps when moving towards the poles to compensate for the reduced circumference of the Earth.