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196 Datensätze

Luft- und Raumfahrt

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Geo-ForPy - Forest Cover Changes in the Paraguayan Chaco - Landsat-5/7/8,1987-2020

The dataset is based on the analysis of forest cover dynamics in the Paraguayan Chaco (northeastern part of Paraguay) between 1987 and 2020. The underlying forest masks were derived through annual forst classifications with a Random-Forest-Classifier trained on Landsat data from 1987 until 2020. The map shows the year in which the forest area was lost.

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.01.1987 — 31.12.2020

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

IceLines - Sentinel-1 - Antarctica

IceLines (Ice Shelf and Glacier Front Time Series) is an automated calving front monitoring service providing monthly ice shelf front time series of major Antarctic ice shelves. The provided time series allows to discover the dynamics of ice shelf front changes and calving events. The front positions are automatically derived from Sentinel-1 data based on a deep neuronal network called HED-U-Net. The time series covers the timespan 2014 to today (partly limited due to Sentinel-1 data availability). Incorrectly extracted fronts are truncated which might lead to gaps in the time series especially between December to March due to strong surface melt. Annual averages are calculated based on the extracted monthly fronts (excluding the summer months) and provide more robust results due to temporal aggregation

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.12.2014 —

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Global SnowPack - MODIS - Yearly

This product shows the snow cover duration for a hydrological year. Its beginning differs from the calendar year, since some of the precipitation that falls in late autumn and winter falls as snow and only drains away when the snow melts in the following spring or summer. The meteorological seasons are used for subdivision and the hydrological year begins in autumn and ends in summer. The snow cover duration is made available for three time periods: the snow cover duration for the entire hydrological year (SCD), the early snow cover duration (SCDE), which extends from autumn to midwinter (), and the late snow cover duration (SCDL), which in turn extends over the period from mid-winter to the end of summer. For the northern hemisphere SCD lasts from September 1st to August 31st, for the southern hemisphere it lasts from March 1st to February 28th/29th. The SCDE lasts from September 1st to January 14th in the northern hemisphere and from March 1st to July 14th in the southern hemisphere. The SCDL lasts from January 15th to August 31st in the northern hemisphere and from July 15th to February 28th/29th in the southern hemisphere.
The “Global SnowPack” is derived from daily, operational MODIS snow cover product for each day since February 2000. Data gaps due to polar night and cloud cover are filled in several processing steps, which provides a unique global data set characterized by its high accuracy, spatial resolution of 500 meters and continuous future expansion. It consists of the two main elements daily snow cover extent (SCE) and seasonal snow cover duration (SCD; full and for early and late season). Both parameters have been designated by the WMO as essential climate variables, the accurate determination of which is important in order to be able to record the effects of climate change. Changes in the largest part of the cryosphere in terms of area have drastic effects on people and the environment.
For more information please also refer to:

Dietz, A.J., Kuenzer, C., Conrad, C., 2013. Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products. International Journal of Remote Sensing 34, 3879–3902. https://doi.org/10.1080/01431161.2013.767480
Dietz, A.J., Kuenzer, C., Dech, S., 2015. Global SnowPack: a new set of snow cover parameters for studying status and dynamics of the planetary snow cover extent. Remote Sensing Letters 6, 844–853. https://doi.org/10.1080/2150704X.2015.1084551
Dietz, A.J., Wohner, C., Kuenzer, C., 2012. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products. Remote Sensing 4. https://doi.org/10.3390/rs4082432
Dietz, J.A., Conrad, C., Kuenzer, C., Gesell, G., Dech, S., 2014. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data. Remote Sensing 6. https://doi.org/10.3390/rs61212752
Rößler, S., Witt, M.S., Ikonen, J., Brown, I.A., Dietz, A.J., 2021. Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers. Geosciences 11, 130. https://doi.org/10.3390/geosciences11030130

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

DFD-LAX

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.01.2000 — 28.02.2022

Raumbezug

SCMaP - Landsat - Germany, 1984-2014

The Soil Composite Mapping Processor (SCMaP) is a new approach designed to make use of per-pixel compositing to overcome the issue of limited soil exposure due to vegetation. Three primary product levels are generated that will allow for a long term assessment and distribution of soils that include the distribution of exposed soils, a statistical information related to soil use and intensity and the generation of exposed soil reflectance image composites. The resulting composite maps provide useful value-added information on soils with the exposed soil reflectance composites showing high spatial coverage that correlate well with existing soil maps and the underlying geological structural regions.

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

13.04.1984 — 09.11.2014

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Geo-ForPy - Forest Structure Information for the Paraguayan Chaco - Sentinel-1/2/GEDI, 2019

The dataset is based on an analysis combining Sentinel-1 (SAR), -2 (Multispectral) and GEDI (Global Ecosystem Dynamics Investigation, LiDAR) data to model vegetation structure information.
The derived products show high-spatial resolution maps (10 m) of total canopy cover (cover density in %), Foliage height diversity (Fhd) index in meter, Plant area index (Pai) in meter and canopy height (rh95) in meter.

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.04.2019 — 30.09.2019

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Geo-ForPy - Fragmentation of Forest Cover in the Paraguayan Chaco - Landsat-5/7/8, 2000/2010/2020

This product is a shape file of all detected forest patches in the Paraguayan Chaco that are larger than 10 hectars fort he years 2000, 2010, and 2020. Every forest patch contains information on its perimeter, size, shape, and core area. By looking at all forest patches together, an impression can be gained of the fragmentation of the forest in the Paraguayan Chaco.
Proximity is a measure of fragmentation. Areas of large and close by forest patches show high proximity values while isolated patches or patchest hat are only surrounded by small forest patches, have a small proximity.
The Core area index quantifies the share of core area in the entire forest patch area. Thereby, corea area is the area of a forest patch with at least 500m distance to the edge of the forest.
The Shape index is calculated from perimeter and area of a patch. The fragementation of a forest often has the effect that the ratio between area and perimeter is affected. The edge lengths become longer while the surface area becomes smaller.

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.01.2000 — 31.12.2020

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Sentinel-2 MSI - Vegetation Indices (AGRO-DE) - Germany, Monthly Composites

This product comprises monthly composites and temporal statistics of selected vegetation indices (VI) for all of Germany from 2015 to today in 10m resolution, which were calculated using the DLR TimeScan processor. VIs (EVI, HA56, NDRE, NDVI, NDWI, PSRI and REIP) were calculated from Sentinel-2 Level 2A data at 10m spatial resolution produced by means of the DLR-PACO processor. Monthly compositing and temporal statistics are based on all valid observations per vegetation index. Derived variables per index are: minimum, maximum, mean and standard-deviation as well as the number of valid observations. Products are available in tiles according to the ESA Sentinel 2 granule grid (UTM). This is a product of AGRO-DE project (https://agro-de.info/).

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.07.2015 —

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Tree Canopy Cover Loss Yearly per District - Germany, 2018-2021

The product contains information of tree canopy cover loss in Germany per district (Landkreis) between January 2018 and April 2021 at monthly temporal resolution. The information is aggregated at from the 10 m spatial resolution Sentinel-2 and Landsat-based raster product (Tree Canopy Cover Loss Monthly - Landsat-8/Sentinel-2 - Germany, 2018-2021). The method used to derive this product as well as the mapping results are described in detail in Thonfeld et al. (2022). The map depicts areas of natural disturbances (windthrow, fire, droughts, insect infestation) as well as sanitation and salvage logging, and regular forest harvest without explicitly differentiating these drivers. The vector files contain information about tree canopy cover loss area per forest type (deciduous, coniferous, both) and per year (2018, 2019, 2020, January-April 2021, and January 2018-April 2021) in absolute numbers and in percentages. In addition, the vector files contain the district area and the total forest area per district.

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.01.2018 — 30.04.2021

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Sentinel-2 MSI - Vegetation Indices (AGRO-DE) - Germany, Yearly Composites

This product comprises yearly composites and temporal statistics of selected vegetation indices (VI) for all of Germany from 2015 to today in 10m resolution, which were calculated using the DLR TimeScan processor. VIs (EVI, HA56, NDRE, NDVI, NDWI, PSRI and REIP) were calculated from Sentinel-2 Level 2A data at 10m spatial resolution produced by means of the DLR-PACO processor. Yearly compositing and temporal statistics are based on all valid and cloud-free observations per vegetation index. Derived variables per index are: minimum (min), maximum (max), mean, standard-deviation (sd), average absolute difference between observations (masd) as well as the number of cloud-free observations (n-cloudfree) and the total number of observations (n-obs). This is a product of the AGRO-DE project (https://agro-de.info/).

Luft- und Raumfahrt
Straßen
Bereitgestellt durch

German Aerospace Center (DLR)

Art des Datenzugangs

WWW / WMS

Aktualität der Datensatzbeschreibung

18.01.2023

Zeitbezug der Daten

01.01.2016 —

Aktualisierungsfrequenz

Unregelmäßig

Raumbezug

Digitale Topographische Karte 1:10 000 (DTK10)

Die Digitale Topographische Karte 1:10 000 ist die aus dem Basis-DLM und einem DGM erzeugte topographische Karte im Rasterformat. Die Rasterdaten sind nach kartographischen Inhaltselementen in 23 einzelnen Ebenen (Einzellayer) mit einer Auflösung von 508 ppi und in einfarbiger oder farbiger Kombination (Summenlayer) erhältlich. Sie werden sowohl im Blattschnitt der TK10 als auch blattschnittfrei für den Freistaat Sachsen abgegeben.

Straßen
Bahn
Wasserstraßen und Gewässer
Luft- und Raumfahrt
Bereitgestellt durch

Landesamt für Geobasisinformation Sachsen (GeoSN)

Art des Datenzugangs

TIFF

Aktualität der Datensatzbeschreibung

03.01.2023

Aktualisierungsfrequenz

Kontinuierlich

Raumbezug

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