The yield on Germany 10Y Bond Yield eased to 2.57% on July 1, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.04 points, though it remains 0.04 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Germany 10-Year Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for Germany from May 1956 to May 2025 about long-term, Germany, 10-year, bonds, yield, government, interest rate, interest, and rate.

U.S. ten-year government bonds have provided significantly higher yields compared to German ten-year bonds since 2008, with the former yielding 4.42 percent in May 2025 compared to 2.56 percent for the latter. Being safe but low-return investments, treasury bond yields are generally considered an indicator of investor confidence about the economy. A rising yield indicates falling rates and falling demand, meaning that investors prefer to invest in higher-risk, higher-reward investments; a falling yield suggests the opposite.

The average yearly yield of German10-year government bonds has shown a significant downward trend from 1990 to 2024. Starting at nearly **** percent in 1990, yields steadily declined, with slight fluctuations, reaching a low of ***** percent in 2020. After 2020, yields began to rise again, reflecting recent increases in interest rates and inflation expectations. This long-term decline indicates decreasing inflation and interest rates in Australia over the past decades, with recent economic conditions prompting a reversal in bond yields.

Graph and download economic data for Interest Rates: Long-Term Government Bond Yields: 10-Year: Main (Including Benchmark) for Germany (IRLTLT01DEQ156N) from Q3 1956 to Q1 2025 about long-term, Germany, 10-year, bonds, yield, government, interest rate, interest, and rate.

The yield on Germany 30 Year Bond Yield rose to 3.09% on July 4, 2025, marking a 0.01 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.04 points and is 0.37 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Germany 30 Year Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on France 10Y Bond Yield eased to 3.27% on July 4, 2025, marking a 0.01 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0 points and is 0.10 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. France 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

As of December 30, 2024, the major economy with the highest yield on 10-year government bonds was Turkey, with a yield of ***** percent. This is due to the risks investors take when investing in Turkey, notably due to high inflation rates potentially eradicating any profits made when using a foreign currency to investing in securities denominated in Turkish lira. Of the major developed economies, United States had one the highest yield on 10-year government bonds at this time with **** percent, while Switzerland had the lowest at **** percent. How does inflation influence the yields of government bonds? Inflation reduces purchasing power over time. Due to this, investors seek higher returns to offset the anticipated decrease in purchasing power resulting from rapid price rises. In countries with high inflation, government bond yields often incorporate investor expectations and risk premiums, resulting in comparatively higher rates offered by these bonds. Why are government bond rates significant? Government bond rates are an important indicator of financial markets, serving as a benchmark for borrowing costs, interest rates, and investor sentiment. They affect the cost of government borrowing, influence the price of various financial instruments, and serve as a reflection of expectations regarding inflation and economic growth. For instance, in financial analysis and investing, people often use the 10-year U.S. government bond rates as a proxy for the longer-term risk-free rate.

The yield on Switzerland 10Y Bond Yield eased to 0.40% on July 4, 2025, marking a 0.01 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.05 points, though it remains 0.27 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Switzerland 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on Italy 10Y Bond Yield eased to 3.47% on July 4, 2025, marking a 0 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.07 points and is 0.47 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Italy 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on Germany 3 Year Bond Yield eased to 1.89% on July 4, 2025, marking a 0.03 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.06 points and is 0.80 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for Germany 3Y.

The yield on Spain 10Y Bond Yield eased to 3.21% on July 4, 2025, marking a 0.01 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.04 points, though it remains 0.13 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Spain 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on Japan 10Y Bond Yield eased to 1.44% on July 4, 2025, marking a 0.01 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.03 points, though it remains 0.37 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Japan 10 Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on Germany 15 Year Bond rose to 2.94% on June 27, 2025, marking a 0.02 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.04 points and is 0.23 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for Germany 15 Year Bond Yield.

The yield on Germany 7 Year Bond Yield eased to 2.35% on July 3, 2025, marking a 0.04 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.06 points, though it remains 0.15 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. This dataset includes a chart with historical data for Germany 7Y.

The yield on Austria 10Y Bond Yield eased to 2.96% on July 4, 2025, marking a 0 percentage point decrease from the previous session. Over the past month, the yield has fallen by 0.02 points and is 0.10 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Austria 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on Germany 1 Year Bond Yield rose to 1.79% on July 4, 2025, marking a 0.04 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.01 points, though it remains 1.47 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Germany 12 Month Bubill Yield - values, historical data, forecasts and news - updated on July of 2025.

The yield on United Kingdom 10Y Bond Yield rose to 4.56% on July 4, 2025, marking a 0.02 percentage point increase from the previous session. Over the past month, the yield has fallen by 0.06 points, though it remains 0.43 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. UK 10 Year Gilt Bond Yield - values, historical data, forecasts and news - updated on July of 2025.

This dataset consists of 1,759,830 multi-spectral image patches from the Sentinel-2 mission, annotated with image- and pixel-level land cover and land usage labels from the German land cover model LBM-DE2018 with land cover classes based on the CORINE Land Cover database (CLC) 2018. It includes pixel synchronous examples from each of the four seasons, plus an additional snowy set, spanning the time from April 2018 to February 2019. The patches were taken from 519,547 unique locations, covering the whole surface area of Germany, with each patch covering an area of 1.2km x 1.2km. The set is split into two overlapping grids, consisting of roughly 880,000 samples each, which are shifted by half the patch size in both dimensions. The images in each of the both grids themselves do not overlap.

Contents

Each sample includes:

3 10m resolution bands (RGB), 120px x 120px

1 10m resolution band (infrared), 120px x 120px

6 20m resolution bands, 60px x 60px

2 60m resolution bands, 20xp x 20px

1 pixel-level label map

2 binary masks for cloud and snow coverage

2 binary masks for easy and medium segmentation difficulties, marks areas <300px and <100px respectively

1 JSON-file containing additional meta-information

The meta.csv contains the following information about each sample:

Which season it belongs to

Which of the two grids it belongs to

Coordinates of the patch center

Whether it was acquired from Sentinel-2 Satellite A or B

Date and time of image acquisition

Snow and cloud coverage percentages

Image-level multi-class labels

Three additional image-level urbanization labels, based on the center pixel (details below)

The path to the sample

Classes

    ID
    Class




    1
    Continuous urban fabric


    2
    Discontinuous urban fabric


    3
    Industrial or commercial units


    4
    Road and rail networks and associated land


    5
    Port areas


    6
    Airports


    7
    Mineral extraction sites


    8
    Dump sites


    9
    Construction sites


    10
    Green urban areas


    11
    Sport and leisure facilities


    12
    Non-irrigated arable land


    13
    Vineyards


    14
    Fruit trees and berry plantations


    15
    Pastures


    16
    Broad-leaved forest


    17
    Coniferous forest


    18
    Mixed forest


    19
    Natural grasslands


    20
    Moors and heathland


    21
    Transitional woodland/shrub


    22
    Beaches, dunes, sands


    23
    Bare rock


    24
    Sparsely vegetated areas


    25
    Inland marshes


    26
    Peat bogs


    27
    Salt marshes


    28
    Intertidal flats


    29
    Water courses


    30
    Water bodies


    31
    Coastal lagoons


    32
    Estuaries


    33
    Sea and ocean

Urbanization classes

SLRAUM

0: None

1: Ländlicher Raum (~ rural area)

2: Städtischer Raum (~ urban area)

RTYP3

0: None

1: Ländliche Regionen (~ rural areas)

2: Regionen mit Verstädterungsansätzen (~ urbanizing areas)

3: Städtische Regionen (~ urban areas)

KTYP4

0: None

1: Dünn besiedelte ländliche Kreise

2: Kreisfreie Großstädte

3: Ländliche Kreise mit Verdichtungsansätzen

4: Städtische Kreise

Further information on the urbanization classes can be found here:

SLRAUM

https://www.bbsr.bund.de/BBSR/DE/forschung/raumbeobachtung/Raumabgrenzungen/deutschland/kreise/staedtischer-laendlicher-raum/kreistypen.html

RTYP3

https://www.bbsr.bund.de/BBSR/DE/forschung/raumbeobachtung/Raumabgrenzungen/deutschland/regionen/siedlungsstrukturelle-regionstypen/regionstypen.html

KTYP4

https://www.bbsr.bund.de/BBSR/DE/forschung/raumbeobachtung/Raumabgrenzungen/deutschland/kreise/siedlungsstrukturelle-kreistypen/kreistypen.html

License of landcover model

Bundesamt für Kartographie und Geodäsie

dl-de/by-2-0 from https://www.govdata.de/dl-de/by-2-0

© GeoBasis-DE / BKG 2022

Source of landcover model

https://gdz.bkg.bund.de/index.php/default/catalog/product/view/id/1071/s/corine-land-cover-5-ha-stand-2018-clc5-2018/

This landcover map was produced with a classification method developed in the project incora (Inwertsetzung von Copernicus-Daten für die Raumbeobachtung, mFUND Förderkennzeichen: 19F2079C) in cooperation with ILS (Institut für Landes- und Stadtentwicklungsforschung gGmbH) and BBSR (Bundesinstitut für Bau-, Stadt- und Raumforschung) funded by BMVI (Federal Ministry of Transport and Digital Infrastructure). The goal of incora is an analysis of settlement and infrastructure dynamics in Germany based on Copernicus Sentinel data. Even though the project is concluded, the annual land cover classification product is continuously generated. This classification is based on a time-series of monthly averaged, atmospherically corrected Sentinel-2 tiles (MAJA L3A-WASP: https://geoservice.dlr.de/web/maps/sentinel2:l3a:wasp; DLR (2019): Sentinel-2 MSI - Level 2A (MAJA-Tiles)- Germany). It consists of the following landcover classes: 10: forest 20: low vegetation 30: water 40: built-up 50: bare soil 60: agriculture Potential training and validation areas were automatically extracted using spectral indices and their temporal variability from the Sentinel-2 data itself as well as the following auxiliary datasets: - OpenStreetMap (Map data copyrighted OpenStreetMap contributors and available from htttps://www.openstreetmap.org) - Copernicus HRL Imperviousness Status Map 2018 (© European Union, Copernicus Land Monitoring Service 2018, European Environment Agency (EEA)) - S2GLC Land Cover Map of Europe 2017 (Malinowski et al. 2020: Automated Production of Land Cover/Use Map of Europe Based on Sentinel-2 Imagery. Remote Sens. 2020, 12(21), 3523; https://doi.org/10.3390/rs12213523) - Germany NUTS administrative areas 1:250000 (© GeoBasis-DE / BKG 2020 / dl-de/by-2-0 / https://gdz.bkg.bund.de/index.php/default/nuts-gebiete-1-250-000-stand-31-12-nuts250-31-12.html) - Contains modified Copernicus Sentinel data (2020), processed by mundialis Processing was performed for blocks of federal states and individual maps were mosaicked afterwards. For each class 100,000 pixels from the potential training areas were extracted as training data. An exemplary validation of the classification results was perfomed for the federal state of North Rhine-Westphalia as its open data policy allows for direct access to official data to be used as reference. Rules to convert relevant ATKIS Basis-DLM object classes to the incora nomenclature were defined. Subsequently, 5.000 reference points were randomly sampled and their classification in each case visually examined and, if necessary, revised to obtain a robust reference data set. The comparison of this reference data set with the incora classification yielded the following results: overall accuracy: 83.5% class: user's accuracy / producer's accuracy (number of reference points n) forest: 90.6% / 91.9% (1410) low vegetation: 69.2% / 82.8% (844) water: 97.0% / 94.2% (69) built-up: 96.5% / 97.4% (983) bare soil: 8.5% / 68.3% (41) agriculture: 96.6% / 68.4% (1653) Compared to the previous years, the overall accuracy and accuracies of some classes is reduced. 2021 was a rather cloudy year in Germany, which means that the detection of agricultural areas is hampered as it is based on the variance of the NDVI throughout the year. With fewer cloud-free images available, the NDVI variance is not fully covered and as no adaptations have been applied to the algorithm, agricultural fields may get classified as low vegetation or bare soil more often. Another reason for lower classification accuracy is the significant damage that occured to forest areas due to storm and bark beetle. The validation dataset was generated based on aerial imagery from the years 2018/2019 which and is slowly becoming obsolete. An up-to-date validation dataset will be applied. Incora report with details on methods and results: pending