eu-cdse · aostrowiecka · Sep 4, 2025 · Sep 4, 2025 · Sep 8, 2025 · Sep 8, 2025
diff --git a/APIs/OData.qmd b/APIs/OData.qmd
@@ -184,7 +184,9 @@ The following collections are currently available:
   * **ENVISAT** (ENVISAT- Medium Resolution Imaging Spectrometer - MERIS)
   * **LANDSAT-5**
   * **LANDSAT-7**
+  * **LANDSAT-8**
   * **LANDSAT-8-ESA**
+  * **LANDSAT-9**
   * **COP-DEM** (Copernicus DEM)
   * **TERRAAQUA** (Terra MODIS and Aqua MODIS)
   * **S2GLC** (S2GLC 2017)
@@ -449,17 +451,17 @@ df[columns_to_print].head(3)
 
 :::
 
-To get products with cloudCover\< 10% and productType=S2MSI2A and ASCENDING orbitDirection between two dates:
+To get products with cloudCover\< 10% and productType=S2MSI2A
 
 ::: {.panel-tabset}
 
 # HTTPS Request
 
-[`https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name eq 'SENTINEL-2' and Attributes/OData.CSC.DoubleAttribute/any(att:att/Name eq 'cloudCover' and att/OData.CSC.DoubleAttribute/Value lt 10.00) and Attributes/OData.CSC.StringAttribute/any(att:att/Name eq 'productType' and att/OData.CSC.StringAttribute/Value eq 'S2MSI2A') and Attributes/OData.CSC.StringAttribute/any(att:att/Name eq 'orbitDirection' and att/OData.CSC.StringAttribute/Value eq 'ASCENDING') and ContentDate/Start gt 2022-05-03T00:00:00.000Z and ContentDate/Start lt 2022-05-03T04:00:00.000Z&$top=10`](https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name%20eq%20%27SENTINEL-2%27%20and%20Attributes/OData.CSC.DoubleAttribute/any(att:att/Name%20eq%20%27cloudCover%27%20and%20att/OData.CSC.DoubleAttribute/Value%20lt%2010.00)%20and%20Attributes/OData.CSC.StringAttribute/any(att:att/Name%20eq%20%27productType%27%20and%20att/OData.CSC.StringAttribute/Value%20eq%20%27S2MSI2A%27)%20and%20Attributes/OData.CSC.StringAttribute/any(att:att/Name%20eq%20%27orbitDirection%27%20and%20att/OData.CSC.StringAttribute/Value%20eq%20%27ASCENDING%27)%20and%20ContentDate/Start%20gt%202022-05-03T00:00:00.000Z%20and%20ContentDate/Start%20lt%202022-05-03T04:00:00.000Z&$top=10){target="_blank"}
+[`https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name%20eq%20%27SENTINEL-2%27%20and%20Attributes/OData.CSC.DoubleAttribute/any(att:att/Name%20eq%20%27cloudCover%27%20and%20att/OData.CSC.DoubleAttribute/Value%20lt%2010.00)%20and%20Attributes/OData.CSC.StringAttribute/any(att:att/Name%20eq%20%27productType%27%20and%20att/OData.CSC.StringAttribute/Value%20eq%20%27S2MSI2A%27)%20and%20ContentDate/Start%20gt%202022-05-03T00:00:00.000Z%20and%20ContentDate/Start%20lt%202022-05-03T04:00:00.000Z&$top=10`](https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name%20eq%20%27SENTINEL-2%27%20and%20Attributes/OData.CSC.DoubleAttribute/any(att:att/Name%20eq%20%27cloudCover%27%20and%20att/OData.CSC.DoubleAttribute/Value%20lt%2010.00)%20and%20Attributes/OData.CSC.StringAttribute/any(att:att/Name%20eq%20%27productType%27%20and%20att/OData.CSC.StringAttribute/Value%20eq%20%27S2MSI2A%27)%20and%20ContentDate/Start%20gt%202022-05-03T00:00:00.000Z%20and%20ContentDate/Start%20lt%202022-05-03T04:00:00.000Z&$top=10){target="_blank"}
 
 # Python
 ```{python}
-json = requests.get("https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name eq 'SENTINEL-2' and Attributes/OData.CSC.DoubleAttribute/any(att:att/Name eq 'cloudCover' and att/OData.CSC.DoubleAttribute/Value lt 10.00) and Attributes/OData.CSC.StringAttribute/any(att:att/Name eq 'productType' and att/OData.CSC.StringAttribute/Value eq 'S2MSI2A') and Attributes/OData.CSC.StringAttribute/any(att:att/Name eq 'orbitDirection' and att/OData.CSC.StringAttribute/Value eq 'ASCENDING') and ContentDate/Start gt 2022-05-03T00:00:00.000Z and ContentDate/Start lt 2022-05-03T04:00:00.000Z&$top=10").json()
+json = requests.get("https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name%20eq%20%27SENTINEL-2%27%20and%20Attributes/OData.CSC.DoubleAttribute/any(att:att/Name%20eq%20%27cloudCover%27%20and%20att/OData.CSC.DoubleAttribute/Value%20lt%2010.00)%20and%20Attributes/OData.CSC.StringAttribute/any(att:att/Name%20eq%20%27productType%27%20and%20att/OData.CSC.StringAttribute/Value%20eq%20%27S2MSI2A%27)%20and%20ContentDate/Start%20gt%202022-05-03T00:00:00.000Z%20and%20ContentDate/Start%20lt%202022-05-03T04:00:00.000Z&$top=10").json()
 df = pd.DataFrame.from_dict(json['value'])
 
 # Print only specific columns
@@ -588,10 +590,18 @@ To check acceptable attribute names for Complementary data:
 
 [`https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-7)`](https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-7)){target="_blank"}
 
+# LANDSAT-8
+
+[`https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-8)`](https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-8)){target="_blank"}
+
 # LANDSAT-8-ESA
 
 [`https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-8-ESA)`](https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-8-ESA)){target="_blank"}
 
+# LANDSAT-9
+
+[`https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-9)`](https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(LANDSAT-9)){target="_blank"}
+
 # COP-DEM
 
 [`https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(COP-DEM)`](https://catalogue.dataspace.copernicus.eu/odata/v1/Attributes(COP-DEM)){target="_blank"}
@@ -1377,11 +1387,11 @@ build a filter with the specified structure as defined [Query Collection of Prod
 
 # HTTPS Request
 
-[`https://catalogue.dataspace.copernicus.eu/odata/v1/DeletedProducts?$filter=Attributes/OData.CSC.IntegerAttribute/any(att:att/Name eq 'orbitNumber' and att/OData.CSC.IntegerAttribute/Value eq 10844) and attributes/OData.CSC.StringAttribute/any(att:att/Name eq 'orbitDirection' and att/OData.CSC.StringAttribute/Value eq 'ASCENDING')`](https://catalogue.dataspace.copernicus.eu/odata/v1/DeletedProducts?$filter=Attributes/OData.CSC.IntegerAttribute/any(att:att/Name%20eq%20%27orbitNumber%27%20and%20att/OData.CSC.IntegerAttribute/Value%20eq%2010844)%20and%20attributes/OData.CSC.StringAttribute/any(att:att/Name%20eq%20%27orbitDirection%27%20and%20att/OData.CSC.StringAttribute/Value%20eq%20%27ASCENDING%27)){target="_blank"}
+[`https://catalogue.dataspace.copernicus.eu/odata/v1/DeletedProducts?$filter=Attributes/OData.CSC.IntegerAttribute/any(att:att/Name%20eq%20%27orbitNumber%27%20and%20att/OData.CSC.IntegerAttribute/Value%20eq%2010844)`](https://catalogue.dataspace.copernicus.eu/odata/v1/DeletedProducts?$filter=Attributes/OData.CSC.IntegerAttribute/any(att:att/Name%20eq%20%27orbitNumber%27%20and%20att/OData.CSC.IntegerAttribute/Value%20eq%2010844)){target="_blank"}
 
 # Python
 ```{python}
-json = requests.get("https://catalogue.dataspace.copernicus.eu/odata/v1/DeletedProducts?$filter=Attributes/OData.CSC.IntegerAttribute/any(att:att/Name eq 'orbitNumber' and att/OData.CSC.IntegerAttribute/Value eq 10844) and attributes/OData.CSC.StringAttribute/any(att:att/Name eq 'orbitDirection' and att/OData.CSC.StringAttribute/Value eq 'ASCENDING')").json()
+json = requests.get("https://catalogue.dataspace.copernicus.eu/odata/v1/DeletedProducts?$filter=Attributes/OData.CSC.IntegerAttribute/any(att:att/Name%20eq%20%27orbitNumber%27%20and%20att/OData.CSC.IntegerAttribute/Value%20eq%2010844)").json()
 df = pd.DataFrame.from_dict(json['value'])
 
 # Print only specific columns

diff --git a/APIs/OpenSearch.qmd b/APIs/OpenSearch.qmd
@@ -88,6 +88,7 @@ As for today, the following collections are defined and may be used:
   * **Landsat5 or LANDSAT-5**
   * **Landsat7 or LANDSAT-7**
   * **Landsat8 or LANDSAT-8**
+  * **Landsat9 or LANDSAT-9**
   * **COP-DEM** (Copernicus DEM)
   * **TERRAAQUA** (Terra MODIS and Aqua MODIS)
   * **S2GLC** (S2GLC 2017)

diff --git a/APIs/S3.qmd b/APIs/S3.qmd
@@ -365,6 +365,8 @@ eouser@aws-cli:~$ aws s3 ls s3://eodata/
                            PRE Landsat-5/
                            PRE Landsat-7/
                            PRE Landsat-8/
+                           PRE Landsat-8-ESA/
+                           PRE Landsat-9/
                            PRE SMOS/
                            PRE Sentinel-1/
                            PRE Sentinel-1-COG/

diff --git a/Data.qmd b/Data.qmd
@@ -18,6 +18,7 @@ listing:
     - Data/ComplementaryData/Landsat5.qmd
     - Data/ComplementaryData/Landsat7.qmd
     - Data/ComplementaryData/Landsat8.qmd
+    - Data/ComplementaryData/Landsat9.qmd
     - Data/ComplementaryData/MERIS.qmd
     - Data/ComplementaryData/SMOS.qmd
   exclude:
@@ -35,4 +36,4 @@ For the latest information about available satellite data, users and stakeholder
 
 
 ::: {#listings}
-:::
+:::
diff --git a/Data/ComplementaryData/Landsat5.qmd b/Data/ComplementaryData/Landsat5.qmd
@@ -20,7 +20,7 @@ constellation = "Landsat-5"
 ```
 The Landsat programme is a joint USGS and NASA-led enterprise for Earth observation that represents the world's longest running system of satellites for moderate-resolution optical remote sensing for land, coastal areas and shallow waters.
 
-Landsat products in the Copernicus Data Space Ecosystem originate from the ESA processing. For more information please visit [here](https://earth.esa.int/eogateway/missions/landsat){target="_blank"}.
+Landsat-5 Collection 1 products in the Copernicus Data Space Ecosystem originate from the ESA processing. For more information please visit [here](https://earth.esa.int/eogateway/missions/landsat){target="_blank"}.
 
 Landsat-5 was launched on 1 March 1984 and ended its mission on 5 June 2013. It carried the Thematic Mapper (TM), a multispectral scanning radiometer operating in the visible and infrared regions of the electromagnetic spectrum. It was characterized by 185 km swath width and 30 m resolution for visible (VIS), near infrared (NIR) and shortwave infrared (SWIR), and 120 m for thermal infrared (TIR). The acquired Landsat TM scene covers an area of approximately 183 km x 172.8 km. A standard full scene is nominally centred on the intersection of a path and a row (the actual image centre can vary by up to 100 m). A full image consists of 6920 pixels x 5760 lines and each uncompressed band in the VIS, NIR, SWIR and TIR spectral regions requires 40 MB of storage space.
 

diff --git a/Data/ComplementaryData/Landsat7.qmd b/Data/ComplementaryData/Landsat7.qmd
@@ -20,7 +20,7 @@ constellation = "Landsat-7"
 ```
 The Landsat programme is a joint USGS and NASA-led enterprise for Earth observation that represents the world's longest running system of satellites for moderate-resolution optical remote sensing for land, coastal areas and shallow waters.
 
-Landsat products in the Copernicus Data Space Ecosystem originate from the ESA processing. For more information please visit [here](https://earth.esa.int/eogateway/missions/landsat){target="_blank"}.
+Landsat-7 Collection 1 products in the Copernicus Data Space Ecosystem originate from the ESA processing. For more information please visit [here](https://earth.esa.int/eogateway/missions/landsat){target="_blank"}.
 
 Landsat-7 has continued the goal of the Landsat programme to repeatedly image Earth's land and coastal areas in order to monitor changes to these areas over time. The satellite has continued to provide data continuity for the Thematic Mapper aboard Landsat-4 and 5, utilising an enhanced version of the instrument. 
 

diff --git a/Data/ComplementaryData/Landsat8.qmd b/Data/ComplementaryData/Landsat8.qmd
@@ -20,7 +20,13 @@ constellation = "Landsat-8"
 ```
 The Landsat programme is a joint USGS and NASA-led enterprise for Earth observation that represents the world's longest running system of satellites for moderate-resolution optical remote sensing for land, coastal areas and shallow waters.
 
-Landsat products in the Copernicus Data Space Ecosystem originate from the ESA processing. For more information please visit [here](https://earth.esa.int/eogateway/missions/landsat){target="_blank"}.
+Landsat-8 products (2013 – end of 2020) in the Copernicus Data Space Ecosystem originate from ESA processing and are available through the LANDSAT-8-ESA collection. For more information please visit [here](https://earth.esa.int/eogateway/missions/landsat){target="_blank"}.
+
+::: {.callout-note}
+
+Landsat-8 Collection 2 Level-1 products with full worldwide coverage, provided by USGS, will soon be added to the Copernicus Data Space Ecosystem. These datasets will be progressively indexed in the OData Catalogue, with full availability expected by the end of Q3 2025. The data will be visible in the search browser, but only users with special permissions will be able to download the products. To obtain permissions, you must submit a request to the mission officer.
+
+:::
 
 Landsat-8 carries the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). OLI provides imagery in the VIS, NIR and SWIR spectral ranges.  It acquires images with 15 m panchromatic and 30 m multi-spectral spatial resolutions, covering a wide 185 km swath. This allows it to capture extensive areas of the Earth's landscape while maintaining enough resolution to identify features like urban centers, farms, forests, and other land uses. The entire Earth falls within view once every 16 days due to Landsat-8’s near-polar orbit. The TIRS instrument is a thermal imager operating in a pushbroom mode with two Infra-Red channels: 10.8 µm and 12 µm with 100 m spatial resolution.
 

diff --git a/Data/ComplementaryData/Landsat9.qmd b/Data/ComplementaryData/Landsat9.qmd
@@ -0,0 +1,51 @@
+---
+title: "Landsat-9"
+aliases: 
+  - /Data/Landsat9.html
+format:
+  html:
+    code-fold: true
+execute:
+  echo: false
+  output: asis
+jupyter: python3
+image: https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/media/images/L9_Detroit_hyperwall_rgb_nolabels.jpg
+---
+
+```{python}
+#| tags: [parameters]
+
+constellation = "Landsat-9"
+
+```
+Landsat 9 mission, collaborative effort between the U.S. Geological Survey (USGS) and NASA, continuing the Landsat program’s legacy of providing crucial global observations for monitoring, understanding and managing Earth's natural resources.
+
+::: {.callout-note}
+
+Landsat-9 Collection 2 Level-1 products with full worldwide coverage, provided by USGS, will soon be added to the Copernicus Data Space Ecosystem. These datasets will be progressively indexed in the OData Catalogue, with full availability expected by the end of Q3 2025. The data will be visible in the search browser, but only users with special permissions will be able to download the products. To obtain permissions, you must submit a request to the mission officer. 
+
+:::
+
+Launched in September 2021 satellite continues the legacy of providing critical moderate-resolution satellite imagery for land, coastal, and shallow water analysis. It is equiped in two primary sensors: the Operational Land Imager 2 (OLI-2) and the Thermal Infrared Sensor 2 (TIRS-2). OLI-2 captures multispectral imagery in the visible, near-infrared, and shortwave infrared spectral ranges, with spatial resolutions of 30 meters and a panchromatic band at 15 meters, covering a swath width of 185 km. TIRS-2 provides thermal imaging in two infrared channels 10.8 µm and 12 µm with a spatial resolution of 100 meters. The instruments on Landsat-9, while similar to those on Landsat-8, have been refined to improve data accuracy and reliability. Collecting up to 750 scenes daily, this mission ensures the continuity of Earth's observational record with a revisit period of 16 days, supporting environmental monitoring, land use planning, and climate research. Landsat 9 expands the archive's volume by capturing images of all global landmasses and nearshore coastal areas, including islands, at solar elevation angles greater than 5 degrees - areas that were not consistently imaged prior to Landsat 8.
+
+Access to Landsat-9 data is possible via API
+
+::: {.panel-tabset}
+
+# OpenSearch
+[https://catalogue.dataspace.copernicus.eu/resto/api/collections/LANDSAT-9/search.json?](https://catalogue.dataspace.copernicus.eu/resto/api/collections/LANDSAT-9/search.json?){target="_blank"}
+
+
+# OData
+[`https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name eq 'LANDSAT-9'`](<https://catalogue.dataspace.copernicus.eu/odata/v1/Products?$filter=Collection/Name eq 'LANDSAT-9'>){target="_blank"}
+
+:::
+
+In order to get access to data at specific processing level as well as specific product types, you are advised to use queries provided in each section below.
+
+If it is required to customize query in respect to spatial and time coverage, satellite features etc. please, follow instructions on:
+
+•	[OpenSearch](https://documentation.dataspace.copernicus.eu/APIs/OpenSearch.html){target="_blank"}\
+•	[OData](https://documentation.dataspace.copernicus.eu/APIs/OData.html){target="_blank"}
+
+{{< include ../_render_collections.qmd >}}
diff --git a/Data/Datafunctions/data_availability.py b/Data/Datafunctions/data_availability.py
@@ -15,6 +15,7 @@ def main(c):
         "Landsat-5": ComplementaryOffer,
         "Landsat-7": ComplementaryOffer,
         "Landsat-8": ComplementaryOffer,
+        "Landsat-9": ComplementaryOffer,
         "Commercial data": VHROffer,            
         "AdditionalComplementaryData": Additional,      
         "CAMS": CAMSOffer,
@@ -135,9 +136,12 @@ def DataFetch(c,i):
         odata = c['summaries']['DataAvailability'][i]['OData']
     except Exception:
         odata = ''
+    try:
+        Origin = c['summaries']['DataAvailability'][i]['Origin']
+    except Exception:
+        Origin = ''
 
-
-    return type,status,access,product_type,specific_product,spatial,temporal,product_link,catalogue,footnotes,provider,satellite,resolution,opensearch,odata
+    return type,status,access,product_type,specific_product,spatial,temporal,product_link,catalogue,footnotes,provider,satellite,resolution,opensearch,odata,Origin
 
 def auxillary(c):
     tabletitle = "Offered Data"
@@ -292,10 +296,10 @@ def ComplementaryOffer(c):
         empty_columns = []  # Track empty columns
 
         for i in range(0, data_offer):
-            type,status,access,product_type,specific_product,spatial,temporal,product_link,catalogue,footnotes,provider,satellite,resolution,opensearch,odata = DataFetch(c,i)
-            t.append([type,status, access, spatial, temporal,catalogue])
+            type,status,access,product_type,specific_product,spatial,temporal,product_link,catalogue,footnotes,provider,satellite,resolution,opensearch,odata,Origin = DataFetch(c,i)
+            t.append([type, status, access, spatial, temporal, catalogue,Origin])
             note += footnotes
-            headers = ["Product","Archive Status", "Access Type", "Spatial Extent", "Temporal Extent","Catalogue"]
+            headers = ["Product","Archive Status", "Access Type", "Spatial Extent", "Temporal Extent", "Catalogue","Origin"]
 
         # Find and remove empty columns
         t,headers=removeempty(t,headers)
@@ -679,4 +683,4 @@ def CCMOffer(c):
     except Exception:
         table = " "
 
-    return table
+    return table