Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

64 results

Time (local)	Label
2021-11-23 10:02:50	ga_ls9c_ard_3-2-1_098070_2021-11-23_final.stac-item
2021-12-12 10:10:39	ga_ls9c_ard_3-2-1_099070_2021-12-12_final.stac-item
2022-01-10 11:18:10	ga_ls9c_ard_3-2-1_110069_2022-01-10_final.stac-item
2022-01-14 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-01-13_final.stac-item
2022-01-26 09:42:53	ga_ls9c_ard_3-2-1_094078_2022-01-26_final.stac-item
2022-02-07 10:04:00	ga_ls9c_ard_3-2-1_098069_2022-02-07_final.stac-item
2022-03-25 10:19:39	ga_ls9c_ard_3-2-1_100078_2022-03-25_final.stac-item
2022-04-12 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-04-12_final.stac-item
2022-05-05 10:08:26	ga_ls9c_ard_3-2-1_099066_2022-05-05_final.stac-item
2022-05-18 11:17:27	ga_ls9c_ard_3-2-1_110069_2022-05-18_final.stac-item
2022-05-23 09:56:41	ga_ls9c_ard_3-2-1_097068_2022-05-23_final.stac-item
2022-05-30 11:46:56	ga_ls9c_ard_3-2-1_114081_2022-05-30_final.stac-item
2022-07-03 09:52:27	ga_ls9c_ard_3-2-1_096072_2022-07-03_final.stac-item
2022-07-12 09:46:37	ga_ls9c_ard_3-2-1_095073_2022-07-12_final.stac-item
2022-08-03 10:48:18	ga_ls9c_ard_3-2-1_105072_2022-08-03_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-08-09 10:14:04	ga_ls9c_ard_3-2-1_099079_2022-08-09_final.stac-item
2022-08-14 10:33:27	ga_ls9c_ard_3-2-1_102081_2022-08-14_final.stac-item
2022-08-25 10:13:45	ga_ls9c_ard_3-2-1_099078_2022-08-25_final.stac-item
2022-08-27 11:41:05	ga_ls9c_ard_3-2-1_113080_2022-08-27_final.stac-item
2022-09-07 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-09-07_final.stac-item
2022-09-09 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-09-09_final.stac-item
2022-09-10 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-09-10_final.stac-item
2022-09-26 10:09:53	ga_ls9c_ard_3-2-1_099068_2022-09-26_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-28 10:09:11	ga_ls9c_ard_3-2-1_099066_2022-10-28_final.stac-item
2022-11-24 11:36:19	ga_ls9c_ard_3-2-1_112083_2022-11-24_final.stac-item
2022-12-09 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-12-09_final.stac-item
2022-12-24 10:03:44	ga_ls9c_ard_3-2-1_098068_2022-12-24_final.stac-item
2023-01-10 10:53:02	ga_ls9c_ard_3-2-1_105083_2023-01-10_final.stac-item
2023-01-26 10:52:59	ga_ls9c_ard_3-2-1_105083_2023-01-26_final.stac-item
2023-02-10 10:10:15	ga_ls9c_ard_3-2-1_098084_2023-02-10_final.stac-item
2023-02-11 10:53:06	ga_ls9c_ard_3-2-1_105083_2023-02-11_final.stac-item
2023-02-25 09:23:33	ga_ls9c_ard_3-2-1_091076_2023-02-24_final.stac-item
2023-03-29 09:22:50	ga_ls9c_ard_3-2-1_091075_2023-03-28_final.stac-item
2023-03-30 10:02:54	ga_ls9c_ard_3-2-1_098067_2023-03-30_final.stac-item
2023-04-09 09:07:03	ga_ls9c_ard_3-2-1_088082_2023-04-08_final.stac-item
2023-05-16 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-05-15_final.stac-item
2023-06-11 11:41:49	ga_ls9c_ard_3-2-1_113084_2023-06-11_final.stac-item
2023-06-24 09:32:46	ga_ls9c_ard_3-2-1_092086_2023-06-24_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-07-26 11:05:33	ga_ls9c_ard_3-2-1_108070_2023-07-26_final.stac-item
2023-08-05 10:02:42	ga_ls9c_ard_3-2-1_098067_2023-08-05_final.stac-item
2023-08-15 09:06:54	ga_ls9c_ard_3-2-1_088082_2023-08-14_final.stac-item
2023-08-21 10:03:34	ga_ls9c_ard_3-2-1_098069_2023-08-21_final.stac-item
2023-08-26 10:25:22	ga_ls9c_ard_3-2-1_101077_2023-08-26_final.stac-item
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-10-08 10:03:05	ga_ls9c_ard_3-2-1_098067_2023-10-08_final.stac-item
2023-10-31 11:51:46	ga_ls9c_ard_3-2-1_115076_2023-10-31_final.stac-item
2023-11-01 09:22:50	ga_ls9c_ard_3-2-1_090090_2023-10-31_final.stac-item
2023-11-04 11:29:48	ga_ls9c_ard_3-2-1_111083_2023-11-04_final.stac-item
2023-11-20 09:46:15	ga_ls9c_ard_3-2-1_095071_2023-11-20_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-19 09:22:37	ga_ls9c_ard_3-2-1_090089_2023-12-18_final.stac-item
2023-12-20 11:39:59	ga_ls9c_ard_3-2-1_113077_2023-12-20_final.stac-item
2024-01-18 09:30:08	ga_ls9c_ard_3-2-1_092077_2024-01-18_final.stac-item
2024-01-28 10:07:12	ga_ls9c_ard_3-2-1_098077_2024-01-28_final.stac-item
2024-02-21 09:20:01	ga_ls9c_ard_3-2-1_090083_2024-02-20_final.stac-item
2024-03-06 09:28:51	ga_ls9c_ard_3-2-1_092074_2024-03-05_final.stac-item
2024-03-31 09:28:53	ga_ls9c_ard_3-2-1_091090_2024-03-30_final.stac-item
2024-04-01 10:07:45	ga_ls9c_ard_3-2-1_098079_2024-04-01_final.stac-item
2024-05-02 09:22:29	ga_ls9c_ard_3-2-1_091075_2024-05-01_final.stac-item
2024-05-20 09:12:47	ga_ls9c_ard_3-2-1_089082_2024-05-19_nrt.stac-item
2024-05-21 09:57:14	ga_ls9c_ard_3-2-1_096085_2024-05-21_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years