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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

60 results

Time (local)	Label
2021-11-14 10:41:03	ga_ls9c_ard_3-2-1_103078_2021-11-14_final.stac-item
2021-11-25 09:50:27	ga_ls9c_ard_3-2-1_095086_2021-11-25_final.stac-item
2022-01-13 10:15:45	ga_ls9c_ard_3-2-1_099083_2022-01-13_final.stac-item
2022-01-24 11:31:44	ga_ls9c_ard_3-2-1_112072_2022-01-24_final.stac-item
2022-01-29 10:13:24	ga_ls9c_ard_3-2-1_099077_2022-01-29_final.stac-item
2022-02-03 10:28:44	ga_ls9c_ard_3-2-1_102069_2022-02-03_final.stac-item
2022-02-03 10:29:08	ga_ls9c_ard_3-2-1_102070_2022-02-03_final.stac-item
2022-02-20 11:11:53	ga_ls9c_ard_3-2-1_109069_2022-02-20_final.stac-item
2022-02-27 09:41:05	ga_ls9c_ard_3-2-1_094074_2022-02-27_final.stac-item
2022-03-26 09:28:25	ga_ls9c_ard_3-2-1_091089_2022-03-25_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-04-11 09:27:58	ga_ls9c_ard_3-2-1_091088_2022-04-10_final.stac-item
2022-04-13 10:46:53	ga_ls9c_ard_3-2-1_105069_2022-04-13_final.stac-item
2022-04-23 09:50:09	ga_ls9c_ard_3-2-1_095082_2022-04-23_final.stac-item
2022-07-23 11:05:53	ga_ls9c_ard_3-2-1_108070_2022-07-23_final.stac-item
2022-08-19 09:12:44	ga_ls9c_ard_3-2-1_089080_2022-08-18_final.stac-item
2022-08-22 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-08-22_final.stac-item
2022-09-18 09:28:23	ga_ls9c_ard_3-2-1_091088_2022-09-17_final.stac-item
2022-09-20 09:10:51	ga_ls9c_ard_3-2-1_089075_2022-09-19_final.stac-item
2022-09-30 09:52:21	ga_ls9c_ard_3-2-1_095086_2022-09-30_final.stac-item
2022-10-04 09:26:50	ga_ls9c_ard_3-2-1_091084_2022-10-03_final.stac-item
2022-10-11 09:32:39	ga_ls9c_ard_3-2-1_092083_2022-10-11_final.stac-item
2022-11-12 09:28:20	ga_ls9c_ard_3-2-1_092072_2022-11-11_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-12-03 11:24:30	ga_ls9c_ard_3-2-1_111069_2022-12-03_final.stac-item
2022-12-04 10:32:05	ga_ls9c_ard_3-2-1_102077_2022-12-04_final.stac-item
2022-12-28 11:21:08	ga_ls9c_ard_3-2-1_110076_2022-12-28_final.stac-item
2023-01-28 10:35:28	ga_ls9c_ard_3-2-1_103070_2023-01-28_final.stac-item
2023-03-02 09:40:29	ga_ls9c_ard_3-2-1_094072_2023-03-02_final.stac-item
2023-03-18 09:40:22	ga_ls9c_ard_3-2-1_094072_2023-03-18_final.stac-item
2023-03-27 09:37:15	ga_ls9c_ard_3-2-1_093080_2023-03-27_final.stac-item
2023-04-13 11:58:27	ga_ls9c_ard_3-2-1_116078_2023-04-13_final.stac-item
2023-04-19 09:43:16	ga_ls9c_ard_3-2-1_094080_2023-04-19_final.stac-item
2023-04-22 10:15:45	ga_ls9c_ard_3-2-1_099084_2023-04-22_final.stac-item
2023-05-12 11:24:56	ga_ls9c_ard_3-2-1_111072_2023-05-12_final.stac-item
2023-05-19 11:35:25	ga_ls9c_ard_3-2-1_112083_2023-05-19_final.stac-item
2023-06-17 09:26:11	ga_ls9c_ard_3-2-1_091085_2023-06-16_final.stac-item
2023-06-24 09:33:58	ga_ls9c_ard_3-2-1_092089_2023-06-24_final.stac-item
2023-06-29 11:23:07	ga_ls9c_ard_3-2-1_111068_2023-06-29_final.stac-item
2023-07-15 11:24:53	ga_ls9c_ard_3-2-1_111072_2023-07-15_final.stac-item
2023-07-22 09:57:46	ga_ls9c_ard_3-2-1_096086_2023-07-22_final.stac-item
2023-07-24 09:44:59	ga_ls9c_ard_3-2-1_094085_2023-07-24_final.stac-item
2023-08-04 11:04:41	ga_ls9c_ard_3-2-1_107083_2023-08-04_final.stac-item
2023-08-11 09:28:26	ga_ls9c_ard_3-2-1_092074_2023-08-10_final.stac-item
2023-09-13 11:52:28	ga_ls9c_ard_3-2-1_115078_2023-09-13_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final.stac-item
2023-11-17 09:17:17	ga_ls9c_ard_3-2-1_090076_2023-11-16_final.stac-item
2023-11-18 10:04:10	ga_ls9c_ard_3-2-1_097085_2023-11-18_final.stac-item
2023-12-15 11:19:49	ga_ls9c_ard_3-2-1_110073_2023-12-15_final.stac-item
2023-12-17 11:06:16	ga_ls9c_ard_3-2-1_108070_2023-12-17_final.stac-item
2024-01-13 09:12:48	ga_ls9c_ard_3-2-1_089080_2024-01-12_final.stac-item
2024-01-18 09:32:55	ga_ls9c_ard_3-2-1_092084_2024-01-18_final.stac-item
2024-01-29 10:49:40	ga_ls9c_ard_3-2-1_105075_2024-01-29_final.stac-item
2024-02-08 09:52:18	ga_ls9c_ard_3-2-1_095086_2024-02-08_final.stac-item
2024-02-27 11:58:19	ga_ls9c_ard_3-2-1_116077_2024-02-27_final.stac-item
2024-03-02 09:52:45	ga_ls9c_ard_3-2-1_096072_2024-03-02_final.stac-item
2024-03-26 10:45:17	ga_ls9c_ard_3-2-1_104080_2024-03-26_final.stac-item
2024-04-14 11:11:38	ga_ls9c_ard_3-2-1_109069_2024-04-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years