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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

68 results

Time (local)	Label
2021-11-15 11:19:25	ga_ls9c_ard_3-2-1_110074_2021-11-15_final.stac-item
2021-12-22 09:11:36	ga_ls9c_ard_3-2-1_089077_2021-12-21_final.stac-item
2022-03-06 09:46:02	ga_ls9c_ard_3-2-1_095071_2022-03-06_final.stac-item
2022-03-21 09:07:07	ga_ls9c_ard_3-2-1_088082_2022-03-20_final.stac-item
2022-03-21 10:46:00	ga_ls9c_ard_3-2-1_104082_2022-03-21_final.stac-item
2022-04-03 10:13:52	ga_ls9c_ard_3-2-1_099079_2022-04-03_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-21 09:56:32	ga_ls9c_ard_3-2-1_097067_2022-04-21_final.stac-item
2022-05-15 09:13:18	ga_ls9c_ard_3-2-1_089083_2022-05-14_final.stac-item
2022-05-22 09:21:00	ga_ls9c_ard_3-2-1_090087_2022-05-21_final.stac-item
2022-06-09 09:07:04	ga_ls9c_ard_3-2-1_088083_2022-06-08_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-12 09:39:36	ga_ls9c_ard_3-2-1_093087_2022-06-12_final.stac-item
2022-06-16 09:14:08	ga_ls9c_ard_3-2-1_089085_2022-06-15_final.stac-item
2022-06-22 10:09:44	ga_ls9c_ard_3-2-1_099069_2022-06-22_final.stac-item
2022-06-30 11:05:14	ga_ls9c_ard_3-2-1_107084_2022-06-30_final.stac-item
2022-07-01 10:03:37	ga_ls9c_ard_3-2-1_098069_2022-07-01_final.stac-item
2022-08-03 10:46:42	ga_ls9c_ard_3-2-1_105068_2022-08-03_final.stac-item
2022-08-07 10:25:37	ga_ls9c_ard_3-2-1_101077_2022-08-07_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-08-10 10:54:33	ga_ls9c_ard_3-2-1_106072_2022-08-10_final.stac-item
2022-10-06 10:47:21	ga_ls9c_ard_3-2-1_105069_2022-10-06_final.stac-item
2022-10-11 09:34:39	ga_ls9c_ard_3-2-1_092088_2022-10-11_final.stac-item
2022-10-13 09:17:55	ga_ls9c_ard_3-2-1_090077_2022-10-12_final.stac-item
2022-10-25 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-10-25_final.stac-item
2022-11-13 11:52:52	ga_ls9c_ard_3-2-1_115078_2022-11-13_final.stac-item
2022-11-26 09:41:28	ga_ls9c_ard_3-2-1_094074_2022-11-26_final.stac-item
2022-12-08 10:04:35	ga_ls9c_ard_3-2-1_098070_2022-12-08_final.stac-item
2022-12-09 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-12-08_final.stac-item
2022-12-15 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-12-15_final.stac-item
2023-01-15 09:28:15	ga_ls9c_ard_3-2-1_092072_2023-01-14_final.stac-item
2023-01-24 11:02:07	ga_ls9c_ard_3-2-1_107075_2023-01-24_final.stac-item
2023-02-11 10:52:42	ga_ls9c_ard_3-2-1_105082_2023-02-11_final.stac-item
2023-02-27 10:46:29	ga_ls9c_ard_3-2-1_105067_2023-02-27_final.stac-item
2023-03-02 11:23:21	ga_ls9c_ard_3-2-1_110082_2023-03-02_final.stac-item
2023-03-08 09:04:54	ga_ls9c_ard_3-2-1_088076_2023-03-07_interim.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-31 10:52:09	ga_ls9c_ard_3-2-1_105082_2023-03-31_final.stac-item
2023-04-27 10:28:39	ga_ls9c_ard_3-2-1_102070_2023-04-27_final.stac-item
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final.stac-item
2023-06-11 11:41:25	ga_ls9c_ard_3-2-1_113083_2023-06-11_final.stac-item
2023-06-19 09:15:50	ga_ls9c_ard_3-2-1_089090_2023-06-18_final.stac-item
2023-06-29 11:24:18	ga_ls9c_ard_3-2-1_111071_2023-06-29_final.stac-item
2023-07-22 11:31:52	ga_ls9c_ard_3-2-1_112074_2023-07-22_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-17 10:33:25	ga_ls9c_ard_3-2-1_102082_2023-08-17_final.stac-item
2023-09-05 10:59:45	ga_ls9c_ard_3-2-1_107070_2023-09-05_final.stac-item
2023-09-06 10:09:44	ga_ls9c_ard_3-2-1_098084_2023-09-06_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-09-19 11:11:49	ga_ls9c_ard_3-2-1_109069_2023-09-19_final.stac-item
2023-09-27 10:27:29	ga_ls9c_ard_3-2-1_101082_2023-09-27_final.stac-item
2023-11-06 09:35:48	ga_ls9c_ard_3-2-1_093076_2023-11-06_final.stac-item
2023-11-13 11:19:41	ga_ls9c_ard_3-2-1_110073_2023-11-13_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_final.stac-item
2023-12-01 09:29:22	ga_ls9c_ard_3-2-1_092075_2023-11-30_final.stac-item
2023-12-02 11:52:42	ga_ls9c_ard_3-2-1_115078_2023-12-02_final.stac-item
2023-12-19 09:23:01	ga_ls9c_ard_3-2-1_090090_2023-12-18_final.stac-item
2023-12-27 10:03:17	ga_ls9c_ard_3-2-1_098067_2023-12-27_final.stac-item
2024-01-17 10:23:22	ga_ls9c_ard_3-2-1_101071_2024-01-17_final.stac-item
2024-01-17 10:26:09	ga_ls9c_ard_3-2-1_101078_2024-01-17_final.stac-item
2024-02-15 09:58:25	ga_ls9c_ard_3-2-1_096086_2024-02-15_final.stac-item
2024-03-04 09:41:12	ga_ls9c_ard_3-2-1_094074_2024-03-04_final.stac-item
2024-03-05 10:24:28	ga_ls9c_ard_3-2-1_101074_2024-03-05_final.stac-item
2024-03-15 11:00:19	ga_ls9c_ard_3-2-1_107071_2024-03-15_final.stac-item
2024-03-24 09:21:36	ga_ls9c_ard_3-2-1_090087_2024-03-23_final.stac-item
2024-04-02 09:10:08	ga_ls9c_ard_3-2-1_089074_2024-04-01_final.stac-item
2024-05-12 09:56:45	ga_ls9c_ard_3-2-1_097068_2024-05-12_interim.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