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

First 100 results (query limit)

Time (local)	Label
2021-11-10 11:20:56	ga_ls9c_ard_3-2-1_110084_2021-11-10_final.stac-item
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2021-11-22 09:25:16	ga_ls9c_ard_3-2-1_091076_2021-11-21_final.stac-item
2021-12-16 09:47:29	ga_ls9c_ard_3-2-1_095074_2021-12-16_final.stac-item
2021-12-27 11:06:14	ga_ls9c_ard_3-2-1_108070_2021-12-27_final.stac-item
2021-12-31 10:44:18	ga_ls9c_ard_3-2-1_104077_2021-12-31_final.stac-item
2022-01-19 09:35:06	ga_ls9c_ard_3-2-1_093074_2022-01-19_final.stac-item
2022-02-03 10:29:08	ga_ls9c_ard_3-2-1_102070_2022-02-03_final.stac-item
2022-03-20 11:38:26	ga_ls9c_ard_3-2-1_113074_2022-03-20_final.stac-item
2022-03-28 10:46:57	ga_ls9c_ard_3-2-1_105069_2022-03-28_final.stac-item
2022-04-25 09:36:59	ga_ls9c_ard_3-2-1_093080_2022-04-25_final.stac-item
2022-05-03 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-05-03_final.stac-item
2022-05-18 09:45:45	ga_ls9c_ard_3-2-1_094087_2022-05-18_final.stac-item
2022-05-20 09:32:33	ga_ls9c_ard_3-2-1_092085_2022-05-20_final.stac-item
2022-05-20 11:06:39	ga_ls9c_ard_3-2-1_108073_2022-05-20_final.stac-item
2022-06-07 10:57:07	ga_ls9c_ard_3-2-1_106080_2022-06-07_final.stac-item
2022-06-27 10:28:45	ga_ls9c_ard_3-2-1_102070_2022-06-27_final.stac-item
2022-07-01 10:02:49	ga_ls9c_ard_3-2-1_098067_2022-07-01_final.stac-item
2022-07-17 10:09:58	ga_ls9c_ard_3-2-1_098085_2022-07-17_final.stac-item
2022-07-24 10:09:29	ga_ls9c_ard_3-2-1_099068_2022-07-24_final.stac-item
2022-08-03 10:48:18	ga_ls9c_ard_3-2-1_105072_2022-08-03_final.stac-item
2022-08-09 10:15:16	ga_ls9c_ard_3-2-1_099082_2022-08-09_final.stac-item
2022-08-09 11:52:57	ga_ls9c_ard_3-2-1_115079_2022-08-09_final.stac-item
2022-09-07 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-09-07_final.stac-item
2022-09-10 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-09-10_final.stac-item
2022-09-14 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-09-14_final.stac-item
2022-09-16 09:37:08	ga_ls9c_ard_3-2-1_093079_2022-09-16_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-23 11:19:27	ga_ls9c_ard_3-2-1_110072_2022-09-23_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_2022-10-03_final.stac-item
2022-10-05 10:07:41	ga_ls9c_ard_3-2-1_098078_2022-10-05_final.stac-item
2022-10-16 09:52:02	ga_ls9c_ard_3-2-1_095085_2022-10-16_final.stac-item
2022-10-21 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-10-21_final.stac-item
2022-10-29 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-10-29_final.stac-item
2022-11-19 11:14:12	ga_ls9c_ard_3-2-1_109074_2022-11-19_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-11-22 10:08:36	ga_ls9c_ard_3-2-1_098080_2022-11-22_final.stac-item
2022-11-29 10:14:44	ga_ls9c_ard_3-2-1_099080_2022-11-29_final.stac-item
2022-11-30 10:54:48	ga_ls9c_ard_3-2-1_106072_2022-11-30_final.stac-item
2022-12-05 11:13:45	ga_ls9c_ard_3-2-1_109073_2022-12-05_final.stac-item
2022-12-05 11:14:09	ga_ls9c_ard_3-2-1_109074_2022-12-05_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-06 10:22:08	ga_ls9c_ard_3-2-1_100083_2022-12-06_final.stac-item
2022-12-07 09:23:43	ga_ls9c_ard_3-2-1_091076_2022-12-06_final.stac-item
2022-12-08 10:04:11	ga_ls9c_ard_3-2-1_098069_2022-12-08_final.stac-item
2023-01-08 11:00:37	ga_ls9c_ard_3-2-1_107071_2023-01-08_final.stac-item
2023-01-11 09:58:36	ga_ls9c_ard_3-2-1_096086_2023-01-11_final.stac-item
2023-01-13 11:21:07	ga_ls9c_ard_3-2-1_110076_2023-01-13_final.stac-item
2023-01-21 10:28:45	ga_ls9c_ard_3-2-1_102069_2023-01-21_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-01-27 11:36:16	ga_ls9c_ard_3-2-1_112083_2023-01-27_final.stac-item
2023-02-01 11:51:40	ga_ls9c_ard_3-2-1_115075_2023-02-01_final.stac-item
2023-02-08 10:18:37	ga_ls9c_ard_3-2-1_100074_2023-02-08_final.stac-item
2023-02-20 10:41:11	ga_ls9c_ard_3-2-1_104069_2023-02-20_final.stac-item
2023-02-27 09:13:59	ga_ls9c_ard_3-2-1_089083_2023-02-26_final.stac-item
2023-03-06 10:55:23	ga_ls9c_ard_3-2-1_106074_2023-03-06_final.stac-item
2023-03-15 10:46:22	ga_ls9c_ard_3-2-1_105067_2023-03-15_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-04-06 10:11:04	ga_ls9c_ard_3-2-1_099072_2023-04-06_final.stac-item
2023-04-06 11:53:09	ga_ls9c_ard_3-2-1_115080_2023-04-06_final.stac-item
2023-04-10 09:46:19	ga_ls9c_ard_3-2-1_095072_2023-04-10_final.stac-item
2023-04-10 09:46:43	ga_ls9c_ard_3-2-1_095073_2023-04-10_final.stac-item
2023-04-10 11:26:00	ga_ls9c_ard_3-2-1_111074_2023-04-10_final.stac-item
2023-04-14 09:27:07	ga_ls9c_ard_3-2-1_091086_2023-04-13_final.stac-item
2023-04-14 09:27:55	ga_ls9c_ard_3-2-1_091088_2023-04-13_final.stac-item
2023-04-21 09:28:54	ga_ls9c_ard_3-2-1_092075_2023-04-20_final.stac-item
2023-05-01 10:03:28	ga_ls9c_ard_3-2-1_098069_2023-05-01_final.stac-item
2023-05-03 09:51:28	ga_ls9c_ard_3-2-1_096070_2023-05-03_final.stac-item
2023-05-16 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-05-15_final.stac-item
2023-05-17 10:03:44	ga_ls9c_ard_3-2-1_098070_2023-05-17_final.stac-item
2023-05-21 11:18:15	ga_ls9c_ard_3-2-1_110071_2023-05-21_final.stac-item
2023-06-20 11:34:23	ga_ls9c_ard_3-2-1_112081_2023-06-20_final.stac-item
2023-06-23 10:22:25	ga_ls9c_ard_3-2-1_101071_2023-06-23_final.stac-item
2023-06-24 11:05:16	ga_ls9c_ard_3-2-1_108070_2023-06-24_final.stac-item
2023-06-30 10:31:30	ga_ls9c_ard_3-2-1_102078_2023-06-30_final.stac-item
2023-07-13 11:38:03	ga_ls9c_ard_3-2-1_113074_2023-07-13_final.stac-item
2023-07-16 10:33:16	ga_ls9c_ard_3-2-1_102082_2023-07-16_final.stac-item
2023-08-03 10:17:02	ga_ls9c_ard_3-2-1_100072_2023-08-03_final.stac-item
2023-08-11 09:33:13	ga_ls9c_ard_3-2-1_092086_2023-08-11_final.stac-item
2023-08-12 11:52:58	ga_ls9c_ard_3-2-1_115080_2023-08-12_final.stac-item
2023-08-13 09:22:04	ga_ls9c_ard_3-2-1_090089_2023-08-12_final.stac-item
2023-09-19 09:39:43	ga_ls9c_ard_3-2-1_093086_2023-09-19_final.stac-item
2023-09-19 09:40:07	ga_ls9c_ard_3-2-1_093087_2023-09-19_final.stac-item
2023-10-03 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-10-03_final.stac-item
2023-10-06 10:17:01	ga_ls9c_ard_3-2-1_100071_2023-10-06_final.stac-item
2023-10-07 11:01:53	ga_ls9c_ard_3-2-1_107075_2023-10-07_final.stac-item
2023-10-23 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-10-23_final.stac-item
2023-11-03 10:40:32	ga_ls9c_ard_3-2-1_104068_2023-11-03_final.stac-item
2023-11-06 09:35:00	ga_ls9c_ard_3-2-1_093074_2023-11-06_final.stac-item
2023-11-13 11:19:17	ga_ls9c_ard_3-2-1_110072_2023-11-13_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-25 10:09:38	ga_ls9c_ard_3-2-1_098083_2023-11-25_final.stac-item
2023-11-26 10:49:43	ga_ls9c_ard_3-2-1_105075_2023-11-26_final.stac-item
2023-12-03 10:55:04	ga_ls9c_ard_3-2-1_106073_2023-12-03_final.stac-item
2023-12-04 09:57:02	ga_ls9c_ard_3-2-1_097067_2023-12-04_final.stac-item
2023-12-06 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-12-06_final.stac-item
2023-12-23 10:32:00	ga_ls9c_ard_3-2-1_102077_2023-12-23_final.stac-item
2024-01-11 09:26:21	ga_ls9c_ard_3-2-1_091083_2024-01-10_final.stac-item
2024-01-14 09:52:04	ga_ls9c_ard_3-2-1_096070_2024-01-14_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years