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
2021-11-07 09:23:03	ga_ls9c_ard_3-2-1_090089_2021-11-06_final.stac-item
2021-12-11 11:06:17	ga_ls9c_ard_3-2-1_108070_2021-12-11_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2021-12-29 10:54:40	ga_ls9c_ard_3-2-1_106072_2021-12-29_final.stac-item
2022-01-22 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-22_final.stac-item
2022-01-29 10:15:47	ga_ls9c_ard_3-2-1_099083_2022-01-29_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-02-22 09:23:24	ga_ls9c_ard_3-2-1_091076_2022-02-21_final.stac-item
2022-03-01 09:29:29	ga_ls9c_ard_3-2-1_092076_2022-02-28_final.stac-item
2022-03-02 11:51:37	ga_ls9c_ard_3-2-1_115076_2022-03-02_final.stac-item
2022-03-08 11:14:33	ga_ls9c_ard_3-2-1_109076_2022-03-08_final.stac-item
2022-03-19 10:54:23	ga_ls9c_ard_3-2-1_106072_2022-03-19_final.stac-item
2022-04-02 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-04-01_final.stac-item
2022-04-05 09:57:30	ga_ls9c_ard_3-2-1_097069_2022-04-05_final.stac-item
2022-04-07 11:25:13	ga_ls9c_ard_3-2-1_111072_2022-04-07_final.stac-item
2022-04-14 11:34:55	ga_ls9c_ard_3-2-1_112081_2022-04-14_final.stac-item
2022-04-16 11:19:44	ga_ls9c_ard_3-2-1_110074_2022-04-16_final.stac-item
2022-04-18 11:06:57	ga_ls9c_ard_3-2-1_108073_2022-04-18_final.stac-item
2022-04-28 10:03:06	ga_ls9c_ard_3-2-1_098068_2022-04-28_final.stac-item
2022-06-03 11:19:02	ga_ls9c_ard_3-2-1_110073_2022-06-03_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-06-23 09:20:55	ga_ls9c_ard_3-2-1_090086_2022-06-22_final.stac-item
2022-07-04 10:34:07	ga_ls9c_ard_3-2-1_103068_2022-07-04_final.stac-item
2022-07-18 10:50:27	ga_ls9c_ard_3-2-1_105078_2022-07-18_final.stac-item
2022-07-26 11:41:37	ga_ls9c_ard_3-2-1_113082_2022-07-26_final.stac-item
2022-08-26 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-08-26_final.stac-item
2022-08-28 10:42:40	ga_ls9c_ard_3-2-1_104073_2022-08-28_final.stac-item
2022-08-31 11:13:34	ga_ls9c_ard_3-2-1_109073_2022-08-31_final.stac-item
2022-09-04 09:14:21	ga_ls9c_ard_3-2-1_089084_2022-09-03_final.stac-item
2022-09-07 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-09-07_final.stac-item
2022-09-09 11:07:22	ga_ls9c_ard_3-2-1_108073_2022-09-09_final.stac-item
2022-09-19 10:05:16	ga_ls9c_ard_3-2-1_098072_2022-09-19_final.stac-item
2022-10-07 11:36:12	ga_ls9c_ard_3-2-1_112083_2022-10-07_final.stac-item
2022-10-09 11:19:05	ga_ls9c_ard_3-2-1_110071_2022-10-09_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-14_final.stac-item
2022-10-20 11:00:37	ga_ls9c_ard_3-2-1_107071_2022-10-20_final.stac-item
2022-10-27 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-10-27_final.stac-item
2022-11-01 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-11-01_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-04 10:19:18	ga_ls9c_ard_3-2-1_100076_2022-11-04_final.stac-item
2022-11-06 10:04:10	ga_ls9c_ard_3-2-1_098069_2022-11-06_final.stac-item
2022-11-10 11:20:22	ga_ls9c_ard_3-2-1_110074_2022-11-10_final.stac-item
2022-11-21 09:27:44	ga_ls9c_ard_3-2-1_091086_2022-11-20_final.stac-item
2022-11-24 09:58:14	ga_ls9c_ard_3-2-1_096085_2022-11-24_final.stac-item
2022-11-26 11:19:09	ga_ls9c_ard_3-2-1_110071_2022-11-26_final.stac-item
2022-11-28 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-11-28_final.stac-item
2022-11-28 11:11:34	ga_ls9c_ard_3-2-1_108083_2022-11-28_final.stac-item
2022-12-02 10:44:49	ga_ls9c_ard_3-2-1_104078_2022-12-02_final.stac-item
2022-12-03 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-12-03_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 10:22:32	ga_ls9c_ard_3-2-1_100084_2022-12-06_final.stac-item
2022-12-09 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-12-08_final.stac-item
2022-12-09 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-12-09_final.stac-item
2022-12-13 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-12-13_final.stac-item
2022-12-16 09:18:20	ga_ls9c_ard_3-2-1_090078_2022-12-15_final.stac-item
2022-12-19 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-12-19_final.stac-item
2022-12-26 11:36:16	ga_ls9c_ard_3-2-1_112083_2022-12-26_final.stac-item
2023-01-02 11:39:18	ga_ls9c_ard_3-2-1_113075_2023-01-02_final.stac-item
2023-01-09 11:47:52	ga_ls9c_ard_3-2-1_114081_2023-01-09_final.stac-item
2023-01-13 09:44:38	ga_ls9c_ard_3-2-1_094082_2023-01-13_final.stac-item
2023-01-17 09:21:50	ga_ls9c_ard_3-2-1_090087_2023-01-16_final.stac-item
2023-01-26 09:14:06	ga_ls9c_ard_3-2-1_089083_2023-01-25_final.stac-item
2023-01-26 10:52:35	ga_ls9c_ard_3-2-1_105082_2023-01-26_final.stac-item
2023-01-27 11:32:16	ga_ls9c_ard_3-2-1_112073_2023-01-27_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-05 11:30:11	ga_ls9c_ard_3-2-1_111083_2023-02-05_final.stac-item
2023-02-27 09:13:59	ga_ls9c_ard_3-2-1_089083_2023-02-26_final.stac-item
2023-03-02 11:20:09	ga_ls9c_ard_3-2-1_110074_2023-03-02_final.stac-item
2023-03-28 10:17:17	ga_ls9c_ard_3-2-1_100072_2023-03-28_final.stac-item
2023-03-30 10:09:17	ga_ls9c_ard_3-2-1_098083_2023-03-30_final.stac-item
2023-04-01 11:34:37	ga_ls9c_ard_3-2-1_112080_2023-04-01_final.stac-item
2023-04-06 10:15:28	ga_ls9c_ard_3-2-1_099083_2023-04-06_final.stac-item
2023-04-26 09:50:12	ga_ls9c_ard_3-2-1_095082_2023-04-26_final.stac-item
2023-05-03 09:51:28	ga_ls9c_ard_3-2-1_096070_2023-05-03_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-16 09:26:05	ga_ls9c_ard_3-2-1_091084_2023-05-15_final.stac-item
2023-05-21 11:18:39	ga_ls9c_ard_3-2-1_110072_2023-05-21_final.stac-item
2023-06-01 09:25:57	ga_ls9c_ard_3-2-1_091084_2023-05-31_final.stac-item
2023-06-19 09:13:02	ga_ls9c_ard_3-2-1_089083_2023-06-18_final.stac-item
2023-06-23 10:27:12	ga_ls9c_ard_3-2-1_101083_2023-06-23_final.stac-item
2023-06-26 09:20:01	ga_ls9c_ard_3-2-1_090085_2023-06-25_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-07-20 10:03:45	ga_ls9c_ard_3-2-1_098070_2023-07-20_final.stac-item
2023-07-25 10:25:27	ga_ls9c_ard_3-2-1_101078_2023-07-25_final.stac-item
2023-07-25 10:27:27	ga_ls9c_ard_3-2-1_101083_2023-07-25_final.stac-item
2023-08-02 11:17:02	ga_ls9c_ard_3-2-1_109083_2023-08-02_final.stac-item
2023-08-09 11:18:52	ga_ls9c_ard_3-2-1_110072_2023-08-09_final.stac-item
2023-10-13 10:25:41	ga_ls9c_ard_3-2-1_101077_2023-10-13_final.stac-item
2023-10-15 10:14:33	ga_ls9c_ard_3-2-1_099080_2023-10-15_final.stac-item
2023-10-16 10:54:13	ga_ls9c_ard_3-2-1_106071_2023-10-16_final.stac-item
2023-10-19 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-10-19_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-21 09:40:41	ga_ls9c_ard_3-2-1_093088_2023-10-21_final.stac-item
2023-10-31 10:11:41	ga_ls9c_ard_3-2-1_099073_2023-10-31_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-17 10:54:11	ga_ls9c_ard_3-2-1_106071_2023-11-17_final.stac-item
2023-11-22 09:35:31	ga_ls9c_ard_3-2-1_093075_2023-11-22_final.stac-item
2023-11-24 11:01:39	ga_ls9c_ard_3-2-1_107074_2023-11-24_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