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
2021-12-29 10:54:17	ga_ls9c_ard_3-2-1_106071_2021-12-29_final.stac-item
2022-01-15 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-01-15_final.stac-item
2022-01-23 09:13:59	ga_ls9c_ard_3-2-1_089083_2022-01-22_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-03-09 10:17:20	ga_ls9c_ard_3-2-1_100072_2022-03-09_final.stac-item
2022-03-10 09:27:18	ga_ls9c_ard_3-2-1_091086_2022-03-09_final.stac-item
2022-03-25 10:19:39	ga_ls9c_ard_3-2-1_100078_2022-03-25_final.stac-item
2022-03-26 09:23:38	ga_ls9c_ard_3-2-1_091077_2022-03-25_final.stac-item
2022-04-28 10:04:42	ga_ls9c_ard_3-2-1_098072_2022-04-28_final.stac-item
2022-05-04 11:10:03	ga_ls9c_ard_3-2-1_108081_2022-05-04_final.stac-item
2022-05-07 10:03:39	ga_ls9c_ard_3-2-1_097085_2022-05-07_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-06-07 10:52:43	ga_ls9c_ard_3-2-1_106069_2022-06-07_final.stac-item
2022-06-29 10:17:11	ga_ls9c_ard_3-2-1_100072_2022-06-29_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-08-08 11:05:41	ga_ls9c_ard_3-2-1_108069_2022-08-08_final.stac-item
2022-08-16 10:21:54	ga_ls9c_ard_3-2-1_100083_2022-08-16_final.stac-item
2022-08-30 10:30:18	ga_ls9c_ard_3-2-1_102073_2022-08-30_final.stac-item
2022-09-04 09:14:21	ga_ls9c_ard_3-2-1_089084_2022-09-03_final.stac-item
2022-09-25 09:34:36	ga_ls9c_ard_3-2-1_092088_2022-09-25_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_2022-09-27_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_2022-10-03_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-16 09:46:51	ga_ls9c_ard_3-2-1_095072_2022-10-16_final.stac-item
2022-10-17 10:29:43	ga_ls9c_ard_3-2-1_102071_2022-10-17_final.stac-item
2022-10-18 09:37:17	ga_ls9c_ard_3-2-1_093079_2022-10-18_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_final.stac-item
2022-11-07 09:14:09	ga_ls9c_ard_3-2-1_089083_2022-11-06_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-12 09:35:31	ga_ls9c_ard_3-2-1_092090_2022-11-12_final.stac-item
2022-11-13 11:51:40	ga_ls9c_ard_3-2-1_115075_2022-11-13_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-24 09:58:14	ga_ls9c_ard_3-2-1_096085_2022-11-24_final.stac-item
2022-11-25 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-25_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-04 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-04_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_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 11:01:48	ga_ls9c_ard_3-2-1_107074_2022-12-07_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-15 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-12-15_final.stac-item
2022-12-23 09:27:16	ga_ls9c_ard_3-2-1_091085_2022-12-22_final.stac-item
2022-12-24 11:45:25	ga_ls9c_ard_3-2-1_114075_2022-12-24_final.stac-item
2022-12-28 09:45:50	ga_ls9c_ard_3-2-1_094085_2022-12-28_final.stac-item
2023-01-09 10:09:47	ga_ls9c_ard_3-2-1_098083_2023-01-09_final.stac-item
2023-01-09 11:47:28	ga_ls9c_ard_3-2-1_114080_2023-01-09_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-01-17 10:55:08	ga_ls9c_ard_3-2-1_106073_2023-01-17_final.stac-item
2023-01-24 11:01:43	ga_ls9c_ard_3-2-1_107074_2023-01-24_final.stac-item
2023-01-27 11:36:16	ga_ls9c_ard_3-2-1_112083_2023-01-27_final.stac-item
2023-01-29 09:41:03	ga_ls9c_ard_3-2-1_094073_2023-01-29_final.stac-item
2023-01-31 11:11:59	ga_ls9c_ard_3-2-1_108084_2023-01-31_final.stac-item
2023-02-03 11:38:08	ga_ls9c_ard_3-2-1_113072_2023-02-03_final.stac-item
2023-02-09 11:02:40	ga_ls9c_ard_3-2-1_107076_2023-02-09_final.stac-item
2023-04-02 10:37:24	ga_ls9c_ard_3-2-1_103076_2023-04-02_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-04-30 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-04-29_final.stac-item
2023-05-05 11:23:09	ga_ls9c_ard_3-2-1_110083_2023-05-05_final.stac-item
2023-05-11 09:06:47	ga_ls9c_ard_3-2-1_088082_2023-05-10_final.stac-item
2023-05-12 11:24:56	ga_ls9c_ard_3-2-1_111072_2023-05-12_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-05-14 11:16:56	ga_ls9c_ard_3-2-1_109083_2023-05-14_final.stac-item
2023-05-16 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-05-15_final.stac-item
2023-05-16 09:21:41	ga_ls9c_ard_3-2-1_091073_2023-05-15_final.stac-item
2023-05-17 10:03:20	ga_ls9c_ard_3-2-1_098069_2023-05-17_final.stac-item
2023-05-17 10:06:32	ga_ls9c_ard_3-2-1_098077_2023-05-17_final.stac-item
2023-06-02 10:04:01	ga_ls9c_ard_3-2-1_098071_2023-06-02_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-06-23 10:22:25	ga_ls9c_ard_3-2-1_101071_2023-06-23_final.stac-item
2023-06-26 09:19:37	ga_ls9c_ard_3-2-1_090084_2023-06-25_final.stac-item
2023-06-29 11:23:07	ga_ls9c_ard_3-2-1_111068_2023-06-29_final.stac-item
2023-07-03 09:25:10	ga_ls9c_ard_3-2-1_091082_2023-07-02_final.stac-item
2023-07-17 09:39:14	ga_ls9c_ard_3-2-1_093086_2023-07-17_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-19 11:01:46	ga_ls9c_ard_3-2-1_107076_2023-07-19_final.stac-item
2023-07-20 10:09:44	ga_ls9c_ard_3-2-1_098085_2023-07-20_final.stac-item
2023-07-24 11:19:05	ga_ls9c_ard_3-2-1_110073_2023-07-24_final.stac-item
2023-07-25 10:27:27	ga_ls9c_ard_3-2-1_101083_2023-07-25_final.stac-item
2023-07-27 10:14:44	ga_ls9c_ard_3-2-1_099082_2023-07-27_final.stac-item
2023-07-31 09:52:04	ga_ls9c_ard_3-2-1_095087_2023-07-31_final.stac-item
2023-07-31 11:23:23	ga_ls9c_ard_3-2-1_111068_2023-07-31_final.stac-item
2023-08-02 09:33:45	ga_ls9c_ard_3-2-1_093072_2023-08-02_final.stac-item
2023-08-06 09:13:04	ga_ls9c_ard_3-2-1_089082_2023-08-05_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-10-14 11:11:21	ga_ls9c_ard_3-2-1_108083_2023-10-14_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-11-03 10:40:32	ga_ls9c_ard_3-2-1_104068_2023-11-03_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-16 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-11-16_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-22 09:33:55	ga_ls9c_ard_3-2-1_093071_2023-11-22_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_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