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
2021-11-06 10:19:22	ga_ls9c_ard_3-2-1_100083_2021-11-06_final.stac-item
2021-11-10 11:15:22	ga_ls9c_ard_3-2-1_110070_2021-11-10_final.stac-item
2021-11-20 09:42:01	ga_ls9c_ard_3-2-1_094071_2021-11-20_final.stac-item
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-06 10:50:11	ga_ls9c_ard_3-2-1_105076_2021-12-06_final.stac-item
2021-12-07 09:52:10	ga_ls9c_ard_3-2-1_096070_2021-12-07_final.stac-item
2021-12-07 11:32:39	ga_ls9c_ard_3-2-1_112074_2021-12-07_final.stac-item
2021-12-20 09:22:22	ga_ls9c_ard_3-2-1_091073_2021-12-19_final.stac-item
2021-12-22 10:49:17	ga_ls9c_ard_3-2-1_105074_2021-12-22_final.stac-item
2021-12-26 10:26:10	ga_ls9c_ard_3-2-1_101078_2021-12-26_final.stac-item
2022-01-23 10:46:53	ga_ls9c_ard_3-2-1_105068_2022-01-23_final.stac-item
2022-02-04 11:14:47	ga_ls9c_ard_3-2-1_109076_2022-02-04_final.stac-item
2022-03-01 09:28:41	ga_ls9c_ard_3-2-1_092074_2022-02-28_final.stac-item
2022-03-10 09:22:31	ga_ls9c_ard_3-2-1_091074_2022-03-09_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-04-06 09:07:04	ga_ls9c_ard_3-2-1_088082_2022-04-05_final.stac-item
2022-04-07 09:45:56	ga_ls9c_ard_3-2-1_095071_2022-04-07_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-11 09:21:35	ga_ls9c_ard_3-2-1_091072_2022-04-10_final.stac-item
2022-04-28 10:04:18	ga_ls9c_ard_3-2-1_098071_2022-04-28_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-22 09:21:48	ga_ls9c_ard_3-2-1_090089_2022-05-21_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-05-25 09:51:30	ga_ls9c_ard_3-2-1_095086_2022-05-25_final.stac-item
2022-05-28 10:16:25	ga_ls9c_ard_3-2-1_100071_2022-05-28_final.stac-item
2022-06-03 11:18:38	ga_ls9c_ard_3-2-1_110072_2022-06-03_final.stac-item
2022-06-08 11:41:34	ga_ls9c_ard_3-2-1_113083_2022-06-08_final.stac-item
2022-06-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-06-23_final.stac-item
2022-08-10 10:52:57	ga_ls9c_ard_3-2-1_106068_2022-08-10_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-29 09:52:14	ga_ls9c_ard_3-2-1_095086_2022-08-29_final.stac-item
2022-09-05 09:57:36	ga_ls9c_ard_3-2-1_096084_2022-09-05_final.stac-item
2022-09-20 10:52:31	ga_ls9c_ard_3-2-1_105082_2022-09-20_final.stac-item
2022-10-03 10:17:16	ga_ls9c_ard_3-2-1_100071_2022-10-03_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-11 09:34:15	ga_ls9c_ard_3-2-1_092087_2022-10-11_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-10-27 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-10-26_final.stac-item
2022-11-26 09:41:28	ga_ls9c_ard_3-2-1_094074_2022-11-26_final.stac-item
2022-12-03 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-12-03_final.stac-item
2022-12-07 09:22:07	ga_ls9c_ard_3-2-1_091072_2022-12-06_final.stac-item
2022-12-11 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-12-11_final.stac-item
2022-12-17 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-12-17_final.stac-item
2022-12-24 10:04:56	ga_ls9c_ard_3-2-1_098071_2022-12-24_final.stac-item
2022-12-25 09:13:19	ga_ls9c_ard_3-2-1_089081_2022-12-24_final.stac-item
2022-12-31 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-31_final.stac-item
2023-01-01 09:17:57	ga_ls9c_ard_3-2-1_090077_2022-12-31_final.stac-item
2023-01-10 10:47:51	ga_ls9c_ard_3-2-1_105070_2023-01-10_final.stac-item
2023-01-20 11:24:23	ga_ls9c_ard_3-2-1_111069_2023-01-20_final.stac-item
2023-01-29 11:20:20	ga_ls9c_ard_3-2-1_110074_2023-01-29_final.stac-item
2023-02-20 10:46:23	ga_ls9c_ard_3-2-1_104082_2023-02-20_final.stac-item
2023-03-02 09:40:29	ga_ls9c_ard_3-2-1_094072_2023-03-02_final.stac-item
2023-03-04 09:34:29	ga_ls9c_ard_3-2-1_092088_2023-03-04_final.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-14 10:03:30	ga_ls9c_ard_3-2-1_098068_2023-03-14_final.stac-item
2023-03-21 10:11:14	ga_ls9c_ard_3-2-1_099072_2023-03-21_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-04-06 10:09:05	ga_ls9c_ard_3-2-1_099067_2023-04-06_final.stac-item
2023-04-26 09:46:36	ga_ls9c_ard_3-2-1_095073_2023-04-26_final.stac-item
2023-04-27 10:28:39	ga_ls9c_ard_3-2-1_102070_2023-04-27_final.stac-item
2023-04-28 09:34:13	ga_ls9c_ard_3-2-1_093073_2023-04-28_final.stac-item
2023-05-03 11:31:09	ga_ls9c_ard_3-2-1_112072_2023-05-03_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-09 09:16:21	ga_ls9c_ard_3-2-1_090075_2023-05-08_final.stac-item
2023-05-28 11:25:34	ga_ls9c_ard_3-2-1_111074_2023-05-28_final.stac-item
2023-06-04 11:30:55	ga_ls9c_ard_3-2-1_112072_2023-06-04_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-11 11:37:50	ga_ls9c_ard_3-2-1_113074_2023-06-11_final.stac-item
2023-06-16 10:16:13	ga_ls9c_ard_3-2-1_100071_2023-06-16_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-07-05 10:50:32	ga_ls9c_ard_3-2-1_105079_2023-07-05_final.stac-item
2023-07-15 11:25:17	ga_ls9c_ard_3-2-1_111073_2023-07-15_final.stac-item
2023-07-24 11:23:29	ga_ls9c_ard_3-2-1_110084_2023-07-24_final.stac-item
2023-07-27 10:10:20	ga_ls9c_ard_3-2-1_099071_2023-07-27_final.stac-item
2023-07-28 09:16:20	ga_ls9c_ard_3-2-1_090075_2023-07-27_final.stac-item
2023-07-31 11:25:46	ga_ls9c_ard_3-2-1_111074_2023-07-31_final.stac-item
2023-09-05 10:59:45	ga_ls9c_ard_3-2-1_107070_2023-09-05_final.stac-item
2023-09-11 10:25:32	ga_ls9c_ard_3-2-1_101077_2023-09-11_final.stac-item
2023-09-23 09:11:46	ga_ls9c_ard_3-2-1_089078_2023-09-22_final.stac-item
2023-10-03 11:24:58	ga_ls9c_ard_3-2-1_111071_2023-10-03_final.stac-item
2023-10-22 10:17:09	ga_ls9c_ard_3-2-1_100071_2023-10-22_final.stac-item
2023-10-24 10:04:23	ga_ls9c_ard_3-2-1_098070_2023-10-24_final.stac-item
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final.stac-item
2023-11-13 11:20:05	ga_ls9c_ard_3-2-1_110074_2023-11-13_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-27 09:52:06	ga_ls9c_ard_3-2-1_096070_2023-11-27_final.stac-item
2023-12-01 09:30:10	ga_ls9c_ard_3-2-1_092077_2023-12-01_final.stac-item
2023-12-04 11:38:43	ga_ls9c_ard_3-2-1_113074_2023-12-04_final.stac-item
2023-12-04 11:42:19	ga_ls9c_ard_3-2-1_113083_2023-12-04_final.stac-item
2023-12-25 10:17:39	ga_ls9c_ard_3-2-1_100072_2023-12-25_final.stac-item
2023-12-31 09:40:31	ga_ls9c_ard_3-2-1_094072_2023-12-31_final.stac-item
2024-01-07 09:46:38	ga_ls9c_ard_3-2-1_095072_2024-01-07_final.stac-item
2024-01-08 10:28:43	ga_ls9c_ard_3-2-1_102069_2024-01-08_final.stac-item
2024-01-22 09:06:58	ga_ls9c_ard_3-2-1_088081_2024-01-21_final.stac-item
2024-01-27 09:26:43	ga_ls9c_ard_3-2-1_091084_2024-01-26_final.stac-item
2024-01-29 09:13:59	ga_ls9c_ard_3-2-1_089083_2024-01-28_final.stac-item
2024-02-04 11:53:07	ga_ls9c_ard_3-2-1_115079_2024-02-04_final.stac-item
2024-02-05 10:55:54	ga_ls9c_ard_3-2-1_106075_2024-02-05_final.stac-item
2024-02-23 09:07:12	ga_ls9c_ard_3-2-1_088082_2024-02-22_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