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

95 results

Time (local)	Label
2021-11-05 09:34:38	ga_ls9c_ard_3-2-1_093071_2021-11-05_final.stac-item
2021-11-08 09:59:50	ga_ls9c_ard_3-2-1_097081_2021-11-08_final.stac-item
2021-12-16 11:25:58	ga_ls9c_ard_3-2-1_111073_2021-12-16_final.stac-item
2021-12-23 09:58:28	ga_ls9c_ard_3-2-1_096086_2021-12-23_final.stac-item
2022-01-22 10:03:37	ga_ls9c_ard_3-2-1_098068_2022-01-22_final.stac-item
2022-01-26 09:42:29	ga_ls9c_ard_3-2-1_094077_2022-01-26_final.stac-item
2022-02-15 10:53:23	ga_ls9c_ard_3-2-1_106069_2022-02-15_final.stac-item
2022-02-18 09:47:22	ga_ls9c_ard_3-2-1_095074_2022-02-18_final.stac-item
2022-02-27 09:44:16	ga_ls9c_ard_3-2-1_094082_2022-02-27_final.stac-item
2022-03-06 11:25:19	ga_ls9c_ard_3-2-1_111072_2022-03-06_final.stac-item
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final.stac-item
2022-04-02 09:27:49	ga_ls9c_ard_3-2-1_092072_2022-04-01_final.stac-item
2022-04-07 09:50:19	ga_ls9c_ard_3-2-1_095082_2022-04-07_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-13 09:13:59	ga_ls9c_ard_3-2-1_089084_2022-04-12_final.stac-item
2022-04-20 09:22:04	ga_ls9c_ard_3-2-1_090089_2022-04-19_final.stac-item
2022-04-21 11:39:24	ga_ls9c_ard_3-2-1_113077_2022-04-21_final.stac-item
2022-05-05 11:51:43	ga_ls9c_ard_3-2-1_115077_2022-05-05_final.stac-item
2022-05-13 11:00:59	ga_ls9c_ard_3-2-1_107074_2022-05-13_final.stac-item
2022-05-31 10:46:32	ga_ls9c_ard_3-2-1_105069_2022-05-31_final.stac-item
2022-06-16 10:50:14	ga_ls9c_ard_3-2-1_105078_2022-06-16_final.stac-item
2022-06-30 09:23:09	ga_ls9c_ard_3-2-1_091076_2022-06-29_final.stac-item
2022-07-10 10:03:47	ga_ls9c_ard_3-2-1_097085_2022-07-10_final.stac-item
2022-07-17 10:03:11	ga_ls9c_ard_3-2-1_098068_2022-07-17_final.stac-item
2022-07-19 09:51:40	ga_ls9c_ard_3-2-1_096070_2022-07-19_final.stac-item
2022-07-24 10:11:05	ga_ls9c_ard_3-2-1_099072_2022-07-24_final.stac-item
2022-07-26 09:58:21	ga_ls9c_ard_3-2-1_097071_2022-07-26_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-09 10:14:28	ga_ls9c_ard_3-2-1_099080_2022-08-09_final.stac-item
2022-08-10 10:53:21	ga_ls9c_ard_3-2-1_106069_2022-08-10_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-08-24 09:32:53	ga_ls9c_ard_3-2-1_092084_2022-08-24_final.stac-item
2022-08-24 11:06:11	ga_ls9c_ard_3-2-1_108070_2022-08-24_final.stac-item
2022-09-30 09:52:21	ga_ls9c_ard_3-2-1_095086_2022-09-30_final.stac-item
2022-10-04 11:00:07	ga_ls9c_ard_3-2-1_107070_2022-10-04_final.stac-item
2022-10-13 09:19:07	ga_ls9c_ard_3-2-1_090080_2022-10-12_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-05 09:22:06	ga_ls9c_ard_3-2-1_091072_2022-11-04_final.stac-item
2022-11-07 09:14:09	ga_ls9c_ard_3-2-1_089083_2022-11-06_final.stac-item
2022-11-08 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-11-08_final.stac-item
2022-11-10 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-11-10_final.stac-item
2022-11-16 09:07:12	ga_ls9c_ard_3-2-1_088081_2022-11-15_final.stac-item
2022-11-19 09:35:19	ga_ls9c_ard_3-2-1_093074_2022-11-19_final.stac-item
2022-11-21 09:22:09	ga_ls9c_ard_3-2-1_091072_2022-11-20_final.stac-item
2022-12-09 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-12-08_final.stac-item
2022-12-19 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-19_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-21 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-12-21_final.stac-item
2023-01-22 09:40:20	ga_ls9c_ard_3-2-1_093087_2023-01-22_final.stac-item
2023-01-29 09:41:03	ga_ls9c_ard_3-2-1_094073_2023-01-29_final.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-23 09:39:55	ga_ls9c_ard_3-2-1_093086_2023-02-23_final.stac-item
2023-03-15 10:49:09	ga_ls9c_ard_3-2-1_105074_2023-03-15_final.stac-item
2023-03-20 09:34:22	ga_ls9c_ard_3-2-1_092088_2023-03-20_final.stac-item
2023-03-24 09:06:25	ga_ls9c_ard_3-2-1_088080_2023-03-23_final.stac-item
2023-03-27 09:34:27	ga_ls9c_ard_3-2-1_093073_2023-03-27_final.stac-item
2023-03-27 09:37:15	ga_ls9c_ard_3-2-1_093080_2023-03-27_final.stac-item
2023-03-30 10:04:06	ga_ls9c_ard_3-2-1_098070_2023-03-30_final.stac-item
2023-03-30 10:04:53	ga_ls9c_ard_3-2-1_098072_2023-03-30_final.stac-item
2023-04-18 10:35:18	ga_ls9c_ard_3-2-1_103071_2023-04-18_final.stac-item
2023-04-24 11:37:29	ga_ls9c_ard_3-2-1_113072_2023-04-24_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-08 11:52:03	ga_ls9c_ard_3-2-1_115078_2023-05-08_final.stac-item
2023-05-21 09:39:22	ga_ls9c_ard_3-2-1_094071_2023-05-21_final.stac-item
2023-05-26 10:03:02	ga_ls9c_ard_3-2-1_097084_2023-05-26_final.stac-item
2023-06-06 09:44:03	ga_ls9c_ard_3-2-1_094083_2023-06-06_final.stac-item
2023-06-29 09:45:49	ga_ls9c_ard_3-2-1_095072_2023-06-29_final.stac-item
2023-06-29 09:51:01	ga_ls9c_ard_3-2-1_095085_2023-06-29_final.stac-item
2023-07-03 11:00:04	ga_ls9c_ard_3-2-1_107072_2023-07-03_final.stac-item
2023-07-19 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-07-18_final.stac-item
2023-07-27 10:09:33	ga_ls9c_ard_3-2-1_099069_2023-07-27_final.stac-item
2023-08-12 10:08:54	ga_ls9c_ard_3-2-1_099067_2023-08-12_final.stac-item
2023-08-21 10:07:33	ga_ls9c_ard_3-2-1_098079_2023-08-21_final.stac-item
2023-08-27 11:07:27	ga_ls9c_ard_3-2-1_108074_2023-08-27_final.stac-item
2023-09-14 09:21:34	ga_ls9c_ard_3-2-1_090087_2023-09-13_final.stac-item
2023-09-18 10:32:56	ga_ls9c_ard_3-2-1_102080_2023-09-18_final.stac-item
2023-09-21 10:59:50	ga_ls9c_ard_3-2-1_107070_2023-09-21_final.stac-item
2023-10-17 10:04:12	ga_ls9c_ard_3-2-1_097085_2023-10-17_final.stac-item
2023-11-07 10:19:04	ga_ls9c_ard_3-2-1_100076_2023-11-07_final.stac-item
2023-12-02 11:51:30	ga_ls9c_ard_3-2-1_115075_2023-12-02_final.stac-item
2023-12-10 09:27:31	ga_ls9c_ard_3-2-1_091086_2023-12-09_final.stac-item
2024-01-04 10:56:14	ga_ls9c_ard_3-2-1_106076_2024-01-04_final.stac-item
2024-01-19 10:16:11	ga_ls9c_ard_3-2-1_099084_2024-01-19_final.stac-item
2024-01-24 10:32:40	ga_ls9c_ard_3-2-1_102079_2024-01-24_final.stac-item
2024-02-28 09:27:00	ga_ls9c_ard_3-2-1_091085_2024-02-27_final.stac-item
2024-03-17 09:12:16	ga_ls9c_ard_3-2-1_089079_2024-03-16_final.stac-item
2024-03-29 11:13:20	ga_ls9c_ard_3-2-1_109073_2024-03-29_final.stac-item
2024-05-07 09:40:14	ga_ls9c_ard_3-2-1_094073_2024-05-07_final.stac-item
2024-05-13 09:07:06	ga_ls9c_ard_3-2-1_088083_2024-05-12_final.stac-item
2024-05-17 11:57:15	ga_ls9c_ard_3-2-1_116076_2024-05-17_nrt.stac-item
2024-05-18 11:01:38	ga_ls9c_ard_3-2-1_107076_2024-05-18_nrt.stac-item
2024-05-24 10:24:07	ga_ls9c_ard_3-2-1_101075_2024-05-24_final.stac-item
2024-05-30 11:28:38	ga_ls9c_ard_3-2-1_111082_2024-05-30_nrt.stac-item
2024-06-06 11:35:37	ga_ls9c_ard_3-2-1_112084_2024-06-06_nrt.stac-item
2024-06-08 11:18:27	ga_ls9c_ard_3-2-1_110072_2024-06-08_nrt.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