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
2021-11-12 10:58:13	ga_ls9c_ard_3-2-1_106074_2021-11-12_final.stac-item
2021-11-13 11:40:57	ga_ls9c_ard_3-2-1_113081_2021-11-13_final.stac-item
2021-11-18 10:01:58	ga_ls9c_ard_3-2-1_097074_2021-11-18_final.stac-item
2021-12-14 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-14_final.stac-item
2021-12-18 09:33:55	ga_ls9c_ard_3-2-1_093071_2021-12-18_final.stac-item
2021-12-27 11:08:38	ga_ls9c_ard_3-2-1_108076_2021-12-27_final.stac-item
2022-01-04 10:18:47	ga_ls9c_ard_3-2-1_100075_2022-01-04_final.stac-item
2022-01-07 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-07_final.stac-item
2022-01-12 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-01-12_final.stac-item
2022-01-14 09:18:55	ga_ls9c_ard_3-2-1_090080_2022-01-13_final.stac-item
2022-01-15 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-01-15_final.stac-item
2022-01-17 09:51:50	ga_ls9c_ard_3-2-1_095085_2022-01-17_final.stac-item
2022-01-21 09:29:08	ga_ls9c_ard_3-2-1_091090_2022-01-20_final.stac-item
2022-02-04 09:37:54	ga_ls9c_ard_3-2-1_093081_2022-02-04_final.stac-item
2022-02-27 09:43:52	ga_ls9c_ard_3-2-1_094081_2022-02-27_final.stac-item
2022-03-20 10:01:33	ga_ls9c_ard_3-2-1_097079_2022-03-20_final.stac-item
2022-03-22 09:50:23	ga_ls9c_ard_3-2-1_095082_2022-03-22_final.stac-item
2022-04-30 11:35:12	ga_ls9c_ard_3-2-1_112082_2022-04-30_final.stac-item
2022-06-05 09:31:23	ga_ls9c_ard_3-2-1_092082_2022-06-05_final.stac-item
2022-06-12 11:16:30	ga_ls9c_ard_3-2-1_109082_2022-06-12_final.stac-item
2022-06-20 10:24:01	ga_ls9c_ard_3-2-1_101074_2022-06-20_final.stac-item
2022-07-14 11:14:43	ga_ls9c_ard_3-2-1_109077_2022-07-14_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-11 09:59:44	ga_ls9c_ard_3-2-1_097074_2022-08-11_final.stac-item
2022-08-20 09:53:12	ga_ls9c_ard_3-2-1_096073_2022-08-20_final.stac-item
2022-08-29 09:47:50	ga_ls9c_ard_3-2-1_095075_2022-08-29_final.stac-item
2022-09-02 09:27:06	ga_ls9c_ard_3-2-1_091085_2022-09-01_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-09-19 11:45:45	ga_ls9c_ard_3-2-1_114076_2022-09-19_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-09-28 11:41:36	ga_ls9c_ard_3-2-1_113081_2022-09-28_final.stac-item
2022-10-15 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-10-15_final.stac-item
2022-10-21 11:47:29	ga_ls9c_ard_3-2-1_114080_2022-10-21_final.stac-item
2022-10-25 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-10-25_final.stac-item
2022-11-05 11:05:46	ga_ls9c_ard_3-2-1_107084_2022-11-05_final.stac-item
2022-11-24 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-11-24_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-30 09:31:54	ga_ls9c_ard_3-2-1_092081_2022-12-30_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-01-31 11:10:24	ga_ls9c_ard_3-2-1_108080_2023-01-31_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-06 10:30:10	ga_ls9c_ard_3-2-1_102072_2023-02-06_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-09 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-02-12 11:33:10	ga_ls9c_ard_3-2-1_112075_2023-02-12_final.stac-item
2023-02-14 11:23:58	ga_ls9c_ard_3-2-1_110083_2023-02-14_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-02-19 10:00:45	ga_ls9c_ard_3-2-1_097076_2023-02-19_final.stac-item
2023-02-23 09:37:55	ga_ls9c_ard_3-2-1_093081_2023-02-23_final.stac-item
2023-03-18 09:45:09	ga_ls9c_ard_3-2-1_094084_2023-03-18_final.stac-item
2023-03-20 09:29:35	ga_ls9c_ard_3-2-1_092076_2023-03-19_final.stac-item
2023-03-20 11:10:28	ga_ls9c_ard_3-2-1_108081_2023-03-20_final.stac-item
2023-03-21 10:12:50	ga_ls9c_ard_3-2-1_099076_2023-03-21_final.stac-item
2023-03-21 11:52:07	ga_ls9c_ard_3-2-1_115077_2023-03-21_final.stac-item
2023-04-08 09:59:06	ga_ls9c_ard_3-2-1_097073_2023-04-08_final.stac-item
2023-04-08 11:40:46	ga_ls9c_ard_3-2-1_113080_2023-04-08_final.stac-item
2023-04-10 11:29:35	ga_ls9c_ard_3-2-1_111083_2023-04-10_final.stac-item
2023-04-12 09:38:19	ga_ls9c_ard_3-2-1_093083_2023-04-12_final.stac-item
2023-04-18 10:38:29	ga_ls9c_ard_3-2-1_103079_2023-04-18_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-04-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2023-04-23_final.stac-item
2023-04-26 11:29:53	ga_ls9c_ard_3-2-1_111084_2023-04-26_final.stac-item
2023-05-08 10:14:46	ga_ls9c_ard_3-2-1_099082_2023-05-08_final.stac-item
2023-05-09 09:18:45	ga_ls9c_ard_3-2-1_090081_2023-05-08_final.stac-item
2023-05-10 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-05-10_final.stac-item
2023-05-10 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-05-10_final.stac-item
2023-06-05 10:34:06	ga_ls9c_ard_3-2-1_103069_2023-06-05_final.stac-item
2023-06-26 09:19:13	ga_ls9c_ard_3-2-1_090083_2023-06-25_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_final.stac-item
2023-07-04 11:44:32	ga_ls9c_ard_3-2-1_114075_2023-07-04_final.stac-item
2023-07-06 09:52:31	ga_ls9c_ard_3-2-1_096073_2023-07-06_final.stac-item
2023-07-06 09:54:31	ga_ls9c_ard_3-2-1_096078_2023-07-06_final.stac-item
2023-07-06 09:56:07	ga_ls9c_ard_3-2-1_096082_2023-07-06_final.stac-item
2023-07-07 10:35:48	ga_ls9c_ard_3-2-1_103073_2023-07-07_final.stac-item
2023-07-07 10:36:12	ga_ls9c_ard_3-2-1_103074_2023-07-07_final.stac-item
2023-07-09 10:23:51	ga_ls9c_ard_3-2-1_101074_2023-07-09_final.stac-item
2023-07-11 10:14:42	ga_ls9c_ard_3-2-1_099082_2023-07-11_final.stac-item
2023-09-05 09:25:15	ga_ls9c_ard_3-2-1_091081_2023-09-04_final.stac-item
2023-09-05 09:26:51	ga_ls9c_ard_3-2-1_091085_2023-09-04_final.stac-item
2023-09-05 11:03:45	ga_ls9c_ard_3-2-1_107080_2023-09-05_final.stac-item
2023-09-05 11:04:32	ga_ls9c_ard_3-2-1_107082_2023-09-05_final.stac-item
2023-09-10 11:20:45	ga_ls9c_ard_3-2-1_110076_2023-09-10_final.stac-item
2023-09-11 10:22:45	ga_ls9c_ard_3-2-1_101070_2023-09-11_final.stac-item
2023-09-12 09:31:07	ga_ls9c_ard_3-2-1_092080_2023-09-12_final.stac-item
2023-09-15 10:02:02	ga_ls9c_ard_3-2-1_097080_2023-09-15_final.stac-item
2023-09-22 10:10:12	ga_ls9c_ard_3-2-1_098085_2023-09-22_final.stac-item
2023-09-22 11:45:29	ga_ls9c_ard_3-2-1_114076_2023-09-22_final.stac-item
2023-09-27 10:22:41	ga_ls9c_ard_3-2-1_101070_2023-09-27_final.stac-item
2023-09-27 10:25:05	ga_ls9c_ard_3-2-1_101076_2023-09-27_final.stac-item
2023-09-28 09:32:38	ga_ls9c_ard_3-2-1_092084_2023-09-28_final.stac-item
2023-09-29 10:15:56	ga_ls9c_ard_3-2-1_099084_2023-09-29_final.stac-item
2023-09-30 09:19:08	ga_ls9c_ard_3-2-1_090081_2023-09-29_final.stac-item
2023-10-01 10:02:00	ga_ls9c_ard_3-2-1_097080_2023-10-01_final.stac-item
2023-10-05 11:13:02	ga_ls9c_ard_3-2-1_109072_2023-10-05_final.stac-item
2023-10-07 11:04:41	ga_ls9c_ard_3-2-1_107082_2023-10-07_final.stac-item
2023-10-08 10:05:28	ga_ls9c_ard_3-2-1_098073_2023-10-08_final.stac-item
2023-10-14 09:32:04	ga_ls9c_ard_3-2-1_092082_2023-10-14_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years