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
2021-11-22 09:28:51	ga_ls9c_ard_3-2-1_091085_2021-11-21_final.stac-item
2021-11-23 11:43:29	ga_ls9c_ard_3-2-1_114075_2021-11-23_final.stac-item
2021-12-21 11:46:54	ga_ls9c_ard_3-2-1_114079_2021-12-21_final.stac-item
2021-12-25 11:21:24	ga_ls9c_ard_3-2-1_110077_2021-12-25_final.stac-item
2022-01-03 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-01-03_final.stac-item
2022-01-18 10:31:31	ga_ls9c_ard_3-2-1_102076_2022-01-18_final.stac-item
2022-01-21 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-01-21_final.stac-item
2022-01-29 10:15:47	ga_ls9c_ard_3-2-1_099083_2022-01-29_final.stac-item
2022-02-07 11:46:29	ga_ls9c_ard_3-2-1_114078_2022-02-07_final.stac-item
2022-02-14 11:53:01	ga_ls9c_ard_3-2-1_115079_2022-02-14_final.stac-item
2022-02-21 10:20:38	ga_ls9c_ard_3-2-1_100080_2022-02-21_final.stac-item
2022-02-23 11:46:44	ga_ls9c_ard_3-2-1_114079_2022-02-23_final.stac-item
2022-03-11 11:44:39	ga_ls9c_ard_3-2-1_114074_2022-03-11_final.stac-item
2022-03-24 09:36:48	ga_ls9c_ard_3-2-1_093079_2022-03-24_final.stac-item
2022-03-25 10:21:15	ga_ls9c_ard_3-2-1_100082_2022-03-25_final.stac-item
2022-03-27 11:45:22	ga_ls9c_ard_3-2-1_114076_2022-03-27_final.stac-item
2022-03-31 11:21:51	ga_ls9c_ard_3-2-1_110079_2022-03-31_final.stac-item
2022-04-09 11:12:02	ga_ls9c_ard_3-2-1_109070_2022-04-09_final.stac-item
2022-04-23 09:50:09	ga_ls9c_ard_3-2-1_095082_2022-04-23_final.stac-item
2022-04-27 09:27:01	ga_ls9c_ard_3-2-1_091086_2022-04-26_final.stac-item
2022-05-03 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-05-03_final.stac-item
2022-05-05 11:52:07	ga_ls9c_ard_3-2-1_115078_2022-05-05_final.stac-item
2022-05-21 10:12:14	ga_ls9c_ard_3-2-1_099076_2022-05-21_final.stac-item
2022-05-25 11:24:00	ga_ls9c_ard_3-2-1_111070_2022-05-25_final.stac-item
2022-05-26 10:30:46	ga_ls9c_ard_3-2-1_102076_2022-05-26_final.stac-item
2022-05-27 09:35:09	ga_ls9c_ard_3-2-1_093076_2022-05-27_final.stac-item
2022-05-29 11:03:16	ga_ls9c_ard_3-2-1_107080_2022-05-29_final.stac-item
2022-06-19 11:19:12	ga_ls9c_ard_3-2-1_110073_2022-06-19_final.stac-item
2022-06-21 11:10:54	ga_ls9c_ard_3-2-1_108083_2022-06-21_final.stac-item
2022-07-12 11:27:06	ga_ls9c_ard_3-2-1_111077_2022-07-12_final.stac-item
2022-07-28 11:24:30	ga_ls9c_ard_3-2-1_111070_2022-07-28_final.stac-item
2022-08-02 11:45:30	ga_ls9c_ard_3-2-1_114076_2022-08-02_final.stac-item
2022-08-10 10:58:56	ga_ls9c_ard_3-2-1_106083_2022-08-10_final.stac-item
2022-08-30 10:31:30	ga_ls9c_ard_3-2-1_102076_2022-08-30_final.stac-item
2022-09-02 11:04:00	ga_ls9c_ard_3-2-1_107080_2022-09-02_final.stac-item
2022-09-03 11:45:39	ga_ls9c_ard_3-2-1_114076_2022-09-03_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-17 10:21:12	ga_ls9c_ard_3-2-1_100081_2022-09-17_final.stac-item
2022-09-25 09:30:37	ga_ls9c_ard_3-2-1_092078_2022-09-25_final.stac-item
2022-10-16 11:27:19	ga_ls9c_ard_3-2-1_111076_2022-10-16_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-25 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-10-25_final.stac-item
2022-10-28 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-10-28_final.stac-item
2022-10-29 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-10-28_final.stac-item
2022-11-07 10:48:14	ga_ls9c_ard_3-2-1_105071_2022-11-07_final.stac-item
2022-11-09 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-11-09_final.stac-item
2022-11-10 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-10_final.stac-item
2022-11-16 10:46:05	ga_ls9c_ard_3-2-1_104081_2022-11-16_final.stac-item
2022-11-22 11:45:29	ga_ls9c_ard_3-2-1_114075_2022-11-22_final.stac-item
2022-11-22 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-11-22_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-28 10:35:28	ga_ls9c_ard_3-2-1_103070_2023-01-28_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-11 09:14:13	ga_ls9c_ard_3-2-1_089083_2023-02-10_final.stac-item
2023-02-17 11:51:14	ga_ls9c_ard_3-2-1_115074_2023-02-17_final.stac-item
2023-02-18 09:17:54	ga_ls9c_ard_3-2-1_090077_2023-02-17_final.stac-item
2023-02-21 11:27:13	ga_ls9c_ard_3-2-1_111076_2023-02-21_final.stac-item
2023-03-09 11:27:25	ga_ls9c_ard_3-2-1_111077_2023-03-09_final.stac-item
2023-03-20 11:06:04	ga_ls9c_ard_3-2-1_108070_2023-03-20_final.stac-item
2023-03-21 10:10:50	ga_ls9c_ard_3-2-1_099071_2023-03-21_final.stac-item
2023-03-22 10:58:29	ga_ls9c_ard_3-2-1_106082_2023-03-22_final.stac-item
2023-04-10 11:29:59	ga_ls9c_ard_3-2-1_111084_2023-04-10_final.stac-item
2023-04-11 10:32:21	ga_ls9c_ard_3-2-1_102079_2023-04-11_final.stac-item
2023-04-16 09:12:46	ga_ls9c_ard_3-2-1_089081_2023-04-15_final.stac-item
2023-04-17 11:34:31	ga_ls9c_ard_3-2-1_112080_2023-04-17_final.stac-item
2023-04-22 10:15:45	ga_ls9c_ard_3-2-1_099084_2023-04-22_final.stac-item
2023-04-22 11:50:39	ga_ls9c_ard_3-2-1_115074_2023-04-22_final.stac-item
2023-04-26 11:26:41	ga_ls9c_ard_3-2-1_111076_2023-04-26_final.stac-item
2023-04-28 11:16:41	ga_ls9c_ard_3-2-1_109082_2023-04-28_final.stac-item
2023-05-01 11:46:20	ga_ls9c_ard_3-2-1_114079_2023-05-01_final.stac-item
2023-05-06 10:22:20	ga_ls9c_ard_3-2-1_101070_2023-05-06_final.stac-item
2023-05-10 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-05-10_final.stac-item
2023-05-12 11:26:55	ga_ls9c_ard_3-2-1_111077_2023-05-12_final.stac-item
2023-05-13 10:32:29	ga_ls9c_ard_3-2-1_102080_2023-05-13_final.stac-item
2023-05-15 10:18:07	ga_ls9c_ard_3-2-1_100075_2023-05-15_final.stac-item
2023-05-18 09:11:42	ga_ls9c_ard_3-2-1_089079_2023-05-17_final.stac-item
2023-05-20 10:35:24	ga_ls9c_ard_3-2-1_103072_2023-05-20_final.stac-item
2023-05-23 09:32:33	ga_ls9c_ard_3-2-1_092085_2023-05-23_final.stac-item
2023-05-28 11:26:46	ga_ls9c_ard_3-2-1_111077_2023-05-28_final.stac-item
2023-05-28 11:27:57	ga_ls9c_ard_3-2-1_111080_2023-05-28_final.stac-item
2023-06-02 10:03:13	ga_ls9c_ard_3-2-1_098069_2023-06-02_final.stac-item
2023-06-19 09:13:02	ga_ls9c_ard_3-2-1_089083_2023-06-18_final.stac-item
2023-06-24 11:07:40	ga_ls9c_ard_3-2-1_108076_2023-06-24_final.stac-item
2023-07-01 11:16:47	ga_ls9c_ard_3-2-1_109083_2023-07-01_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-08 11:23:03	ga_ls9c_ard_3-2-1_110083_2023-07-08_final.stac-item
2023-07-10 09:33:26	ga_ls9c_ard_3-2-1_092087_2023-07-10_final.stac-item
2023-07-10 11:09:07	ga_ls9c_ard_3-2-1_108079_2023-07-10_final.stac-item
2023-09-06 10:09:44	ga_ls9c_ard_3-2-1_098084_2023-09-06_final.stac-item
2023-09-07 10:46:37	ga_ls9c_ard_3-2-1_105068_2023-09-07_final.stac-item
2023-09-13 10:13:11	ga_ls9c_ard_3-2-1_099077_2023-09-13_final.stac-item
2023-09-13 11:52:04	ga_ls9c_ard_3-2-1_115077_2023-09-13_final.stac-item
2023-09-22 11:46:17	ga_ls9c_ard_3-2-1_114078_2023-09-22_final.stac-item
2023-09-28 11:05:32	ga_ls9c_ard_3-2-1_108069_2023-09-28_final.stac-item
2023-09-29 11:50:49	ga_ls9c_ard_3-2-1_115074_2023-09-29_final.stac-item
2023-10-06 10:19:25	ga_ls9c_ard_3-2-1_100077_2023-10-06_final.stac-item
2023-10-08 11:44:45	ga_ls9c_ard_3-2-1_114074_2023-10-08_final.stac-item
2023-10-12 09:45:12	ga_ls9c_ard_3-2-1_094084_2023-10-12_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