Search ga_ls8c_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:

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First 100 results (query limit)

Time (local)	Label
2021-10-05 11:25:40	ga_ls8c_ard_3-2-0_111072_2021-10-05_final
2021-10-05 11:26:28	ga_ls8c_ard_3-2-0_111074_2021-10-05_final
2022-01-05 10:16:09	ga_ls8c_ard_3-2-1_099084_2022-01-05_final
2022-01-22 09:17:17	ga_ls8c_ard_3-2-1_090076_2022-01-21_final
2022-01-22 09:21:16	ga_ls8c_ard_3-2-1_090086_2022-01-21_final
2022-01-24 09:06:54	ga_ls8c_ard_3-2-1_088081_2022-01-23_final
2022-02-05 11:07:40	ga_ls8c_ard_3-2-1_108074_2022-02-05_final
2022-02-09 09:07:15	ga_ls8c_ard_3-2-1_088082_2022-02-08_final
2022-02-09 10:46:08	ga_ls8c_ard_3-2-1_104082_2022-02-09_final
2022-03-02 09:23:18	ga_ls8c_ard_3-2-1_091076_2022-03-01_final
2022-03-07 11:23:06	ga_ls8c_ard_3-2-1_110082_2022-03-07_final
2022-03-14 11:25:14	ga_ls8c_ard_3-2-1_111072_2022-03-14_final
2022-03-18 11:00:04	ga_ls8c_ard_3-2-1_107071_2022-03-18_final
2022-03-26 11:52:12	ga_ls8c_ard_3-2-1_115078_2022-03-26_final
2022-03-30 11:23:26	ga_ls8c_ard_3-2-1_111068_2022-03-30_final
2022-04-11 10:14:08	ga_ls8c_ard_3-2-1_099080_2022-04-11_final
2022-04-13 10:03:47	ga_ls8c_ard_3-2-1_097085_2022-04-13_final
2022-04-19 09:23:06	ga_ls8c_ard_3-2-1_091076_2022-04-18_final
2022-04-25 10:26:28	ga_ls8c_ard_3-2-1_101080_2022-04-25_final
2022-04-28 09:16:51	ga_ls8c_ard_3-2-1_090076_2022-04-27_final
2022-04-29 10:03:18	ga_ls8c_ard_3-2-1_097084_2022-04-29_final
2022-05-02 10:27:52	ga_ls8c_ard_3-2-1_102068_2022-05-02_final
2022-05-05 09:21:31	ga_ls8c_ard_3-2-1_091072_2022-05-04_final
2022-05-08 09:53:15	ga_ls8c_ard_3-2-1_096074_2022-05-08_final
2022-05-09 10:34:08	ga_ls8c_ard_3-2-1_103068_2022-05-09_final
2022-05-19 09:33:59	ga_ls8c_ard_3-2-1_093072_2022-05-19_final
2022-05-19 11:17:40	ga_ls8c_ard_3-2-1_109084_2022-05-19_final
2022-05-21 11:02:06	ga_ls8c_ard_3-2-1_107076_2022-05-21_final
2022-05-29 10:09:52	ga_ls8c_ard_3-2-1_099069_2022-05-29_final
2022-05-31 09:57:56	ga_ls8c_ard_3-2-1_097070_2022-05-31_final
2022-06-05 11:58:14	ga_ls8c_ard_3-2-1_116077_2022-06-05_final
2022-06-06 09:22:33	ga_ls8c_ard_3-2-1_091074_2022-06-05_final
2022-06-06 09:28:32	ga_ls8c_ard_3-2-1_091089_2022-06-05_final
2022-06-11 11:19:14	ga_ls8c_ard_3-2-1_110072_2022-06-11_final
2022-06-11 11:24:01	ga_ls8c_ard_3-2-1_110084_2022-06-11_final
2022-06-19 10:30:16	ga_ls8c_ard_3-2-1_102073_2022-06-19_final
2022-07-08 11:02:24	ga_ls8c_ard_3-2-1_107076_2022-07-08_final
2022-07-16 10:16:08	ga_ls8c_ard_3-2-1_099084_2022-07-16_final
2022-07-22 11:16:02	ga_ls8c_ard_3-2-1_109079_2022-07-22_final
2022-07-27 09:57:45	ga_ls8c_ard_3-2-1_096084_2022-07-27_final
2022-08-02 09:23:07	ga_ls8c_ard_3-2-1_090090_2022-08-01_final
2022-08-03 11:42:29	ga_ls8c_ard_3-2-1_113083_2022-08-03_final
2022-08-04 10:42:52	ga_ls8c_ard_3-2-1_104073_2022-08-04_final
2022-08-05 11:26:33	ga_ls8c_ard_3-2-1_111074_2022-08-05_final
2022-08-09 09:23:22	ga_ls8c_ard_3-2-1_091075_2022-08-08_final
2022-08-11 09:14:37	ga_ls8c_ard_3-2-1_089084_2022-08-10_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-08-28 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-08-28_final
2022-08-30 11:20:02	ga_ls8c_ard_3-2-1_110073_2022-08-30_final
2022-09-02 10:13:39	ga_ls8c_ard_3-2-1_099077_2022-09-02_final
2022-09-06 11:25:51	ga_ls8c_ard_3-2-1_111072_2022-09-06_final
2022-09-10 09:22:41	ga_ls8c_ard_3-2-1_091073_2022-09-09_final
2022-09-17 09:34:05	ga_ls8c_ard_3-2-1_092086_2022-09-17_final
2022-09-19 09:17:21	ga_ls8c_ard_3-2-1_090075_2022-09-18_final
2022-09-19 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-09-19_final
2022-09-24 09:35:06	ga_ls8c_ard_3-2-1_093073_2022-09-24_final
2022-10-03 09:28:29	ga_ls8c_ard_3-2-1_092072_2022-10-02_final
2022-10-06 11:39:03	ga_ls8c_ard_3-2-1_113074_2022-10-06_final
2022-10-08 09:51:46	ga_ls8c_ard_3-2-1_095084_2022-10-08_final
2022-10-08 11:26:40	ga_ls8c_ard_3-2-1_111074_2022-10-08_final
2022-10-19 09:34:48	ga_ls8c_ard_3-2-1_092088_2022-10-19_final
2022-10-22 09:57:22	ga_ls8c_ard_3-2-1_097067_2022-10-22_final
2022-10-26 09:38:15	ga_ls8c_ard_3-2-1_093081_2022-10-26_final
2022-10-28 09:23:31	ga_ls8c_ard_3-2-1_091075_2022-10-27_final
2022-10-29 10:07:59	ga_ls8c_ard_3-2-1_098078_2022-10-29_final
2022-11-05 10:09:46	ga_ls8c_ard_3-2-1_099067_2022-11-05_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-13 11:02:20	ga_ls8c_ard_3-2-1_107075_2022-11-13_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-20 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-11-19_final
2022-11-28 10:20:16	ga_ls8c_ard_3-2-1_100078_2022-11-28_final
2022-12-13 11:17:49	ga_ls8c_ard_3-2-1_109083_2022-12-13_final
2022-12-15 11:02:39	ga_ls8c_ard_3-2-1_107076_2022-12-15_final
2022-12-25 11:38:50	ga_ls8c_ard_3-2-1_113074_2022-12-25_final
2022-12-26 09:06:44	ga_ls8c_ard_3-2-1_088080_2022-12-25_final
2023-01-10 11:38:02	ga_ls8c_ard_3-2-1_113072_2023-01-10_final
2023-01-10 11:38:50	ga_ls8c_ard_3-2-1_113074_2023-01-10_final
2023-01-11 10:46:23	ga_ls8c_ard_3-2-1_104082_2023-01-11_final
2023-01-14 11:12:52	ga_ls8c_ard_3-2-1_109071_2023-01-14_final
2023-01-18 09:11:59	ga_ls8c_ard_3-2-1_089078_2023-01-17_final
2023-01-19 09:58:28	ga_ls8c_ard_3-2-1_096086_2023-01-19_final
2023-01-20 10:36:09	ga_ls8c_ard_3-2-1_103072_2023-01-20_final
2023-01-21 09:41:21	ga_ls8c_ard_3-2-1_094074_2023-01-21_final
2023-01-22 10:23:25	ga_ls8c_ard_3-2-1_101071_2023-01-22_final
2023-01-25 09:21:27	ga_ls8c_ard_3-2-1_090086_2023-01-24_final
2023-01-26 09:58:20	ga_ls8c_ard_3-2-1_097070_2023-01-26_final
2023-01-26 09:59:08	ga_ls8c_ard_3-2-1_097072_2023-01-26_final
2023-01-29 10:30:27	ga_ls8c_ard_3-2-1_102073_2023-01-29_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-10 09:21:49	ga_ls8c_ard_3-2-1_090087_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-10 10:54:43	ga_ls8c_ard_3-2-1_106072_2023-02-10_final
2023-02-11 11:38:46	ga_ls8c_ard_3-2-1_113074_2023-02-11_final
2023-02-13 09:47:05	ga_ls8c_ard_3-2-1_095073_2023-02-13_final
2023-02-14 10:30:21	ga_ls8c_ard_3-2-1_102073_2023-02-14_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-20 11:36:26	ga_ls8c_ard_3-2-1_112084_2023-02-20_final
2023-02-26 09:17:33	ga_ls8c_ard_3-2-1_090077_2023-02-25_final
2023-03-01 09:52:03	ga_ls8c_ard_3-2-1_095086_2023-03-01_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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