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:

Add field

First 100 results (query limit)

Time (local)	Label
2022-01-26 10:29:01	ga_ls8c_ard_3-2-1_102070_2022-01-26_final
2022-01-30 10:07:29	ga_ls8c_ard_3-2-1_098078_2022-01-30_final
2022-01-30 11:47:09	ga_ls8c_ard_3-2-1_114080_2022-01-30_final
2022-02-05 11:07:40	ga_ls8c_ard_3-2-1_108074_2022-02-05_final
2022-02-10 11:26:36	ga_ls8c_ard_3-2-1_111075_2022-02-10_final
2022-02-14 11:00:15	ga_ls8c_ard_3-2-1_107071_2022-02-14_final
2022-02-17 11:36:19	ga_ls8c_ard_3-2-1_112084_2022-02-17_final
2022-02-19 11:19:57	ga_ls8c_ard_3-2-1_110074_2022-02-19_final
2022-02-24 11:37:41	ga_ls8c_ard_3-2-1_113072_2022-02-24_final
2022-02-26 09:47:14	ga_ls8c_ard_3-2-1_095074_2022-02-26_final
2022-02-28 11:14:33	ga_ls8c_ard_3-2-1_109076_2022-02-28_final
2022-03-01 10:18:55	ga_ls8c_ard_3-2-1_100076_2022-03-01_final
2022-03-03 10:04:57	ga_ls8c_ard_3-2-1_098072_2022-03-03_final
2022-03-09 09:33:50	ga_ls8c_ard_3-2-1_092087_2022-03-09_final
2022-03-11 09:22:39	ga_ls8c_ard_3-2-1_090090_2022-03-10_final
2022-03-19 10:02:50	ga_ls8c_ard_3-2-1_098067_2022-03-19_final
2022-03-19 11:46:55	ga_ls8c_ard_3-2-1_114080_2022-03-19_final
2022-03-20 09:12:00	ga_ls8c_ard_3-2-1_089079_2022-03-19_final
2022-03-24 10:25:42	ga_ls8c_ard_3-2-1_101078_2022-03-24_final
2022-03-25 09:34:27	ga_ls8c_ard_3-2-1_092089_2022-03-25_final
2022-03-26 10:13:43	ga_ls8c_ard_3-2-1_099079_2022-03-26_final
2022-03-26 11:51:48	ga_ls8c_ard_3-2-1_115077_2022-03-26_final
2022-03-27 09:20:52	ga_ls8c_ard_3-2-1_090086_2022-03-26_final
2022-03-27 09:22:04	ga_ls8c_ard_3-2-1_090089_2022-03-26_final
2022-03-30 09:51:44	ga_ls8c_ard_3-2-1_095086_2022-03-30_final
2022-03-30 11:23:26	ga_ls8c_ard_3-2-1_111068_2022-03-30_final
2022-04-12 10:55:48	ga_ls8c_ard_3-2-1_106076_2022-04-12_final
2022-04-20 10:06:46	ga_ls8c_ard_3-2-1_098077_2022-04-20_final
2022-05-03 09:39:51	ga_ls8c_ard_3-2-1_093087_2022-05-03_final
2022-05-13 10:11:02	ga_ls8c_ard_3-2-1_099072_2022-05-13_final
2022-05-28 11:05:52	ga_ls8c_ard_3-2-1_108070_2022-05-28_final
2022-05-28 11:11:04	ga_ls8c_ard_3-2-1_108083_2022-05-28_final
2022-06-02 09:46:25	ga_ls8c_ard_3-2-1_095072_2022-06-02_final
2022-06-02 09:51:12	ga_ls8c_ard_3-2-1_095084_2022-06-02_final
2022-06-04 09:33:41	ga_ls8c_ard_3-2-1_093071_2022-06-04_final
2022-06-09 11:36:22	ga_ls8c_ard_3-2-1_112084_2022-06-09_final
2022-06-11 11:19:38	ga_ls8c_ard_3-2-1_110073_2022-06-11_final
2022-06-13 09:33:12	ga_ls8c_ard_3-2-1_092085_2022-06-13_final
2022-06-18 11:25:05	ga_ls8c_ard_3-2-1_111071_2022-06-18_final
2022-06-23 10:07:10	ga_ls8c_ard_3-2-1_098077_2022-06-23_final
2022-06-23 10:07:58	ga_ls8c_ard_3-2-1_098079_2022-06-23_final
2022-06-27 11:19:45	ga_ls8c_ard_3-2-1_110073_2022-06-27_final
2022-06-27 11:20:32	ga_ls8c_ard_3-2-1_110075_2022-06-27_final
2022-06-27 11:20:56	ga_ls8c_ard_3-2-1_110076_2022-06-27_final
2022-07-02 10:04:12	ga_ls8c_ard_3-2-1_097085_2022-07-02_final
2022-07-05 10:30:18	ga_ls8c_ard_3-2-1_102073_2022-07-05_final
2022-07-17 10:56:13	ga_ls8c_ard_3-2-1_106076_2022-07-17_final
2022-08-05 09:46:52	ga_ls8c_ard_3-2-1_095072_2022-08-05_final
2022-08-05 11:26:33	ga_ls8c_ard_3-2-1_111074_2022-08-05_final
2022-08-16 09:29:11	ga_ls8c_ard_3-2-1_092074_2022-08-15_final
2022-08-22 10:30:36	ga_ls8c_ard_3-2-1_102073_2022-08-22_final
2022-08-23 09:40:34	ga_ls8c_ard_3-2-1_093087_2022-08-23_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-08-26 10:10:16	ga_ls8c_ard_3-2-1_098084_2022-08-26_final
2022-09-05 09:07:17	ga_ls8c_ard_3-2-1_088081_2022-09-04_final
2022-09-10 09:25:52	ga_ls8c_ard_3-2-1_091081_2022-09-09_final
2022-09-11 10:05:09	ga_ls8c_ard_3-2-1_098071_2022-09-11_final
2022-09-12 09:16:43	ga_ls8c_ard_3-2-1_089089_2022-09-11_final
2022-09-19 10:56:38	ga_ls8c_ard_3-2-1_106076_2022-09-19_final
2022-09-24 11:15:10	ga_ls8c_ard_3-2-1_109076_2022-09-24_final
2022-09-26 09:23:56	ga_ls8c_ard_3-2-1_091076_2022-09-25_final
2022-09-27 10:09:59	ga_ls8c_ard_3-2-1_098083_2022-09-27_final
2022-10-01 11:19:21	ga_ls8c_ard_3-2-1_110071_2022-10-01_final
2022-10-05 09:23:18	ga_ls8c_ard_3-2-1_090090_2022-10-04_final
2022-10-12 11:01:05	ga_ls8c_ard_3-2-1_107072_2022-10-12_final
2022-10-12 11:02:41	ga_ls8c_ard_3-2-1_107076_2022-10-12_final
2022-10-12 11:05:28	ga_ls8c_ard_3-2-1_107083_2022-10-12_final
2022-10-13 11:47:55	ga_ls8c_ard_3-2-1_114081_2022-10-13_final
2022-10-17 11:23:38	ga_ls8c_ard_3-2-1_110082_2022-10-17_final
2022-10-28 09:24:19	ga_ls8c_ard_3-2-1_091077_2022-10-27_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-10-30 09:15:33	ga_ls8c_ard_3-2-1_089086_2022-10-29_final
2022-11-01 10:38:29	ga_ls8c_ard_3-2-1_103077_2022-11-01_final
2022-11-05 10:14:57	ga_ls8c_ard_3-2-1_099080_2022-11-05_final
2022-11-09 09:52:36	ga_ls8c_ard_3-2-1_095086_2022-11-09_final
2022-11-14 10:06:18	ga_ls8c_ard_3-2-1_098074_2022-11-14_final
2022-11-15 10:46:46	ga_ls8c_ard_3-2-1_105067_2022-11-15_final
2022-11-26 10:30:37	ga_ls8c_ard_3-2-1_102073_2022-11-26_final
2022-11-29 09:22:39	ga_ls8c_ard_3-2-1_091073_2022-11-28_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-06 09:34:00	ga_ls8c_ard_3-2-1_092086_2022-12-06_final
2022-12-14 10:19:48	ga_ls8c_ard_3-2-1_100077_2022-12-14_final
2022-12-16 11:45:06	ga_ls8c_ard_3-2-1_114074_2022-12-16_final
2022-12-18 11:36:42	ga_ls8c_ard_3-2-1_112084_2022-12-18_final
2022-12-28 10:31:40	ga_ls8c_ard_3-2-1_102076_2022-12-28_final
2022-12-30 10:18:07	ga_ls8c_ard_3-2-1_100073_2022-12-30_final
2022-12-31 09:28:05	ga_ls8c_ard_3-2-1_091087_2022-12-30_final
2023-01-03 09:52:36	ga_ls8c_ard_3-2-1_096071_2023-01-03_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-10 09:22:37	ga_ls8c_ard_3-2-1_090089_2023-02-09_final
2023-02-10 10:55:55	ga_ls8c_ard_3-2-1_106075_2023-02-10_final
2023-02-15 09:35:30	ga_ls8c_ard_3-2-1_093075_2023-02-15_final
2023-02-16 10:18:21	ga_ls8c_ard_3-2-1_100074_2023-02-16_final
2023-02-16 10:19:09	ga_ls8c_ard_3-2-1_100076_2023-02-16_final
2023-02-18 10:09:33	ga_ls8c_ard_3-2-1_098083_2023-02-18_final
2023-02-19 09:13:07	ga_ls8c_ard_3-2-1_089081_2023-02-18_final
2023-02-26 10:55:14	ga_ls8c_ard_3-2-1_106074_2023-02-26_final
2023-02-27 10:03:37	ga_ls8c_ard_3-2-1_097084_2023-02-27_final
2023-03-06 11:47:02	ga_ls8c_ard_3-2-1_114080_2023-03-06_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