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
2022-08-20 09:06:52	ga_ls8c_ard_3-2-1_088080_2022-08-19_final
2022-08-20 09:07:16	ga_ls8c_ard_3-2-1_088081_2022-08-19_final
2022-08-20 09:07:40	ga_ls8c_ard_3-2-1_088082_2022-08-19_final
2022-08-20 09:08:04	ga_ls8c_ard_3-2-1_088083_2022-08-19_final
2022-08-21 09:46:32	ga_ls8c_ard_3-2-1_095071_2022-08-21_final
2022-08-21 09:46:56	ga_ls8c_ard_3-2-1_095072_2022-08-21_final
2022-08-21 09:47:20	ga_ls8c_ard_3-2-1_095073_2022-08-21_final
2022-08-21 09:47:44	ga_ls8c_ard_3-2-1_095074_2022-08-21_final
2022-08-21 09:48:08	ga_ls8c_ard_3-2-1_095075_2022-08-21_final
2022-08-21 09:48:32	ga_ls8c_ard_3-2-1_095076_2022-08-21_final
2022-08-21 09:48:56	ga_ls8c_ard_3-2-1_095077_2022-08-21_final
2022-08-21 09:49:20	ga_ls8c_ard_3-2-1_095078_2022-08-21_final
2022-08-21 09:49:44	ga_ls8c_ard_3-2-1_095079_2022-08-21_final
2022-08-21 09:50:08	ga_ls8c_ard_3-2-1_095080_2022-08-21_final
2022-08-21 09:50:32	ga_ls8c_ard_3-2-1_095081_2022-08-21_final
2022-08-21 09:50:56	ga_ls8c_ard_3-2-1_095082_2022-08-21_final
2022-08-21 09:51:20	ga_ls8c_ard_3-2-1_095083_2022-08-21_final
2022-08-21 09:52:08	ga_ls8c_ard_3-2-1_095085_2022-08-21_final
2022-08-21 09:52:32	ga_ls8c_ard_3-2-1_095086_2022-08-21_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-21 11:26:13	ga_ls8c_ard_3-2-1_111073_2022-08-21_final
2022-08-21 11:26:37	ga_ls8c_ard_3-2-1_111074_2022-08-21_final
2022-08-21 11:27:01	ga_ls8c_ard_3-2-1_111075_2022-08-21_final
2022-08-21 11:27:25	ga_ls8c_ard_3-2-1_111076_2022-08-21_final
2022-08-21 11:27:49	ga_ls8c_ard_3-2-1_111077_2022-08-21_final
2022-08-21 11:28:13	ga_ls8c_ard_3-2-1_111078_2022-08-21_final
2022-08-21 11:28:37	ga_ls8c_ard_3-2-1_111079_2022-08-21_final
2022-08-22 10:28:36	ga_ls8c_ard_3-2-1_102068_2022-08-22_final
2022-08-22 10:29:00	ga_ls8c_ard_3-2-1_102069_2022-08-22_final
2022-08-22 10:29:24	ga_ls8c_ard_3-2-1_102070_2022-08-22_final
2022-08-22 10:29:48	ga_ls8c_ard_3-2-1_102071_2022-08-22_final
2022-08-22 10:30:12	ga_ls8c_ard_3-2-1_102072_2022-08-22_final
2022-08-22 10:32:36	ga_ls8c_ard_3-2-1_102078_2022-08-22_final
2022-08-22 10:33:00	ga_ls8c_ard_3-2-1_102079_2022-08-22_final
2022-08-22 10:33:24	ga_ls8c_ard_3-2-1_102080_2022-08-22_final
2022-08-22 10:33:48	ga_ls8c_ard_3-2-1_102081_2022-08-22_final
2022-08-22 10:34:12	ga_ls8c_ard_3-2-1_102082_2022-08-22_final
2022-08-23 09:34:11	ga_ls8c_ard_3-2-1_093071_2022-08-23_final
2022-08-23 09:34:35	ga_ls8c_ard_3-2-1_093072_2022-08-23_final
2022-08-23 09:34:59	ga_ls8c_ard_3-2-1_093073_2022-08-23_final
2022-08-23 09:35:23	ga_ls8c_ard_3-2-1_093074_2022-08-23_final
2022-08-23 09:35:47	ga_ls8c_ard_3-2-1_093075_2022-08-23_final
2022-08-23 09:36:11	ga_ls8c_ard_3-2-1_093076_2022-08-23_final
2022-08-23 09:36:35	ga_ls8c_ard_3-2-1_093077_2022-08-23_final
2022-08-23 09:36:58	ga_ls8c_ard_3-2-1_093078_2022-08-23_final
2022-08-23 09:37:22	ga_ls8c_ard_3-2-1_093079_2022-08-23_final
2022-08-23 09:38:10	ga_ls8c_ard_3-2-1_093081_2022-08-23_final
2022-08-23 09:40:58	ga_ls8c_ard_3-2-1_093088_2022-08-23_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-08-23 11:12:40	ga_ls8c_ard_3-2-1_109070_2022-08-23_final
2022-08-23 11:13:04	ga_ls8c_ard_3-2-1_109071_2022-08-23_final
2022-08-23 11:13:28	ga_ls8c_ard_3-2-1_109072_2022-08-23_final
2022-08-23 11:13:52	ga_ls8c_ard_3-2-1_109073_2022-08-23_final
2022-08-23 11:14:16	ga_ls8c_ard_3-2-1_109074_2022-08-23_final
2022-08-23 11:14:40	ga_ls8c_ard_3-2-1_109075_2022-08-23_final
2022-08-23 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-08-23_final
2022-08-23 11:15:28	ga_ls8c_ard_3-2-1_109077_2022-08-23_final
2022-08-23 11:15:51	ga_ls8c_ard_3-2-1_109078_2022-08-23_final
2022-08-23 11:16:15	ga_ls8c_ard_3-2-1_109079_2022-08-23_final
2022-08-23 11:16:39	ga_ls8c_ard_3-2-1_109080_2022-08-23_final
2022-08-23 11:17:51	ga_ls8c_ard_3-2-1_109083_2022-08-23_final
2022-08-24 10:19:02	ga_ls8c_ard_3-2-1_100075_2022-08-24_final
2022-08-24 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-08-24_final
2022-08-24 10:19:50	ga_ls8c_ard_3-2-1_100077_2022-08-24_final
2022-08-24 10:20:14	ga_ls8c_ard_3-2-1_100078_2022-08-24_final
2022-08-24 10:20:38	ga_ls8c_ard_3-2-1_100079_2022-08-24_final
2022-08-24 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-08-24_final
2022-08-24 10:21:26	ga_ls8c_ard_3-2-1_100081_2022-08-24_final
2022-08-24 10:21:50	ga_ls8c_ard_3-2-1_100082_2022-08-24_final
2022-08-24 10:22:14	ga_ls8c_ard_3-2-1_100083_2022-08-24_final
2022-08-24 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-08-24_final
2022-08-24 11:58:19	ga_ls8c_ard_3-2-1_116076_2022-08-24_final
2022-08-24 11:58:43	ga_ls8c_ard_3-2-1_116077_2022-08-24_final
2022-08-25 09:22:13	ga_ls8c_ard_3-2-1_091072_2022-08-24_final
2022-08-25 09:23:49	ga_ls8c_ard_3-2-1_091076_2022-08-24_final
2022-08-25 09:24:37	ga_ls8c_ard_3-2-1_091078_2022-08-24_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-25 09:29:00	ga_ls8c_ard_3-2-1_091089_2022-08-24_final
2022-08-25 09:29:24	ga_ls8c_ard_3-2-1_091090_2022-08-24_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-08-25 11:00:42	ga_ls8c_ard_3-2-1_107071_2022-08-25_final
2022-08-25 11:01:06	ga_ls8c_ard_3-2-1_107072_2022-08-25_final
2022-08-25 11:01:54	ga_ls8c_ard_3-2-1_107074_2022-08-25_final
2022-08-25 11:02:18	ga_ls8c_ard_3-2-1_107075_2022-08-25_final
2022-08-25 11:02:42	ga_ls8c_ard_3-2-1_107076_2022-08-25_final
2022-08-25 11:03:06	ga_ls8c_ard_3-2-1_107077_2022-08-25_final
2022-08-25 11:03:54	ga_ls8c_ard_3-2-1_107079_2022-08-25_final
2022-08-25 11:04:18	ga_ls8c_ard_3-2-1_107080_2022-08-25_final
2022-08-25 11:04:42	ga_ls8c_ard_3-2-1_107081_2022-08-25_final
2022-08-26 10:04:17	ga_ls8c_ard_3-2-1_098069_2022-08-26_final
2022-08-26 10:04:41	ga_ls8c_ard_3-2-1_098070_2022-08-26_final
2022-08-26 10:05:05	ga_ls8c_ard_3-2-1_098071_2022-08-26_final
2022-08-26 10:05:29	ga_ls8c_ard_3-2-1_098072_2022-08-26_final
2022-08-26 10:05:53	ga_ls8c_ard_3-2-1_098073_2022-08-26_final
2022-08-26 10:06:17	ga_ls8c_ard_3-2-1_098074_2022-08-26_final
2022-08-26 10:07:05	ga_ls8c_ard_3-2-1_098076_2022-08-26_final
2022-08-26 10:07:29	ga_ls8c_ard_3-2-1_098077_2022-08-26_final
2022-08-26 10:07:52	ga_ls8c_ard_3-2-1_098078_2022-08-26_final
2022-08-26 10:08:16	ga_ls8c_ard_3-2-1_098079_2022-08-26_final
2022-08-26 10:09:04	ga_ls8c_ard_3-2-1_098081_2022-08-26_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years