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
2022-01-14 10:08:22	ga_ls8c_ard_3-2-1_098080_2022-01-14_final
2022-08-22 10:31:00	ga_ls8c_ard_3-2-1_102074_2022-08-22_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-08-25 11:00:18	ga_ls8c_ard_3-2-1_107070_2022-08-25_final
2022-09-12 10:47:37	ga_ls8c_ard_3-2-1_105069_2022-09-12_final
2022-09-20 11:42:17	ga_ls8c_ard_3-2-1_113082_2022-09-20_final
2022-10-03 09:35:16	ga_ls8c_ard_3-2-1_092089_2022-10-03_final
2022-10-04 10:16:08	ga_ls8c_ard_3-2-1_099083_2022-10-04_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-11 10:21:02	ga_ls8c_ard_3-2-1_100080_2022-10-11_final
2022-10-14 09:13:00	ga_ls8c_ard_3-2-1_089080_2022-10-13_final
2022-10-17 09:44:45	ga_ls8c_ard_3-2-1_094082_2022-10-17_final
2022-10-17 11:19:39	ga_ls8c_ard_3-2-1_110072_2022-10-17_final
2022-10-29 10:07:35	ga_ls8c_ard_3-2-1_098077_2022-10-29_final
2022-10-29 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-10-29_final
2022-10-29 11:46:52	ga_ls8c_ard_3-2-1_114078_2022-10-29_final
2022-10-31 09:52:50	ga_ls8c_ard_3-2-1_096071_2022-10-31_final
2022-10-31 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-10-31_final
2022-11-01 10:39:41	ga_ls8c_ard_3-2-1_103080_2022-11-01_final
2022-11-02 11:20:09	ga_ls8c_ard_3-2-1_110073_2022-11-02_final
2022-11-06 10:55:25	ga_ls8c_ard_3-2-1_106073_2022-11-06_final
2022-11-06 10:55:49	ga_ls8c_ard_3-2-1_106074_2022-11-06_final
2022-11-06 10:58:13	ga_ls8c_ard_3-2-1_106080_2022-11-06_final
2022-11-12 10:18:17	ga_ls8c_ard_3-2-1_100073_2022-11-12_final
2022-11-27 09:40:11	ga_ls8c_ard_3-2-1_093086_2022-11-27_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-01 10:47:58	ga_ls8c_ard_3-2-1_105070_2022-12-01_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-13 09:36:09	ga_ls8c_ard_3-2-1_093076_2022-12-13_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-15 09:26:57	ga_ls8c_ard_3-2-1_091084_2022-12-14_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-26 10:44:49	ga_ls8c_ard_3-2-1_104078_2022-12-26_final
2023-01-01 10:09:45	ga_ls8c_ard_3-2-1_098083_2023-01-01_final
2023-01-02 09:12:56	ga_ls8c_ard_3-2-1_089080_2023-01-01_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-02-17 09:28:42	ga_ls8c_ard_3-2-1_091089_2023-02-16_final
2023-02-19 10:52:23	ga_ls8c_ard_3-2-1_105082_2023-02-19_final
2023-02-22 11:23:13	ga_ls8c_ard_3-2-1_110082_2023-02-22_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-03-07 09:14:31	ga_ls8c_ard_3-2-1_089085_2023-03-06_final
2023-03-11 10:23:52	ga_ls8c_ard_3-2-1_101073_2023-03-11_final
2023-03-16 10:42:23	ga_ls8c_ard_3-2-1_104073_2023-03-16_final
2023-03-19 11:17:38	ga_ls8c_ard_3-2-1_109084_2023-03-19_final
2023-03-19 11:17:38	ga_ls8c_ard_3-2-1_109084_2023-03-19_nrt
2023-03-25 10:38:52	ga_ls8c_ard_3-2-1_103080_2023-03-25_final
2023-03-28 11:05:46	ga_ls8c_ard_3-2-1_108070_2023-03-28_final
2023-03-30 10:58:11	ga_ls8c_ard_3-2-1_106082_2023-03-30_final
2023-04-04 11:12:39	ga_ls8c_ard_3-2-1_109072_2023-04-04_final
2023-04-05 10:19:48	ga_ls8c_ard_3-2-1_100079_2023-04-05_final
2023-04-06 09:24:57	ga_ls8c_ard_3-2-1_091081_2023-04-05_final
2023-04-06 09:25:21	ga_ls8c_ard_3-2-1_091082_2023-04-05_final
2023-04-15 09:17:03	ga_ls8c_ard_3-2-1_090077_2023-04-14_final
2023-04-17 10:41:58	ga_ls8c_ard_3-2-1_104073_2023-04-17_final
2023-04-18 09:51:55	ga_ls8c_ard_3-2-1_095087_2023-04-18_final
2023-04-30 10:10:37	ga_ls8c_ard_3-2-1_099072_2023-04-30_final
2023-04-30 10:15:00	ga_ls8c_ard_3-2-1_099083_2023-04-30_final
2023-05-02 09:58:14	ga_ls8c_ard_3-2-1_097072_2023-05-02_final
2023-05-02 11:37:55	ga_ls8c_ard_3-2-1_113074_2023-05-02_final
2023-05-04 09:50:38	ga_ls8c_ard_3-2-1_095084_2023-05-04_final
2023-05-06 09:39:26	ga_ls8c_ard_3-2-1_093087_2023-05-06_final
2023-05-06 11:17:08	ga_ls8c_ard_3-2-1_109084_2023-05-06_final
2023-05-11 09:56:41	ga_ls8c_ard_3-2-1_096084_2023-05-11_final
2023-05-12 10:33:33	ga_ls8c_ard_3-2-1_103068_2023-05-12_final
2023-05-15 11:06:49	ga_ls8c_ard_3-2-1_108074_2023-05-15_final
2023-05-20 09:50:28	ga_ls8c_ard_3-2-1_095084_2023-05-20_final
2023-05-25 11:46:44	ga_ls8c_ard_3-2-1_114081_2023-05-25_final
2023-05-27 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-27_final
2023-06-04 10:41:46	ga_ls8c_ard_3-2-1_104073_2023-06-04_final
2023-06-09 09:23:53	ga_ls8c_ard_3-2-1_091079_2023-06-08_final
2023-06-09 10:59:35	ga_ls8c_ard_3-2-1_107071_2023-06-09_final
2023-06-10 10:07:09	ga_ls8c_ard_3-2-1_098079_2023-06-10_final
2023-06-11 09:15:32	ga_ls8c_ard_3-2-1_089089_2023-06-10_final
2023-06-14 11:18:10	ga_ls8c_ard_3-2-1_110071_2023-06-14_final
2023-06-15 10:27:20	ga_ls8c_ard_3-2-1_101083_2023-06-15_final
2023-06-17 11:51:28	ga_ls8c_ard_3-2-1_115077_2023-06-17_final
2023-06-21 11:28:45	ga_ls8c_ard_3-2-1_111082_2023-06-21_final
2023-06-24 10:18:23	ga_ls8c_ard_3-2-1_100076_2023-06-24_final
2023-06-25 11:04:52	ga_ls8c_ard_3-2-1_107084_2023-06-25_final
2023-06-26 10:09:40	ga_ls8c_ard_3-2-1_098085_2023-06-26_final
2023-07-03 11:51:14	ga_ls8c_ard_3-2-1_115076_2023-07-03_final
2023-07-10 10:20:59	ga_ls8c_ard_3-2-1_100082_2023-07-10_final
2023-07-12 10:04:39	ga_ls8c_ard_3-2-1_098072_2023-07-12_final
2023-07-16 09:45:31	ga_ls8c_ard_3-2-1_094086_2023-07-16_final
2023-07-16 11:20:25	ga_ls8c_ard_3-2-1_110076_2023-07-16_final
2023-07-18 09:32:45	ga_ls8c_ard_3-2-1_092085_2023-07-18_final
2023-07-18 11:10:50	ga_ls8c_ard_3-2-1_108083_2023-07-18_final
2023-07-26 11:58:22	ga_ls8c_ard_3-2-1_116078_2023-07-26_final
2023-08-11 11:57:38	ga_ls8c_ard_3-2-1_116076_2023-08-11_final
2023-08-17 11:23:02	ga_ls8c_ard_3-2-1_110082_2023-08-17_final
2023-08-21 09:21:04	ga_ls8c_ard_3-2-1_090086_2023-08-20_final
2023-08-26 09:40:26	ga_ls8c_ard_3-2-1_093088_2023-08-26_nrt
2023-08-28 11:01:46	ga_ls8c_ard_3-2-1_107075_2023-08-28_nrt
2023-08-28 11:02:10	ga_ls8c_ard_3-2-1_107076_2023-08-28_nrt
2023-08-30 09:16:30	ga_ls8c_ard_3-2-1_089090_2023-08-29_nrt
2023-09-05 10:10:42	ga_ls8c_ard_3-2-1_099071_2023-09-05_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