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
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-19 09:32:49	ga_ls8c_ard_3-2-1_092083_2022-10-19_final
2022-10-21 10:55:22	ga_ls8c_ard_3-2-1_106073_2022-10-21_final
2022-10-28 09:23:07	ga_ls8c_ard_3-2-1_091074_2022-10-27_final
2022-10-29 10:07:59	ga_ls8c_ard_3-2-1_098078_2022-10-29_final
2022-11-04 09:33:42	ga_ls8c_ard_3-2-1_092085_2022-11-04_final
2022-11-04 09:34:30	ga_ls8c_ard_3-2-1_092087_2022-11-04_final
2022-11-06 10:54:37	ga_ls8c_ard_3-2-1_106071_2022-11-06_final
2022-11-07 11:39:05	ga_ls8c_ard_3-2-1_113074_2022-11-07_final
2022-11-10 10:30:40	ga_ls8c_ard_3-2-1_102073_2022-11-10_final
2022-11-13 09:25:27	ga_ls8c_ard_3-2-1_091080_2022-11-12_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-15 10:47:33	ga_ls8c_ard_3-2-1_105069_2022-11-15_final
2022-11-15 10:48:45	ga_ls8c_ard_3-2-1_105072_2022-11-15_final
2022-11-17 10:35:10	ga_ls8c_ard_3-2-1_103069_2022-11-17_final
2022-11-18 11:21:13	ga_ls8c_ard_3-2-1_110076_2022-11-18_final
2022-11-20 11:07:40	ga_ls8c_ard_3-2-1_108073_2022-11-20_final
2022-11-21 10:10:28	ga_ls8c_ard_3-2-1_099069_2022-11-21_final
2022-11-21 10:10:51	ga_ls8c_ard_3-2-1_099070_2022-11-21_final
2022-11-22 10:54:08	ga_ls8c_ard_3-2-1_106070_2022-11-22_final
2022-11-25 11:26:38	ga_ls8c_ard_3-2-1_111074_2022-11-25_final
2022-11-25 11:30:38	ga_ls8c_ard_3-2-1_111084_2022-11-25_final
2022-11-27 09:40:35	ga_ls8c_ard_3-2-1_093087_2022-11-27_final
2022-11-29 09:27:50	ga_ls8c_ard_3-2-1_091086_2022-11-28_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-04 09:44:46	ga_ls8c_ard_3-2-1_094082_2022-12-04_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-05 10:28:02	ga_ls8c_ard_3-2-1_101082_2022-12-05_final
2022-12-06 09:34:00	ga_ls8c_ard_3-2-1_092086_2022-12-06_final
2022-12-09 11:42:35	ga_ls8c_ard_3-2-1_113083_2022-12-09_final
2022-12-13 11:12:38	ga_ls8c_ard_3-2-1_109070_2022-12-13_final
2022-12-19 10:35:05	ga_ls8c_ard_3-2-1_103069_2022-12-19_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-20 09:44:38	ga_ls8c_ard_3-2-1_094082_2022-12-20_final
2022-12-22 09:33:02	ga_ls8c_ard_3-2-1_092084_2022-12-22_final
2022-12-26 09:06:44	ga_ls8c_ard_3-2-1_088080_2022-12-25_final
2022-12-29 09:40:50	ga_ls8c_ard_3-2-1_093088_2022-12-29_final
2022-12-31 11:05:22	ga_ls8c_ard_3-2-1_107083_2022-12-31_final
2023-01-03 09:53:48	ga_ls8c_ard_3-2-1_096074_2023-01-03_final
2023-01-03 11:36:16	ga_ls8c_ard_3-2-1_112083_2023-01-03_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-06 10:27:53	ga_ls8c_ard_3-2-1_101082_2023-01-06_final
2023-01-08 10:11:55	ga_ls8c_ard_3-2-1_099073_2023-01-08_final
2023-01-08 10:15:31	ga_ls8c_ard_3-2-1_099082_2023-01-08_final
2023-01-08 11:53:12	ga_ls8c_ard_3-2-1_115079_2023-01-08_final
2023-01-09 10:54:23	ga_ls8c_ard_3-2-1_106071_2023-01-09_final
2023-01-09 10:55:10	ga_ls8c_ard_3-2-1_106073_2023-01-09_final
2023-01-10 10:03:56	ga_ls8c_ard_3-2-1_097084_2023-01-10_final
2023-01-18 09:11:59	ga_ls8c_ard_3-2-1_089078_2023-01-17_final
2023-01-20 10:36:09	ga_ls8c_ard_3-2-1_103072_2023-01-20_final
2023-01-29 10:28:51	ga_ls8c_ard_3-2-1_102069_2023-01-29_final
2023-01-30 11:12:31	ga_ls8c_ard_3-2-1_109070_2023-01-30_final
2023-02-07 10:23:27	ga_ls8c_ard_3-2-1_101071_2023-02-07_final
2023-02-07 10:24:15	ga_ls8c_ard_3-2-1_101073_2023-02-07_final
2023-02-09 10:13:52	ga_ls8c_ard_3-2-1_099078_2023-02-09_final
2023-02-10 10:54:19	ga_ls8c_ard_3-2-1_106071_2023-02-10_final
2023-02-10 10:55:31	ga_ls8c_ard_3-2-1_106074_2023-02-10_final
2023-02-10 10:57:55	ga_ls8c_ard_3-2-1_106080_2023-02-10_final
2023-02-11 09:57:53	ga_ls8c_ard_3-2-1_097069_2023-02-11_final
2023-02-14 10:30:21	ga_ls8c_ard_3-2-1_102073_2023-02-14_final
2023-02-15 09:39:30	ga_ls8c_ard_3-2-1_093085_2023-02-15_final
2023-02-17 09:27:06	ga_ls8c_ard_3-2-1_091085_2023-02-16_final
2023-02-20 11:36:02	ga_ls8c_ard_3-2-1_112083_2023-02-20_final
2023-02-24 09:29:08	ga_ls8c_ard_3-2-1_092075_2023-02-23_final
2023-02-24 09:34:19	ga_ls8c_ard_3-2-1_092088_2023-02-24_final
2023-02-26 09:17:33	ga_ls8c_ard_3-2-1_090077_2023-02-25_final
2023-03-01 09:46:28	ga_ls8c_ard_3-2-1_095072_2023-03-01_final
2023-03-03 11:12:58	ga_ls8c_ard_3-2-1_109072_2023-03-03_final
2023-03-04 10:18:56	ga_ls8c_ard_3-2-1_100076_2023-03-04_final
2023-03-05 09:28:30	ga_ls8c_ard_3-2-1_091089_2023-03-04_final
2023-03-12 11:11:07	ga_ls8c_ard_3-2-1_108083_2023-03-12_final
2023-03-13 10:13:53	ga_ls8c_ard_3-2-1_099079_2023-03-13_final
2023-03-23 09:15:57	ga_ls8c_ard_3-2-1_089089_2023-03-22_final
2023-03-26 09:40:27	ga_ls8c_ard_3-2-1_094073_2023-03-26_final
2023-03-28 11:07:22	ga_ls8c_ard_3-2-1_108074_2023-03-28_final
2023-03-31 09:58:09	ga_ls8c_ard_3-2-1_097071_2023-03-31_final
2023-03-31 10:03:44	ga_ls8c_ard_3-2-1_097085_2023-03-31_final
2023-04-06 09:22:58	ga_ls8c_ard_3-2-1_091076_2023-04-05_final
2023-04-06 10:59:27	ga_ls8c_ard_3-2-1_107070_2023-04-06_final
2023-04-06 11:01:51	ga_ls8c_ard_3-2-1_107076_2023-04-06_final
2023-04-08 09:14:09	ga_ls8c_ard_3-2-1_089085_2023-04-07_final
2023-04-09 11:35:04	ga_ls8c_ard_3-2-1_112082_2023-04-09_final
2023-04-11 11:19:04	ga_ls8c_ard_3-2-1_110073_2023-04-11_final
2023-04-18 11:24:49	ga_ls8c_ard_3-2-1_111072_2023-04-18_final
2023-04-18 11:25:37	ga_ls8c_ard_3-2-1_111074_2023-04-18_final
2023-04-24 10:48:31	ga_ls8c_ard_3-2-1_105074_2023-04-24_final
2023-04-25 11:31:23	ga_ls8c_ard_3-2-1_112073_2023-04-25_final
2023-04-30 10:09:25	ga_ls8c_ard_3-2-1_099069_2023-04-30_final
2023-04-30 10:13:24	ga_ls8c_ard_3-2-1_099079_2023-04-30_final
2023-05-04 09:46:15	ga_ls8c_ard_3-2-1_095073_2023-05-04_final
2023-05-07 10:19:06	ga_ls8c_ard_3-2-1_100078_2023-05-07_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-10 10:51:08	ga_ls8c_ard_3-2-1_105081_2023-05-10_final
2023-05-14 10:27:09	ga_ls8c_ard_3-2-1_101083_2023-05-14_final
2023-05-15 09:29:56	ga_ls8c_ard_3-2-1_092079_2023-05-14_final
2023-05-16 10:08:48	ga_ls8c_ard_3-2-1_099068_2023-05-16_final
2023-05-16 10:09:36	ga_ls8c_ard_3-2-1_099070_2023-05-16_final
2023-05-18 10:03:12	ga_ls8c_ard_3-2-1_097085_2023-05-18_final
2023-05-24 09:26:34	ga_ls8c_ard_3-2-1_091086_2023-05-23_final
2023-05-24 11:01:04	ga_ls8c_ard_3-2-1_107075_2023-05-24_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