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
2022-02-24 11:42:28	ga_ls8c_ard_3-2-1_113084_2022-02-24_final
2022-05-05 09:21:31	ga_ls8c_ard_3-2-1_091072_2022-05-04_final
2022-05-20 10:22:02	ga_ls8c_ard_3-2-1_100084_2022-05-20_final
2022-05-20 11:58:08	ga_ls8c_ard_3-2-1_116077_2022-05-20_final
2022-05-24 09:57:19	ga_ls8c_ard_3-2-1_096084_2022-05-24_final
2022-05-31 09:57:09	ga_ls8c_ard_3-2-1_097068_2022-05-31_final
2022-05-31 10:03:56	ga_ls8c_ard_3-2-1_097085_2022-05-31_final
2022-06-06 11:02:14	ga_ls8c_ard_3-2-1_107076_2022-06-06_final
2022-06-08 09:11:24	ga_ls8c_ard_3-2-1_089077_2022-06-07_final
2022-06-15 09:17:40	ga_ls8c_ard_3-2-1_090077_2022-06-14_final
2022-07-14 10:25:42	ga_ls8c_ard_3-2-1_101077_2022-07-14_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_2022-08-08_final
2022-08-09 11:02:15	ga_ls8c_ard_3-2-1_107075_2022-08-09_final
2022-08-16 09:34:46	ga_ls8c_ard_3-2-1_092088_2022-08-16_final
2022-08-17 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-08-17_final
2022-08-29 10:35:35	ga_ls8c_ard_3-2-1_103070_2022-08-29_final
2022-09-01 09:29:35	ga_ls8c_ard_3-2-1_092075_2022-08-31_final
2022-09-06 11:25:27	ga_ls8c_ard_3-2-1_111071_2022-09-06_final
2022-09-06 11:25:51	ga_ls8c_ard_3-2-1_111072_2022-09-06_final
2022-09-08 11:15:06	ga_ls8c_ard_3-2-1_109076_2022-09-08_final
2022-09-18 10:15:45	ga_ls8c_ard_3-2-1_099082_2022-09-18_final
2022-09-24 09:40:17	ga_ls8c_ard_3-2-1_093086_2022-09-24_final
2022-09-26 09:25:31	ga_ls8c_ard_3-2-1_091080_2022-09-25_final
2022-10-01 09:45:39	ga_ls8c_ard_3-2-1_094084_2022-10-01_final
2022-10-07 09:07:43	ga_ls8c_ard_3-2-1_088082_2022-10-06_final
2022-10-07 10:43:01	ga_ls8c_ard_3-2-1_104073_2022-10-07_final
2022-10-14 10:52:41	ga_ls8c_ard_3-2-1_105082_2022-10-14_final
2022-10-17 11:24:26	ga_ls8c_ard_3-2-1_110084_2022-10-17_final
2022-10-19 09:29:13	ga_ls8c_ard_3-2-1_092074_2022-10-18_final
2022-10-24 11:25:54	ga_ls8c_ard_3-2-1_111072_2022-10-24_final
2022-10-28 11:00:24	ga_ls8c_ard_3-2-1_107070_2022-10-28_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-11-03 10:23:44	ga_ls8c_ard_3-2-1_101071_2022-11-03_final
2022-11-05 10:10:58	ga_ls8c_ard_3-2-1_099070_2022-11-05_final
2022-11-06 09:21:20	ga_ls8c_ard_3-2-1_090085_2022-11-05_final
2022-11-14 10:05:06	ga_ls8c_ard_3-2-1_098071_2022-11-14_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-21 10:13:39	ga_ls8c_ard_3-2-1_099077_2022-11-21_final
2022-11-29 09:28:14	ga_ls8c_ard_3-2-1_091087_2022-11-28_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-20 09:41:26	ga_ls8c_ard_3-2-1_094074_2022-12-20_final
2022-12-31 09:26:29	ga_ls8c_ard_3-2-1_091083_2022-12-30_final
2023-01-04 10:35:52	ga_ls8c_ard_3-2-1_103071_2023-01-04_final
2023-01-07 11:06:21	ga_ls8c_ard_3-2-1_108070_2023-01-07_final
2023-01-09 09:22:17	ga_ls8c_ard_3-2-1_090088_2023-01-08_final
2023-01-18 09:16:23	ga_ls8c_ard_3-2-1_089089_2023-01-17_final
2023-01-21 09:43:20	ga_ls8c_ard_3-2-1_094079_2023-01-21_final
2023-01-26 11:41:13	ga_ls8c_ard_3-2-1_113080_2023-01-26_final
2023-02-22 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-02-22_final
2023-03-14 10:53:33	ga_ls8c_ard_3-2-1_106070_2023-03-14_final
2023-03-14 10:53:57	ga_ls8c_ard_3-2-1_106071_2023-03-14_final
2023-03-26 09:40:51	ga_ls8c_ard_3-2-1_094074_2023-03-26_final
2023-03-29 10:10:56	ga_ls8c_ard_3-2-1_099072_2023-03-29_final
2023-04-21 10:19:13	ga_ls8c_ard_3-2-1_100078_2023-04-21_final
2023-04-24 09:16:01	ga_ls8c_ard_3-2-1_089090_2023-04-23_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-13 11:22:47	ga_ls8c_ard_3-2-1_110083_2023-05-13_final
2023-05-15 09:27:08	ga_ls8c_ard_3-2-1_092072_2023-05-14_final
2023-05-15 11:06:49	ga_ls8c_ard_3-2-1_108074_2023-05-15_final
2023-05-20 11:24:58	ga_ls8c_ard_3-2-1_111073_2023-05-20_final
2023-06-05 11:23:03	ga_ls8c_ard_3-2-1_111068_2023-06-05_final
2023-06-16 11:07:00	ga_ls8c_ard_3-2-1_108074_2023-06-16_final
2023-07-07 09:52:04	ga_ls8c_ard_3-2-1_095087_2023-07-07_final
2023-07-18 09:30:45	ga_ls8c_ard_3-2-1_092080_2023-07-18_final
2023-07-22 10:42:09	ga_ls8c_ard_3-2-1_104073_2023-07-22_final
2023-08-09 10:29:55	ga_ls8c_ard_3-2-1_102073_2023-08-09_final
2023-08-20 10:10:18	ga_ls8c_ard_3-2-1_099070_2023-08-20_final
2023-09-13 09:22:31	ga_ls8c_ard_3-2-1_091074_2023-09-12_final
2023-09-22 10:52:51	ga_ls8c_ard_3-2-1_106068_2023-09-22_final
2023-09-29 09:23:24	ga_ls8c_ard_3-2-1_091076_2023-09-28_final
2023-09-29 09:26:36	ga_ls8c_ard_3-2-1_091084_2023-09-28_final
2023-10-01 09:16:38	ga_ls8c_ard_3-2-1_089090_2023-09-30_final
2023-10-17 09:14:16	ga_ls8c_ard_3-2-1_089084_2023-10-16_final
2023-10-21 10:27:37	ga_ls8c_ard_3-2-1_101082_2023-10-21_final
2023-10-31 09:28:41	ga_ls8c_ard_3-2-1_091089_2023-10-30_final
2023-11-19 09:53:37	ga_ls8c_ard_3-2-1_096074_2023-11-19_final
2023-12-02 09:25:28	ga_ls8c_ard_3-2-1_091081_2023-12-01_final
2023-12-04 09:12:16	ga_ls8c_ard_3-2-1_089079_2023-12-03_final
2023-12-07 09:41:06	ga_ls8c_ard_3-2-1_094074_2023-12-07_final
2023-12-09 09:27:59	ga_ls8c_ard_3-2-1_092072_2023-12-08_final
2023-12-09 09:33:10	ga_ls8c_ard_3-2-1_092085_2023-12-09_final
2023-12-12 09:58:07	ga_ls8c_ard_3-2-1_097070_2023-12-12_final
2023-12-23 11:19:19	ga_ls8c_ard_3-2-1_110072_2023-12-23_final
2023-12-27 09:21:17	ga_ls8c_ard_3-2-1_090086_2023-12-26_final
2023-12-27 09:23:17	ga_ls8c_ard_3-2-1_090091_2023-12-26_final
2024-01-03 10:59:52	ga_ls8c_ard_3-2-1_107070_2024-01-03_final
2024-01-04 10:05:01	ga_ls8c_ard_3-2-1_098072_2024-01-04_final
2024-01-10 09:33:10	ga_ls8c_ard_3-2-1_092085_2024-01-10_final
2024-02-04 11:01:51	ga_ls8c_ard_3-2-1_107075_2024-02-04_final
2024-02-09 09:45:31	ga_ls8c_ard_3-2-1_094085_2024-02-09_final
2024-02-13 09:21:11	ga_ls8c_ard_3-2-1_090086_2024-02-12_final
2024-02-13 09:23:10	ga_ls8c_ard_3-2-1_090091_2024-02-12_final
2024-02-22 10:48:40	ga_ls8c_ard_3-2-1_105073_2024-02-22_final
2024-02-29 09:17:29	ga_ls8c_ard_3-2-1_090077_2024-02-28_final
2024-03-14 11:11:22	ga_ls8c_ard_3-2-1_108084_2024-03-14_final
2024-03-15 11:51:26	ga_ls8c_ard_3-2-1_115076_2024-03-15_final
2024-03-16 09:20:30	ga_ls8c_ard_3-2-1_090085_2024-03-15_final
2024-03-17 09:56:58	ga_ls8c_ard_3-2-1_097068_2024-03-17_final
2024-03-19 11:25:52	ga_ls8c_ard_3-2-1_111074_2024-03-19_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