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
2022-11-03 10:24:08	ga_ls8c_ard_3-2-1_101072_2022-11-03_final
2022-11-04 09:31:18	ga_ls8c_ard_3-2-1_092079_2022-11-04_final
2022-11-04 09:32:30	ga_ls8c_ard_3-2-1_092082_2022-11-04_final
2022-11-06 10:57:25	ga_ls8c_ard_3-2-1_106078_2022-11-06_final
2022-11-07 10:02:35	ga_ls8c_ard_3-2-1_097080_2022-11-07_final
2022-11-07 10:02:59	ga_ls8c_ard_3-2-1_097081_2022-11-07_final
2022-11-08 09:07:45	ga_ls8c_ard_3-2-1_088082_2022-11-07_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-11 11:13:08	ga_ls8c_ard_3-2-1_109071_2022-11-11_final
2022-11-14 10:06:42	ga_ls8c_ard_3-2-1_098075_2022-11-14_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-16 09:56:19	ga_ls8c_ard_3-2-1_096080_2022-11-16_final
2022-11-17 10:38:22	ga_ls8c_ard_3-2-1_103077_2022-11-17_final
2022-11-18 09:43:32	ga_ls8c_ard_3-2-1_094079_2022-11-18_final
2022-11-23 10:02:30	ga_ls8c_ard_3-2-1_097080_2022-11-23_final
2022-11-27 11:17:05	ga_ls8c_ard_3-2-1_109081_2022-11-27_final
2022-11-29 11:01:08	ga_ls8c_ard_3-2-1_107072_2022-11-29_final
2022-11-30 10:07:30	ga_ls8c_ard_3-2-1_098077_2022-11-30_final
2022-12-01 10:48:22	ga_ls8c_ard_3-2-1_105071_2022-12-01_final
2022-12-05 10:25:38	ga_ls8c_ard_3-2-1_101076_2022-12-05_final
2022-12-05 10:26:26	ga_ls8c_ard_3-2-1_101078_2022-12-05_final
2022-12-06 09:30:49	ga_ls8c_ard_3-2-1_092078_2022-12-06_final
2022-12-09 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-12-09_final
2022-12-09 10:00:06	ga_ls8c_ard_3-2-1_097074_2022-12-09_final
2022-12-09 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-12-09_final
2022-12-10 10:45:45	ga_ls8c_ard_3-2-1_104080_2022-12-10_final
2022-12-13 09:38:09	ga_ls8c_ard_3-2-1_093081_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-14 10:21:00	ga_ls8c_ard_3-2-1_100080_2022-12-14_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-18 09:52:38	ga_ls8c_ard_3-2-1_096071_2022-12-18_final
2022-12-19 10:35:53	ga_ls8c_ard_3-2-1_103071_2022-12-19_final
2022-12-19 10:38:40	ga_ls8c_ard_3-2-1_103078_2022-12-19_final
2022-12-24 09:20:40	ga_ls8c_ard_3-2-1_090084_2022-12-23_final
2022-12-25 09:59:57	ga_ls8c_ard_3-2-1_097074_2022-12-25_final
2022-12-25 11:42:02	ga_ls8c_ard_3-2-1_113082_2022-12-25_final
2022-12-27 09:52:00	ga_ls8c_ard_3-2-1_095085_2022-12-27_final
2022-12-31 11:04:58	ga_ls8c_ard_3-2-1_107082_2022-12-31_final
2023-01-01 10:07:21	ga_ls8c_ard_3-2-1_098077_2023-01-01_final
2023-01-05 09:46:37	ga_ls8c_ard_3-2-1_094087_2023-01-05_final
2023-01-05 11:20:43	ga_ls8c_ard_3-2-1_110075_2023-01-05_final
2023-01-05 11:21:31	ga_ls8c_ard_3-2-1_110077_2023-01-05_final
2023-01-05 11:24:18	ga_ls8c_ard_3-2-1_110084_2023-01-05_final
2023-01-06 10:26:41	ga_ls8c_ard_3-2-1_101079_2023-01-06_final
2023-01-07 09:30:16	ga_ls8c_ard_3-2-1_092077_2023-01-07_final
2023-01-07 09:32:15	ga_ls8c_ard_3-2-1_092082_2023-01-07_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-08 10:12:43	ga_ls8c_ard_3-2-1_099075_2023-01-08_final
2023-01-09 10:58:22	ga_ls8c_ard_3-2-1_106081_2023-01-09_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-10 10:03:32	ga_ls8c_ard_3-2-1_097083_2023-01-10_final
2023-01-10 11:39:14	ga_ls8c_ard_3-2-1_113075_2023-01-10_final
2023-01-11 10:41:36	ga_ls8c_ard_3-2-1_104070_2023-01-11_final
2023-01-12 09:47:34	ga_ls8c_ard_3-2-1_095074_2023-01-12_final
2023-01-12 11:27:15	ga_ls8c_ard_3-2-1_111076_2023-01-12_final
2023-01-14 09:37:58	ga_ls8c_ard_3-2-1_093081_2023-01-14_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-14 09:40:22	ga_ls8c_ard_3-2-1_093087_2023-01-14_final
2023-01-17 11:46:30	ga_ls8c_ard_3-2-1_114078_2023-01-17_final
2023-01-19 09:55:40	ga_ls8c_ard_3-2-1_096079_2023-01-19_final
2023-01-19 09:56:04	ga_ls8c_ard_3-2-1_096080_2023-01-19_final
2023-01-19 09:57:16	ga_ls8c_ard_3-2-1_096083_2023-01-19_final
2023-01-20 10:35:45	ga_ls8c_ard_3-2-1_103071_2023-01-20_final
2023-01-20 10:38:57	ga_ls8c_ard_3-2-1_103079_2023-01-20_final
2023-01-21 09:41:44	ga_ls8c_ard_3-2-1_094075_2023-01-21_final
2023-01-23 09:31:48	ga_ls8c_ard_3-2-1_092081_2023-01-23_final
2023-01-23 09:33:00	ga_ls8c_ard_3-2-1_092084_2023-01-23_final
2023-01-23 11:08:41	ga_ls8c_ard_3-2-1_108076_2023-01-23_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-25 09:18:39	ga_ls8c_ard_3-2-1_090079_2023-01-24_final
2023-01-25 09:19:03	ga_ls8c_ard_3-2-1_090080_2023-01-24_final
2023-01-26 10:03:07	ga_ls8c_ard_3-2-1_097082_2023-01-26_final
2023-02-08 09:32:13	ga_ls8c_ard_3-2-1_092082_2023-02-08_final
2023-02-08 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-02-08_final
2023-02-08 11:09:54	ga_ls8c_ard_3-2-1_108079_2023-02-08_final
2023-02-09 10:12:40	ga_ls8c_ard_3-2-1_099075_2023-02-09_final
2023-02-09 11:53:33	ga_ls8c_ard_3-2-1_115080_2023-02-09_final
2023-02-11 10:02:40	ga_ls8c_ard_3-2-1_097081_2023-02-11_final
2023-02-12 09:07:50	ga_ls8c_ard_3-2-1_088083_2023-02-11_final
2023-02-13 09:50:17	ga_ls8c_ard_3-2-1_095081_2023-02-13_final
2023-02-13 11:26:46	ga_ls8c_ard_3-2-1_111075_2023-02-13_final
2023-02-14 10:31:08	ga_ls8c_ard_3-2-1_102075_2023-02-14_final
2023-02-15 09:37:06	ga_ls8c_ard_3-2-1_093079_2023-02-15_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-15 09:39:54	ga_ls8c_ard_3-2-1_093086_2023-02-15_final
2023-02-17 09:24:43	ga_ls8c_ard_3-2-1_091079_2023-02-16_final
2023-02-17 11:01:12	ga_ls8c_ard_3-2-1_107073_2023-02-17_final
2023-02-21 10:37:36	ga_ls8c_ard_3-2-1_103076_2023-02-21_final
2023-02-22 09:45:08	ga_ls8c_ard_3-2-1_094084_2023-02-22_final
2023-02-24 09:34:43	ga_ls8c_ard_3-2-1_092089_2023-02-24_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-02-27 10:02:01	ga_ls8c_ard_3-2-1_097080_2023-02-27_final
2023-02-28 10:45:40	ga_ls8c_ard_3-2-1_104081_2023-02-28_final
2023-03-03 09:35:17	ga_ls8c_ard_3-2-1_093075_2023-03-03_final
2023-03-03 09:40:28	ga_ls8c_ard_3-2-1_093088_2023-03-03_final
2023-03-07 10:50:12	ga_ls8c_ard_3-2-1_105077_2023-03-07_final
2023-03-08 11:35:26	ga_ls8c_ard_3-2-1_112082_2023-03-08_final
2023-03-10 09:45:23	ga_ls8c_ard_3-2-1_094085_2023-03-10_final
2023-03-10 11:21:05	ga_ls8c_ard_3-2-1_110077_2023-03-10_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