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 10:05:10	ga_ls8c_ard_3-2-1_098072_2022-01-14_final
2022-03-04 09:16:31	ga_ls8c_ard_3-2-1_089090_2022-03-03_final
2022-03-14 11:25:38	ga_ls8c_ard_3-2-1_111073_2022-03-14_final
2022-03-21 09:58:02	ga_ls8c_ard_3-2-1_096086_2022-03-21_final
2022-03-21 11:36:07	ga_ls8c_ard_3-2-1_112084_2022-03-21_final
2022-04-10 09:34:04	ga_ls8c_ard_3-2-1_092088_2022-04-10_final
2022-04-13 09:56:36	ga_ls8c_ard_3-2-1_097067_2022-04-13_final
2022-05-01 09:46:11	ga_ls8c_ard_3-2-1_095072_2022-05-01_final
2022-05-03 09:34:15	ga_ls8c_ard_3-2-1_093073_2022-05-03_final
2022-05-05 09:27:30	ga_ls8c_ard_3-2-1_091087_2022-05-04_final
2022-05-16 10:45:57	ga_ls8c_ard_3-2-1_104082_2022-05-16_final
2022-05-29 10:15:51	ga_ls8c_ard_3-2-1_099084_2022-05-29_final
2022-05-30 09:22:15	ga_ls8c_ard_3-2-1_090089_2022-05-29_final
2022-06-05 10:19:45	ga_ls8c_ard_3-2-1_100078_2022-06-05_final
2022-06-18 11:29:28	ga_ls8c_ard_3-2-1_111082_2022-06-18_final
2022-06-23 10:03:34	ga_ls8c_ard_3-2-1_098068_2022-06-23_final
2022-06-26 10:36:05	ga_ls8c_ard_3-2-1_103072_2022-06-26_final
2022-06-29 09:29:18	ga_ls8c_ard_3-2-1_092075_2022-06-28_final
2022-06-29 09:34:29	ga_ls8c_ard_3-2-1_092088_2022-06-29_final
2022-07-01 10:56:14	ga_ls8c_ard_3-2-1_106076_2022-07-01_final
2022-07-02 11:38:41	ga_ls8c_ard_3-2-1_113074_2022-07-02_final
2022-07-08 09:22:43	ga_ls8c_ard_3-2-1_091074_2022-07-07_final
2022-07-11 09:57:36	ga_ls8c_ard_3-2-1_096084_2022-07-11_final
2022-07-16 10:10:57	ga_ls8c_ard_3-2-1_099071_2022-07-16_final
2022-07-21 10:33:57	ga_ls8c_ard_3-2-1_102082_2022-07-21_final
2022-08-04 09:07:35	ga_ls8c_ard_3-2-1_088082_2022-08-03_final
2022-08-09 09:28:10	ga_ls8c_ard_3-2-1_091087_2022-08-08_final
2022-08-09 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-08-08_final
2022-08-12 11:32:46	ga_ls8c_ard_3-2-1_112074_2022-08-12_final
2022-08-17 11:51:44	ga_ls8c_ard_3-2-1_115075_2022-08-17_final
2022-08-19 09:57:42	ga_ls8c_ard_3-2-1_097068_2022-08-19_final
2022-08-27 10:47:09	ga_ls8c_ard_3-2-1_105068_2022-08-27_final
2022-09-01 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-09-01_final
2022-09-02 10:11:15	ga_ls8c_ard_3-2-1_099071_2022-09-02_final
2022-09-13 11:34:29	ga_ls8c_ard_3-2-1_112078_2022-09-13_final
2022-09-16 10:28:07	ga_ls8c_ard_3-2-1_101082_2022-09-16_final
2022-09-20 09:57:25	ga_ls8c_ard_3-2-1_097067_2022-09-20_final
2022-09-22 11:29:56	ga_ls8c_ard_3-2-1_111082_2022-09-22_final
2022-09-24 09:40:41	ga_ls8c_ard_3-2-1_093087_2022-09-24_final
2022-10-06 10:01:45	ga_ls8c_ard_3-2-1_097078_2022-10-06_final
2022-10-11 10:22:38	ga_ls8c_ard_3-2-1_100084_2022-10-11_final
2022-10-15 09:57:53	ga_ls8c_ard_3-2-1_096084_2022-10-15_final
2022-10-27 10:21:55	ga_ls8c_ard_3-2-1_100082_2022-10-27_final
2022-10-28 11:05:35	ga_ls8c_ard_3-2-1_107083_2022-10-28_final
2022-10-29 10:09:34	ga_ls8c_ard_3-2-1_098082_2022-10-29_final
2022-10-29 10:09:58	ga_ls8c_ard_3-2-1_098083_2022-10-29_final
2022-10-31 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-10-31_final
2022-11-16 11:36:24	ga_ls8c_ard_3-2-1_112083_2022-11-16_final
2022-11-18 09:40:44	ga_ls8c_ard_3-2-1_094072_2022-11-18_final
2022-11-22 09:21:38	ga_ls8c_ard_3-2-1_090086_2022-11-21_final
2022-11-23 10:04:06	ga_ls8c_ard_3-2-1_097084_2022-11-23_final
2022-11-24 09:06:53	ga_ls8c_ard_3-2-1_088080_2022-11-23_final
2022-11-29 11:02:19	ga_ls8c_ard_3-2-1_107075_2022-11-29_final
2022-12-03 10:36:24	ga_ls8c_ard_3-2-1_103072_2022-12-03_final
2022-12-07 10:11:17	ga_ls8c_ard_3-2-1_099071_2022-12-07_final
2022-12-08 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-12-07_final
2022-12-15 09:27:21	ga_ls8c_ard_3-2-1_091085_2022-12-14_final
2022-12-21 10:27:52	ga_ls8c_ard_3-2-1_101082_2022-12-21_final
2022-12-28 10:29:16	ga_ls8c_ard_3-2-1_102070_2022-12-28_final
2022-12-30 10:20:07	ga_ls8c_ard_3-2-1_100078_2022-12-30_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-08 10:11:07	ga_ls8c_ard_3-2-1_099071_2023-01-08_final
2023-01-15 10:19:37	ga_ls8c_ard_3-2-1_100077_2023-01-15_final
2023-01-18 10:49:41	ga_ls8c_ard_3-2-1_105075_2023-01-18_final
2023-01-21 11:19:50	ga_ls8c_ard_3-2-1_110073_2023-01-21_final
2023-01-25 09:22:15	ga_ls8c_ard_3-2-1_090088_2023-01-24_final
2023-02-02 10:07:19	ga_ls8c_ard_3-2-1_098077_2023-02-02_final
2023-02-24 11:07:37	ga_ls8c_ard_3-2-1_108074_2023-02-24_final
2023-03-07 09:12:07	ga_ls8c_ard_3-2-1_089079_2023-03-06_final
2023-03-08 09:52:10	ga_ls8c_ard_3-2-1_096071_2023-03-08_final
2023-03-14 09:21:51	ga_ls8c_ard_3-2-1_090088_2023-03-13_final
2023-03-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2023-03-18_final
2023-03-25 10:39:16	ga_ls8c_ard_3-2-1_103081_2023-03-25_final
2023-03-31 09:56:57	ga_ls8c_ard_3-2-1_097068_2023-03-31_final
2023-04-09 09:51:24	ga_ls8c_ard_3-2-1_096070_2023-04-09_final
2023-04-29 09:29:45	ga_ls8c_ard_3-2-1_092078_2023-04-28_final
2023-04-30 10:09:01	ga_ls8c_ard_3-2-1_099068_2023-04-30_final
2023-05-03 10:41:53	ga_ls8c_ard_3-2-1_104073_2023-05-03_final
2023-05-15 09:33:31	ga_ls8c_ard_3-2-1_092088_2023-05-15_final
2023-05-20 11:23:22	ga_ls8c_ard_3-2-1_111069_2023-05-20_final
2023-05-23 10:16:12	ga_ls8c_ard_3-2-1_100071_2023-05-23_final
2023-05-24 09:28:10	ga_ls8c_ard_3-2-1_091090_2023-05-23_final
2023-06-02 09:20:24	ga_ls8c_ard_3-2-1_090086_2023-06-01_final
2023-06-02 09:22:00	ga_ls8c_ard_3-2-1_090090_2023-06-01_final
2023-06-10 10:02:46	ga_ls8c_ard_3-2-1_098068_2023-06-10_final
2023-06-15 10:24:56	ga_ls8c_ard_3-2-1_101077_2023-06-15_final
2023-06-16 09:33:43	ga_ls8c_ard_3-2-1_092088_2023-06-16_final
2023-07-02 09:32:40	ga_ls8c_ard_3-2-1_092085_2023-07-02_final
2023-07-11 09:27:46	ga_ls8c_ard_3-2-1_091088_2023-07-10_final
2023-07-18 11:07:15	ga_ls8c_ard_3-2-1_108074_2023-07-18_final
2023-08-01 11:23:44	ga_ls8c_ard_3-2-1_110084_2023-08-01_final
2023-08-05 10:55:50	ga_ls8c_ard_3-2-1_106076_2023-08-05_final
2023-08-06 09:56:38	ga_ls8c_ard_3-2-1_097067_2023-08-06_final
2023-08-10 09:34:18	ga_ls8c_ard_3-2-1_093073_2023-08-10_final
2023-08-22 11:38:26	ga_ls8c_ard_3-2-1_113074_2023-08-22_final
2023-08-24 09:46:00	ga_ls8c_ard_3-2-1_095071_2023-08-24_final
2023-08-28 09:22:29	ga_ls8c_ard_3-2-1_091074_2023-08-27_final
2023-09-09 11:24:29	ga_ls8c_ard_3-2-1_111070_2023-09-09_final
2023-09-13 09:22:07	ga_ls8c_ard_3-2-1_091073_2023-09-12_final
2023-09-19 10:27:33	ga_ls8c_ard_3-2-1_101082_2023-09-19_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years