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
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-06 09:24:56	ga_ls8c_ard_3-2-1_091080_2022-06-05_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-17 09:06:31	ga_ls8c_ard_3-2-1_088080_2022-06-16_final
2022-06-17 10:40:37	ga_ls8c_ard_3-2-1_104068_2022-06-17_final
2022-07-04 11:25:32	ga_ls8c_ard_3-2-1_111072_2022-07-04_final
2022-07-06 09:39:28	ga_ls8c_ard_3-2-1_093085_2022-07-06_final
2022-07-08 09:25:55	ga_ls8c_ard_3-2-1_091082_2022-07-07_final
2022-07-08 11:05:36	ga_ls8c_ard_3-2-1_107084_2022-07-08_final
2022-07-09 10:07:59	ga_ls8c_ard_3-2-1_098079_2022-07-09_final
2022-07-13 09:45:14	ga_ls8c_ard_3-2-1_094084_2022-07-13_final
2022-07-16 10:09:45	ga_ls8c_ard_3-2-1_099068_2022-07-16_final
2022-07-16 10:14:32	ga_ls8c_ard_3-2-1_099080_2022-07-16_final
2022-07-26 10:52:09	ga_ls8c_ard_3-2-1_105081_2022-07-26_final
2022-08-01 10:16:20	ga_ls8c_ard_3-2-1_099084_2022-08-01_final
2022-08-16 09:31:35	ga_ls8c_ard_3-2-1_092080_2022-08-16_final
2022-08-17 10:14:51	ga_ls8c_ard_3-2-1_099080_2022-08-17_final
2022-08-19 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-08-19_final
2022-08-21 11:25:49	ga_ls8c_ard_3-2-1_111072_2022-08-21_final
2022-08-25 09:27:24	ga_ls8c_ard_3-2-1_091085_2022-08-24_final
2022-08-25 09:28:36	ga_ls8c_ard_3-2-1_091088_2022-08-24_final
2022-09-03 09:21:13	ga_ls8c_ard_3-2-1_090085_2022-09-02_final
2022-09-14 10:37:40	ga_ls8c_ard_3-2-1_103075_2022-09-14_final
2022-09-17 09:32:29	ga_ls8c_ard_3-2-1_092082_2022-09-17_final
2022-09-17 11:12:10	ga_ls8c_ard_3-2-1_108084_2022-09-17_final
2022-09-19 10:54:14	ga_ls8c_ard_3-2-1_106070_2022-09-19_final
2022-09-24 11:13:11	ga_ls8c_ard_3-2-1_109071_2022-09-24_final
2022-09-30 10:35:17	ga_ls8c_ard_3-2-1_103069_2022-09-30_final
2022-10-01 11:20:56	ga_ls8c_ard_3-2-1_110075_2022-10-01_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-24 09:47:48	ga_ls8c_ard_3-2-1_095074_2022-10-24_final
2022-10-29 10:05:35	ga_ls8c_ard_3-2-1_098072_2022-10-29_final
2022-10-30 10:48:51	ga_ls8c_ard_3-2-1_105072_2022-10-30_final
2022-11-07 10:01:47	ga_ls8c_ard_3-2-1_097078_2022-11-07_final
2022-11-08 10:43:03	ga_ls8c_ard_3-2-1_104073_2022-11-08_final
2022-11-18 11:19:13	ga_ls8c_ard_3-2-1_110071_2022-11-18_final
2022-12-04 11:18:52	ga_ls8c_ard_3-2-1_110070_2022-12-04_final
2022-12-06 11:08:54	ga_ls8c_ard_3-2-1_108076_2022-12-06_final
2022-12-09 09:58:30	ga_ls8c_ard_3-2-1_097070_2022-12-09_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2023-01-08 11:51:12	ga_ls8c_ard_3-2-1_115074_2023-01-08_final
2023-01-09 09:18:17	ga_ls8c_ard_3-2-1_090078_2023-01-08_final
2023-01-10 10:00:44	ga_ls8c_ard_3-2-1_097076_2023-01-10_final
2023-01-12 09:46:22	ga_ls8c_ard_3-2-1_095071_2023-01-12_final
2023-01-16 09:25:11	ga_ls8c_ard_3-2-1_091080_2023-01-15_final
2023-01-16 11:02:04	ga_ls8c_ard_3-2-1_107075_2023-01-16_final
2023-01-17 11:45:42	ga_ls8c_ard_3-2-1_114076_2023-01-17_final
2023-01-22 10:23:01	ga_ls8c_ard_3-2-1_101070_2023-01-22_final
2023-01-24 10:11:53	ga_ls8c_ard_3-2-1_099073_2023-01-24_final
2023-02-13 11:29:10	ga_ls8c_ard_3-2-1_111081_2023-02-13_final
2023-02-17 09:26:18	ga_ls8c_ard_3-2-1_091083_2023-02-16_final
2023-02-19 09:13:54	ga_ls8c_ard_3-2-1_089083_2023-02-18_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-02-27 11:41:18	ga_ls8c_ard_3-2-1_113081_2023-02-27_final
2023-03-05 11:02:11	ga_ls8c_ard_3-2-1_107076_2023-03-05_final
2023-03-08 11:35:50	ga_ls8c_ard_3-2-1_112083_2023-03-08_final
2023-03-10 11:23:52	ga_ls8c_ard_3-2-1_110084_2023-03-10_final
2023-03-14 09:22:15	ga_ls8c_ard_3-2-1_090089_2023-03-13_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-03-28 11:07:22	ga_ls8c_ard_3-2-1_108074_2023-03-28_final
2023-04-04 11:17:26	ga_ls8c_ard_3-2-1_109084_2023-04-04_final
2023-04-12 10:24:15	ga_ls8c_ard_3-2-1_101075_2023-04-12_final
2023-05-02 11:41:30	ga_ls8c_ard_3-2-1_113083_2023-05-02_final
2023-05-08 09:22:39	ga_ls8c_ard_3-2-1_091076_2023-05-07_final
2023-05-09 11:43:59	ga_ls8c_ard_3-2-1_114074_2023-05-09_final
2023-05-18 10:00:49	ga_ls8c_ard_3-2-1_097079_2023-05-18_final
2023-06-01 10:10:26	ga_ls8c_ard_3-2-1_099072_2023-06-01_final
2023-06-03 09:58:05	ga_ls8c_ard_3-2-1_097072_2023-06-03_final
2023-06-09 11:04:46	ga_ls8c_ard_3-2-1_107084_2023-06-09_final
2023-06-10 10:07:33	ga_ls8c_ard_3-2-1_098080_2023-06-10_final
2023-06-11 09:12:45	ga_ls8c_ard_3-2-1_089082_2023-06-10_final
2023-06-22 10:28:20	ga_ls8c_ard_3-2-1_102070_2023-06-22_final
2023-06-27 09:16:03	ga_ls8c_ard_3-2-1_089090_2023-06-26_final
2023-06-30 09:40:37	ga_ls8c_ard_3-2-1_094074_2023-06-30_final
2023-07-18 09:32:45	ga_ls8c_ard_3-2-1_092085_2023-07-18_final
2023-07-22 10:45:44	ga_ls8c_ard_3-2-1_104082_2023-07-22_final
2023-07-23 11:29:25	ga_ls8c_ard_3-2-1_111083_2023-07-23_final
2023-08-13 11:44:31	ga_ls8c_ard_3-2-1_114074_2023-08-13_final
2023-08-17 11:18:15	ga_ls8c_ard_3-2-1_110070_2023-08-17_final
2023-08-23 09:07:31	ga_ls8c_ard_3-2-1_088083_2023-08-22_final
2023-08-26 09:39:14	ga_ls8c_ard_3-2-1_093085_2023-08-26_final
2023-09-04 09:29:02	ga_ls8c_ard_3-2-1_092075_2023-09-03_final
2023-09-07 09:59:31	ga_ls8c_ard_3-2-1_097074_2023-09-07_final
2023-09-09 11:26:05	ga_ls8c_ard_3-2-1_111074_2023-09-09_final
2023-09-13 10:59:49	ga_ls8c_ard_3-2-1_107070_2023-09-13_final
2023-09-21 11:50:53	ga_ls8c_ard_3-2-1_115074_2023-09-21_final
2023-09-22 10:54:51	ga_ls8c_ard_3-2-1_106073_2023-09-22_final
2023-09-26 10:28:34	ga_ls8c_ard_3-2-1_102069_2023-09-26_final
2023-10-07 11:53:20	ga_ls8c_ard_3-2-1_115080_2023-10-07_final
2023-10-08 09:20:26	ga_ls8c_ard_3-2-1_090084_2023-10-07_final
2023-10-17 10:51:57	ga_ls8c_ard_3-2-1_105081_2023-10-17_final
2023-10-23 10:16:05	ga_ls8c_ard_3-2-1_099084_2023-10-23_final
2023-10-27 09:52:36	ga_ls8c_ard_3-2-1_095087_2023-10-27_final
2023-10-30 10:21:31	ga_ls8c_ard_3-2-1_100082_2023-10-30_final
2023-11-01 10:04:22	ga_ls8c_ard_3-2-1_098070_2023-11-01_final
2023-11-06 10:28:03	ga_ls8c_ard_3-2-1_101083_2023-11-06_final
2023-11-16 09:25:05	ga_ls8c_ard_3-2-1_091080_2023-11-15_final
2023-11-17 10:03:34	ga_ls8c_ard_3-2-1_098068_2023-11-17_final
2023-11-23 09:32:30	ga_ls8c_ard_3-2-1_092083_2023-11-23_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