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
2022-07-06 09:40:16	ga_ls8c_ard_3-2-1_093087_2022-07-06_final
2022-07-08 09:25:07	ga_ls8c_ard_3-2-1_091080_2022-07-07_final
2022-07-09 11:46:28	ga_ls8c_ard_3-2-1_114078_2022-07-09_final
2022-07-17 09:22:31	ga_ls8c_ard_3-2-1_090089_2022-07-16_final
2022-07-31 11:11:33	ga_ls8c_ard_3-2-1_108083_2022-07-31_final
2022-08-04 10:43:16	ga_ls8c_ard_3-2-1_104074_2022-08-04_final
2022-08-08 10:22:11	ga_ls8c_ard_3-2-1_100083_2022-08-08_final
2022-08-17 11:52:56	ga_ls8c_ard_3-2-1_115078_2022-08-17_final
2022-08-22 10:34:12	ga_ls8c_ard_3-2-1_102082_2022-08-22_final
2022-08-26 10:03:29	ga_ls8c_ard_3-2-1_098067_2022-08-26_final
2022-09-05 10:40:59	ga_ls8c_ard_3-2-1_104068_2022-09-05_final
2022-09-07 10:33:26	ga_ls8c_ard_3-2-1_102080_2022-09-07_final
2022-09-10 09:23:05	ga_ls8c_ard_3-2-1_091074_2022-09-09_final
2022-09-15 11:24:08	ga_ls8c_ard_3-2-1_110083_2022-09-15_final
2022-09-16 10:26:31	ga_ls8c_ard_3-2-1_101078_2022-09-16_final
2022-09-26 09:25:31	ga_ls8c_ard_3-2-1_091080_2022-09-25_final
2022-09-30 10:40:05	ga_ls8c_ard_3-2-1_103081_2022-09-30_final
2022-10-03 09:30:53	ga_ls8c_ard_3-2-1_092078_2022-10-03_final
2022-10-05 09:22:06	ga_ls8c_ard_3-2-1_090087_2022-10-04_final
2022-10-08 09:47:47	ga_ls8c_ard_3-2-1_095074_2022-10-08_final
2022-10-10 11:15:04	ga_ls8c_ard_3-2-1_109076_2022-10-10_final
2022-10-22 11:42:14	ga_ls8c_ard_3-2-1_113082_2022-10-22_final
2022-10-25 10:29:53	ga_ls8c_ard_3-2-1_102071_2022-10-25_final
2022-11-08 10:45:03	ga_ls8c_ard_3-2-1_104078_2022-11-08_final
2022-11-13 09:24:15	ga_ls8c_ard_3-2-1_091077_2022-11-12_final
2022-11-13 09:24:39	ga_ls8c_ard_3-2-1_091078_2022-11-12_final
2022-11-15 10:47:10	ga_ls8c_ard_3-2-1_105068_2022-11-15_final
2022-11-21 10:10:04	ga_ls8c_ard_3-2-1_099068_2022-11-21_final
2022-11-22 09:22:26	ga_ls8c_ard_3-2-1_090088_2022-11-21_final
2022-11-30 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-30_final
2022-11-30 11:47:35	ga_ls8c_ard_3-2-1_114080_2022-11-30_final
2022-12-06 11:06:06	ga_ls8c_ard_3-2-1_108069_2022-12-06_final
2022-12-06 11:11:41	ga_ls8c_ard_3-2-1_108083_2022-12-06_final
2022-12-12 10:31:47	ga_ls8c_ard_3-2-1_102076_2022-12-12_final
2022-12-19 10:40:16	ga_ls8c_ard_3-2-1_103082_2022-12-19_final
2022-12-26 09:07:32	ga_ls8c_ard_3-2-1_088082_2022-12-25_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2022-12-28 10:32:04	ga_ls8c_ard_3-2-1_102077_2022-12-28_final
2022-12-31 09:25:17	ga_ls8c_ard_3-2-1_091080_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2023-01-05 11:21:07	ga_ls8c_ard_3-2-1_110076_2023-01-05_final
2023-01-24 10:10:17	ga_ls8c_ard_3-2-1_099069_2023-01-24_final
2023-01-24 11:51:10	ga_ls8c_ard_3-2-1_115074_2023-01-24_final
2023-02-08 11:07:54	ga_ls8c_ard_3-2-1_108074_2023-02-08_final
2023-02-25 11:52:27	ga_ls8c_ard_3-2-1_115078_2023-02-25_final
2023-02-28 09:07:11	ga_ls8c_ard_3-2-1_088082_2023-02-27_final
2023-03-05 09:27:18	ga_ls8c_ard_3-2-1_091086_2023-03-04_final
2023-03-07 10:47:48	ga_ls8c_ard_3-2-1_105071_2023-03-07_final
2023-03-12 09:29:50	ga_ls8c_ard_3-2-1_092077_2023-03-11_final
2023-03-14 10:55:09	ga_ls8c_ard_3-2-1_106074_2023-03-14_final
2023-03-25 10:37:40	ga_ls8c_ard_3-2-1_103077_2023-03-25_final
2023-03-27 10:24:30	ga_ls8c_ard_3-2-1_101075_2023-03-27_final
2023-03-31 10:01:45	ga_ls8c_ard_3-2-1_097080_2023-03-31_final
2023-04-06 09:22:10	ga_ls8c_ard_3-2-1_091074_2023-04-05_final
2023-04-14 10:13:52	ga_ls8c_ard_3-2-1_099080_2023-04-14_final
2023-04-20 09:36:44	ga_ls8c_ard_3-2-1_093080_2023-04-20_final
2023-04-24 10:48:07	ga_ls8c_ard_3-2-1_105073_2023-04-24_final
2023-04-25 09:51:18	ga_ls8c_ard_3-2-1_096070_2023-04-25_final
2023-05-03 09:06:35	ga_ls8c_ard_3-2-1_088082_2023-05-02_final
2023-05-15 09:33:31	ga_ls8c_ard_3-2-1_092088_2023-05-15_final
2023-05-20 09:50:28	ga_ls8c_ard_3-2-1_095084_2023-05-20_final
2023-05-20 11:24:58	ga_ls8c_ard_3-2-1_111073_2023-05-20_final
2023-05-23 10:18:12	ga_ls8c_ard_3-2-1_100076_2023-05-23_final
2023-05-26 10:50:42	ga_ls8c_ard_3-2-1_105080_2023-05-26_final
2023-05-31 11:06:51	ga_ls8c_ard_3-2-1_108074_2023-05-31_final
2023-06-09 09:27:29	ga_ls8c_ard_3-2-1_091088_2023-06-08_final
2023-06-11 10:46:02	ga_ls8c_ard_3-2-1_105068_2023-06-11_final
2023-07-09 11:14:12	ga_ls8c_ard_3-2-1_109076_2023-07-09_final
2023-07-16 09:45:31	ga_ls8c_ard_3-2-1_094086_2023-07-16_final
2023-07-18 11:10:50	ga_ls8c_ard_3-2-1_108083_2023-07-18_final
2023-07-21 10:01:39	ga_ls8c_ard_3-2-1_097080_2023-07-21_final
2023-07-27 11:03:57	ga_ls8c_ard_3-2-1_107081_2023-07-27_final
2023-07-29 09:13:08	ga_ls8c_ard_3-2-1_089082_2023-07-28_final
2023-08-03 11:07:24	ga_ls8c_ard_3-2-1_108074_2023-08-03_final
2023-08-04 10:10:59	ga_ls8c_ard_3-2-1_099072_2023-08-04_final
2023-08-06 11:39:54	ga_ls8c_ard_3-2-1_113078_2023-08-06_final
2023-08-22 09:57:33	ga_ls8c_ard_3-2-1_097069_2023-08-22_final
2023-09-10 10:28:52	ga_ls8c_ard_3-2-1_102070_2023-09-10_final
2023-09-14 11:44:41	ga_ls8c_ard_3-2-1_114074_2023-09-14_final
2023-09-15 09:12:10	ga_ls8c_ard_3-2-1_089079_2023-09-14_final
2023-09-18 09:45:53	ga_ls8c_ard_3-2-1_094086_2023-09-18_final
2023-10-04 11:24:01	ga_ls8c_ard_3-2-1_110084_2023-10-04_final
2023-10-20 09:40:21	ga_ls8c_ard_3-2-1_094072_2023-10-20_final
2023-10-26 10:43:01	ga_ls8c_ard_3-2-1_104074_2023-10-26_final
2023-10-29 11:14:44	ga_ls8c_ard_3-2-1_109076_2023-10-29_final
2023-11-08 10:14:28	ga_ls8c_ard_3-2-1_099080_2023-11-08_final
2023-11-22 10:25:44	ga_ls8c_ard_3-2-1_101077_2023-11-22_final
2023-11-26 09:59:01	ga_ls8c_ard_3-2-1_097072_2023-11-26_final
2023-11-29 10:29:29	ga_ls8c_ard_3-2-1_102071_2023-11-29_final
2023-12-12 09:57:19	ga_ls8c_ard_3-2-1_097068_2023-12-12_final
2023-12-13 09:06:54	ga_ls8c_ard_3-2-1_088081_2023-12-12_final
2023-12-13 10:41:00	ga_ls8c_ard_3-2-1_104069_2023-12-13_final
2023-12-15 10:28:15	ga_ls8c_ard_3-2-1_102068_2023-12-15_final
2023-12-28 10:02:32	ga_ls8c_ard_3-2-1_097081_2023-12-28_final
2024-02-02 11:14:36	ga_ls8c_ard_3-2-1_109076_2024-02-02_final
2024-02-06 09:12:37	ga_ls8c_ard_3-2-1_089080_2024-02-05_final
2024-02-06 09:13:25	ga_ls8c_ard_3-2-1_089082_2024-02-05_final
2024-02-16 11:27:21	ga_ls8c_ard_3-2-1_111077_2024-02-16_final
2024-02-28 11:52:24	ga_ls8c_ard_3-2-1_115078_2024-02-28_final
2024-03-07 09:23:56	ga_ls8c_ard_3-2-1_091078_2024-03-06_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