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
2022-09-30 10:36:53	ga_ls8c_ard_3-2-1_103073_2022-09-30_final
2022-10-02 10:26:07	ga_ls8c_ard_3-2-1_101077_2022-10-02_final
2022-10-03 09:30:53	ga_ls8c_ard_3-2-1_092078_2022-10-03_final
2022-10-03 09:32:53	ga_ls8c_ard_3-2-1_092083_2022-10-03_final
2022-10-05 10:57:23	ga_ls8c_ard_3-2-1_106078_2022-10-05_final
2022-10-05 10:58:35	ga_ls8c_ard_3-2-1_106081_2022-10-05_final
2022-10-06 10:02:09	ga_ls8c_ard_3-2-1_097079_2022-10-06_final
2022-10-10 11:16:40	ga_ls8c_ard_3-2-1_109080_2022-10-10_final
2022-10-11 10:18:38	ga_ls8c_ard_3-2-1_100074_2022-10-11_final
2022-10-11 10:19:26	ga_ls8c_ard_3-2-1_100076_2022-10-11_final
2022-10-12 09:24:36	ga_ls8c_ard_3-2-1_091078_2022-10-11_final
2022-10-17 11:19:15	ga_ls8c_ard_3-2-1_110071_2022-10-17_final
2022-10-17 11:21:38	ga_ls8c_ard_3-2-1_110077_2022-10-17_final
2022-10-19 11:12:06	ga_ls8c_ard_3-2-1_108084_2022-10-19_final
2022-10-20 10:16:53	ga_ls8c_ard_3-2-1_099085_2022-10-20_final
2022-10-21 10:58:33	ga_ls8c_ard_3-2-1_106081_2022-10-21_final
2022-10-22 10:02:33	ga_ls8c_ard_3-2-1_097080_2022-10-22_final
2022-10-22 10:03:45	ga_ls8c_ard_3-2-1_097083_2022-10-22_final
2022-10-24 09:50:12	ga_ls8c_ard_3-2-1_095080_2022-10-24_final
2022-10-31 09:53:38	ga_ls8c_ard_3-2-1_096073_2022-10-31_final
2022-11-04 11:11:23	ga_ls8c_ard_3-2-1_108082_2022-11-04_final
2022-11-08 10:45:51	ga_ls8c_ard_3-2-1_104080_2022-11-08_final
2022-11-09 11:28:42	ga_ls8c_ard_3-2-1_111079_2022-11-09_final
2022-11-11 09:36:14	ga_ls8c_ard_3-2-1_093076_2022-11-11_final
2022-11-14 10:09:06	ga_ls8c_ard_3-2-1_098081_2022-11-14_final
2022-11-15 10:49:09	ga_ls8c_ard_3-2-1_105073_2022-11-15_final
2022-11-16 11:36:00	ga_ls8c_ard_3-2-1_112082_2022-11-16_final
2022-11-22 09:19:14	ga_ls8c_ard_3-2-1_090080_2022-11-21_final
2022-11-22 10:58:31	ga_ls8c_ard_3-2-1_106081_2022-11-22_final
2022-11-23 10:00:54	ga_ls8c_ard_3-2-1_097076_2022-11-23_final
2022-11-23 11:41:23	ga_ls8c_ard_3-2-1_113080_2022-11-23_final
2022-11-25 09:48:09	ga_ls8c_ard_3-2-1_095075_2022-11-25_final
2022-11-25 11:29:26	ga_ls8c_ard_3-2-1_111081_2022-11-25_final
2022-11-25 11:29:50	ga_ls8c_ard_3-2-1_111082_2022-11-25_final
2022-11-26 10:31:01	ga_ls8c_ard_3-2-1_102074_2022-11-26_final
2022-11-29 11:05:55	ga_ls8c_ard_3-2-1_107084_2022-11-29_final
2022-12-02 09:55:56	ga_ls8c_ard_3-2-1_096079_2022-12-02_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-06 09:30:25	ga_ls8c_ard_3-2-1_092077_2022-12-06_final
2022-12-06 09:32:01	ga_ls8c_ard_3-2-1_092081_2022-12-06_final
2022-12-07 11:52:33	ga_ls8c_ard_3-2-1_115077_2022-12-07_final
2022-12-09 09:59:42	ga_ls8c_ard_3-2-1_097073_2022-12-09_final
2022-12-09 10:02:54	ga_ls8c_ard_3-2-1_097081_2022-12-09_final
2022-12-10 10:42:34	ga_ls8c_ard_3-2-1_104072_2022-12-10_final
2022-12-10 10:44:33	ga_ls8c_ard_3-2-1_104077_2022-12-10_final
2022-12-13 09:36:33	ga_ls8c_ard_3-2-1_093077_2022-12-13_final
2022-12-13 11:16:14	ga_ls8c_ard_3-2-1_109079_2022-12-13_final
2022-12-13 11:16:38	ga_ls8c_ard_3-2-1_109080_2022-12-13_final
2022-12-15 11:01:03	ga_ls8c_ard_3-2-1_107072_2022-12-15_final
2022-12-16 10:06:13	ga_ls8c_ard_3-2-1_098074_2022-12-16_final
2022-12-16 11:46:18	ga_ls8c_ard_3-2-1_114077_2022-12-16_final
2022-12-17 09:12:59	ga_ls8c_ard_3-2-1_089080_2022-12-16_final
2022-12-18 09:57:25	ga_ls8c_ard_3-2-1_096083_2022-12-18_final
2022-12-19 10:38:40	ga_ls8c_ard_3-2-1_103078_2022-12-19_final
2022-12-19 10:40:16	ga_ls8c_ard_3-2-1_103082_2022-12-19_final
2022-12-20 09:42:38	ga_ls8c_ard_3-2-1_094077_2022-12-20_final
2022-12-21 10:25:05	ga_ls8c_ard_3-2-1_101075_2022-12-21_final
2022-12-22 11:11:55	ga_ls8c_ard_3-2-1_108084_2022-12-22_final
2022-12-25 11:39:38	ga_ls8c_ard_3-2-1_113076_2022-12-25_final
2022-12-30 10:20:31	ga_ls8c_ard_3-2-1_100079_2022-12-30_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
2023-01-01 11:46:38	ga_ls8c_ard_3-2-1_114078_2023-01-01_final
2023-01-05 09:45:02	ga_ls8c_ard_3-2-1_094083_2023-01-05_final
2023-01-05 11:21:31	ga_ls8c_ard_3-2-1_110077_2023-01-05_final
2023-01-07 11:09:57	ga_ls8c_ard_3-2-1_108079_2023-01-07_final
2023-01-08 11:52:24	ga_ls8c_ard_3-2-1_115077_2023-01-08_final
2023-01-09 10:58:46	ga_ls8c_ard_3-2-1_106082_2023-01-09_final
2023-01-11 10:41:36	ga_ls8c_ard_3-2-1_104070_2023-01-11_final
2023-01-14 09:38:46	ga_ls8c_ard_3-2-1_093083_2023-01-14_final
2023-01-16 09:25:34	ga_ls8c_ard_3-2-1_091081_2023-01-15_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-19 09:56:52	ga_ls8c_ard_3-2-1_096082_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
2023-01-21 11:23:49	ga_ls8c_ard_3-2-1_110083_2023-01-21_final
2023-01-23 09:31:48	ga_ls8c_ard_3-2-1_092081_2023-01-23_final
2023-01-23 11:09:53	ga_ls8c_ard_3-2-1_108079_2023-01-23_final
2023-01-26 10:02:19	ga_ls8c_ard_3-2-1_097080_2023-01-26_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-02-07 10:23:51	ga_ls8c_ard_3-2-1_101072_2023-02-07_final
2023-02-07 10:27:26	ga_ls8c_ard_3-2-1_101081_2023-02-07_final
2023-02-08 09:33:00	ga_ls8c_ard_3-2-1_092084_2023-02-08_final
2023-02-08 09:33:48	ga_ls8c_ard_3-2-1_092086_2023-02-08_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-11 11:39:10	ga_ls8c_ard_3-2-1_113075_2023-02-11_final
2023-02-11 11:41:09	ga_ls8c_ard_3-2-1_113080_2023-02-11_final
2023-02-13 09:51:29	ga_ls8c_ard_3-2-1_095084_2023-02-13_final
2023-02-13 11:27:58	ga_ls8c_ard_3-2-1_111078_2023-02-13_final
2023-02-13 11:29:58	ga_ls8c_ard_3-2-1_111083_2023-02-13_final
2023-02-15 09:35:54	ga_ls8c_ard_3-2-1_093076_2023-02-15_final
2023-02-15 09:38:42	ga_ls8c_ard_3-2-1_093083_2023-02-15_final
2023-02-21 10:35:12	ga_ls8c_ard_3-2-1_103070_2023-02-21_final
2023-02-23 10:27:11	ga_ls8c_ard_3-2-1_101081_2023-02-23_final
2023-02-24 09:31:56	ga_ls8c_ard_3-2-1_092082_2023-02-24_final
2023-02-26 10:58:02	ga_ls8c_ard_3-2-1_106081_2023-02-26_final
2023-03-01 11:29:44	ga_ls8c_ard_3-2-1_111083_2023-03-01_final
2023-03-06 11:44:38	ga_ls8c_ard_3-2-1_114074_2023-03-06_final
2023-03-06 11:46:14	ga_ls8c_ard_3-2-1_114078_2023-03-06_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