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
2019-06-26 09:51:04	ga_ls8c_ard_3-1-0_095084_2019-06-26_final
2019-07-28 09:48:25	ga_ls8c_ard_3-1-0_095077_2019-07-28_final
2019-09-14 09:46:40	ga_ls8c_ard_3-1-0_095072_2019-09-14_final
2019-09-30 09:48:21	ga_ls8c_ard_3-1-0_095076_2019-09-30_final
2019-09-30 09:51:09	ga_ls8c_ard_3-1-0_095083_2019-09-30_final
2019-10-16 09:47:36	ga_ls8c_ard_3-1-0_095074_2019-10-16_final
2019-11-17 09:46:45	ga_ls8c_ard_3-1-0_095072_2019-11-17_final
2019-12-03 09:49:55	ga_ls8c_ard_3-1-0_095080_2019-12-03_final
2020-01-20 09:47:21	ga_ls8c_ard_3-1-0_095074_2020-01-20_final
2020-01-20 09:50:09	ga_ls8c_ard_3-1-0_095081_2020-01-20_final
2020-03-08 09:47:55	ga_ls8c_ard_3-1-0_095076_2020-03-08_final
2020-03-24 09:46:35	ga_ls8c_ard_3-1-0_095073_2020-03-24_final
2020-04-09 09:50:50	ga_ls8c_ard_3-1-0_095084_2020-04-09_final
2020-04-25 09:51:07	ga_ls8c_ard_3-1-0_095085_2020-04-25_final
2022-03-31 10:29:48	ga_ls8c_ard_3-2-1_102073_2022-03-31_final
2022-03-31 10:32:36	ga_ls8c_ard_3-2-1_102080_2022-03-31_final
2022-04-01 09:37:22	ga_ls8c_ard_3-2-1_093081_2022-04-01_final
2022-04-01 09:38:10	ga_ls8c_ard_3-2-1_093083_2022-04-01_final
2022-04-03 10:59:30	ga_ls8c_ard_3-2-1_107070_2022-04-03_final
2022-04-06 09:55:57	ga_ls8c_ard_3-2-1_096081_2022-04-06_final
2022-04-07 10:34:26	ga_ls8c_ard_3-2-1_103069_2022-04-07_final
2022-04-08 11:22:06	ga_ls8c_ard_3-2-1_110080_2022-04-08_final
2022-04-08 11:23:17	ga_ls8c_ard_3-2-1_110083_2022-04-08_final
2022-04-09 10:22:29	ga_ls8c_ard_3-2-1_101070_2022-04-09_final
2022-04-09 10:26:05	ga_ls8c_ard_3-2-1_101079_2022-04-09_final
2022-04-13 10:02:35	ga_ls8c_ard_3-2-1_097082_2022-04-13_final
2022-04-13 10:02:59	ga_ls8c_ard_3-2-1_097083_2022-04-13_final
2022-04-13 11:39:05	ga_ls8c_ard_3-2-1_113076_2022-04-13_final
2022-04-13 11:40:40	ga_ls8c_ard_3-2-1_113080_2022-04-13_final
2022-04-15 09:49:50	ga_ls8c_ard_3-2-1_095081_2022-04-15_final
2022-04-16 10:30:42	ga_ls8c_ard_3-2-1_102075_2022-04-16_final
2022-04-16 10:31:06	ga_ls8c_ard_3-2-1_102076_2022-04-16_final
2022-04-17 09:39:52	ga_ls8c_ard_3-2-1_093087_2022-04-17_final
2022-04-19 09:28:42	ga_ls8c_ard_3-2-1_091090_2022-04-18_final
2022-04-19 11:02:23	ga_ls8c_ard_3-2-1_107077_2022-04-19_final
2022-04-20 10:08:21	ga_ls8c_ard_3-2-1_098081_2022-04-20_final
2022-04-21 09:12:44	ga_ls8c_ard_3-2-1_089081_2022-04-20_final
2022-04-21 10:48:25	ga_ls8c_ard_3-2-1_105073_2022-04-21_final
2022-04-22 11:32:52	ga_ls8c_ard_3-2-1_112076_2022-04-22_final
2022-04-24 09:42:25	ga_ls8c_ard_3-2-1_094078_2022-04-24_final
2022-04-24 11:20:06	ga_ls8c_ard_3-2-1_110075_2022-04-24_final
2022-04-25 10:26:04	ga_ls8c_ard_3-2-1_101079_2022-04-25_final
2022-04-26 09:33:14	ga_ls8c_ard_3-2-1_092086_2022-04-26_final
2022-04-27 10:11:18	ga_ls8c_ard_3-2-1_099073_2022-04-27_final
2022-04-27 10:15:41	ga_ls8c_ard_3-2-1_099084_2022-04-27_final
2022-04-28 09:20:51	ga_ls8c_ard_3-2-1_090086_2022-04-27_final
2022-04-28 10:56:32	ga_ls8c_ard_3-2-1_106078_2022-04-28_final
2022-04-29 09:59:43	ga_ls8c_ard_3-2-1_097075_2022-04-29_final
2022-04-29 10:00:55	ga_ls8c_ard_3-2-1_097078_2022-04-29_final
2022-04-30 10:40:12	ga_ls8c_ard_3-2-1_104068_2022-04-30_final
2022-04-30 10:42:59	ga_ls8c_ard_3-2-1_104075_2022-04-30_final
2022-05-01 09:50:59	ga_ls8c_ard_3-2-1_095084_2022-05-01_final
2022-05-01 11:29:04	ga_ls8c_ard_3-2-1_111082_2022-05-01_final
2022-05-02 10:27:52	ga_ls8c_ard_3-2-1_102068_2022-05-02_final
2022-05-02 10:31:04	ga_ls8c_ard_3-2-1_102076_2022-05-02_final
2022-05-02 10:31:51	ga_ls8c_ard_3-2-1_102078_2022-05-02_final
2022-05-05 11:01:12	ga_ls8c_ard_3-2-1_107074_2022-05-05_final
2022-05-06 10:04:24	ga_ls8c_ard_3-2-1_098071_2022-05-06_final
2022-05-06 10:08:23	ga_ls8c_ard_3-2-1_098081_2022-05-06_final
2022-05-08 09:56:27	ga_ls8c_ard_3-2-1_096082_2022-05-08_final
2022-05-11 10:23:23	ga_ls8c_ard_3-2-1_101072_2022-05-11_final
2022-05-11 10:26:11	ga_ls8c_ard_3-2-1_101079_2022-05-11_final
2022-05-14 09:18:37	ga_ls8c_ard_3-2-1_090080_2022-05-13_final
2022-05-15 10:00:17	ga_ls8c_ard_3-2-1_097076_2022-05-15_final
2022-05-16 10:41:34	ga_ls8c_ard_3-2-1_104071_2022-05-16_final
2022-05-16 10:43:09	ga_ls8c_ard_3-2-1_104075_2022-05-16_final
2022-05-19 09:38:46	ga_ls8c_ard_3-2-1_093084_2022-05-19_final
2022-05-20 10:17:39	ga_ls8c_ard_3-2-1_100073_2022-05-20_final
2022-05-20 10:21:38	ga_ls8c_ard_3-2-1_100083_2022-05-20_final
2022-05-24 09:56:55	ga_ls8c_ard_3-2-1_096083_2022-05-24_final
2022-05-25 10:36:11	ga_ls8c_ard_3-2-1_103073_2022-05-25_final
2022-05-25 10:37:46	ga_ls8c_ard_3-2-1_103077_2022-05-25_final
2022-05-26 09:43:21	ga_ls8c_ard_3-2-1_094080_2022-05-26_final
2022-05-26 09:43:45	ga_ls8c_ard_3-2-1_094081_2022-05-26_final
2022-05-30 10:53:57	ga_ls8c_ard_3-2-1_106071_2022-05-30_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-06-01 09:06:43	ga_ls8c_ard_3-2-1_088081_2022-05-31_final
2022-06-01 10:40:49	ga_ls8c_ard_3-2-1_104069_2022-06-01_final
2022-06-01 10:42:01	ga_ls8c_ard_3-2-1_104072_2022-06-01_final
2022-06-02 11:29:17	ga_ls8c_ard_3-2-1_111082_2022-06-02_final
2022-06-04 11:11:46	ga_ls8c_ard_3-2-1_109069_2022-06-04_final
2022-06-04 11:14:58	ga_ls8c_ard_3-2-1_109077_2022-06-04_final
2022-06-04 11:16:33	ga_ls8c_ard_3-2-1_109081_2022-06-04_final
2022-06-05 10:20:57	ga_ls8c_ard_3-2-1_100081_2022-06-05_final
2022-06-06 09:25:20	ga_ls8c_ard_3-2-1_091081_2022-06-05_final
2022-06-07 11:47:06	ga_ls8c_ard_3-2-1_114080_2022-06-07_final
2022-06-08 09:14:12	ga_ls8c_ard_3-2-1_089084_2022-06-07_final
2022-06-13 09:30:00	ga_ls8c_ard_3-2-1_092077_2022-06-13_final
2022-06-13 09:31:12	ga_ls8c_ard_3-2-1_092080_2022-06-13_final
2022-06-13 09:31:36	ga_ls8c_ard_3-2-1_092081_2022-06-13_final
2022-06-13 11:06:54	ga_ls8c_ard_3-2-1_108072_2022-06-13_final
2022-06-15 10:56:33	ga_ls8c_ard_3-2-1_106077_2022-06-15_final
2022-06-15 10:58:57	ga_ls8c_ard_3-2-1_106083_2022-06-15_final
2022-06-17 10:43:01	ga_ls8c_ard_3-2-1_104074_2022-06-17_final
2022-06-17 10:43:25	ga_ls8c_ard_3-2-1_104075_2022-06-17_final
2022-06-18 09:51:23	ga_ls8c_ard_3-2-1_095084_2022-06-18_final
2022-06-20 09:35:27	ga_ls8c_ard_3-2-1_093075_2022-06-20_final
2022-06-20 09:38:14	ga_ls8c_ard_3-2-1_093082_2022-06-20_final
2022-06-20 09:39:02	ga_ls8c_ard_3-2-1_093084_2022-06-20_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