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
2022-05-15 11:40:22	ga_ls8c_ard_3-2-1_113079_2022-05-15_final
2022-05-16 10:42:21	ga_ls8c_ard_3-2-1_104073_2022-05-16_final
2022-05-24 11:35:24	ga_ls8c_ard_3-2-1_112082_2022-05-24_final
2022-05-26 11:22:38	ga_ls8c_ard_3-2-1_110081_2022-05-26_final
2022-06-06 09:26:56	ga_ls8c_ard_3-2-1_091085_2022-06-05_final
2022-06-07 11:46:18	ga_ls8c_ard_3-2-1_114078_2022-06-07_final
2022-06-08 10:47:06	ga_ls8c_ard_3-2-1_105069_2022-06-08_final
2022-06-09 09:52:41	ga_ls8c_ard_3-2-1_096072_2022-06-09_final
2022-06-20 09:35:51	ga_ls8c_ard_3-2-1_093076_2022-06-20_final
2022-07-15 09:32:28	ga_ls8c_ard_3-2-1_092083_2022-07-15_final
2022-07-16 10:12:08	ga_ls8c_ard_3-2-1_099074_2022-07-16_final
2022-07-22 09:35:33	ga_ls8c_ard_3-2-1_093075_2022-07-22_final
2022-07-28 10:38:37	ga_ls8c_ard_3-2-1_103078_2022-07-28_final
2022-07-29 09:41:01	ga_ls8c_ard_3-2-1_094073_2022-07-29_final
2022-07-29 09:43:25	ga_ls8c_ard_3-2-1_094079_2022-07-29_final
2022-08-01 10:12:21	ga_ls8c_ard_3-2-1_099074_2022-08-01_final
2022-08-03 11:39:41	ga_ls8c_ard_3-2-1_113076_2022-08-03_final
2022-08-09 09:24:10	ga_ls8c_ard_3-2-1_091077_2022-08-08_final
2022-08-16 09:32:47	ga_ls8c_ard_3-2-1_092083_2022-08-16_final
2022-08-20 09:08:04	ga_ls8c_ard_3-2-1_088083_2022-08-19_final
2022-08-23 11:12:16	ga_ls8c_ard_3-2-1_109069_2022-08-23_final
2022-09-01 11:08:04	ga_ls8c_ard_3-2-1_108074_2022-09-01_final
2022-09-15 09:46:50	ga_ls8c_ard_3-2-1_094087_2022-09-15_final
2022-09-19 09:19:44	ga_ls8c_ard_3-2-1_090081_2022-09-18_final
2022-09-24 09:39:53	ga_ls8c_ard_3-2-1_093085_2022-09-24_final
2022-10-08 11:25:28	ga_ls8c_ard_3-2-1_111071_2022-10-08_final
2022-10-17 09:43:33	ga_ls8c_ard_3-2-1_094079_2022-10-17_final
2022-11-04 11:12:11	ga_ls8c_ard_3-2-1_108084_2022-11-04_final
2022-11-06 09:20:32	ga_ls8c_ard_3-2-1_090083_2022-11-05_final
2022-11-15 09:13:04	ga_ls8c_ard_3-2-1_089080_2022-11-14_final
2022-11-18 11:20:49	ga_ls8c_ard_3-2-1_110075_2022-11-18_final
2022-11-20 11:10:52	ga_ls8c_ard_3-2-1_108081_2022-11-20_final
2022-11-22 10:58:55	ga_ls8c_ard_3-2-1_106082_2022-11-22_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-12 10:30:11	ga_ls8c_ard_3-2-1_102072_2022-12-12_final
2022-12-14 10:21:48	ga_ls8c_ard_3-2-1_100082_2022-12-14_final
2022-12-15 11:01:27	ga_ls8c_ard_3-2-1_107073_2022-12-15_final
2022-12-20 11:23:31	ga_ls8c_ard_3-2-1_110082_2022-12-20_final
2022-12-26 09:07:56	ga_ls8c_ard_3-2-1_088083_2022-12-25_final
2022-12-29 11:14:56	ga_ls8c_ard_3-2-1_109076_2022-12-29_final
2022-12-31 11:02:35	ga_ls8c_ard_3-2-1_107076_2022-12-31_final
2023-01-01 11:45:03	ga_ls8c_ard_3-2-1_114074_2023-01-01_final
2023-01-06 10:24:18	ga_ls8c_ard_3-2-1_101073_2023-01-06_final
2023-01-07 09:35:27	ga_ls8c_ard_3-2-1_092090_2023-01-07_final
2023-01-11 10:44:24	ga_ls8c_ard_3-2-1_104077_2023-01-11_final
2023-01-14 09:39:10	ga_ls8c_ard_3-2-1_093084_2023-01-14_final
2023-01-16 09:29:10	ga_ls8c_ard_3-2-1_091090_2023-01-15_final
2023-01-21 09:43:44	ga_ls8c_ard_3-2-1_094080_2023-01-21_final
2023-01-29 10:30:51	ga_ls8c_ard_3-2-1_102074_2023-01-29_final
2023-03-03 09:35:17	ga_ls8c_ard_3-2-1_093075_2023-03-03_final
2023-03-03 09:38:53	ga_ls8c_ard_3-2-1_093084_2023-03-03_final
2023-03-05 09:25:18	ga_ls8c_ard_3-2-1_091081_2023-03-04_final
2023-03-12 11:10:43	ga_ls8c_ard_3-2-1_108082_2023-03-12_final
2023-03-15 09:59:08	ga_ls8c_ard_3-2-1_097073_2023-03-15_final
2023-03-15 11:41:36	ga_ls8c_ard_3-2-1_113082_2023-03-15_final
2023-03-19 11:15:38	ga_ls8c_ard_3-2-1_109079_2023-03-19_final
2023-03-26 09:43:39	ga_ls8c_ard_3-2-1_094081_2023-03-26_final
2023-03-31 11:40:38	ga_ls8c_ard_3-2-1_113080_2023-03-31_final
2023-04-07 11:44:41	ga_ls8c_ard_3-2-1_114075_2023-04-07_final
2023-04-09 11:35:52	ga_ls8c_ard_3-2-1_112084_2023-04-09_final
2023-04-12 10:26:38	ga_ls8c_ard_3-2-1_101081_2023-04-12_final
2023-04-13 09:30:37	ga_ls8c_ard_3-2-1_092080_2023-04-13_final
2023-04-18 09:50:19	ga_ls8c_ard_3-2-1_095083_2023-04-18_final
2023-04-20 09:35:57	ga_ls8c_ard_3-2-1_093078_2023-04-20_final
2023-04-30 10:12:12	ga_ls8c_ard_3-2-1_099076_2023-04-30_final
2023-05-27 09:51:54	ga_ls8c_ard_3-2-1_096072_2023-05-27_final
2023-05-28 10:37:09	ga_ls8c_ard_3-2-1_103077_2023-05-28_final
2023-06-06 10:32:14	ga_ls8c_ard_3-2-1_102080_2023-06-06_final
2023-06-16 09:32:07	ga_ls8c_ard_3-2-1_092084_2023-06-16_final
2023-06-18 10:57:51	ga_ls8c_ard_3-2-1_106082_2023-06-18_final
2023-06-19 10:00:14	ga_ls8c_ard_3-2-1_097077_2023-06-19_final
2023-06-21 09:47:52	ga_ls8c_ard_3-2-1_095077_2023-06-21_final
2023-06-22 10:29:56	ga_ls8c_ard_3-2-1_102074_2023-06-22_final
2023-06-24 10:20:23	ga_ls8c_ard_3-2-1_100081_2023-06-24_final
2023-06-26 11:45:45	ga_ls8c_ard_3-2-1_114078_2023-06-26_final
2023-07-06 10:40:53	ga_ls8c_ard_3-2-1_104070_2023-07-06_final
2023-07-10 10:20:35	ga_ls8c_ard_3-2-1_100081_2023-07-10_final
2023-07-24 10:31:01	ga_ls8c_ard_3-2-1_102076_2023-07-24_final
2023-07-25 11:12:18	ga_ls8c_ard_3-2-1_109071_2023-07-25_final
2023-07-26 10:17:53	ga_ls8c_ard_3-2-1_100074_2023-07-26_final
2023-07-27 09:24:16	ga_ls8c_ard_3-2-1_091079_2023-07-26_final
2023-07-31 10:34:53	ga_ls8c_ard_3-2-1_103070_2023-07-31_final
2023-08-12 10:59:38	ga_ls8c_ard_3-2-1_107070_2023-08-12_final
2023-08-15 09:55:41	ga_ls8c_ard_3-2-1_096080_2023-08-15_final
2023-08-20 11:51:58	ga_ls8c_ard_3-2-1_115077_2023-08-20_final
2023-08-22 09:58:45	ga_ls8c_ard_3-2-1_097072_2023-08-22_final
2023-08-24 11:30:04	ga_ls8c_ard_3-2-1_111084_2023-08-24_final
2023-08-25 10:29:16	ga_ls8c_ard_3-2-1_102071_2023-08-25_final
2023-09-09 09:47:59	ga_ls8c_ard_3-2-1_095076_2023-09-09_final
2023-09-13 11:03:48	ga_ls8c_ard_3-2-1_107080_2023-09-13_final
2023-09-21 11:53:16	ga_ls8c_ard_3-2-1_115080_2023-09-21_final
2023-09-24 09:06:49	ga_ls8c_ard_3-2-1_088081_2023-09-23_final
2023-09-25 11:26:59	ga_ls8c_ard_3-2-1_111076_2023-09-25_final
2023-09-27 11:12:14	ga_ls8c_ard_3-2-1_109070_2023-09-27_final
2023-10-08 10:58:55	ga_ls8c_ard_3-2-1_106083_2023-10-08_final
2023-10-10 10:43:23	ga_ls8c_ard_3-2-1_104075_2023-10-10_final
2023-10-13 09:35:48	ga_ls8c_ard_3-2-1_093076_2023-10-13_final
2023-10-13 11:12:42	ga_ls8c_ard_3-2-1_109071_2023-10-13_final
2023-10-16 11:45:59	ga_ls8c_ard_3-2-1_114077_2023-10-16_final
2023-10-30 11:58:24	ga_ls8c_ard_3-2-1_116077_2023-10-30_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