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
2022-09-27 10:05:36	ga_ls8c_ard_3-2-1_098072_2022-09-27_final
2022-09-28 09:13:34	ga_ls8c_ard_3-2-1_089081_2022-09-27_final
2022-09-28 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-09-27_final
2022-10-01 09:44:51	ga_ls8c_ard_3-2-1_094082_2022-10-01_final
2022-10-01 09:46:03	ga_ls8c_ard_3-2-1_094085_2022-10-01_final
2022-10-03 11:08:10	ga_ls8c_ard_3-2-1_108074_2022-10-03_final
2022-10-06 09:58:58	ga_ls8c_ard_3-2-1_097071_2022-10-06_final
2022-10-09 10:29:50	ga_ls8c_ard_3-2-1_102071_2022-10-09_final
2022-10-12 09:24:12	ga_ls8c_ard_3-2-1_091077_2022-10-11_final
2022-10-17 09:45:33	ga_ls8c_ard_3-2-1_094084_2022-10-17_final
2022-10-19 09:34:24	ga_ls8c_ard_3-2-1_092087_2022-10-19_final
2022-10-20 10:12:06	ga_ls8c_ard_3-2-1_099073_2022-10-20_final
2022-10-26 09:35:28	ga_ls8c_ard_3-2-1_093074_2022-10-26_final
2022-10-29 11:45:16	ga_ls8c_ard_3-2-1_114074_2022-10-29_final
2022-10-29 11:47:16	ga_ls8c_ard_3-2-1_114079_2022-10-29_final
2022-10-30 09:12:45	ga_ls8c_ard_3-2-1_089079_2022-10-29_final
2022-10-30 09:14:45	ga_ls8c_ard_3-2-1_089084_2022-10-29_final
2022-10-31 09:53:14	ga_ls8c_ard_3-2-1_096072_2022-10-31_final
2022-10-31 09:56:01	ga_ls8c_ard_3-2-1_096079_2022-10-31_final
2022-11-02 11:20:09	ga_ls8c_ard_3-2-1_110073_2022-11-02_final
2022-11-02 11:21:21	ga_ls8c_ard_3-2-1_110076_2022-11-02_final
2022-11-02 11:21:45	ga_ls8c_ard_3-2-1_110077_2022-11-02_final
2022-11-04 09:34:06	ga_ls8c_ard_3-2-1_092086_2022-11-04_final
2022-11-11 09:35:26	ga_ls8c_ard_3-2-1_093074_2022-11-11_final
2022-11-15 09:14:16	ga_ls8c_ard_3-2-1_089083_2022-11-14_final
2022-11-16 09:53:55	ga_ls8c_ard_3-2-1_096074_2022-11-16_final
2022-11-16 09:57:31	ga_ls8c_ard_3-2-1_096083_2022-11-16_final
2022-11-16 09:58:42	ga_ls8c_ard_3-2-1_096086_2022-11-16_final
2022-11-18 09:45:31	ga_ls8c_ard_3-2-1_094084_2022-11-18_final
2022-11-18 09:46:43	ga_ls8c_ard_3-2-1_094087_2022-11-18_final
2022-11-20 11:11:40	ga_ls8c_ard_3-2-1_108083_2022-11-20_final
2022-11-22 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-11-21_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-25 11:25:26	ga_ls8c_ard_3-2-1_111071_2022-11-25_final
2022-11-27 11:17:52	ga_ls8c_ard_3-2-1_109083_2022-11-27_final
2022-11-29 09:27:02	ga_ls8c_ard_3-2-1_091084_2022-11-28_final
2022-11-30 10:08:18	ga_ls8c_ard_3-2-1_098079_2022-11-30_final
2022-11-30 11:46:23	ga_ls8c_ard_3-2-1_114077_2022-11-30_final
2022-12-01 10:52:46	ga_ls8c_ard_3-2-1_105082_2022-12-01_final
2022-12-02 11:32:26	ga_ls8c_ard_3-2-1_112073_2022-12-02_final
2022-12-06 09:31:13	ga_ls8c_ard_3-2-1_092079_2022-12-06_final
2022-12-06 11:08:06	ga_ls8c_ard_3-2-1_108074_2022-12-06_final
2022-12-06 11:10:54	ga_ls8c_ard_3-2-1_108081_2022-12-06_final
2022-12-09 09:59:18	ga_ls8c_ard_3-2-1_097072_2022-12-09_final
2022-12-10 10:41:22	ga_ls8c_ard_3-2-1_104069_2022-12-10_final
2022-12-10 10:41:46	ga_ls8c_ard_3-2-1_104070_2022-12-10_final
2022-12-11 09:48:08	ga_ls8c_ard_3-2-1_095075_2022-12-11_final
2022-12-12 10:30:11	ga_ls8c_ard_3-2-1_102072_2022-12-12_final
2022-12-13 11:13:26	ga_ls8c_ard_3-2-1_109072_2022-12-13_final
2022-12-13 11:14:14	ga_ls8c_ard_3-2-1_109074_2022-12-13_final
2022-12-15 09:28:57	ga_ls8c_ard_3-2-1_091089_2022-12-14_final
2022-12-15 11:04:39	ga_ls8c_ard_3-2-1_107081_2022-12-15_final
2022-12-18 09:52:38	ga_ls8c_ard_3-2-1_096071_2022-12-18_final
2022-12-18 11:36:18	ga_ls8c_ard_3-2-1_112083_2022-12-18_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-20 09:45:50	ga_ls8c_ard_3-2-1_094085_2022-12-20_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-22 09:33:26	ga_ls8c_ard_3-2-1_092085_2022-12-22_final
2022-12-29 09:39:15	ga_ls8c_ard_3-2-1_093084_2022-12-29_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2023-01-03 11:35:52	ga_ls8c_ard_3-2-1_112082_2023-01-03_final
2023-01-05 09:41:26	ga_ls8c_ard_3-2-1_094074_2023-01-05_final
2023-01-09 09:19:05	ga_ls8c_ard_3-2-1_090080_2023-01-08_final
2023-01-09 09:19:29	ga_ls8c_ard_3-2-1_090081_2023-01-08_final
2023-01-09 09:21:53	ga_ls8c_ard_3-2-1_090087_2023-01-08_final
2023-01-11 10:45:11	ga_ls8c_ard_3-2-1_104079_2023-01-11_final
2023-01-12 11:30:26	ga_ls8c_ard_3-2-1_111084_2023-01-12_final
2023-01-14 11:17:39	ga_ls8c_ard_3-2-1_109083_2023-01-14_final
2023-01-16 09:26:22	ga_ls8c_ard_3-2-1_091083_2023-01-15_final
2023-01-19 09:53:40	ga_ls8c_ard_3-2-1_096074_2023-01-19_final
2023-01-20 10:40:09	ga_ls8c_ard_3-2-1_103082_2023-01-20_final
2023-01-21 11:20:38	ga_ls8c_ard_3-2-1_110075_2023-01-21_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-26 10:01:56	ga_ls8c_ard_3-2-1_097079_2023-01-26_final
2023-01-26 11:42:24	ga_ls8c_ard_3-2-1_113083_2023-01-26_final
2023-01-30 11:14:06	ga_ls8c_ard_3-2-1_109074_2023-01-30_final
2023-01-31 10:18:53	ga_ls8c_ard_3-2-1_100075_2023-01-31_final
2023-01-31 10:19:17	ga_ls8c_ard_3-2-1_100076_2023-01-31_final
2023-02-06 09:44:35	ga_ls8c_ard_3-2-1_094082_2023-02-06_final
2023-02-06 11:20:16	ga_ls8c_ard_3-2-1_110074_2023-02-06_final
2023-02-06 11:21:28	ga_ls8c_ard_3-2-1_110077_2023-02-06_final
2023-02-11 09:59:53	ga_ls8c_ard_3-2-1_097074_2023-02-11_final
2023-02-11 10:01:29	ga_ls8c_ard_3-2-1_097078_2023-02-11_final
2023-02-15 09:33:55	ga_ls8c_ard_3-2-1_093071_2023-02-15_final
2023-02-18 10:08:21	ga_ls8c_ard_3-2-1_098080_2023-02-18_final
2023-02-19 09:12:43	ga_ls8c_ard_3-2-1_089080_2023-02-18_final
2023-02-19 09:15:06	ga_ls8c_ard_3-2-1_089086_2023-02-18_final
2023-02-19 09:16:42	ga_ls8c_ard_3-2-1_089090_2023-02-18_final
2023-02-19 10:52:23	ga_ls8c_ard_3-2-1_105082_2023-02-19_final
2023-02-24 09:33:55	ga_ls8c_ard_3-2-1_092087_2023-02-24_final
2023-02-25 11:52:51	ga_ls8c_ard_3-2-1_115079_2023-02-25_final
2023-02-26 09:21:09	ga_ls8c_ard_3-2-1_090086_2023-02-25_final
2023-03-01 09:50:27	ga_ls8c_ard_3-2-1_095082_2023-03-01_final
2023-03-03 09:35:17	ga_ls8c_ard_3-2-1_093075_2023-03-03_final
2023-03-05 09:24:54	ga_ls8c_ard_3-2-1_091080_2023-03-04_final
2023-03-06 10:05:45	ga_ls8c_ard_3-2-1_098074_2023-03-06_final
2023-03-06 10:08:09	ga_ls8c_ard_3-2-1_098080_2023-03-06_final
2023-03-06 11:45:26	ga_ls8c_ard_3-2-1_114076_2023-03-06_final
2023-03-10 09:44:11	ga_ls8c_ard_3-2-1_094082_2023-03-10_final
2023-03-12 09:29:26	ga_ls8c_ard_3-2-1_092076_2023-03-11_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