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
2019-11-14 12:31:38	ga_ls8c_ard_3-2-1_122067_2019-11-14_final
2019-12-15 10:09:02	ga_ls8c_ard_3-2-1_099066_2019-12-15_final
2019-12-19 08:11:00	ga_ls8c_ard_3-2-1_079080_2019-12-18_final
2021-03-31 12:37:14	ga_ls8c_ard_3-2-1_123067_2021-03-31_final
2022-01-14 10:05:10	ga_ls8c_ard_3-2-1_098072_2022-01-14_final
2022-01-28 11:57:31	ga_ls8c_ard_3-2-1_116075_2022-01-28_final
2022-03-10 10:08:43	ga_ls8c_ard_3-2-1_099066_2022-03-10_final
2022-04-02 11:57:07	ga_ls8c_ard_3-2-1_116075_2022-04-02_final
2022-11-04 09:33:18	ga_ls8c_ard_3-2-1_092084_2022-11-04_final
2022-11-10 10:29:28	ga_ls8c_ard_3-2-1_102070_2022-11-10_final
2022-11-29 11:00:44	ga_ls8c_ard_3-2-1_107071_2022-11-29_final
2022-12-02 11:36:49	ga_ls8c_ard_3-2-1_112084_2022-12-02_final
2022-12-15 11:00:15	ga_ls8c_ard_3-2-1_107070_2022-12-15_final
2022-12-17 10:49:52	ga_ls8c_ard_3-2-1_105075_2022-12-17_final
2022-12-20 09:41:02	ga_ls8c_ard_3-2-1_094073_2022-12-20_final
2022-12-24 09:21:28	ga_ls8c_ard_3-2-1_090086_2022-12-23_final
2022-12-26 09:07:32	ga_ls8c_ard_3-2-1_088082_2022-12-25_final
2022-12-29 11:14:08	ga_ls8c_ard_3-2-1_109074_2022-12-29_final
2023-01-09 10:53:59	ga_ls8c_ard_3-2-1_106070_2023-01-09_final
2023-01-12 09:52:45	ga_ls8c_ard_3-2-1_095087_2023-01-12_final
2023-01-14 11:13:40	ga_ls8c_ard_3-2-1_109073_2023-01-14_final
2023-01-15 10:22:25	ga_ls8c_ard_3-2-1_100084_2023-01-15_final
2023-01-17 10:03:38	ga_ls8c_ard_3-2-1_098068_2023-01-17_final
2023-01-30 11:13:19	ga_ls8c_ard_3-2-1_109072_2023-01-30_final
2023-02-01 11:00:33	ga_ls8c_ard_3-2-1_107071_2023-02-01_final
2023-02-02 10:10:31	ga_ls8c_ard_3-2-1_098085_2023-02-02_final
2023-02-08 11:08:18	ga_ls8c_ard_3-2-1_108075_2023-02-08_final
2023-02-11 09:59:05	ga_ls8c_ard_3-2-1_097072_2023-02-11_final
2023-03-01 09:52:27	ga_ls8c_ard_3-2-1_095087_2023-03-01_final
2023-03-01 11:24:33	ga_ls8c_ard_3-2-1_111070_2023-03-01_final
2023-03-03 09:40:05	ga_ls8c_ard_3-2-1_093087_2023-03-03_final
2023-03-08 09:58:09	ga_ls8c_ard_3-2-1_096086_2023-03-08_final
2023-03-13 11:53:10	ga_ls8c_ard_3-2-1_115080_2023-03-13_final
2023-03-21 09:23:10	ga_ls8c_ard_3-2-1_091076_2023-03-20_final
2023-03-22 10:07:12	ga_ls8c_ard_3-2-1_098078_2023-03-22_final
2023-03-23 10:46:27	ga_ls8c_ard_3-2-1_105068_2023-03-23_final
2023-03-24 09:52:01	ga_ls8c_ard_3-2-1_096071_2023-03-24_final
2023-03-30 09:17:18	ga_ls8c_ard_3-2-1_090077_2023-03-29_final
2023-04-07 10:03:48	ga_ls8c_ard_3-2-1_098070_2023-04-07_final
2023-04-07 10:04:36	ga_ls8c_ard_3-2-1_098072_2023-04-07_final
2023-04-08 09:15:44	ga_ls8c_ard_3-2-1_089089_2023-04-07_final
2023-04-08 10:45:51	ga_ls8c_ard_3-2-1_105067_2023-04-08_final
2023-04-09 09:57:47	ga_ls8c_ard_3-2-1_096086_2023-04-09_final
2023-04-10 10:35:25	ga_ls8c_ard_3-2-1_103072_2023-04-10_final
2023-04-29 11:07:02	ga_ls8c_ard_3-2-1_108074_2023-04-29_final
2023-05-01 10:55:27	ga_ls8c_ard_3-2-1_106076_2023-05-01_final
2023-05-08 09:27:27	ga_ls8c_ard_3-2-1_091088_2023-05-07_final
2023-05-14 10:24:46	ga_ls8c_ard_3-2-1_101077_2023-05-14_final
2023-05-16 10:08:24	ga_ls8c_ard_3-2-1_099067_2023-05-16_final
2023-05-18 11:41:42	ga_ls8c_ard_3-2-1_113084_2023-05-18_final
2023-06-01 10:14:49	ga_ls8c_ard_3-2-1_099083_2023-06-01_final
2023-06-05 11:28:38	ga_ls8c_ard_3-2-1_111082_2023-06-05_final
2023-06-15 10:24:56	ga_ls8c_ard_3-2-1_101077_2023-06-15_final
2023-07-01 10:26:17	ga_ls8c_ard_3-2-1_101080_2023-07-01_final
2023-07-01 10:26:41	ga_ls8c_ard_3-2-1_101081_2023-07-01_final
2023-07-03 10:15:33	ga_ls8c_ard_3-2-1_099084_2023-07-03_final
2023-07-03 11:52:02	ga_ls8c_ard_3-2-1_115078_2023-07-03_final
2023-07-09 09:40:07	ga_ls8c_ard_3-2-1_093088_2023-07-09_final
2023-07-13 10:49:30	ga_ls8c_ard_3-2-1_105076_2023-07-13_final
2023-07-16 11:18:49	ga_ls8c_ard_3-2-1_110072_2023-07-16_final
2023-07-23 11:24:13	ga_ls8c_ard_3-2-1_111070_2023-07-23_final
2023-08-04 10:08:35	ga_ls8c_ard_3-2-1_099066_2023-08-04_final
2023-08-26 11:14:31	ga_ls8c_ard_3-2-1_109076_2023-08-26_final
2023-09-01 10:35:50	ga_ls8c_ard_3-2-1_103072_2023-09-01_final
2023-09-06 09:22:39	ga_ls8c_ard_3-2-1_090090_2023-09-05_final
2023-09-21 11:53:16	ga_ls8c_ard_3-2-1_115080_2023-09-21_final
2023-09-23 09:57:38	ga_ls8c_ard_3-2-1_097069_2023-09-23_final
2023-09-23 11:38:31	ga_ls8c_ard_3-2-1_113074_2023-09-23_final
2023-10-02 11:36:23	ga_ls8c_ard_3-2-1_112084_2023-10-02_final
2023-10-19 10:39:35	ga_ls8c_ard_3-2-1_103081_2023-10-19_final
2023-10-25 09:57:22	ga_ls8c_ard_3-2-1_097068_2023-10-25_final
2023-10-25 09:57:46	ga_ls8c_ard_3-2-1_097069_2023-10-25_final
2023-11-06 10:27:40	ga_ls8c_ard_3-2-1_101082_2023-11-06_final
2023-11-08 11:53:21	ga_ls8c_ard_3-2-1_115080_2023-11-08_final
2023-11-09 09:22:49	ga_ls8c_ard_3-2-1_090090_2023-11-08_final
2023-11-23 09:29:19	ga_ls8c_ard_3-2-1_092075_2023-11-22_final
2023-11-24 10:10:35	ga_ls8c_ard_3-2-1_099070_2023-11-24_final
2023-11-26 09:58:37	ga_ls8c_ard_3-2-1_097071_2023-11-26_final
2023-11-30 11:13:56	ga_ls8c_ard_3-2-1_109074_2023-11-30_final
2023-12-03 11:44:47	ga_ls8c_ard_3-2-1_114074_2023-12-03_final
2023-12-04 09:13:51	ga_ls8c_ard_3-2-1_089083_2023-12-03_final
2023-12-13 10:40:36	ga_ls8c_ard_3-2-1_104068_2023-12-13_final
2023-12-17 10:17:30	ga_ls8c_ard_3-2-1_100072_2023-12-17_final
2023-12-17 11:57:35	ga_ls8c_ard_3-2-1_116075_2023-12-17_final
2023-12-17 11:57:59	ga_ls8c_ard_3-2-1_116076_2023-12-17_final
2023-12-23 11:20:07	ga_ls8c_ard_3-2-1_110074_2023-12-23_final
2023-12-25 11:07:45	ga_ls8c_ard_3-2-1_108074_2023-12-25_final
2023-12-27 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-12-26_final
2023-12-30 09:52:33	ga_ls8c_ard_3-2-1_095087_2023-12-30_final
2024-01-02 10:17:25	ga_ls8c_ard_3-2-1_100072_2024-01-02_final
2024-01-05 09:13:47	ga_ls8c_ard_3-2-1_089083_2024-01-04_final
2024-01-08 11:24:24	ga_ls8c_ard_3-2-1_110085_2024-01-08_final
2024-01-16 10:30:59	ga_ls8c_ard_3-2-1_102075_2024-01-16_final
2024-01-17 11:13:03	ga_ls8c_ard_3-2-1_109072_2024-01-17_final
2024-01-27 11:51:12	ga_ls8c_ard_3-2-1_115075_2024-01-27_final
2024-01-29 09:57:12	ga_ls8c_ard_3-2-1_097068_2024-01-29_final
2024-02-07 09:57:28	ga_ls8c_ard_3-2-1_096084_2024-02-07_final
2024-02-27 09:34:16	ga_ls8c_ard_3-2-1_092088_2024-02-27_final
2024-02-27 11:11:33	ga_ls8c_ard_3-2-1_108084_2024-02-27_final
2024-03-05 11:12:50	ga_ls8c_ard_3-2-1_109072_2024-03-05_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