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
2022-01-14 10:06:46	ga_ls8c_ard_3-2-1_098076_2022-01-14_final
2022-11-22 09:20:02	ga_ls8c_ard_3-2-1_090082_2022-11-21_final
2022-11-30 11:45:59	ga_ls8c_ard_3-2-1_114076_2022-11-30_final
2022-12-01 10:52:22	ga_ls8c_ard_3-2-1_105081_2022-12-01_final
2022-12-02 09:58:44	ga_ls8c_ard_3-2-1_096086_2022-12-02_final
2022-12-04 11:20:04	ga_ls8c_ard_3-2-1_110073_2022-12-04_final
2022-12-04 11:23:39	ga_ls8c_ard_3-2-1_110082_2022-12-04_final
2022-12-06 09:33:12	ga_ls8c_ard_3-2-1_092084_2022-12-06_final
2022-12-07 10:12:04	ga_ls8c_ard_3-2-1_099073_2022-12-07_final
2022-12-08 09:19:38	ga_ls8c_ard_3-2-1_090081_2022-12-07_final
2022-12-09 10:01:42	ga_ls8c_ard_3-2-1_097078_2022-12-09_final
2022-12-09 10:04:30	ga_ls8c_ard_3-2-1_097085_2022-12-09_final
2022-12-15 09:25:22	ga_ls8c_ard_3-2-1_091080_2022-12-14_final
2022-12-18 09:53:02	ga_ls8c_ard_3-2-1_096072_2022-12-18_final
2022-12-19 10:39:28	ga_ls8c_ard_3-2-1_103080_2022-12-19_final
2022-12-20 11:24:19	ga_ls8c_ard_3-2-1_110084_2022-12-20_final
2022-12-21 10:26:17	ga_ls8c_ard_3-2-1_101078_2022-12-21_final
2022-12-24 09:22:40	ga_ls8c_ard_3-2-1_090089_2022-12-23_final
2022-12-26 10:42:25	ga_ls8c_ard_3-2-1_104072_2022-12-26_final
2022-12-29 09:35:15	ga_ls8c_ard_3-2-1_093074_2022-12-29_final
2022-12-31 09:25:41	ga_ls8c_ard_3-2-1_091081_2022-12-30_final
2022-12-31 09:26:53	ga_ls8c_ard_3-2-1_091084_2022-12-30_final
2022-12-31 09:28:53	ga_ls8c_ard_3-2-1_091089_2022-12-30_final
2022-12-31 11:02:35	ga_ls8c_ard_3-2-1_107076_2022-12-31_final
2022-12-31 11:05:46	ga_ls8c_ard_3-2-1_107084_2022-12-31_final
2023-01-01 11:45:50	ga_ls8c_ard_3-2-1_114076_2023-01-01_final
2023-01-02 09:14:32	ga_ls8c_ard_3-2-1_089084_2023-01-01_final
2023-01-06 10:28:17	ga_ls8c_ard_3-2-1_101083_2023-01-06_final
2023-01-10 09:59:57	ga_ls8c_ard_3-2-1_097074_2023-01-10_final
2023-01-11 10:41:12	ga_ls8c_ard_3-2-1_104069_2023-01-11_final
2023-01-14 09:36:46	ga_ls8c_ard_3-2-1_093078_2023-01-14_final
2023-01-14 11:14:51	ga_ls8c_ard_3-2-1_109076_2023-01-14_final
2023-01-16 09:26:46	ga_ls8c_ard_3-2-1_091084_2023-01-15_final
2023-01-20 10:34:33	ga_ls8c_ard_3-2-1_103068_2023-01-20_final
2023-01-21 09:45:44	ga_ls8c_ard_3-2-1_094085_2023-01-21_final
2023-01-22 10:24:13	ga_ls8c_ard_3-2-1_101073_2023-01-22_final
2023-01-23 11:05:54	ga_ls8c_ard_3-2-1_108069_2023-01-23_final
2023-01-26 10:04:19	ga_ls8c_ard_3-2-1_097085_2023-01-26_final
2023-01-26 11:40:25	ga_ls8c_ard_3-2-1_113078_2023-01-26_final
2023-01-31 10:18:53	ga_ls8c_ard_3-2-1_100075_2023-01-31_final
2023-02-07 10:27:50	ga_ls8c_ard_3-2-1_101082_2023-02-07_final
2023-02-08 09:29:25	ga_ls8c_ard_3-2-1_092075_2023-02-07_final
2023-02-08 09:35:00	ga_ls8c_ard_3-2-1_092089_2023-02-08_final
2023-02-11 09:59:53	ga_ls8c_ard_3-2-1_097074_2023-02-11_final
2023-02-13 09:50:41	ga_ls8c_ard_3-2-1_095082_2023-02-13_final
2023-02-14 10:33:56	ga_ls8c_ard_3-2-1_102082_2023-02-14_final
2023-02-15 09:40:42	ga_ls8c_ard_3-2-1_093088_2023-02-15_final
2023-02-16 10:21:57	ga_ls8c_ard_3-2-1_100083_2023-02-16_final
2023-02-16 10:22:21	ga_ls8c_ard_3-2-1_100084_2023-02-16_final
2023-02-17 09:25:31	ga_ls8c_ard_3-2-1_091081_2023-02-16_final
2023-02-22 09:44:20	ga_ls8c_ard_3-2-1_094082_2023-02-22_final
2023-02-24 11:11:13	ga_ls8c_ard_3-2-1_108083_2023-02-24_final
2023-02-25 11:52:03	ga_ls8c_ard_3-2-1_115077_2023-02-25_final
2023-03-03 11:16:58	ga_ls8c_ard_3-2-1_109082_2023-03-03_final
2023-03-04 10:21:44	ga_ls8c_ard_3-2-1_100083_2023-03-04_final
2023-03-05 11:03:23	ga_ls8c_ard_3-2-1_107079_2023-03-05_final
2023-03-06 11:45:26	ga_ls8c_ard_3-2-1_114076_2023-03-06_final
2023-03-07 10:51:48	ga_ls8c_ard_3-2-1_105081_2023-03-07_final
2023-03-13 10:15:53	ga_ls8c_ard_3-2-1_099084_2023-03-13_final
2023-03-16 10:40:23	ga_ls8c_ard_3-2-1_104068_2023-03-16_final
2023-03-22 10:06:48	ga_ls8c_ard_3-2-1_098077_2023-03-22_final
2023-03-26 09:45:14	ga_ls8c_ard_3-2-1_094085_2023-03-26_final
2023-03-26 11:19:20	ga_ls8c_ard_3-2-1_110073_2023-03-26_final
2023-03-27 10:22:55	ga_ls8c_ard_3-2-1_101071_2023-03-27_final
2023-03-29 11:52:37	ga_ls8c_ard_3-2-1_115079_2023-03-29_final
2023-03-30 10:57:47	ga_ls8c_ard_3-2-1_106081_2023-03-30_final
2023-04-02 09:46:10	ga_ls8c_ard_3-2-1_095072_2023-04-02_final
2023-04-04 09:35:22	ga_ls8c_ard_3-2-1_093076_2023-04-04_final
2023-04-04 09:39:45	ga_ls8c_ard_3-2-1_093087_2023-04-04_final
2023-04-06 09:26:33	ga_ls8c_ard_3-2-1_091085_2023-04-05_final
2023-04-08 09:12:57	ga_ls8c_ard_3-2-1_089082_2023-04-07_final
2023-04-09 11:35:52	ga_ls8c_ard_3-2-1_112084_2023-04-09_final
2023-04-13 11:10:42	ga_ls8c_ard_3-2-1_108083_2023-04-13_final
2023-04-16 10:00:42	ga_ls8c_ard_3-2-1_097078_2023-04-16_final
2023-04-18 11:24:25	ga_ls8c_ard_3-2-1_111071_2023-04-18_final
2023-04-21 10:16:49	ga_ls8c_ard_3-2-1_100072_2023-04-21_final
2023-04-24 10:48:07	ga_ls8c_ard_3-2-1_105073_2023-04-24_final
2023-04-25 09:56:53	ga_ls8c_ard_3-2-1_096084_2023-04-25_final
2023-04-28 10:25:23	ga_ls8c_ard_3-2-1_101078_2023-04-28_final
2023-04-29 11:10:38	ga_ls8c_ard_3-2-1_108083_2023-04-29_final
2023-04-30 10:15:00	ga_ls8c_ard_3-2-1_099083_2023-04-30_final
2023-04-30 11:52:17	ga_ls8c_ard_3-2-1_115079_2023-04-30_final
2023-05-02 09:57:50	ga_ls8c_ard_3-2-1_097071_2023-05-02_final
2023-05-02 10:01:25	ga_ls8c_ard_3-2-1_097080_2023-05-02_final
2023-05-06 09:39:02	ga_ls8c_ard_3-2-1_093086_2023-05-06_final
2023-05-06 11:11:56	ga_ls8c_ard_3-2-1_109071_2023-05-06_final
2023-05-08 09:22:39	ga_ls8c_ard_3-2-1_091076_2023-05-07_final
2023-05-09 11:46:23	ga_ls8c_ard_3-2-1_114080_2023-05-09_final
2023-05-10 10:45:57	ga_ls8c_ard_3-2-1_105068_2023-05-10_final
2023-05-12 10:33:33	ga_ls8c_ard_3-2-1_103068_2023-05-12_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-16 10:13:35	ga_ls8c_ard_3-2-1_099080_2023-05-16_final
2023-05-16 11:51:16	ga_ls8c_ard_3-2-1_115077_2023-05-16_final
2023-05-17 09:19:33	ga_ls8c_ard_3-2-1_090084_2023-05-16_final
2023-05-18 09:57:37	ga_ls8c_ard_3-2-1_097071_2023-05-18_final
2023-05-20 09:46:05	ga_ls8c_ard_3-2-1_095073_2023-05-20_final
2023-05-20 11:24:34	ga_ls8c_ard_3-2-1_111072_2023-05-20_final
2023-05-20 11:25:22	ga_ls8c_ard_3-2-1_111074_2023-05-20_final
2023-05-24 11:03:04	ga_ls8c_ard_3-2-1_107080_2023-05-24_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