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
2016-11-24 11:25:14	ga_ls8c_ard_3-0-0_111071_2016-11-24_final
2016-11-24 11:25:38	ga_ls8c_ard_3-0-0_111072_2016-11-24_final
2016-11-24 11:26:02	ga_ls8c_ard_3-0-0_111073_2016-11-24_final
2016-11-24 11:26:26	ga_ls8c_ard_3-1-0_111074_2016-11-24_final
2016-11-24 11:26:49	ga_ls8c_ard_3-0-0_111075_2016-11-24_final
2016-11-24 11:27:13	ga_ls8c_ard_3-0-0_111076_2016-11-24_final
2016-11-24 11:27:37	ga_ls8c_ard_3-0-0_111077_2016-11-24_final
2016-12-12 11:16:24	ga_ls8c_ard_3-0-0_109080_2016-12-12_final
2016-12-12 11:16:48	ga_ls8c_ard_3-0-0_109081_2016-12-12_final
2016-12-12 11:17:12	ga_ls8c_ard_3-0-0_109082_2016-12-12_final
2016-12-12 11:17:36	ga_ls8c_ard_3-0-0_109083_2016-12-12_final
2016-12-12 11:18:00	ga_ls8c_ard_3-0-0_109084_2016-12-12_final
2016-12-12 11:18:24	ga_ls8c_ard_3-0-0_109085_2016-12-12_final
2017-01-11 11:25:04	ga_ls8c_ard_3-0-0_111071_2017-01-11_final
2017-01-11 11:25:28	ga_ls8c_ard_3-0-0_111072_2017-01-11_final
2017-01-11 11:25:52	ga_ls8c_ard_3-0-0_111073_2017-01-11_final
2017-01-11 11:26:16	ga_ls8c_ard_3-0-0_111074_2017-01-11_final
2017-01-11 11:26:40	ga_ls8c_ard_3-0-0_111075_2017-01-11_final
2017-01-11 11:27:04	ga_ls8c_ard_3-0-0_111076_2017-01-11_final
2017-01-11 11:27:28	ga_ls8c_ard_3-0-0_111077_2017-01-11_final
2017-01-13 11:16:17	ga_ls8c_ard_3-0-0_109080_2017-01-13_final
2017-01-13 11:16:41	ga_ls8c_ard_3-0-0_109081_2017-01-13_final
2017-01-13 11:17:05	ga_ls8c_ard_3-0-0_109082_2017-01-13_final
2017-01-13 11:17:29	ga_ls8c_ard_3-0-0_109083_2017-01-13_final
2017-01-13 11:17:53	ga_ls8c_ard_3-0-0_109084_2017-01-13_final
2017-01-13 11:18:17	ga_ls8c_ard_3-0-0_109085_2017-01-13_final
2017-01-27 11:24:58	ga_ls8c_ard_3-0-0_111071_2017-01-27_final
2017-01-27 11:25:22	ga_ls8c_ard_3-0-0_111072_2017-01-27_final
2017-01-27 11:25:46	ga_ls8c_ard_3-0-0_111073_2017-01-27_final
2017-01-27 11:26:10	ga_ls8c_ard_3-0-0_111074_2017-01-27_final
2017-01-27 11:26:34	ga_ls8c_ard_3-0-0_111075_2017-01-27_final
2017-01-27 11:26:58	ga_ls8c_ard_3-0-0_111076_2017-01-27_final
2017-01-27 11:27:22	ga_ls8c_ard_3-0-0_111077_2017-01-27_final
2017-03-16 11:24:36	ga_ls8c_ard_3-0-0_111071_2017-03-16_final
2017-03-16 11:25:00	ga_ls8c_ard_3-0-0_111072_2017-03-16_final
2017-03-16 11:25:24	ga_ls8c_ard_3-0-0_111073_2017-03-16_final
2017-03-16 11:25:48	ga_ls8c_ard_3-0-0_111074_2017-03-16_final
2017-03-16 11:26:12	ga_ls8c_ard_3-0-0_111075_2017-03-16_final
2017-03-16 11:26:36	ga_ls8c_ard_3-0-0_111076_2017-03-16_final
2017-03-16 11:27:00	ga_ls8c_ard_3-0-0_111077_2017-03-16_final
2018-07-02 11:19:46	ga_ls8c_ard_3-0-0_110076_2018-07-02_final
2018-07-02 11:20:10	ga_ls8c_ard_3-0-0_110077_2018-07-02_final
2018-07-02 11:20:34	ga_ls8c_ard_3-0-0_110078_2018-07-02_final
2018-07-02 11:20:58	ga_ls8c_ard_3-0-0_110079_2018-07-02_final
2018-07-02 11:21:22	ga_ls8c_ard_3-0-0_110080_2018-07-02_final
2018-07-02 11:21:46	ga_ls8c_ard_3-0-0_110081_2018-07-02_final
2018-09-02 11:29:02	ga_ls8c_ard_3-0-0_112067_2018-09-02_final
2018-09-02 11:29:26	ga_ls8c_ard_3-0-0_112068_2018-09-02_final
2018-09-02 11:29:50	ga_ls8c_ard_3-0-0_112069_2018-09-02_final
2018-09-02 11:30:14	ga_ls8c_ard_3-0-0_112070_2018-09-02_final
2018-09-02 11:30:38	ga_ls8c_ard_3-0-0_112071_2018-09-02_final
2018-09-02 11:31:02	ga_ls8c_ard_3-0-0_112072_2018-09-02_final
2018-09-04 11:20:16	ga_ls8c_ard_3-0-0_110076_2018-09-04_final
2018-09-04 11:20:40	ga_ls8c_ard_3-0-0_110077_2018-09-04_final
2018-09-04 11:21:04	ga_ls8c_ard_3-0-0_110078_2018-09-04_final
2018-09-04 11:21:28	ga_ls8c_ard_3-0-0_110079_2018-09-04_final
2018-09-04 11:21:52	ga_ls8c_ard_3-0-0_110080_2018-09-04_final
2018-09-04 11:22:16	ga_ls8c_ard_3-0-0_110081_2018-09-04_final
2022-12-04 11:20:52	ga_ls8c_ard_3-2-1_110075_2022-12-04_final
2022-12-04 11:21:16	ga_ls8c_ard_3-2-1_110076_2022-12-04_final
2022-12-04 11:21:40	ga_ls8c_ard_3-2-1_110077_2022-12-04_final
2022-12-04 11:22:04	ga_ls8c_ard_3-2-1_110078_2022-12-04_final
2022-12-04 11:22:28	ga_ls8c_ard_3-2-1_110079_2022-12-04_final
2022-12-04 11:22:52	ga_ls8c_ard_3-2-1_110080_2022-12-04_final
2022-12-04 11:23:16	ga_ls8c_ard_3-2-1_110081_2022-12-04_final
2022-12-27 11:25:17	ga_ls8c_ard_3-2-1_111071_2022-12-27_final
2022-12-27 11:25:41	ga_ls8c_ard_3-2-1_111072_2022-12-27_final
2022-12-27 11:26:05	ga_ls8c_ard_3-2-1_111073_2022-12-27_final
2022-12-27 11:26:29	ga_ls8c_ard_3-2-1_111074_2022-12-27_final
2022-12-27 11:26:53	ga_ls8c_ard_3-2-1_111075_2022-12-27_final
2022-12-27 11:27:17	ga_ls8c_ard_3-2-1_111076_2022-12-27_final
2022-12-27 11:27:41	ga_ls8c_ard_3-2-1_111077_2022-12-27_final
2023-01-03 11:31:53	ga_ls8c_ard_3-2-1_112072_2023-01-03_final
2023-12-05 11:31:35	ga_ls8c_ard_3-2-1_112072_2023-12-05_final
2023-12-09 11:11:39	ga_ls8c_ard_3-2-1_108084_2023-12-09_final
2023-12-14 11:25:28	ga_ls8c_ard_3-2-1_111072_2023-12-14_final
2023-12-14 11:26:16	ga_ls8c_ard_3-2-1_111074_2023-12-14_final
2023-12-16 11:16:19	ga_ls8c_ard_3-2-1_109080_2023-12-16_final
2023-12-16 11:16:43	ga_ls8c_ard_3-2-1_109081_2023-12-16_final
2023-12-16 11:17:07	ga_ls8c_ard_3-2-1_109082_2023-12-16_final
2023-12-16 11:17:31	ga_ls8c_ard_3-2-1_109083_2023-12-16_final
2023-12-16 11:17:55	ga_ls8c_ard_3-2-1_109084_2023-12-16_final
2023-12-23 11:20:31	ga_ls8c_ard_3-2-1_110075_2023-12-23_final
2023-12-23 11:20:55	ga_ls8c_ard_3-2-1_110076_2023-12-23_final
2023-12-23 11:21:19	ga_ls8c_ard_3-2-1_110077_2023-12-23_final
2023-12-23 11:21:43	ga_ls8c_ard_3-2-1_110078_2023-12-23_final
2023-12-23 11:22:07	ga_ls8c_ard_3-2-1_110079_2023-12-23_final
2023-12-23 11:22:31	ga_ls8c_ard_3-2-1_110080_2023-12-23_final
2023-12-23 11:22:55	ga_ls8c_ard_3-2-1_110081_2023-12-23_final
2023-12-25 11:11:45	ga_ls8c_ard_3-2-1_108084_2023-12-25_final
2024-01-01 11:16:15	ga_ls8c_ard_3-2-1_109080_2024-01-01_final
2024-01-01 11:16:39	ga_ls8c_ard_3-2-1_109081_2024-01-01_final
2024-01-01 11:17:03	ga_ls8c_ard_3-2-1_109082_2024-01-01_final
2024-01-01 11:17:27	ga_ls8c_ard_3-2-1_109083_2024-01-01_final
2024-01-01 11:17:51	ga_ls8c_ard_3-2-1_109084_2024-01-01_final
2024-04-22 11:15:35	ga_ls8c_ard_3-2-1_109080_2024-04-22_nrt
2024-04-22 11:15:59	ga_ls8c_ard_3-2-1_109081_2024-04-22_nrt
2024-04-22 11:16:23	ga_ls8c_ard_3-2-1_109082_2024-04-22_nrt
2024-04-22 11:16:47	ga_ls8c_ard_3-2-1_109083_2024-04-22_nrt
2024-04-22 11:17:11	ga_ls8c_ard_3-2-1_109084_2024-04-22_nrt

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