Search ga_ls9c_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
2021-11-07 09:22:39	ga_ls9c_ard_3-2-1_090088_2021-11-06_final.stac-item
2021-12-11 09:34:59	ga_ls9c_ard_3-2-1_092089_2021-12-11_final.stac-item
2021-12-13 09:22:12	ga_ls9c_ard_3-2-1_090088_2021-12-12_final.stac-item
2021-12-20 09:28:45	ga_ls9c_ard_3-2-1_091089_2021-12-19_final.stac-item
2021-12-27 09:34:56	ga_ls9c_ard_3-2-1_092089_2021-12-27_final.stac-item
2022-01-05 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-01-04_final.stac-item
2022-01-12 09:34:53	ga_ls9c_ard_3-2-1_092089_2022-01-12_final.stac-item
2022-01-14 09:22:31	ga_ls9c_ard_3-2-1_090089_2022-01-13_final.stac-item
2022-01-21 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-01-20_final.stac-item
2022-01-28 09:34:55	ga_ls9c_ard_3-2-1_092089_2022-01-28_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-02-06 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-02-05_final.stac-item
2022-02-13 09:34:52	ga_ls9c_ard_3-2-1_092089_2022-02-13_final.stac-item
2022-02-22 09:28:36	ga_ls9c_ard_3-2-1_091089_2022-02-21_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-10 09:28:30	ga_ls9c_ard_3-2-1_091089_2022-03-09_final.stac-item
2022-03-26 09:28:25	ga_ls9c_ard_3-2-1_091089_2022-03-25_final.stac-item
2022-04-11 09:28:22	ga_ls9c_ard_3-2-1_091089_2022-04-10_final.stac-item
2022-04-18 09:34:27	ga_ls9c_ard_3-2-1_092089_2022-04-18_final.stac-item
2022-04-20 09:22:04	ga_ls9c_ard_3-2-1_090089_2022-04-19_final.stac-item
2022-04-27 09:28:13	ga_ls9c_ard_3-2-1_091089_2022-04-26_final.stac-item
2022-05-04 09:34:22	ga_ls9c_ard_3-2-1_092089_2022-05-04_final.stac-item
2022-05-13 09:28:05	ga_ls9c_ard_3-2-1_091089_2022-05-12_final.stac-item
2022-05-20 09:34:09	ga_ls9c_ard_3-2-1_092089_2022-05-20_final.stac-item
2022-05-22 09:21:48	ga_ls9c_ard_3-2-1_090089_2022-05-21_final.stac-item
2022-05-31 09:15:38	ga_ls9c_ard_3-2-1_089089_2022-05-30_final.stac-item
2022-06-05 09:34:11	ga_ls9c_ard_3-2-1_092089_2022-06-05_final.stac-item
2022-06-07 09:21:49	ga_ls9c_ard_3-2-1_090089_2022-06-06_final.stac-item
2022-06-12 09:40:00	ga_ls9c_ard_3-2-1_093088_2022-06-12_final.stac-item
2022-06-23 09:21:43	ga_ls9c_ard_3-2-1_090088_2022-06-22_final.stac-item
2022-06-28 09:40:19	ga_ls9c_ard_3-2-1_093088_2022-06-28_final.stac-item
2022-07-02 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-07-01_final.stac-item
2022-07-16 09:28:17	ga_ls9c_ard_3-2-1_091089_2022-07-15_final.stac-item
2022-08-10 09:22:03	ga_ls9c_ard_3-2-1_090088_2022-08-09_final.stac-item
2022-08-15 09:40:37	ga_ls9c_ard_3-2-1_093088_2022-08-15_final.stac-item
2022-08-26 09:22:07	ga_ls9c_ard_3-2-1_090088_2022-08-25_final.stac-item
2022-09-04 09:16:20	ga_ls9c_ard_3-2-1_089089_2022-09-03_final.stac-item
2022-09-11 09:22:08	ga_ls9c_ard_3-2-1_090088_2022-09-10_final.stac-item
2022-09-16 09:40:44	ga_ls9c_ard_3-2-1_093088_2022-09-16_final.stac-item
2022-09-25 09:35:00	ga_ls9c_ard_3-2-1_092089_2022-09-25_final.stac-item
2022-09-27 09:22:15	ga_ls9c_ard_3-2-1_090088_2022-09-26_final.stac-item
2022-10-02 09:40:47	ga_ls9c_ard_3-2-1_093088_2022-10-02_final.stac-item
2022-10-04 09:28:49	ga_ls9c_ard_3-2-1_091089_2022-10-03_final.stac-item
2022-10-11 09:35:03	ga_ls9c_ard_3-2-1_092089_2022-10-11_final.stac-item
2022-10-13 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-10-12_final.stac-item
2022-10-13 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-10-12_final.stac-item
2022-10-18 09:40:53	ga_ls9c_ard_3-2-1_093088_2022-10-18_final.stac-item
2022-10-27 09:35:06	ga_ls9c_ard_3-2-1_092089_2022-10-27_final.stac-item
2022-10-29 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-10-28_final.stac-item
2022-11-05 09:28:53	ga_ls9c_ard_3-2-1_091089_2022-11-04_final.stac-item
2022-11-12 09:35:07	ga_ls9c_ard_3-2-1_092089_2022-11-12_final.stac-item
2022-11-14 09:22:22	ga_ls9c_ard_3-2-1_090088_2022-11-13_final.stac-item
2022-11-14 09:22:45	ga_ls9c_ard_3-2-1_090089_2022-11-13_final.stac-item
2022-11-21 09:28:56	ga_ls9c_ard_3-2-1_091089_2022-11-20_final.stac-item
2022-11-28 09:35:05	ga_ls9c_ard_3-2-1_092089_2022-11-28_final.stac-item
2022-11-30 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-11-29_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-07 09:28:54	ga_ls9c_ard_3-2-1_091089_2022-12-06_final.stac-item
2022-12-14 09:35:06	ga_ls9c_ard_3-2-1_092089_2022-12-14_final.stac-item
2022-12-16 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-15_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-30 09:35:05	ga_ls9c_ard_3-2-1_092089_2022-12-30_final.stac-item
2023-01-01 09:22:20	ga_ls9c_ard_3-2-1_090088_2022-12-31_final.stac-item
2023-01-01 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-31_final.stac-item
2023-01-08 09:28:55	ga_ls9c_ard_3-2-1_091089_2023-01-07_final.stac-item
2023-01-15 09:35:02	ga_ls9c_ard_3-2-1_092089_2023-01-15_final.stac-item
2023-01-17 09:22:38	ga_ls9c_ard_3-2-1_090089_2023-01-16_final.stac-item
2023-01-24 09:28:49	ga_ls9c_ard_3-2-1_091089_2023-01-23_final.stac-item
2023-01-31 09:35:06	ga_ls9c_ard_3-2-1_092089_2023-01-31_final.stac-item
2023-02-16 09:35:06	ga_ls9c_ard_3-2-1_092089_2023-02-16_final.stac-item
2023-03-04 09:34:53	ga_ls9c_ard_3-2-1_092089_2023-03-04_final.stac-item
2023-03-20 09:34:46	ga_ls9c_ard_3-2-1_092089_2023-03-20_final.stac-item
2023-04-14 09:28:19	ga_ls9c_ard_3-2-1_091089_2023-04-13_final.stac-item
2023-04-21 09:34:30	ga_ls9c_ard_3-2-1_092089_2023-04-21_final.stac-item
2023-04-30 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-04-29_final.stac-item
2023-05-07 09:34:18	ga_ls9c_ard_3-2-1_092089_2023-05-07_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-23 09:34:09	ga_ls9c_ard_3-2-1_092089_2023-05-23_final.stac-item
2023-05-25 09:21:45	ga_ls9c_ard_3-2-1_090089_2023-05-24_final.stac-item
2023-06-01 09:27:56	ga_ls9c_ard_3-2-1_091089_2023-05-31_final.stac-item
2023-06-08 09:34:04	ga_ls9c_ard_3-2-1_092089_2023-06-08_final.stac-item
2023-06-10 09:21:41	ga_ls9c_ard_3-2-1_090089_2023-06-09_final.stac-item
2023-06-19 09:15:02	ga_ls9c_ard_3-2-1_089088_2023-06-18_final.stac-item
2023-06-19 09:15:26	ga_ls9c_ard_3-2-1_089089_2023-06-18_final.stac-item
2023-06-24 09:33:58	ga_ls9c_ard_3-2-1_092089_2023-06-24_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_2023-06-25_final.stac-item
2023-07-05 09:15:14	ga_ls9c_ard_3-2-1_089088_2023-07-04_final.stac-item
2023-07-05 09:15:38	ga_ls9c_ard_3-2-1_089089_2023-07-04_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-12 09:21:53	ga_ls9c_ard_3-2-1_090089_2023-07-11_final.stac-item
2023-07-28 09:21:31	ga_ls9c_ard_3-2-1_090088_2023-07-27_final.stac-item
2023-08-06 09:15:28	ga_ls9c_ard_3-2-1_089088_2023-08-05_final.stac-item
2023-08-13 09:21:40	ga_ls9c_ard_3-2-1_090088_2023-08-12_final.stac-item
2023-08-22 09:15:33	ga_ls9c_ard_3-2-1_089088_2023-08-21_final.stac-item
2023-09-14 09:21:58	ga_ls9c_ard_3-2-1_090088_2023-09-13_final.stac-item
2023-09-23 09:15:46	ga_ls9c_ard_3-2-1_089088_2023-09-22_final.stac-item
2023-09-30 09:21:55	ga_ls9c_ard_3-2-1_090088_2023-09-29_final.stac-item
2023-10-25 09:15:56	ga_ls9c_ard_3-2-1_089088_2023-10-24_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 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