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
2021-11-23 10:04:49	ga_ls9c_ard_3-2-1_098075_2021-11-23_final.stac-item
2021-12-05 10:06:32	ga_ls9c_ard_3-2-1_098075_2021-12-05_final.stac-item
2022-01-13 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-01-13_final.stac-item
2022-04-03 10:10:16	ga_ls9c_ard_3-2-1_099070_2022-04-03_final.stac-item
2022-04-28 10:05:54	ga_ls9c_ard_3-2-1_098075_2022-04-28_final.stac-item
2022-05-14 10:05:45	ga_ls9c_ard_3-2-1_098075_2022-05-14_final.stac-item
2022-06-15 10:05:46	ga_ls9c_ard_3-2-1_098075_2022-06-15_final.stac-item
2022-06-24 09:59:50	ga_ls9c_ard_3-2-1_097075_2022-06-24_final.stac-item
2022-07-08 10:10:10	ga_ls9c_ard_3-2-1_099070_2022-07-08_final.stac-item
2022-08-02 10:06:13	ga_ls9c_ard_3-2-1_098075_2022-08-02_final.stac-item
2022-08-09 10:10:05	ga_ls9c_ard_3-2-1_099069_2022-08-09_final.stac-item
2022-08-11 10:00:08	ga_ls9c_ard_3-2-1_097075_2022-08-11_final.stac-item
2022-08-18 10:06:21	ga_ls9c_ard_3-2-1_098075_2022-08-18_final.stac-item
2022-08-25 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-08-25_final.stac-item
2022-08-25 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-08-25_final.stac-item
2022-08-27 10:00:12	ga_ls9c_ard_3-2-1_097075_2022-08-27_final.stac-item
2022-09-03 10:06:22	ga_ls9c_ard_3-2-1_098075_2022-09-03_final.stac-item
2022-09-10 10:10:34	ga_ls9c_ard_3-2-1_099070_2022-09-10_final.stac-item
2022-09-19 10:06:28	ga_ls9c_ard_3-2-1_098075_2022-09-19_final.stac-item
2022-09-26 10:10:41	ga_ls9c_ard_3-2-1_099070_2022-09-26_final.stac-item
2022-10-05 10:06:29	ga_ls9c_ard_3-2-1_098075_2022-10-05_final.stac-item
2022-10-12 10:10:20	ga_ls9c_ard_3-2-1_099069_2022-10-12_final.stac-item
2022-10-14 10:00:23	ga_ls9c_ard_3-2-1_097075_2022-10-14_final.stac-item
2022-10-21 10:06:36	ga_ls9c_ard_3-2-1_098075_2022-10-21_final.stac-item
2022-10-28 10:10:22	ga_ls9c_ard_3-2-1_099069_2022-10-28_final.stac-item
2022-11-06 10:06:34	ga_ls9c_ard_3-2-1_098075_2022-11-06_final.stac-item
2022-11-22 10:06:36	ga_ls9c_ard_3-2-1_098075_2022-11-22_final.stac-item
2022-11-29 10:10:45	ga_ls9c_ard_3-2-1_099070_2022-11-29_final.stac-item
2022-12-08 10:06:35	ga_ls9c_ard_3-2-1_098075_2022-12-08_final.stac-item
2022-12-15 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-12-15_final.stac-item
2022-12-24 10:06:32	ga_ls9c_ard_3-2-1_098075_2022-12-24_final.stac-item
2022-12-31 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-12-31_final.stac-item
2023-01-09 10:06:35	ga_ls9c_ard_3-2-1_098075_2023-01-09_final.stac-item
2023-01-25 10:06:31	ga_ls9c_ard_3-2-1_098075_2023-01-25_final.stac-item
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-03 10:00:27	ga_ls9c_ard_3-2-1_097075_2023-02-03_final.stac-item
2023-02-10 10:06:39	ga_ls9c_ard_3-2-1_098075_2023-02-10_final.stac-item
2023-02-17 10:10:21	ga_ls9c_ard_3-2-1_099069_2023-02-17_final.stac-item
2023-02-26 10:06:25	ga_ls9c_ard_3-2-1_098075_2023-02-26_final.stac-item
2023-03-07 10:02:09	ga_ls9c_ard_3-2-1_097080_2023-03-07_final.stac-item
2023-03-14 10:06:18	ga_ls9c_ard_3-2-1_098075_2023-03-14_final.stac-item
2023-03-21 10:10:02	ga_ls9c_ard_3-2-1_099069_2023-03-21_final.stac-item
2023-03-21 10:10:26	ga_ls9c_ard_3-2-1_099070_2023-03-21_final.stac-item
2023-04-01 09:55:44	ga_ls9c_ard_3-2-1_096080_2023-04-01_final.stac-item
2023-04-06 10:10:16	ga_ls9c_ard_3-2-1_099070_2023-04-06_final.stac-item
2023-04-15 10:05:59	ga_ls9c_ard_3-2-1_098075_2023-04-15_final.stac-item
2023-04-22 10:10:10	ga_ls9c_ard_3-2-1_099070_2023-04-22_final.stac-item
2023-05-01 10:05:52	ga_ls9c_ard_3-2-1_098075_2023-05-01_final.stac-item
2023-05-08 10:09:35	ga_ls9c_ard_3-2-1_099069_2023-05-08_final.stac-item
2023-05-08 10:09:59	ga_ls9c_ard_3-2-1_099070_2023-05-08_final.stac-item
2023-05-17 10:05:44	ga_ls9c_ard_3-2-1_098075_2023-05-17_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-05-24 10:09:48	ga_ls9c_ard_3-2-1_099070_2023-05-24_final.stac-item
2023-06-02 10:05:36	ga_ls9c_ard_3-2-1_098075_2023-06-02_final.stac-item
2023-06-09 10:09:20	ga_ls9c_ard_3-2-1_099069_2023-06-09_final.stac-item
2023-06-09 10:09:44	ga_ls9c_ard_3-2-1_099070_2023-06-09_final.stac-item
2023-06-11 10:01:20	ga_ls9c_ard_3-2-1_097080_2023-06-11_final.stac-item
2023-06-18 10:05:28	ga_ls9c_ard_3-2-1_098075_2023-06-18_final.stac-item
2023-06-25 10:09:15	ga_ls9c_ard_3-2-1_099069_2023-06-25_final.stac-item
2023-06-25 10:09:38	ga_ls9c_ard_3-2-1_099070_2023-06-25_final.stac-item
2023-07-04 10:05:39	ga_ls9c_ard_3-2-1_098075_2023-07-04_final.stac-item
2023-07-11 10:09:31	ga_ls9c_ard_3-2-1_099069_2023-07-11_final.stac-item
2023-07-27 10:09:33	ga_ls9c_ard_3-2-1_099069_2023-07-27_final.stac-item
2023-08-12 10:09:42	ga_ls9c_ard_3-2-1_099069_2023-08-12_final.stac-item
2023-08-30 10:01:53	ga_ls9c_ard_3-2-1_097080_2023-08-30_final.stac-item
2023-09-08 09:55:48	ga_ls9c_ard_3-2-1_096080_2023-09-08_final.stac-item
2023-09-15 10:02:02	ga_ls9c_ard_3-2-1_097080_2023-09-15_final.stac-item
2023-09-24 09:55:49	ga_ls9c_ard_3-2-1_096080_2023-09-24_final.stac-item
2023-10-01 10:02:00	ga_ls9c_ard_3-2-1_097080_2023-10-01_final.stac-item
2023-10-10 09:55:56	ga_ls9c_ard_3-2-1_096080_2023-10-10_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_2023-10-17_final.stac-item
2023-10-26 09:56:00	ga_ls9c_ard_3-2-1_096080_2023-10-26_final.stac-item
2023-10-31 10:10:29	ga_ls9c_ard_3-2-1_099070_2023-10-31_final.stac-item
2023-11-02 10:02:05	ga_ls9c_ard_3-2-1_097080_2023-11-02_final.stac-item
2023-11-11 09:55:57	ga_ls9c_ard_3-2-1_096080_2023-11-11_final.stac-item
2023-11-16 10:10:30	ga_ls9c_ard_3-2-1_099070_2023-11-16_final.stac-item
2023-11-27 09:56:05	ga_ls9c_ard_3-2-1_096080_2023-11-27_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-13 09:56:04	ga_ls9c_ard_3-2-1_096080_2023-12-13_final.stac-item
2023-12-18 10:10:39	ga_ls9c_ard_3-2-1_099070_2023-12-18_final.stac-item
2023-12-29 09:56:06	ga_ls9c_ard_3-2-1_096080_2023-12-29_final.stac-item
2024-01-03 10:10:35	ga_ls9c_ard_3-2-1_099070_2024-01-03_final.stac-item
2024-01-14 09:56:03	ga_ls9c_ard_3-2-1_096080_2024-01-14_final.stac-item
2024-01-19 10:10:35	ga_ls9c_ard_3-2-1_099070_2024-01-19_final.stac-item
2024-01-30 09:56:03	ga_ls9c_ard_3-2-1_096080_2024-01-30_final.stac-item
2024-02-04 10:10:14	ga_ls9c_ard_3-2-1_099069_2024-02-04_final.stac-item
2024-02-04 10:10:38	ga_ls9c_ard_3-2-1_099070_2024-02-04_final.stac-item
2024-02-15 09:56:01	ga_ls9c_ard_3-2-1_096080_2024-02-15_final.stac-item
2024-02-20 10:10:04	ga_ls9c_ard_3-2-1_099069_2024-02-20_final.stac-item
2024-02-20 10:10:28	ga_ls9c_ard_3-2-1_099070_2024-02-20_final.stac-item
2024-03-02 09:55:56	ga_ls9c_ard_3-2-1_096080_2024-03-02_final.stac-item
2024-03-23 10:10:27	ga_ls9c_ard_3-2-1_099070_2024-03-23_final.stac-item
2024-04-03 09:55:47	ga_ls9c_ard_3-2-1_096080_2024-04-03_final.stac-item
2024-04-08 10:10:18	ga_ls9c_ard_3-2-1_099070_2024-04-08_final.stac-item
2024-04-17 10:05:59	ga_ls9c_ard_3-2-1_098075_2024-04-17_final.stac-item
2024-04-19 09:55:34	ga_ls9c_ard_3-2-1_096080_2024-04-19_final.stac-item
2024-04-24 10:09:57	ga_ls9c_ard_3-2-1_099070_2024-04-24_final.stac-item
2024-05-03 10:05:44	ga_ls9c_ard_3-2-1_098075_2024-05-03_final.stac-item
2024-05-05 09:55:23	ga_ls9c_ard_3-2-1_096080_2024-05-05_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