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
2021-11-03 09:56:57	ga_ls9c_ard_3-2-1_096080_2021-11-03_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-11-15 09:42:45	ga_ls9c_ard_3-2-1_094079_2021-11-15_final.stac-item
2021-11-20 09:45:12	ga_ls9c_ard_3-2-1_094079_2021-11-20_final.stac-item
2021-12-07 09:56:09	ga_ls9c_ard_3-2-1_096080_2021-12-07_final.stac-item
2021-12-09 09:43:22	ga_ls9c_ard_3-2-1_094079_2021-12-09_final.stac-item
2021-12-25 09:43:18	ga_ls9c_ard_3-2-1_094079_2021-12-25_final.stac-item
2022-01-08 09:56:02	ga_ls9c_ard_3-2-1_096080_2022-01-08_final.stac-item
2022-01-11 10:26:55	ga_ls9c_ard_3-2-1_101080_2022-01-11_final.stac-item
2022-01-13 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-01-13_final.stac-item
2022-01-15 10:02:12	ga_ls9c_ard_3-2-1_097080_2022-01-15_final.stac-item
2022-01-17 09:49:27	ga_ls9c_ard_3-2-1_095079_2022-01-17_final.stac-item
2022-02-09 09:56:01	ga_ls9c_ard_3-2-1_096080_2022-02-09_final.stac-item
2022-02-11 09:43:15	ga_ls9c_ard_3-2-1_094079_2022-02-11_final.stac-item
2022-02-28 10:26:43	ga_ls9c_ard_3-2-1_101080_2022-02-28_final.stac-item
2022-03-06 09:49:13	ga_ls9c_ard_3-2-1_095079_2022-03-06_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-20 10:01:57	ga_ls9c_ard_3-2-1_097080_2022-03-20_final.stac-item
2022-03-29 09:55:43	ga_ls9c_ard_3-2-1_096080_2022-03-29_final.stac-item
2022-04-05 10:01:53	ga_ls9c_ard_3-2-1_097080_2022-04-05_final.stac-item
2022-04-10 10:20:24	ga_ls9c_ard_3-2-1_100080_2022-04-10_final.stac-item
2022-04-14 09:55:38	ga_ls9c_ard_3-2-1_096080_2022-04-14_final.stac-item
2022-04-21 10:01:43	ga_ls9c_ard_3-2-1_097080_2022-04-21_final.stac-item
2022-05-16 09:55:21	ga_ls9c_ard_3-2-1_096080_2022-05-16_final.stac-item
2022-06-01 09:55:18	ga_ls9c_ard_3-2-1_096080_2022-06-01_final.stac-item
2022-06-03 09:42:33	ga_ls9c_ard_3-2-1_094079_2022-06-03_final.stac-item
2022-06-04 10:26:13	ga_ls9c_ard_3-2-1_101080_2022-06-04_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-13 10:20:05	ga_ls9c_ard_3-2-1_100080_2022-06-13_final.stac-item
2022-06-19 09:42:42	ga_ls9c_ard_3-2-1_094079_2022-06-19_final.stac-item
2022-06-20 10:26:24	ga_ls9c_ard_3-2-1_101080_2022-06-20_final.stac-item
2022-06-22 10:14:07	ga_ls9c_ard_3-2-1_099080_2022-06-22_final.stac-item
2022-07-05 09:42:53	ga_ls9c_ard_3-2-1_094079_2022-07-05_final.stac-item
2022-07-06 10:26:32	ga_ls9c_ard_3-2-1_101080_2022-07-06_final.stac-item
2022-07-08 10:14:10	ga_ls9c_ard_3-2-1_099080_2022-07-08_final.stac-item
2022-07-15 10:20:18	ga_ls9c_ard_3-2-1_100080_2022-07-15_final.stac-item
2022-07-21 09:42:55	ga_ls9c_ard_3-2-1_094079_2022-07-21_final.stac-item
2022-07-24 10:14:16	ga_ls9c_ard_3-2-1_099080_2022-07-24_final.stac-item
2022-08-06 09:43:08	ga_ls9c_ard_3-2-1_094079_2022-08-06_final.stac-item
2022-08-07 10:26:48	ga_ls9c_ard_3-2-1_101080_2022-08-07_final.stac-item
2022-08-09 10:14:28	ga_ls9c_ard_3-2-1_099080_2022-08-09_final.stac-item
2022-08-22 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-08-22_final.stac-item
2022-08-25 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-08-25_final.stac-item
2022-09-01 10:20:44	ga_ls9c_ard_3-2-1_100080_2022-09-01_final.stac-item
2022-09-05 09:56:00	ga_ls9c_ard_3-2-1_096080_2022-09-05_final.stac-item
2022-09-07 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-09-07_final.stac-item
2022-09-21 09:56:07	ga_ls9c_ard_3-2-1_096080_2022-09-21_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-10-03 10:20:51	ga_ls9c_ard_3-2-1_100080_2022-10-03_final.stac-item
2022-10-05 10:08:29	ga_ls9c_ard_3-2-1_098080_2022-10-05_final.stac-item
2022-10-07 09:56:07	ga_ls9c_ard_3-2-1_096080_2022-10-07_final.stac-item
2022-10-09 09:43:24	ga_ls9c_ard_3-2-1_094079_2022-10-09_final.stac-item
2022-10-10 10:27:04	ga_ls9c_ard_3-2-1_101080_2022-10-10_final.stac-item
2022-10-14 10:02:23	ga_ls9c_ard_3-2-1_097080_2022-10-14_final.stac-item
2022-10-25 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-10-25_final.stac-item
2022-10-30 10:02:24	ga_ls9c_ard_3-2-1_097080_2022-10-30_final.stac-item
2022-11-06 10:08:34	ga_ls9c_ard_3-2-1_098080_2022-11-06_final.stac-item
2022-11-06 10:08:34	ga_ls9c_ard_3-2-1_098080_2022-11-06_nrt.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-11-10 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-10_final.stac-item
2022-11-15 10:02:26	ga_ls9c_ard_3-2-1_097080_2022-11-15_final.stac-item
2022-11-20 10:20:58	ga_ls9c_ard_3-2-1_100080_2022-11-20_final.stac-item
2022-11-22 10:08:36	ga_ls9c_ard_3-2-1_098080_2022-11-22_final.stac-item
2022-11-24 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-11-24_final.stac-item
2022-12-01 10:02:22	ga_ls9c_ard_3-2-1_097080_2022-12-01_final.stac-item
2022-12-06 10:20:56	ga_ls9c_ard_3-2-1_100080_2022-12-06_final.stac-item
2022-12-12 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-12-12_final.stac-item
2022-12-15 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-15_final.stac-item
2022-12-22 10:20:54	ga_ls9c_ard_3-2-1_100080_2022-12-22_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2022-12-28 09:43:27	ga_ls9c_ard_3-2-1_094079_2022-12-28_final.stac-item
2022-12-29 10:27:07	ga_ls9c_ard_3-2-1_101080_2022-12-29_final.stac-item
2022-12-31 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-31_final.stac-item
2023-01-02 10:02:24	ga_ls9c_ard_3-2-1_097080_2023-01-02_final.stac-item
2023-01-11 09:56:12	ga_ls9c_ard_3-2-1_096080_2023-01-11_final.stac-item
2023-01-13 09:43:26	ga_ls9c_ard_3-2-1_094079_2023-01-13_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-16 10:14:41	ga_ls9c_ard_3-2-1_099080_2023-01-16_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-02-12 09:56:16	ga_ls9c_ard_3-2-1_096080_2023-02-12_final.stac-item
2023-02-19 10:02:20	ga_ls9c_ard_3-2-1_097080_2023-02-19_final.stac-item
2023-03-16 09:55:56	ga_ls9c_ard_3-2-1_096080_2023-03-16_final.stac-item
2023-03-21 10:14:26	ga_ls9c_ard_3-2-1_099080_2023-03-21_final.stac-item
2023-03-23 10:02:03	ga_ls9c_ard_3-2-1_097080_2023-03-23_final.stac-item
2023-04-01 09:55:44	ga_ls9c_ard_3-2-1_096080_2023-04-01_final.stac-item
2023-04-08 10:01:53	ga_ls9c_ard_3-2-1_097080_2023-04-08_final.stac-item
2023-04-13 10:20:22	ga_ls9c_ard_3-2-1_100080_2023-04-13_final.stac-item
2023-04-17 09:55:38	ga_ls9c_ard_3-2-1_096080_2023-04-17_final.stac-item
2023-04-24 10:01:47	ga_ls9c_ard_3-2-1_097080_2023-04-24_final.stac-item
2023-04-29 10:20:15	ga_ls9c_ard_3-2-1_100080_2023-04-29_final.stac-item
2023-05-10 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-05-10_final.stac-item
2023-05-19 09:55:21	ga_ls9c_ard_3-2-1_096080_2023-05-19_final.stac-item
2023-06-02 10:07:36	ga_ls9c_ard_3-2-1_098080_2023-06-02_final.stac-item
2023-06-11 10:01:20	ga_ls9c_ard_3-2-1_097080_2023-06-11_final.stac-item
2023-06-20 09:55:06	ga_ls9c_ard_3-2-1_096080_2023-06-20_final.stac-item
2023-06-22 09:42:21	ga_ls9c_ard_3-2-1_094079_2023-06-22_final.stac-item
2023-06-27 10:01:19	ga_ls9c_ard_3-2-1_097080_2023-06-27_final.stac-item
2023-07-08 09:42:35	ga_ls9c_ard_3-2-1_094079_2023-07-08_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years