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
2021-11-02 10:55:39	ga_ls9c_ard_3-2-1_106080_2021-11-02_final.stac-item
2021-11-03 09:56:57	ga_ls9c_ard_3-2-1_096080_2021-11-03_final.stac-item
2021-11-07 10:58:08	ga_ls9c_ard_3-2-1_106080_2021-11-07_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-11-09 10:39:23	ga_ls9c_ard_3-2-1_103080_2021-11-09_final.stac-item
2021-12-07 09:56:09	ga_ls9c_ard_3-2-1_096080_2021-12-07_final.stac-item
2021-12-17 10:33:07	ga_ls9c_ard_3-2-1_102080_2021-12-17_final.stac-item
2021-12-19 10:20:46	ga_ls9c_ard_3-2-1_100080_2021-12-19_final.stac-item
2021-12-28 10:14:36	ga_ls9c_ard_3-2-1_099080_2021-12-28_final.stac-item
2021-12-29 10:57:52	ga_ls9c_ard_3-2-1_106080_2021-12-29_final.stac-item
2022-01-02 10:33:08	ga_ls9c_ard_3-2-1_102080_2022-01-02_final.stac-item
2022-01-04 10:20:46	ga_ls9c_ard_3-2-1_100080_2022-01-04_final.stac-item
2022-01-08 09:56:02	ga_ls9c_ard_3-2-1_096080_2022-01-08_final.stac-item
2022-01-14 10:57:48	ga_ls9c_ard_3-2-1_106080_2022-01-14_final.stac-item
2022-01-15 10:02:12	ga_ls9c_ard_3-2-1_097080_2022-01-15_final.stac-item
2022-01-22 10:08:24	ga_ls9c_ard_3-2-1_098080_2022-01-22_final.stac-item
2022-01-24 09:56:03	ga_ls9c_ard_3-2-1_096080_2022-01-24_final.stac-item
2022-01-30 10:57:51	ga_ls9c_ard_3-2-1_106080_2022-01-30_final.stac-item
2022-01-31 10:02:14	ga_ls9c_ard_3-2-1_097080_2022-01-31_final.stac-item
2022-02-05 10:20:46	ga_ls9c_ard_3-2-1_100080_2022-02-05_final.stac-item
2022-02-09 09:56:01	ga_ls9c_ard_3-2-1_096080_2022-02-09_final.stac-item
2022-02-14 10:14:32	ga_ls9c_ard_3-2-1_099080_2022-02-14_final.stac-item
2022-02-21 10:20:38	ga_ls9c_ard_3-2-1_100080_2022-02-21_final.stac-item
2022-03-02 10:14:20	ga_ls9c_ard_3-2-1_099080_2022-03-02_final.stac-item
2022-03-05 10:45:14	ga_ls9c_ard_3-2-1_104080_2022-03-05_final.stac-item
2022-03-20 10:01:57	ga_ls9c_ard_3-2-1_097080_2022-03-20_final.stac-item
2022-03-23 10:32:50	ga_ls9c_ard_3-2-1_102080_2022-03-23_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_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
2022-04-06 10:45:09	ga_ls9c_ard_3-2-1_104080_2022-04-06_final.stac-item
2022-04-08 10:32:46	ga_ls9c_ard_3-2-1_102080_2022-04-08_final.stac-item
2022-04-12 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-04-12_final.stac-item
2022-04-14 09:55:38	ga_ls9c_ard_3-2-1_096080_2022-04-14_final.stac-item
2022-04-16 09:43:39	ga_ls9c_ard_3-2-1_094081_2022-04-16_final.stac-item
2022-04-17 10:26:30	ga_ls9c_ard_3-2-1_101080_2022-04-17_final.stac-item
2022-04-21 10:01:43	ga_ls9c_ard_3-2-1_097080_2022-04-21_final.stac-item
2022-04-26 10:20:15	ga_ls9c_ard_3-2-1_100080_2022-04-26_final.stac-item
2022-04-30 09:55:31	ga_ls9c_ard_3-2-1_096080_2022-04-30_final.stac-item
2022-05-02 09:43:33	ga_ls9c_ard_3-2-1_094081_2022-05-02_final.stac-item
2022-05-03 10:26:48	ga_ls9c_ard_3-2-1_101081_2022-05-03_final.stac-item
2022-05-05 10:14:02	ga_ls9c_ard_3-2-1_099080_2022-05-05_final.stac-item
2022-05-16 09:55:21	ga_ls9c_ard_3-2-1_096080_2022-05-16_final.stac-item
2022-05-16 09:55:45	ga_ls9c_ard_3-2-1_096081_2022-05-16_final.stac-item
2022-05-19 10:26:12	ga_ls9c_ard_3-2-1_101080_2022-05-19_final.stac-item
2022-05-23 10:01:28	ga_ls9c_ard_3-2-1_097080_2022-05-23_final.stac-item
2022-06-01 09:55:18	ga_ls9c_ard_3-2-1_096080_2022-06-01_final.stac-item
2022-06-07 10:57:07	ga_ls9c_ard_3-2-1_106080_2022-06-07_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-06-23_final.stac-item
2022-06-25 10:45:06	ga_ls9c_ard_3-2-1_104080_2022-06-25_final.stac-item
2022-07-09 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-07-09_final.stac-item
2022-07-11 10:45:02	ga_ls9c_ard_3-2-1_104080_2022-07-11_final.stac-item
2022-07-25 10:57:33	ga_ls9c_ard_3-2-1_106080_2022-07-25_final.stac-item
2022-08-10 10:57:44	ga_ls9c_ard_3-2-1_106080_2022-08-10_final.stac-item
2022-08-12 10:45:24	ga_ls9c_ard_3-2-1_104080_2022-08-12_final.stac-item
2022-08-26 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-08-26_final.stac-item
2022-09-04 10:51:38	ga_ls9c_ard_3-2-1_105080_2022-09-04_final.stac-item
2022-09-05 09:56:00	ga_ls9c_ard_3-2-1_096080_2022-09-05_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-09-13 10:45:29	ga_ls9c_ard_3-2-1_104080_2022-09-13_final.stac-item
2022-09-21 09:56:07	ga_ls9c_ard_3-2-1_096080_2022-09-21_final.stac-item
2022-09-27 10:57:56	ga_ls9c_ard_3-2-1_106080_2022-09-27_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-10-06 10:51:44	ga_ls9c_ard_3-2-1_105080_2022-10-06_final.stac-item
2022-10-07 09:56:07	ga_ls9c_ard_3-2-1_096080_2022-10-07_final.stac-item
2022-10-12 10:14:44	ga_ls9c_ard_3-2-1_099080_2022-10-12_final.stac-item
2022-10-13 10:58:00	ga_ls9c_ard_3-2-1_106080_2022-10-13_final.stac-item
2022-10-14 10:02:23	ga_ls9c_ard_3-2-1_097080_2022-10-14_final.stac-item
2022-10-17 10:33:18	ga_ls9c_ard_3-2-1_102080_2022-10-17_final.stac-item
2022-10-30 10:02:24	ga_ls9c_ard_3-2-1_097080_2022-10-30_final.stac-item
2022-11-07 10:51:50	ga_ls9c_ard_3-2-1_105080_2022-11-07_final.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-11-15 10:02:26	ga_ls9c_ard_3-2-1_097080_2022-11-15_final.stac-item
2022-11-23 10:51:51	ga_ls9c_ard_3-2-1_105080_2022-11-23_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
2022-12-16 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-12-16_final.stac-item
2022-12-25 10:51:48	ga_ls9c_ard_3-2-1_105080_2022-12-25_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2023-01-02 10:02:24	ga_ls9c_ard_3-2-1_097080_2023-01-02_final.stac-item
2023-01-10 10:51:50	ga_ls9c_ard_3-2-1_105080_2023-01-10_final.stac-item
2023-01-11 09:56:12	ga_ls9c_ard_3-2-1_096080_2023-01-11_final.stac-item
2023-01-19 10:45:32	ga_ls9c_ard_3-2-1_104080_2023-01-19_final.stac-item
2023-02-02 10:58:03	ga_ls9c_ard_3-2-1_106080_2023-02-02_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
2023-03-23 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
2023-04-17 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
2023-05-10 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
2023-06-11 10:01:20	ga_ls9c_ard_3-2-1_097080_2023-06-11_final.stac-item
2023-06-12 10:44:35	ga_ls9c_ard_3-2-1_104080_2023-06-12_final.stac-item
2023-06-19 10:50:43	ga_ls9c_ard_3-2-1_105080_2023-06-19_final.stac-item
2023-06-20 09:55:06	ga_ls9c_ard_3-2-1_096080_2023-06-20_final.stac-item
2023-06-27 10:01:19	ga_ls9c_ard_3-2-1_097080_2023-06-27_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