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 09:43:09	ga_ls9c_ard_3-2-1_094080_2021-11-15_final.stac-item
2021-12-07 09:56:09	ga_ls9c_ard_3-2-1_096080_2021-12-07_final.stac-item
2021-12-16 09:49:52	ga_ls9c_ard_3-2-1_095080_2021-12-16_final.stac-item
2021-12-16 09:50:16	ga_ls9c_ard_3-2-1_095081_2021-12-16_final.stac-item
2021-12-25 09:43:42	ga_ls9c_ard_3-2-1_094080_2021-12-25_final.stac-item
2022-01-01 09:49:53	ga_ls9c_ard_3-2-1_095080_2022-01-01_final.stac-item
2022-01-01 09:50:17	ga_ls9c_ard_3-2-1_095081_2022-01-01_final.stac-item
2022-01-08 09:56:02	ga_ls9c_ard_3-2-1_096080_2022-01-08_final.stac-item
2022-01-08 09:56:26	ga_ls9c_ard_3-2-1_096081_2022-01-08_final.stac-item
2022-01-10 09:43:40	ga_ls9c_ard_3-2-1_094080_2022-01-10_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 09:49:51	ga_ls9c_ard_3-2-1_095080_2022-01-17_final.stac-item
2022-01-17 09:50:14	ga_ls9c_ard_3-2-1_095081_2022-01-17_final.stac-item
2022-01-24 09:56:27	ga_ls9c_ard_3-2-1_096081_2022-01-24_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-09 09:56:01	ga_ls9c_ard_3-2-1_096080_2022-02-09_final.stac-item
2022-02-09 09:56:25	ga_ls9c_ard_3-2-1_096081_2022-02-09_final.stac-item
2022-02-18 09:49:46	ga_ls9c_ard_3-2-1_095080_2022-02-18_final.stac-item
2022-02-27 09:43:28	ga_ls9c_ard_3-2-1_094080_2022-02-27_final.stac-item
2022-03-20 10:01:57	ga_ls9c_ard_3-2-1_097080_2022-03-20_final.stac-item
2022-03-22 09:49:35	ga_ls9c_ard_3-2-1_095080_2022-03-22_final.stac-item
2022-03-24 09:37:12	ga_ls9c_ard_3-2-1_093080_2022-03-24_final.stac-item
2022-04-05 10:01:53	ga_ls9c_ard_3-2-1_097080_2022-04-05_final.stac-item
2022-04-16 09:43:15	ga_ls9c_ard_3-2-1_094080_2022-04-16_final.stac-item
2022-04-16 09:43:39	ga_ls9c_ard_3-2-1_094081_2022-04-16_final.stac-item
2022-04-21 10:01:43	ga_ls9c_ard_3-2-1_097080_2022-04-21_final.stac-item
2022-04-23 09:49:45	ga_ls9c_ard_3-2-1_095081_2022-04-23_final.stac-item
2022-04-30 09:55:55	ga_ls9c_ard_3-2-1_096081_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
2022-05-16 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
2022-06-01 09:55:18	ga_ls9c_ard_3-2-1_096080_2022-06-01_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-10 09:49:08	ga_ls9c_ard_3-2-1_095080_2022-06-10_final.stac-item
2022-06-10 09:49:32	ga_ls9c_ard_3-2-1_095081_2022-06-10_final.stac-item
2022-06-17 09:55:49	ga_ls9c_ard_3-2-1_096081_2022-06-17_final.stac-item
2022-07-19 09:56:03	ga_ls9c_ard_3-2-1_096081_2022-07-19_final.stac-item
2022-07-28 09:49:36	ga_ls9c_ard_3-2-1_095080_2022-07-28_final.stac-item
2022-08-06 09:43:32	ga_ls9c_ard_3-2-1_094080_2022-08-06_final.stac-item
2022-08-13 09:50:11	ga_ls9c_ard_3-2-1_095081_2022-08-13_final.stac-item
2022-08-20 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-08-20_final.stac-item
2022-08-29 09:49:50	ga_ls9c_ard_3-2-1_095080_2022-08-29_final.stac-item
2022-09-05 09:56:00	ga_ls9c_ard_3-2-1_096080_2022-09-05_final.stac-item
2022-09-05 09:56:24	ga_ls9c_ard_3-2-1_096081_2022-09-05_final.stac-item
2022-09-14 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-09-14_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
2022-10-02 09:37:36	ga_ls9c_ard_3-2-1_093080_2022-10-02_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 09:43:47	ga_ls9c_ard_3-2-1_094080_2022-10-09_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 09:43:52	ga_ls9c_ard_3-2-1_094080_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
2022-11-01 09:50:01	ga_ls9c_ard_3-2-1_095080_2022-11-01_final.stac-item
2022-11-01 09:50:25	ga_ls9c_ard_3-2-1_095081_2022-11-01_final.stac-item
2022-11-03 09:37:38	ga_ls9c_ard_3-2-1_093080_2022-11-03_final.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-11-08 09:56:37	ga_ls9c_ard_3-2-1_096081_2022-11-08_final.stac-item
2022-11-10 09:43:52	ga_ls9c_ard_3-2-1_094080_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
2022-11-24 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-11-24_final.stac-item
2022-11-24 09:56:38	ga_ls9c_ard_3-2-1_096081_2022-11-24_final.stac-item
2022-11-26 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-11-26_final.stac-item
2022-12-01 10:02:22	ga_ls9c_ard_3-2-1_097080_2022-12-01_final.stac-item
2022-12-03 09:50:00	ga_ls9c_ard_3-2-1_095080_2022-12-03_final.stac-item
2022-12-03 09:50:24	ga_ls9c_ard_3-2-1_095081_2022-12-03_final.stac-item
2022-12-05 09:37:40	ga_ls9c_ard_3-2-1_093080_2022-12-05_final.stac-item
2022-12-19 09:50:01	ga_ls9c_ard_3-2-1_095080_2022-12-19_final.stac-item
2022-12-19 09:50:25	ga_ls9c_ard_3-2-1_095081_2022-12-19_final.stac-item
2022-12-21 09:37:39	ga_ls9c_ard_3-2-1_093080_2022-12-21_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2022-12-26 09:56:35	ga_ls9c_ard_3-2-1_096081_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
2023-01-04 09:50:27	ga_ls9c_ard_3-2-1_095081_2023-01-04_final.stac-item
2023-01-06 09:37:41	ga_ls9c_ard_3-2-1_093080_2023-01-06_final.stac-item
2023-01-11 09:56:12	ga_ls9c_ard_3-2-1_096080_2023-01-11_final.stac-item
2023-01-11 09:56:36	ga_ls9c_ard_3-2-1_096081_2023-01-11_final.stac-item
2023-01-13 09:43:50	ga_ls9c_ard_3-2-1_094080_2023-01-13_final.stac-item
2023-01-20 09:49:53	ga_ls9c_ard_3-2-1_095080_2023-01-20_final.stac-item
2023-01-29 09:43:51	ga_ls9c_ard_3-2-1_094080_2023-01-29_final.stac-item
2023-02-14 09:43:54	ga_ls9c_ard_3-2-1_094080_2023-02-14_final.stac-item
2023-03-02 09:43:40	ga_ls9c_ard_3-2-1_094080_2023-03-02_final.stac-item
2023-03-09 09:50:08	ga_ls9c_ard_3-2-1_095081_2023-03-09_final.stac-item
2023-03-16 09:56:19	ga_ls9c_ard_3-2-1_096081_2023-03-16_final.stac-item
2023-03-18 09:43:33	ga_ls9c_ard_3-2-1_094080_2023-03-18_final.stac-item
2023-03-23 10:02:03	ga_ls9c_ard_3-2-1_097080_2023-03-23_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
2023-04-17 09:56:02	ga_ls9c_ard_3-2-1_096081_2023-04-17_final.stac-item
2023-04-19 09:43:16	ga_ls9c_ard_3-2-1_094080_2023-04-19_final.stac-item
2023-05-05 09:43:04	ga_ls9c_ard_3-2-1_094080_2023-05-05_final.stac-item
2023-05-10 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-05-10_final.stac-item
2023-05-30 09:36:43	ga_ls9c_ard_3-2-1_093080_2023-05-30_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 09:42:44	ga_ls9c_ard_3-2-1_094080_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
2023-06-29 09:49:01	ga_ls9c_ard_3-2-1_095080_2023-06-29_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