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 09:58:56	ga_ls9c_ard_3-2-1_096085_2021-11-03_final.stac-item
2021-11-05 09:40:12	ga_ls9c_ard_3-2-1_093085_2021-11-05_final.stac-item
2021-11-10 09:42:40	ga_ls9c_ard_3-2-1_094085_2021-11-10_final.stac-item
2021-12-07 09:58:09	ga_ls9c_ard_3-2-1_096085_2021-12-07_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-23 09:58:04	ga_ls9c_ard_3-2-1_096085_2021-12-23_final.stac-item
2021-12-25 09:45:42	ga_ls9c_ard_3-2-1_094085_2021-12-25_final.stac-item
2022-01-03 09:39:31	ga_ls9c_ard_3-2-1_093085_2022-01-03_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-17 09:51:50	ga_ls9c_ard_3-2-1_095085_2022-01-17_final.stac-item
2022-01-26 09:45:41	ga_ls9c_ard_3-2-1_094085_2022-01-26_final.stac-item
2022-02-04 09:39:30	ga_ls9c_ard_3-2-1_093085_2022-02-04_final.stac-item
2022-02-09 09:58:01	ga_ls9c_ard_3-2-1_096085_2022-02-09_final.stac-item
2022-02-11 09:45:39	ga_ls9c_ard_3-2-1_094085_2022-02-11_final.stac-item
2022-02-27 09:45:28	ga_ls9c_ard_3-2-1_094085_2022-02-27_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-04-07 09:51:31	ga_ls9c_ard_3-2-1_095085_2022-04-07_final.stac-item
2022-04-09 09:39:08	ga_ls9c_ard_3-2-1_093085_2022-04-09_final.stac-item
2022-04-14 09:57:38	ga_ls9c_ard_3-2-1_096085_2022-04-14_final.stac-item
2022-04-16 09:45:15	ga_ls9c_ard_3-2-1_094085_2022-04-16_final.stac-item
2022-04-30 09:57:31	ga_ls9c_ard_3-2-1_096085_2022-04-30_final.stac-item
2022-05-02 09:45:33	ga_ls9c_ard_3-2-1_094086_2022-05-02_final.stac-item
2022-05-04 09:33:10	ga_ls9c_ard_3-2-1_092086_2022-05-04_final.stac-item
2022-05-11 09:38:53	ga_ls9c_ard_3-2-1_093085_2022-05-11_final.stac-item
2022-05-11 09:39:17	ga_ls9c_ard_3-2-1_093086_2022-05-11_final.stac-item
2022-05-18 09:44:57	ga_ls9c_ard_3-2-1_094085_2022-05-18_final.stac-item
2022-05-20 09:32:57	ga_ls9c_ard_3-2-1_092086_2022-05-20_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-25 09:51:30	ga_ls9c_ard_3-2-1_095086_2022-05-25_final.stac-item
2022-06-01 09:57:18	ga_ls9c_ard_3-2-1_096085_2022-06-01_final.stac-item
2022-06-03 09:44:57	ga_ls9c_ard_3-2-1_094085_2022-06-03_final.stac-item
2022-06-10 09:51:08	ga_ls9c_ard_3-2-1_095085_2022-06-10_final.stac-item
2022-06-17 09:57:25	ga_ls9c_ard_3-2-1_096085_2022-06-17_final.stac-item
2022-07-02 09:14:23	ga_ls9c_ard_3-2-1_089085_2022-07-01_final.stac-item
2022-07-03 09:57:38	ga_ls9c_ard_3-2-1_096085_2022-07-03_final.stac-item
2022-07-18 09:14:22	ga_ls9c_ard_3-2-1_089085_2022-07-17_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-07-21 09:45:19	ga_ls9c_ard_3-2-1_094085_2022-07-21_final.stac-item
2022-07-28 09:51:36	ga_ls9c_ard_3-2-1_095085_2022-07-28_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-06 09:45:32	ga_ls9c_ard_3-2-1_094085_2022-08-06_final.stac-item
2022-08-13 09:51:46	ga_ls9c_ard_3-2-1_095085_2022-08-13_final.stac-item
2022-08-20 09:57:59	ga_ls9c_ard_3-2-1_096085_2022-08-20_final.stac-item
2022-08-31 09:39:28	ga_ls9c_ard_3-2-1_093085_2022-08-31_final.stac-item
2022-09-05 09:58:00	ga_ls9c_ard_3-2-1_096085_2022-09-05_final.stac-item
2022-09-07 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-09-07_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-09-14 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-09-14_final.stac-item
2022-09-16 09:39:32	ga_ls9c_ard_3-2-1_093085_2022-09-16_final.stac-item
2022-09-21 09:58:06	ga_ls9c_ard_3-2-1_096085_2022-09-21_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-25 09:33:24	ga_ls9c_ard_3-2-1_092085_2022-09-25_final.stac-item
2022-09-30 09:51:57	ga_ls9c_ard_3-2-1_095085_2022-09-30_final.stac-item
2022-10-06 09:14:51	ga_ls9c_ard_3-2-1_089085_2022-10-05_final.stac-item
2022-10-07 09:58:07	ga_ls9c_ard_3-2-1_096085_2022-10-07_final.stac-item
2022-10-09 09:45:47	ga_ls9c_ard_3-2-1_094085_2022-10-09_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-11-07 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-11-06_final.stac-item
2022-11-08 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-11-08_final.stac-item
2022-11-23 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-11-22_final.stac-item
2022-12-09 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-12-08_final.stac-item
2022-12-21 09:40:03	ga_ls9c_ard_3-2-1_093086_2022-12-21_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2023-01-04 09:52:27	ga_ls9c_ard_3-2-1_095086_2023-01-04_final.stac-item
2023-01-10 09:14:57	ga_ls9c_ard_3-2-1_089085_2023-01-09_final.stac-item
2023-01-11 09:58:12	ga_ls9c_ard_3-2-1_096085_2023-01-11_final.stac-item
2023-01-26 09:14:54	ga_ls9c_ard_3-2-1_089085_2023-01-25_final.stac-item
2023-01-27 09:58:10	ga_ls9c_ard_3-2-1_096085_2023-01-27_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-02-23 09:39:55	ga_ls9c_ard_3-2-1_093086_2023-02-23_final.stac-item
2023-03-04 09:33:17	ga_ls9c_ard_3-2-1_092085_2023-03-04_final.stac-item
2023-03-11 09:39:46	ga_ls9c_ard_3-2-1_093086_2023-03-11_final.stac-item
2023-03-18 09:45:57	ga_ls9c_ard_3-2-1_094086_2023-03-18_final.stac-item
2023-03-20 09:33:10	ga_ls9c_ard_3-2-1_092085_2023-03-20_final.stac-item
2023-03-20 09:33:34	ga_ls9c_ard_3-2-1_092086_2023-03-20_final.stac-item
2023-04-01 09:57:44	ga_ls9c_ard_3-2-1_096085_2023-04-01_final.stac-item
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final.stac-item
2023-04-10 09:51:54	ga_ls9c_ard_3-2-1_095086_2023-04-10_final.stac-item
2023-04-12 09:39:31	ga_ls9c_ard_3-2-1_093086_2023-04-12_final.stac-item
2023-04-16 09:14:21	ga_ls9c_ard_3-2-1_089085_2023-04-15_final.stac-item
2023-04-17 09:57:37	ga_ls9c_ard_3-2-1_096085_2023-04-17_final.stac-item
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final.stac-item
2023-04-21 09:33:18	ga_ls9c_ard_3-2-1_092086_2023-04-21_final.stac-item
2023-04-26 09:51:48	ga_ls9c_ard_3-2-1_095086_2023-04-26_final.stac-item
2023-05-02 09:14:13	ga_ls9c_ard_3-2-1_089085_2023-05-01_final.stac-item
2023-05-03 09:57:27	ga_ls9c_ard_3-2-1_096085_2023-05-03_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-18 09:14:05	ga_ls9c_ard_3-2-1_089085_2023-05-17_final.stac-item
2023-05-19 09:57:20	ga_ls9c_ard_3-2-1_096085_2023-05-19_final.stac-item
2023-05-19 09:57:44	ga_ls9c_ard_3-2-1_096086_2023-05-19_final.stac-item
2023-06-04 09:57:14	ga_ls9c_ard_3-2-1_096085_2023-06-04_final.stac-item
2023-06-08 09:32:28	ga_ls9c_ard_3-2-1_092085_2023-06-08_final.stac-item
2023-06-19 09:13:50	ga_ls9c_ard_3-2-1_089085_2023-06-18_final.stac-item
2023-06-20 09:57:06	ga_ls9c_ard_3-2-1_096085_2023-06-20_final.stac-item
2023-07-05 09:14:02	ga_ls9c_ard_3-2-1_089085_2023-07-04_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