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
2021-11-07 10:59:20	ga_ls9c_ard_3-2-1_106083_2021-11-07_final.stac-item
2021-11-15 09:44:21	ga_ls9c_ard_3-2-1_094083_2021-11-15_final.stac-item
2021-11-16 10:24:42	ga_ls9c_ard_3-2-1_100084_2021-11-16_final.stac-item
2021-12-09 09:44:58	ga_ls9c_ard_3-2-1_094083_2021-12-09_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-16 09:51:04	ga_ls9c_ard_3-2-1_095083_2021-12-16_final.stac-item
2021-12-29 10:59:04	ga_ls9c_ard_3-2-1_106083_2021-12-29_final.stac-item
2022-01-14 10:59:00	ga_ls9c_ard_3-2-1_106083_2022-01-14_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-11 09:44:51	ga_ls9c_ard_3-2-1_094083_2022-02-11_final.stac-item
2022-02-18 09:50:58	ga_ls9c_ard_3-2-1_095083_2022-02-18_final.stac-item
2022-02-27 09:44:40	ga_ls9c_ard_3-2-1_094083_2022-02-27_final.stac-item
2022-03-01 09:32:41	ga_ls9c_ard_3-2-1_092084_2022-03-01_final.stac-item
2022-03-01 11:11:34	ga_ls9c_ard_3-2-1_108084_2022-03-01_final.stac-item
2022-03-19 10:58:47	ga_ls9c_ard_3-2-1_106083_2022-03-19_final.stac-item
2022-03-22 09:50:46	ga_ls9c_ard_3-2-1_095083_2022-03-22_final.stac-item
2022-03-31 09:44:34	ga_ls9c_ard_3-2-1_094083_2022-03-31_final.stac-item
2022-04-07 09:50:43	ga_ls9c_ard_3-2-1_095083_2022-04-07_final.stac-item
2022-04-23 09:50:33	ga_ls9c_ard_3-2-1_095083_2022-04-23_final.stac-item
2022-05-02 09:44:21	ga_ls9c_ard_3-2-1_094083_2022-05-02_final.stac-item
2022-05-09 09:50:28	ga_ls9c_ard_3-2-1_095083_2022-05-09_final.stac-item
2022-05-29 09:25:59	ga_ls9c_ard_3-2-1_091084_2022-05-28_final.stac-item
2022-06-05 09:32:11	ga_ls9c_ard_3-2-1_092084_2022-06-05_final.stac-item
2022-06-05 11:11:04	ga_ls9c_ard_3-2-1_108084_2022-06-05_final.stac-item
2022-06-10 09:50:20	ga_ls9c_ard_3-2-1_095083_2022-06-10_final.stac-item
2022-06-21 09:32:25	ga_ls9c_ard_3-2-1_092084_2022-06-21_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-30 09:26:21	ga_ls9c_ard_3-2-1_091084_2022-06-29_final.stac-item
2022-07-07 11:11:23	ga_ls9c_ard_3-2-1_108084_2022-07-07_final.stac-item
2022-07-12 09:50:36	ga_ls9c_ard_3-2-1_095083_2022-07-12_final.stac-item
2022-07-23 11:11:29	ga_ls9c_ard_3-2-1_108084_2022-07-23_final.stac-item
2022-07-25 10:58:45	ga_ls9c_ard_3-2-1_106083_2022-07-25_final.stac-item
2022-08-01 11:05:25	ga_ls9c_ard_3-2-1_107084_2022-08-01_final.stac-item
2022-08-10 10:58:56	ga_ls9c_ard_3-2-1_106083_2022-08-10_final.stac-item
2022-08-17 11:05:34	ga_ls9c_ard_3-2-1_107084_2022-08-17_final.stac-item
2022-08-26 10:59:01	ga_ls9c_ard_3-2-1_106083_2022-08-26_final.stac-item
2022-09-07 09:44:50	ga_ls9c_ard_3-2-1_094083_2022-09-07_final.stac-item
2022-09-09 09:32:52	ga_ls9c_ard_3-2-1_092084_2022-09-09_final.stac-item
2022-09-09 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-09-09_final.stac-item
2022-09-14 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-09-14_final.stac-item
2022-09-25 11:11:53	ga_ls9c_ard_3-2-1_108084_2022-09-25_final.stac-item
2022-10-09 09:44:59	ga_ls9c_ard_3-2-1_094083_2022-10-09_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-11 11:11:56	ga_ls9c_ard_3-2-1_108084_2022-10-11_final.stac-item
2022-10-16 09:51:14	ga_ls9c_ard_3-2-1_095083_2022-10-16_final.stac-item
2022-10-27 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-10-27_final.stac-item
2022-10-29 10:59:13	ga_ls9c_ard_3-2-1_106083_2022-10-29_final.stac-item
2022-11-01 09:51:13	ga_ls9c_ard_3-2-1_095083_2022-11-01_final.stac-item
2022-11-05 11:05:46	ga_ls9c_ard_3-2-1_107084_2022-11-05_final.stac-item
2022-11-10 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-11-10_final.stac-item
2022-11-14 10:59:15	ga_ls9c_ard_3-2-1_106083_2022-11-14_final.stac-item
2022-11-28 11:11:58	ga_ls9c_ard_3-2-1_108084_2022-11-28_final.stac-item
2022-12-07 11:05:24	ga_ls9c_ard_3-2-1_107083_2022-12-07_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2022-12-14 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-14_final.stac-item
2022-12-19 09:51:13	ga_ls9c_ard_3-2-1_095083_2022-12-19_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-13 09:45:01	ga_ls9c_ard_3-2-1_094083_2023-01-13_final.stac-item
2023-01-29 09:45:03	ga_ls9c_ard_3-2-1_094083_2023-01-29_final.stac-item
2023-02-05 09:51:18	ga_ls9c_ard_3-2-1_095083_2023-02-05_final.stac-item
2023-02-09 11:05:28	ga_ls9c_ard_3-2-1_107083_2023-02-09_final.stac-item
2023-02-14 09:45:05	ga_ls9c_ard_3-2-1_094083_2023-02-14_final.stac-item
2023-02-18 10:59:11	ga_ls9c_ard_3-2-1_106083_2023-02-18_final.stac-item
2023-03-13 11:05:06	ga_ls9c_ard_3-2-1_107083_2023-03-13_final.stac-item
2023-03-18 09:44:45	ga_ls9c_ard_3-2-1_094083_2023-03-18_final.stac-item
2023-04-03 09:44:34	ga_ls9c_ard_3-2-1_094083_2023-04-03_final.stac-item
2023-04-10 09:50:42	ga_ls9c_ard_3-2-1_095083_2023-04-10_final.stac-item
2023-04-14 11:04:48	ga_ls9c_ard_3-2-1_107083_2023-04-14_final.stac-item
2023-04-26 09:50:36	ga_ls9c_ard_3-2-1_095083_2023-04-26_final.stac-item
2023-05-05 09:44:15	ga_ls9c_ard_3-2-1_094083_2023-05-05_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-05-21 09:44:09	ga_ls9c_ard_3-2-1_094083_2023-05-21_final.stac-item
2023-05-28 09:50:16	ga_ls9c_ard_3-2-1_095083_2023-05-28_final.stac-item
2023-06-13 09:50:09	ga_ls9c_ard_3-2-1_095083_2023-06-13_final.stac-item
2023-06-22 09:43:56	ga_ls9c_ard_3-2-1_094083_2023-06-22_final.stac-item
2023-06-29 09:50:13	ga_ls9c_ard_3-2-1_095083_2023-06-29_final.stac-item
2023-08-25 09:44:29	ga_ls9c_ard_3-2-1_094083_2023-08-25_final.stac-item
2023-09-01 09:50:44	ga_ls9c_ard_3-2-1_095083_2023-09-01_final.stac-item
2023-09-17 09:50:52	ga_ls9c_ard_3-2-1_095083_2023-09-17_final.stac-item
2023-10-03 09:50:53	ga_ls9c_ard_3-2-1_095083_2023-10-03_final.stac-item
2023-10-19 09:51:03	ga_ls9c_ard_3-2-1_095083_2023-10-19_final.stac-item
2023-11-04 09:50:55	ga_ls9c_ard_3-2-1_095083_2023-11-04_final.stac-item
2023-11-20 09:51:02	ga_ls9c_ard_3-2-1_095083_2023-11-20_final.stac-item
2023-11-29 09:44:55	ga_ls9c_ard_3-2-1_094083_2023-11-29_final.stac-item
2023-12-06 09:51:02	ga_ls9c_ard_3-2-1_095083_2023-12-06_final.stac-item
2023-12-22 09:51:08	ga_ls9c_ard_3-2-1_095083_2023-12-22_final.stac-item
2023-12-31 09:44:55	ga_ls9c_ard_3-2-1_094083_2023-12-31_final.stac-item
2024-01-07 09:51:01	ga_ls9c_ard_3-2-1_095083_2024-01-07_final.stac-item
2024-01-23 09:51:01	ga_ls9c_ard_3-2-1_095083_2024-01-23_final.stac-item
2024-02-08 09:51:06	ga_ls9c_ard_3-2-1_095083_2024-02-08_final.stac-item
2024-02-17 09:44:49	ga_ls9c_ard_3-2-1_094083_2024-02-17_final.stac-item
2024-02-24 09:50:52	ga_ls9c_ard_3-2-1_095083_2024-02-24_final.stac-item
2024-03-11 09:50:58	ga_ls9c_ard_3-2-1_095083_2024-03-11_final.stac-item
2024-03-20 09:44:46	ga_ls9c_ard_3-2-1_094083_2024-03-20_final.stac-item
2024-03-27 09:50:51	ga_ls9c_ard_3-2-1_095083_2024-03-27_final.stac-item
2024-04-05 09:44:37	ga_ls9c_ard_3-2-1_094083_2024-04-05_final.stac-item
2024-04-12 09:50:44	ga_ls9c_ard_3-2-1_095083_2024-04-12_final.stac-item
2024-04-21 09:44:21	ga_ls9c_ard_3-2-1_094083_2024-04-21_final.stac-item
2024-04-28 09:50:25	ga_ls9c_ard_3-2-1_095083_2024-04-28_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