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

65 results

Time (local)	Label
2021-11-12 10:57:25	ga_ls9c_ard_3-2-1_106072_2021-11-12_final.stac-item
2021-11-17 09:22:04	ga_ls9c_ard_3-2-1_091074_2021-11-16_final.stac-item
2022-02-11 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-02-11_final.stac-item
2022-02-16 09:58:09	ga_ls9c_ard_3-2-1_097070_2022-02-16_final.stac-item
2022-03-03 10:52:48	ga_ls9c_ard_3-2-1_106068_2022-03-03_final.stac-item
2022-03-06 11:24:07	ga_ls9c_ard_3-2-1_111069_2022-03-06_final.stac-item
2022-04-04 09:17:26	ga_ls9c_ard_3-2-1_090077_2022-04-03_final.stac-item
2022-04-04 09:21:50	ga_ls9c_ard_3-2-1_090088_2022-04-03_final.stac-item
2022-06-01 09:56:54	ga_ls9c_ard_3-2-1_096084_2022-06-01_final.stac-item
2022-06-19 11:18:00	ga_ls9c_ard_3-2-1_110070_2022-06-19_final.stac-item
2022-07-01 10:07:37	ga_ls9c_ard_3-2-1_098079_2022-07-01_final.stac-item
2022-07-02 10:49:40	ga_ls9c_ard_3-2-1_105076_2022-07-02_final.stac-item
2022-07-09 09:21:20	ga_ls9c_ard_3-2-1_090087_2022-07-08_final.stac-item
2022-07-09 09:22:07	ga_ls9c_ard_3-2-1_090089_2022-07-08_final.stac-item
2022-07-18 10:49:39	ga_ls9c_ard_3-2-1_105076_2022-07-18_final.stac-item
2022-07-21 11:18:13	ga_ls9c_ard_3-2-1_110070_2022-07-21_final.stac-item
2022-07-24 10:15:52	ga_ls9c_ard_3-2-1_099084_2022-07-24_final.stac-item
2022-08-01 09:22:33	ga_ls9c_ard_3-2-1_091074_2022-07-31_final.stac-item
2022-08-18 10:09:57	ga_ls9c_ard_3-2-1_098084_2022-08-18_final.stac-item
2022-10-27 11:08:00	ga_ls9c_ard_3-2-1_108074_2022-10-27_final.stac-item
2022-10-30 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-10-30_final.stac-item
2022-10-30 11:38:05	ga_ls9c_ard_3-2-1_113072_2022-10-30_final.stac-item
2022-11-03 09:38:50	ga_ls9c_ard_3-2-1_093083_2022-11-03_final.stac-item
2022-11-21 09:26:56	ga_ls9c_ard_3-2-1_091084_2022-11-20_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-15 10:10:22	ga_ls9c_ard_3-2-1_099069_2022-12-15_final.stac-item
2022-12-15 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-15_final.stac-item
2022-12-16 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-12-16_final.stac-item
2022-12-20 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-20_final.stac-item
2023-01-06 11:12:59	ga_ls9c_ard_3-2-1_109071_2023-01-06_final.stac-item
2023-01-10 10:47:51	ga_ls9c_ard_3-2-1_105070_2023-01-10_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-03-03 10:26:07	ga_ls9c_ard_3-2-1_101078_2023-03-03_final.stac-item
2023-03-27 09:34:03	ga_ls9c_ard_3-2-1_093072_2023-03-27_final.stac-item
2023-04-06 10:10:40	ga_ls9c_ard_3-2-1_099071_2023-04-06_final.stac-item
2023-04-11 10:33:33	ga_ls9c_ard_3-2-1_102082_2023-04-11_final.stac-item
2023-04-24 10:01:47	ga_ls9c_ard_3-2-1_097080_2023-04-24_final.stac-item
2023-05-07 09:33:06	ga_ls9c_ard_3-2-1_092086_2023-05-07_final.stac-item
2023-05-08 10:09:59	ga_ls9c_ard_3-2-1_099070_2023-05-08_final.stac-item
2023-05-09 09:22:20	ga_ls9c_ard_3-2-1_090090_2023-05-08_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-06-08 09:28:05	ga_ls9c_ard_3-2-1_092074_2023-06-07_final.stac-item
2023-06-18 10:03:52	ga_ls9c_ard_3-2-1_098071_2023-06-18_final.stac-item
2023-06-25 10:09:15	ga_ls9c_ard_3-2-1_099069_2023-06-25_final.stac-item
2023-07-04 10:08:51	ga_ls9c_ard_3-2-1_098083_2023-07-04_final.stac-item
2023-07-05 10:51:19	ga_ls9c_ard_3-2-1_105081_2023-07-05_final.stac-item
2023-09-03 09:40:23	ga_ls9c_ard_3-2-1_093088_2023-09-03_final.stac-item
2023-09-13 10:10:48	ga_ls9c_ard_3-2-1_099071_2023-09-13_final.stac-item
2023-09-19 09:40:30	ga_ls9c_ard_3-2-1_093088_2023-09-19_final.stac-item
2023-10-15 11:51:26	ga_ls9c_ard_3-2-1_115075_2023-10-15_final.stac-item
2023-10-23 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-10-23_final.stac-item
2023-11-10 09:14:41	ga_ls9c_ard_3-2-1_089085_2023-11-09_final.stac-item
2023-11-17 10:54:34	ga_ls9c_ard_3-2-1_106072_2023-11-17_final.stac-item
2023-12-08 11:14:21	ga_ls9c_ard_3-2-1_109075_2023-12-08_final.stac-item
2023-12-11 10:10:24	ga_ls9c_ard_3-2-1_098085_2023-12-11_final.stac-item
2023-12-25 10:17:15	ga_ls9c_ard_3-2-1_100071_2023-12-25_final.stac-item
2023-12-27 10:04:05	ga_ls9c_ard_3-2-1_098069_2023-12-27_final.stac-item
2024-01-17 10:26:09	ga_ls9c_ard_3-2-1_101078_2024-01-17_final.stac-item
2024-01-21 11:38:41	ga_ls9c_ard_3-2-1_113074_2024-01-21_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-14 10:17:04	ga_ls9c_ard_3-2-1_100071_2024-03-14_final.stac-item
2024-03-16 10:09:29	ga_ls9c_ard_3-2-1_098083_2024-03-16_final.stac-item
2024-03-24 10:52:54	ga_ls9c_ard_3-2-1_106068_2024-03-24_final.stac-item
2024-04-28 11:24:55	ga_ls9c_ard_3-2-1_111072_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