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

82 results

Time (local)	Label
2021-12-04 11:00:59	ga_ls9c_ard_3-2-1_107072_2021-12-04_final.stac-item
2021-12-13 09:23:00	ga_ls9c_ard_3-2-1_090090_2021-12-12_final.stac-item
2021-12-13 10:59:05	ga_ls9c_ard_3-2-1_106083_2021-12-13_final.stac-item
2021-12-27 09:32:09	ga_ls9c_ard_3-2-1_092082_2021-12-27_final.stac-item
2021-12-27 09:33:20	ga_ls9c_ard_3-2-1_092085_2021-12-27_final.stac-item
2022-01-09 10:34:54	ga_ls9c_ard_3-2-1_103069_2022-01-09_final.stac-item
2022-02-10 10:35:41	ga_ls9c_ard_3-2-1_103071_2022-02-10_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 09:44:45	ga_ls9c_ard_3-2-1_094084_2022-05-02_final.stac-item
2022-05-06 10:53:17	ga_ls9c_ard_3-2-1_106070_2022-05-06_final.stac-item
2022-05-21 10:13:50	ga_ls9c_ard_3-2-1_099080_2022-05-21_final.stac-item
2022-05-22 10:54:42	ga_ls9c_ard_3-2-1_106074_2022-05-22_final.stac-item
2022-05-27 11:12:50	ga_ls9c_ard_3-2-1_109073_2022-05-27_final.stac-item
2022-05-27 11:16:01	ga_ls9c_ard_3-2-1_109081_2022-05-27_final.stac-item
2022-06-18 10:34:42	ga_ls9c_ard_3-2-1_103070_2022-06-18_final.stac-item
2022-06-19 09:40:19	ga_ls9c_ard_3-2-1_094073_2022-06-19_final.stac-item
2022-06-22 10:16:07	ga_ls9c_ard_3-2-1_099085_2022-06-22_final.stac-item
2022-06-25 10:45:30	ga_ls9c_ard_3-2-1_104081_2022-06-25_final.stac-item
2022-07-18 09:09:58	ga_ls9c_ard_3-2-1_089074_2022-07-17_final.stac-item
2022-07-23 11:08:17	ga_ls9c_ard_3-2-1_108076_2022-07-23_final.stac-item
2022-08-04 09:58:16	ga_ls9c_ard_3-2-1_096086_2022-08-04_final.stac-item
2022-08-29 09:48:14	ga_ls9c_ard_3-2-1_095076_2022-08-29_final.stac-item
2022-09-16 11:15:13	ga_ls9c_ard_3-2-1_109077_2022-09-16_final.stac-item
2022-09-23 09:40:58	ga_ls9c_ard_3-2-1_094073_2022-09-23_final.stac-item
2022-10-21 10:08:59	ga_ls9c_ard_3-2-1_098081_2022-10-21_final.stac-item
2022-10-22 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-10-21_final.stac-item
2022-10-30 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-30_final.stac-item
2022-11-17 09:47:40	ga_ls9c_ard_3-2-1_095074_2022-11-17_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-29 10:12:21	ga_ls9c_ard_3-2-1_099074_2022-11-29_final.stac-item
2022-12-09 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-12-09_final.stac-item
2022-12-25 09:16:54	ga_ls9c_ard_3-2-1_089090_2022-12-24_final.stac-item
2022-12-28 09:46:38	ga_ls9c_ard_3-2-1_094087_2022-12-28_final.stac-item
2023-01-01 09:19:57	ga_ls9c_ard_3-2-1_090082_2022-12-31_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-02-19 10:04:20	ga_ls9c_ard_3-2-1_097085_2023-02-19_final.stac-item
2023-02-23 09:40:43	ga_ls9c_ard_3-2-1_093088_2023-02-23_final.stac-item
2023-03-11 11:16:39	ga_ls9c_ard_3-2-1_109081_2023-03-11_final.stac-item
2023-03-13 09:29:01	ga_ls9c_ard_3-2-1_091090_2023-03-12_final.stac-item
2023-03-14 11:44:47	ga_ls9c_ard_3-2-1_114074_2023-03-14_final.stac-item
2023-03-20 09:31:59	ga_ls9c_ard_3-2-1_092082_2023-03-20_final.stac-item
2023-04-12 09:38:19	ga_ls9c_ard_3-2-1_093083_2023-04-12_final.stac-item
2023-04-20 10:24:56	ga_ls9c_ard_3-2-1_101076_2023-04-20_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-05-07 11:05:12	ga_ls9c_ard_3-2-1_108069_2023-05-07_final.stac-item
2023-05-16 09:23:41	ga_ls9c_ard_3-2-1_091078_2023-05-15_final.stac-item
2023-05-31 10:19:58	ga_ls9c_ard_3-2-1_100080_2023-05-31_final.stac-item
2023-06-04 11:33:43	ga_ls9c_ard_3-2-1_112079_2023-06-04_final.stac-item
2023-06-19 09:13:02	ga_ls9c_ard_3-2-1_089083_2023-06-18_final.stac-item
2023-08-03 10:19:49	ga_ls9c_ard_3-2-1_100079_2023-08-03_final.stac-item
2023-08-14 11:41:25	ga_ls9c_ard_3-2-1_113082_2023-08-14_final.stac-item
2023-08-20 09:22:17	ga_ls9c_ard_3-2-1_091074_2023-08-19_final.stac-item
2023-09-16 10:46:06	ga_ls9c_ard_3-2-1_104082_2023-09-16_final.stac-item
2023-09-17 11:29:22	ga_ls9c_ard_3-2-1_111082_2023-09-17_final.stac-item
2023-09-26 09:46:14	ga_ls9c_ard_3-2-1_094087_2023-09-26_final.stac-item
2023-10-03 11:23:47	ga_ls9c_ard_3-2-1_111068_2023-10-03_final.stac-item
2023-10-07 11:02:17	ga_ls9c_ard_3-2-1_107076_2023-10-07_final.stac-item
2023-10-08 10:03:53	ga_ls9c_ard_3-2-1_098069_2023-10-08_final.stac-item
2023-10-21 11:12:47	ga_ls9c_ard_3-2-1_109071_2023-10-21_final.stac-item
2023-10-27 10:36:28	ga_ls9c_ard_3-2-1_103073_2023-10-27_final.stac-item
2023-11-06 09:37:00	ga_ls9c_ard_3-2-1_093079_2023-11-06_final.stac-item
2023-11-06 09:39:23	ga_ls9c_ard_3-2-1_093085_2023-11-06_final.stac-item
2023-11-09 10:10:19	ga_ls9c_ard_3-2-1_098085_2023-11-09_final.stac-item
2023-11-13 11:18:53	ga_ls9c_ard_3-2-1_110071_2023-11-13_final.stac-item
2023-11-25 11:45:20	ga_ls9c_ard_3-2-1_114075_2023-11-25_final.stac-item
2023-12-02 11:51:54	ga_ls9c_ard_3-2-1_115076_2023-12-02_final.stac-item
2023-12-04 11:39:55	ga_ls9c_ard_3-2-1_113077_2023-12-04_final.stac-item
2023-12-18 11:51:08	ga_ls9c_ard_3-2-1_115074_2023-12-18_final.stac-item
2023-12-24 11:12:05	ga_ls9c_ard_3-2-1_109069_2023-12-24_final.stac-item
2023-12-24 11:17:40	ga_ls9c_ard_3-2-1_109083_2023-12-24_final.stac-item
2023-12-27 10:07:16	ga_ls9c_ard_3-2-1_098077_2023-12-27_final.stac-item
2024-01-10 10:21:33	ga_ls9c_ard_3-2-1_100082_2024-01-10_final.stac-item
2024-01-25 11:17:08	ga_ls9c_ard_3-2-1_109082_2024-01-25_final.stac-item
2024-01-30 09:53:16	ga_ls9c_ard_3-2-1_096073_2024-01-30_final.stac-item
2024-02-10 09:35:33	ga_ls9c_ard_3-2-1_093075_2024-02-10_final.stac-item
2024-02-29 11:47:10	ga_ls9c_ard_3-2-1_114080_2024-02-29_final.stac-item
2024-03-16 10:09:05	ga_ls9c_ard_3-2-1_098082_2024-03-16_final.stac-item
2024-03-29 09:39:38	ga_ls9c_ard_3-2-1_093086_2024-03-29_final.stac-item
2024-04-13 10:30:47	ga_ls9c_ard_3-2-1_102075_2024-04-13_final.stac-item
2024-04-20 10:34:25	ga_ls9c_ard_3-2-1_103069_2024-04-20_final.stac-item
2024-04-30 09:36:51	ga_ls9c_ard_3-2-1_093080_2024-04-30_nrt.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