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
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-19 09:37:05	ga_ls9c_ard_3-2-1_093079_2022-01-19_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-02-23 10:08:15	ga_ls9c_ard_3-2-1_098080_2022-02-23_final.stac-item
2022-03-08 09:35:40	ga_ls9c_ard_3-2-1_093076_2022-03-08_final.stac-item
2022-04-09 09:36:45	ga_ls9c_ard_3-2-1_093079_2022-04-09_final.stac-item
2022-05-06 10:54:29	ga_ls9c_ard_3-2-1_106073_2022-05-06_final.stac-item
2022-06-02 10:34:11	ga_ls9c_ard_3-2-1_103069_2022-06-02_final.stac-item
2022-07-25 09:19:52	ga_ls9c_ard_3-2-1_090083_2022-07-24_final.stac-item
2022-07-30 11:12:58	ga_ls9c_ard_3-2-1_109072_2022-07-30_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-10-04 09:24:50	ga_ls9c_ard_3-2-1_091079_2022-10-03_final.stac-item
2022-10-05 11:45:22	ga_ls9c_ard_3-2-1_114075_2022-10-05_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-15 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-10-15_final.stac-item
2022-10-25 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-10-25_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-12 09:32:43	ga_ls9c_ard_3-2-1_092083_2022-11-12_final.stac-item
2022-11-12 11:12:00	ga_ls9c_ard_3-2-1_108084_2022-11-12_final.stac-item
2022-11-19 09:38:06	ga_ls9c_ard_3-2-1_093081_2022-11-19_final.stac-item
2022-11-19 11:16:59	ga_ls9c_ard_3-2-1_109081_2022-11-19_final.stac-item
2022-11-24 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-11-24_final.stac-item
2022-12-01 10:02:46	ga_ls9c_ard_3-2-1_097081_2022-12-01_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-14 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-14_final.stac-item
2022-12-20 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-20_final.stac-item
2022-12-26 09:57:23	ga_ls9c_ard_3-2-1_096083_2022-12-26_final.stac-item
2022-12-28 09:41:51	ga_ls9c_ard_3-2-1_094075_2022-12-28_final.stac-item
2022-12-30 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-30_final.stac-item
2023-01-02 10:01:37	ga_ls9c_ard_3-2-1_097078_2023-01-02_final.stac-item
2023-01-02 11:40:06	ga_ls9c_ard_3-2-1_113077_2023-01-02_final.stac-item
2023-01-06 11:16:58	ga_ls9c_ard_3-2-1_109081_2023-01-06_final.stac-item
2023-01-09 10:09:23	ga_ls9c_ard_3-2-1_098082_2023-01-09_final.stac-item
2023-01-13 09:46:13	ga_ls9c_ard_3-2-1_094086_2023-01-13_final.stac-item
2023-01-15 11:11:07	ga_ls9c_ard_3-2-1_108082_2023-01-15_final.stac-item
2023-01-17 09:19:03	ga_ls9c_ard_3-2-1_090080_2023-01-16_final.stac-item
2023-01-20 09:47:53	ga_ls9c_ard_3-2-1_095075_2023-01-20_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-22 11:14:50	ga_ls9c_ard_3-2-1_109076_2023-01-22_final.stac-item
2023-01-24 09:24:26	ga_ls9c_ard_3-2-1_091078_2023-01-23_final.stac-item
2023-01-24 09:26:01	ga_ls9c_ard_3-2-1_091082_2023-01-23_final.stac-item
2023-01-29 09:43:51	ga_ls9c_ard_3-2-1_094080_2023-01-29_final.stac-item
2023-01-29 11:22:44	ga_ls9c_ard_3-2-1_110080_2023-01-29_final.stac-item
2023-01-31 09:32:42	ga_ls9c_ard_3-2-1_092083_2023-01-31_final.stac-item
2023-02-02 09:20:22	ga_ls9c_ard_3-2-1_090083_2023-02-01_final.stac-item
2023-02-03 11:40:32	ga_ls9c_ard_3-2-1_113078_2023-02-03_final.stac-item
2023-02-04 10:44:31	ga_ls9c_ard_3-2-1_104077_2023-02-04_final.stac-item
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-05 09:51:18	ga_ls9c_ard_3-2-1_095083_2023-02-05_final.stac-item
2023-02-06 10:31:22	ga_ls9c_ard_3-2-1_102075_2023-02-06_final.stac-item
2023-02-07 11:17:26	ga_ls9c_ard_3-2-1_109082_2023-02-07_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-04-23 09:19:20	ga_ls9c_ard_3-2-1_090082_2023-04-22_final.stac-item
2023-04-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2023-04-23_final.stac-item
2023-04-26 09:47:24	ga_ls9c_ard_3-2-1_095075_2023-04-26_final.stac-item
2023-04-27 10:30:39	ga_ls9c_ard_3-2-1_102075_2023-04-27_final.stac-item
2023-04-28 09:38:36	ga_ls9c_ard_3-2-1_093084_2023-04-28_final.stac-item
2023-04-29 11:58:20	ga_ls9c_ard_3-2-1_116078_2023-04-29_final.stac-item
2023-05-28 09:46:41	ga_ls9c_ard_3-2-1_095074_2023-05-28_final.stac-item
2023-05-30 09:38:18	ga_ls9c_ard_3-2-1_093084_2023-05-30_final.stac-item
2023-07-17 09:35:15	ga_ls9c_ard_3-2-1_093076_2023-07-17_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-23 10:37:50	ga_ls9c_ard_3-2-1_103078_2023-07-23_final.stac-item
2023-07-28 09:18:44	ga_ls9c_ard_3-2-1_090081_2023-07-27_final.stac-item
2023-08-02 09:38:33	ga_ls9c_ard_3-2-1_093084_2023-08-02_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-03 11:57:31	ga_ls9c_ard_3-2-1_116076_2023-08-03_final.stac-item
2023-08-04 09:25:24	ga_ls9c_ard_3-2-1_091082_2023-08-03_final.stac-item
2023-10-17 11:39:05	ga_ls9c_ard_3-2-1_113075_2023-10-17_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-20 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-10-20_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-25 09:14:21	ga_ls9c_ard_3-2-1_089084_2023-10-24_final.stac-item
2023-10-26 09:52:48	ga_ls9c_ard_3-2-1_096072_2023-10-26_final.stac-item
2023-10-27 10:36:28	ga_ls9c_ard_3-2-1_103073_2023-10-27_final.stac-item
2023-10-28 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-28_final.stac-item
2023-10-30 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-10-30_final.stac-item
2023-10-30 11:10:31	ga_ls9c_ard_3-2-1_108081_2023-10-30_final.stac-item
2023-10-30 11:10:55	ga_ls9c_ard_3-2-1_108082_2023-10-30_final.stac-item
2023-11-02 10:01:17	ga_ls9c_ard_3-2-1_097078_2023-11-02_final.stac-item
2023-11-02 11:40:10	ga_ls9c_ard_3-2-1_113078_2023-11-02_final.stac-item
2023-11-03 10:45:20	ga_ls9c_ard_3-2-1_104080_2023-11-03_final.stac-item
2023-11-04 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-11-04_final.stac-item
2023-11-05 10:31:24	ga_ls9c_ard_3-2-1_102076_2023-11-05_final.stac-item
2023-11-14 10:24:51	ga_ls9c_ard_3-2-1_101075_2023-11-14_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-18 09:59:22	ga_ls9c_ard_3-2-1_097073_2023-11-18_final.stac-item
2023-11-18 11:40:15	ga_ls9c_ard_3-2-1_113078_2023-11-18_final.stac-item
2023-11-19 10:43:27	ga_ls9c_ard_3-2-1_104075_2023-11-19_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-11-20 11:29:07	ga_ls9c_ard_3-2-1_111081_2023-11-20_final.stac-item
2023-11-21 10:32:19	ga_ls9c_ard_3-2-1_102078_2023-11-21_final.stac-item
2023-11-22 09:37:06	ga_ls9c_ard_3-2-1_093079_2023-11-22_final.stac-item
2023-11-23 11:58:52	ga_ls9c_ard_3-2-1_116078_2023-11-23_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