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
2021-11-08 11:38:53	ga_ls9c_ard_3-2-1_113082_2021-11-08_final.stac-item
2021-11-10 11:15:46	ga_ls9c_ard_3-2-1_110071_2021-11-10_final.stac-item
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2021-12-13 10:57:05	ga_ls9c_ard_3-2-1_106078_2021-12-13_final.stac-item
2022-01-04 10:20:46	ga_ls9c_ard_3-2-1_100080_2022-01-04_final.stac-item
2022-01-09 10:35:18	ga_ls9c_ard_3-2-1_103070_2022-01-09_final.stac-item
2022-01-10 11:18:57	ga_ls9c_ard_3-2-1_110071_2022-01-10_final.stac-item
2022-01-10 11:23:21	ga_ls9c_ard_3-2-1_110082_2022-01-10_final.stac-item
2022-01-13 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-01-13_final.stac-item
2022-01-28 09:29:44	ga_ls9c_ard_3-2-1_092076_2022-01-27_final.stac-item
2022-01-28 11:10:37	ga_ls9c_ard_3-2-1_108081_2022-01-28_final.stac-item
2022-02-06 09:29:08	ga_ls9c_ard_3-2-1_091090_2022-02-05_final.stac-item
2022-02-08 10:48:51	ga_ls9c_ard_3-2-1_105073_2022-02-08_final.stac-item
2022-02-16 11:42:14	ga_ls9c_ard_3-2-1_113083_2022-02-16_final.stac-item
2022-02-20 11:13:28	ga_ls9c_ard_3-2-1_109073_2022-02-20_final.stac-item
2022-03-10 09:28:06	ga_ls9c_ard_3-2-1_091088_2022-03-09_final.stac-item
2022-03-29 11:36:12	ga_ls9c_ard_3-2-1_112084_2022-03-29_final.stac-item
2022-03-31 09:39:46	ga_ls9c_ard_3-2-1_094071_2022-03-31_final.stac-item
2022-04-02 09:29:24	ga_ls9c_ard_3-2-1_092076_2022-04-01_final.stac-item
2022-04-02 11:06:18	ga_ls9c_ard_3-2-1_108071_2022-04-02_final.stac-item
2022-04-02 11:11:05	ga_ls9c_ard_3-2-1_108083_2022-04-02_final.stac-item
2022-04-10 10:18:24	ga_ls9c_ard_3-2-1_100075_2022-04-10_final.stac-item
2022-04-23 11:29:26	ga_ls9c_ard_3-2-1_111083_2022-04-23_final.stac-item
2022-05-14 10:04:33	ga_ls9c_ard_3-2-1_098072_2022-05-14_final.stac-item
2022-05-17 10:34:13	ga_ls9c_ard_3-2-1_103069_2022-05-17_final.stac-item
2022-05-23 09:59:04	ga_ls9c_ard_3-2-1_097074_2022-05-23_final.stac-item
2022-05-30 11:46:08	ga_ls9c_ard_3-2-1_114079_2022-05-30_final.stac-item
2022-06-10 11:28:25	ga_ls9c_ard_3-2-1_111081_2022-06-10_final.stac-item
2022-06-23 10:58:13	ga_ls9c_ard_3-2-1_106082_2022-06-23_final.stac-item
2022-06-28 09:34:19	ga_ls9c_ard_3-2-1_093073_2022-06-28_final.stac-item
2022-07-14 11:14:43	ga_ls9c_ard_3-2-1_109077_2022-07-14_final.stac-item
2022-07-15 11:58:23	ga_ls9c_ard_3-2-1_116078_2022-07-15_final.stac-item
2022-07-16 11:01:59	ga_ls9c_ard_3-2-1_107076_2022-07-16_final.stac-item
2022-08-09 10:16:04	ga_ls9c_ard_3-2-1_099084_2022-08-09_final.stac-item
2022-08-12 10:40:36	ga_ls9c_ard_3-2-1_104068_2022-08-12_final.stac-item
2022-08-15 09:37:50	ga_ls9c_ard_3-2-1_093081_2022-08-15_final.stac-item
2022-08-17 11:00:22	ga_ls9c_ard_3-2-1_107071_2022-08-17_final.stac-item
2022-08-18 10:05:09	ga_ls9c_ard_3-2-1_098072_2022-08-18_final.stac-item
2022-08-18 11:44:50	ga_ls9c_ard_3-2-1_114074_2022-08-18_final.stac-item
2022-08-22 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-08-22_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-05 09:56:48	ga_ls9c_ard_3-2-1_096082_2022-09-05_final.stac-item
2022-09-18 09:22:48	ga_ls9c_ard_3-2-1_091074_2022-09-17_final.stac-item
2022-09-20 09:16:26	ga_ls9c_ard_3-2-1_089089_2022-09-19_final.stac-item
2022-09-21 09:52:07	ga_ls9c_ard_3-2-1_096070_2022-09-21_final.stac-item
2022-10-17 10:28:55	ga_ls9c_ard_3-2-1_102069_2022-10-17_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-18 09:36:53	ga_ls9c_ard_3-2-1_093078_2022-10-18_final.stac-item
2022-10-25 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-10-25_final.stac-item
2022-10-25 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-10-25_final.stac-item
2022-10-30 10:01:36	ga_ls9c_ard_3-2-1_097078_2022-10-30_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-22 10:08:12	ga_ls9c_ard_3-2-1_098079_2022-11-22_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-11-26 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-26_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-15 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-15_final.stac-item
2022-12-18 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-12-18_final.stac-item
2022-12-31 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-12-31_final.stac-item
2023-01-04 09:52:03	ga_ls9c_ard_3-2-1_095085_2023-01-04_final.stac-item
2023-01-13 09:44:38	ga_ls9c_ard_3-2-1_094082_2023-01-13_final.stac-item
2023-01-15 11:11:31	ga_ls9c_ard_3-2-1_108083_2023-01-15_final.stac-item
2023-01-18 11:42:22	ga_ls9c_ard_3-2-1_113083_2023-01-18_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-23 10:18:50	ga_ls9c_ard_3-2-1_100075_2023-01-23_final.stac-item
2023-01-24 09:29:13	ga_ls9c_ard_3-2-1_091090_2023-01-23_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 11:00:17	ga_ls9c_ard_3-2-1_107070_2023-02-09_final.stac-item
2023-02-17 11:53:14	ga_ls9c_ard_3-2-1_115079_2023-02-17_final.stac-item
2023-02-24 10:22:21	ga_ls9c_ard_3-2-1_100084_2023-02-24_final.stac-item
2023-03-09 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-03-09_final.stac-item
2023-03-15 10:47:57	ga_ls9c_ard_3-2-1_105071_2023-03-15_final.stac-item
2023-03-30 10:07:17	ga_ls9c_ard_3-2-1_098078_2023-03-30_final.stac-item
2023-03-31 09:11:16	ga_ls9c_ard_3-2-1_089077_2023-03-30_final.stac-item
2023-04-19 11:21:21	ga_ls9c_ard_3-2-1_110078_2023-04-19_final.stac-item
2023-04-22 11:51:27	ga_ls9c_ard_3-2-1_115076_2023-04-22_final.stac-item
2023-04-27 10:27:52	ga_ls9c_ard_3-2-1_102068_2023-04-27_final.stac-item
2023-04-30 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-04-30_final.stac-item
2023-05-05 09:43:52	ga_ls9c_ard_3-2-1_094082_2023-05-05_final.stac-item
2023-05-08 11:51:15	ga_ls9c_ard_3-2-1_115076_2023-05-08_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-16 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-05-16_final.stac-item
2023-05-17 10:06:56	ga_ls9c_ard_3-2-1_098078_2023-05-17_final.stac-item
2023-05-30 11:12:48	ga_ls9c_ard_3-2-1_109073_2023-05-30_final.stac-item
2023-06-17 09:25:47	ga_ls9c_ard_3-2-1_091084_2023-06-16_final.stac-item
2023-07-01 09:37:06	ga_ls9c_ard_3-2-1_093081_2023-07-01_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-27 10:11:08	ga_ls9c_ard_3-2-1_099073_2023-07-27_final.stac-item
2023-08-01 10:32:33	ga_ls9c_ard_3-2-1_102080_2023-08-01_final.stac-item
2023-08-02 09:34:33	ga_ls9c_ard_3-2-1_093074_2023-08-02_final.stac-item
2023-08-06 09:11:28	ga_ls9c_ard_3-2-1_089078_2023-08-05_final.stac-item
2023-08-07 09:57:32	ga_ls9c_ard_3-2-1_096085_2023-08-07_final.stac-item
2023-09-16 10:42:54	ga_ls9c_ard_3-2-1_104074_2023-09-16_final.stac-item
2023-09-19 11:13:24	ga_ls9c_ard_3-2-1_109073_2023-09-19_final.stac-item
2023-10-19 11:29:08	ga_ls9c_ard_3-2-1_111081_2023-10-19_final.stac-item
2023-10-23 11:03:12	ga_ls9c_ard_3-2-1_107078_2023-10-23_final.stac-item
2023-11-06 11:13:29	ga_ls9c_ard_3-2-1_109073_2023-11-06_final.stac-item
2023-11-17 09:18:05	ga_ls9c_ard_3-2-1_090078_2023-11-16_final.stac-item
2023-11-28 10:36:33	ga_ls9c_ard_3-2-1_103073_2023-11-28_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