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
2021-11-09 10:37:48	ga_ls9c_ard_3-2-1_103076_2021-11-09_final.stac-item
2021-11-17 09:24:28	ga_ls9c_ard_3-2-1_091080_2021-11-16_final.stac-item
2022-01-21 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-01-20_final.stac-item
2022-01-22 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-22_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-04-05 10:01:06	ga_ls9c_ard_3-2-1_097078_2022-04-05_final.stac-item
2022-04-18 09:31:40	ga_ls9c_ard_3-2-1_092082_2022-04-18_final.stac-item
2022-05-11 11:12:58	ga_ls9c_ard_3-2-1_109073_2022-05-11_final.stac-item
2022-05-20 11:05:03	ga_ls9c_ard_3-2-1_108069_2022-05-20_final.stac-item
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final.stac-item
2022-06-19 09:40:19	ga_ls9c_ard_3-2-1_094073_2022-06-19_final.stac-item
2022-07-06 10:25:20	ga_ls9c_ard_3-2-1_101077_2022-07-06_final.stac-item
2022-07-09 10:53:25	ga_ls9c_ard_3-2-1_106070_2022-07-09_final.stac-item
2022-07-23 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-07-23_final.stac-item
2022-07-31 10:21:45	ga_ls9c_ard_3-2-1_100083_2022-07-31_final.stac-item
2022-08-06 11:22:49	ga_ls9c_ard_3-2-1_110081_2022-08-06_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-08-27 10:02:35	ga_ls9c_ard_3-2-1_097081_2022-08-27_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-07 11:32:13	ga_ls9c_ard_3-2-1_112073_2022-10-07_final.stac-item
2022-10-17 10:32:06	ga_ls9c_ard_3-2-1_102077_2022-10-17_final.stac-item
2022-10-25 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-10-25_final.stac-item
2022-10-27 09:33:06	ga_ls9c_ard_3-2-1_092084_2022-10-27_final.stac-item
2022-11-03 11:17:43	ga_ls9c_ard_3-2-1_109083_2022-11-03_final.stac-item
2022-11-06 10:07:22	ga_ls9c_ard_3-2-1_098077_2022-11-06_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-14 09:17:58	ga_ls9c_ard_3-2-1_090077_2022-11-13_final.stac-item
2022-11-18 10:30:56	ga_ls9c_ard_3-2-1_102074_2022-11-18_final.stac-item
2022-11-21 09:24:09	ga_ls9c_ard_3-2-1_091077_2022-11-20_final.stac-item
2022-11-24 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-11-24_final.stac-item
2022-11-26 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-26_final.stac-item
2022-12-14 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-12-13_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-20_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-28 11:23:08	ga_ls9c_ard_3-2-1_110081_2022-12-28_final.stac-item
2023-01-02 10:00:25	ga_ls9c_ard_3-2-1_097075_2023-01-02_final.stac-item
2023-01-06 09:40:29	ga_ls9c_ard_3-2-1_093087_2023-01-06_final.stac-item
2023-01-08 09:22:56	ga_ls9c_ard_3-2-1_091074_2023-01-07_final.stac-item
2023-01-17 10:57:08	ga_ls9c_ard_3-2-1_106078_2023-01-17_final.stac-item
2023-01-18 10:01:05	ga_ls9c_ard_3-2-1_097077_2023-01-18_final.stac-item
2023-01-22 09:35:57	ga_ls9c_ard_3-2-1_093076_2023-01-22_final.stac-item
2023-01-22 09:36:45	ga_ls9c_ard_3-2-1_093078_2023-01-22_final.stac-item
2023-01-28 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-28_final.stac-item
2023-01-29 11:23:08	ga_ls9c_ard_3-2-1_110081_2023-01-29_final.stac-item
2023-02-03 11:40:32	ga_ls9c_ard_3-2-1_113078_2023-02-03_final.stac-item
2023-02-11 09:13:01	ga_ls9c_ard_3-2-1_089080_2023-02-10_final.stac-item
2023-02-11 09:14:13	ga_ls9c_ard_3-2-1_089083_2023-02-10_final.stac-item
2023-02-14 11:24:22	ga_ls9c_ard_3-2-1_110084_2023-02-14_final.stac-item
2023-04-22 11:52:15	ga_ls9c_ard_3-2-1_115078_2023-04-22_final.stac-item
2023-04-26 11:24:41	ga_ls9c_ard_3-2-1_111071_2023-04-26_final.stac-item
2023-04-28 11:12:18	ga_ls9c_ard_3-2-1_109071_2023-04-28_final.stac-item
2023-04-29 10:18:39	ga_ls9c_ard_3-2-1_100076_2023-04-29_final.stac-item
2023-04-30 09:27:48	ga_ls9c_ard_3-2-1_091088_2023-04-29_final.stac-item
2023-05-01 10:06:40	ga_ls9c_ard_3-2-1_098077_2023-05-01_final.stac-item
2023-05-01 11:45:56	ga_ls9c_ard_3-2-1_114078_2023-05-01_final.stac-item
2023-05-08 10:13:34	ga_ls9c_ard_3-2-1_099079_2023-05-08_final.stac-item
2023-05-09 09:20:20	ga_ls9c_ard_3-2-1_090085_2023-05-08_final.stac-item
2023-05-28 09:47:05	ga_ls9c_ard_3-2-1_095075_2023-05-28_final.stac-item
2023-05-28 09:51:28	ga_ls9c_ard_3-2-1_095086_2023-05-28_final.stac-item
2023-05-28 11:24:46	ga_ls9c_ard_3-2-1_111072_2023-05-28_final.stac-item
2023-06-23 10:27:12	ga_ls9c_ard_3-2-1_101083_2023-06-23_final.stac-item
2023-06-24 11:04:52	ga_ls9c_ard_3-2-1_108069_2023-06-24_final.stac-item
2023-07-17 11:11:44	ga_ls9c_ard_3-2-1_109070_2023-07-17_final.stac-item
2023-07-18 10:20:54	ga_ls9c_ard_3-2-1_100082_2023-07-18_final.stac-item
2023-07-18 10:21:18	ga_ls9c_ard_3-2-1_100083_2023-07-18_final.stac-item
2023-07-19 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-07-18_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-20 11:45:49	ga_ls9c_ard_3-2-1_114078_2023-07-20_final.stac-item
2023-07-21 09:10:55	ga_ls9c_ard_3-2-1_089077_2023-07-20_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-07-21 10:52:12	ga_ls9c_ard_3-2-1_105083_2023-07-21_final.stac-item
2023-07-24 09:40:36	ga_ls9c_ard_3-2-1_094074_2023-07-24_final.stac-item
2023-07-25 10:27:27	ga_ls9c_ard_3-2-1_101083_2023-07-25_final.stac-item
2023-07-27 10:08:45	ga_ls9c_ard_3-2-1_099067_2023-07-27_final.stac-item
2023-07-27 10:12:20	ga_ls9c_ard_3-2-1_099076_2023-07-27_final.stac-item
2023-10-15 10:12:57	ga_ls9c_ard_3-2-1_099076_2023-10-15_final.stac-item
2023-10-16 10:55:49	ga_ls9c_ard_3-2-1_106075_2023-10-16_final.stac-item
2023-10-20 10:32:19	ga_ls9c_ard_3-2-1_102078_2023-10-20_final.stac-item
2023-10-28 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-28_final.stac-item
2023-10-29 10:22:53	ga_ls9c_ard_3-2-1_101070_2023-10-29_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_final.stac-item
2023-10-31 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-10-31_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-05 10:32:12	ga_ls9c_ard_3-2-1_102078_2023-11-05_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-18 11:38:39	ga_ls9c_ard_3-2-1_113074_2023-11-18_final.stac-item
2023-11-19 10:44:15	ga_ls9c_ard_3-2-1_104077_2023-11-19_final.stac-item
2023-11-20 09:47:50	ga_ls9c_ard_3-2-1_095075_2023-11-20_final.stac-item
2023-11-21 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-11-21_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 09:33:55	ga_ls9c_ard_3-2-1_093071_2023-11-22_final.stac-item
2023-11-22 11:12:48	ga_ls9c_ard_3-2-1_109071_2023-11-22_final.stac-item
2023-11-22 11:13:36	ga_ls9c_ard_3-2-1_109073_2023-11-22_final.stac-item
2023-11-22 11:17:59	ga_ls9c_ard_3-2-1_109084_2023-11-22_final.stac-item
2023-11-25 10:08:26	ga_ls9c_ard_3-2-1_098080_2023-11-25_final.stac-item
2023-11-25 11:46:55	ga_ls9c_ard_3-2-1_114079_2023-11-25_final.stac-item
2023-11-26 10:48:31	ga_ls9c_ard_3-2-1_105072_2023-11-26_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