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
2021-12-04 11:00:11	ga_ls9c_ard_3-2-1_107070_2021-12-04_final.stac-item
2021-12-09 11:19:04	ga_ls9c_ard_3-2-1_110071_2021-12-09_final.stac-item
2021-12-11 11:07:53	ga_ls9c_ard_3-2-1_108074_2021-12-11_final.stac-item
2021-12-18 09:35:07	ga_ls9c_ard_3-2-1_093074_2021-12-18_final.stac-item
2021-12-18 11:17:35	ga_ls9c_ard_3-2-1_109083_2021-12-18_final.stac-item
2021-12-21 10:10:25	ga_ls9c_ard_3-2-1_098085_2021-12-21_final.stac-item
2021-12-25 09:41:19	ga_ls9c_ard_3-2-1_094074_2021-12-25_final.stac-item
2022-01-03 09:35:31	ga_ls9c_ard_3-2-1_093075_2022-01-03_final.stac-item
2022-01-26 09:42:53	ga_ls9c_ard_3-2-1_094078_2022-01-26_final.stac-item
2022-02-02 09:47:28	ga_ls9c_ard_3-2-1_095074_2022-02-02_final.stac-item
2022-02-22 09:25:48	ga_ls9c_ard_3-2-1_091082_2022-02-21_final.stac-item
2022-02-22 09:28:36	ga_ls9c_ard_3-2-1_091089_2022-02-21_final.stac-item
2022-02-25 09:51:52	ga_ls9c_ard_3-2-1_096070_2022-02-25_final.stac-item
2022-03-07 10:30:06	ga_ls9c_ard_3-2-1_102073_2022-03-07_final.stac-item
2022-03-19 10:58:47	ga_ls9c_ard_3-2-1_106083_2022-03-19_final.stac-item
2022-03-26 11:00:07	ga_ls9c_ard_3-2-1_107071_2022-03-26_final.stac-item
2022-04-09 11:12:26	ga_ls9c_ard_3-2-1_109071_2022-04-09_final.stac-item
2022-04-13 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-04-13_final.stac-item
2022-04-20 10:54:34	ga_ls9c_ard_3-2-1_106073_2022-04-20_final.stac-item
2022-04-20 10:55:45	ga_ls9c_ard_3-2-1_106076_2022-04-20_final.stac-item
2022-04-29 09:13:52	ga_ls9c_ard_3-2-1_089084_2022-04-28_final.stac-item
2022-05-20 11:06:39	ga_ls9c_ard_3-2-1_108073_2022-05-20_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-06-11 10:29:37	ga_ls9c_ard_3-2-1_102073_2022-06-11_final.stac-item
2022-06-17 11:35:30	ga_ls9c_ard_3-2-1_112083_2022-06-17_final.stac-item
2022-06-21 09:34:25	ga_ls9c_ard_3-2-1_092089_2022-06-21_final.stac-item
2022-06-22 11:51:48	ga_ls9c_ard_3-2-1_115077_2022-06-22_final.stac-item
2022-06-28 09:34:43	ga_ls9c_ard_3-2-1_093074_2022-06-28_final.stac-item
2022-07-08 10:09:22	ga_ls9c_ard_3-2-1_099068_2022-07-08_final.stac-item
2022-07-11 10:42:15	ga_ls9c_ard_3-2-1_104073_2022-07-11_final.stac-item
2022-07-13 10:29:52	ga_ls9c_ard_3-2-1_102073_2022-07-13_final.stac-item
2022-07-23 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-07-23_final.stac-item
2022-07-24 10:11:05	ga_ls9c_ard_3-2-1_099072_2022-07-24_final.stac-item
2022-07-25 09:17:28	ga_ls9c_ard_3-2-1_090077_2022-07-24_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-08-09 11:52:09	ga_ls9c_ard_3-2-1_115077_2022-08-09_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-27 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-08-27_final.stac-item
2022-09-02 09:22:19	ga_ls9c_ard_3-2-1_091073_2022-09-01_final.stac-item
2022-09-09 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-09-09_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-25 09:33:00	ga_ls9c_ard_3-2-1_092084_2022-09-25_final.stac-item
2022-10-21 10:09:47	ga_ls9c_ard_3-2-1_098083_2022-10-21_final.stac-item
2022-10-28 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-10-28_final.stac-item
2022-11-07 09:16:56	ga_ls9c_ard_3-2-1_089090_2022-11-06_final.stac-item
2022-11-11 10:23:57	ga_ls9c_ard_3-2-1_101072_2022-11-11_final.stac-item
2022-11-14 09:18:22	ga_ls9c_ard_3-2-1_090078_2022-11-13_final.stac-item
2022-11-19 11:12:12	ga_ls9c_ard_3-2-1_109069_2022-11-19_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-11-21 09:28:56	ga_ls9c_ard_3-2-1_091089_2022-11-20_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_2022-11-26_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-04 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-04_final.stac-item
2022-12-09 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-12-09_final.stac-item
2022-12-13 10:25:56	ga_ls9c_ard_3-2-1_101077_2022-12-13_final.stac-item
2022-12-25 10:53:00	ga_ls9c_ard_3-2-1_105083_2022-12-25_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2022-12-28 09:44:38	ga_ls9c_ard_3-2-1_094082_2022-12-28_final.stac-item
2022-12-31 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-31_final.stac-item
2022-12-31 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-12-31_final.stac-item
2023-01-11 09:58:36	ga_ls9c_ard_3-2-1_096086_2023-01-11_final.stac-item
2023-01-13 11:19:07	ga_ls9c_ard_3-2-1_110071_2023-01-13_final.stac-item
2023-01-15 11:06:44	ga_ls9c_ard_3-2-1_108071_2023-01-15_final.stac-item
2023-01-16 10:14:41	ga_ls9c_ard_3-2-1_099080_2023-01-16_final.stac-item
2023-01-17 09:19:51	ga_ls9c_ard_3-2-1_090082_2023-01-16_final.stac-item
2023-01-18 09:57:06	ga_ls9c_ard_3-2-1_097067_2023-01-18_final.stac-item
2023-01-19 10:46:20	ga_ls9c_ard_3-2-1_104082_2023-01-19_final.stac-item
2023-01-22 11:16:50	ga_ls9c_ard_3-2-1_109081_2023-01-22_final.stac-item
2023-01-23 10:22:02	ga_ls9c_ard_3-2-1_100083_2023-01-23_final.stac-item
2023-02-03 11:42:31	ga_ls9c_ard_3-2-1_113083_2023-02-03_final.stac-item
2023-02-06 10:30:34	ga_ls9c_ard_3-2-1_102073_2023-02-06_final.stac-item
2023-02-26 10:08:00	ga_ls9c_ard_3-2-1_098079_2023-02-26_final.stac-item
2023-03-31 10:48:57	ga_ls9c_ard_3-2-1_105074_2023-03-31_final.stac-item
2023-04-12 11:14:24	ga_ls9c_ard_3-2-1_109076_2023-04-12_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-04-14 09:22:20	ga_ls9c_ard_3-2-1_091074_2023-04-13_final.stac-item
2023-04-22 11:51:03	ga_ls9c_ard_3-2-1_115075_2023-04-22_final.stac-item
2023-04-22 11:52:15	ga_ls9c_ard_3-2-1_115078_2023-04-22_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-05-12 11:24:56	ga_ls9c_ard_3-2-1_111072_2023-05-12_final.stac-item
2023-05-14 09:38:51	ga_ls9c_ard_3-2-1_093085_2023-05-14_final.stac-item
2023-06-03 09:11:59	ga_ls9c_ard_3-2-1_089080_2023-06-02_final.stac-item
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final.stac-item
2023-06-18 11:45:57	ga_ls9c_ard_3-2-1_114079_2023-06-18_final.stac-item
2023-06-29 11:29:06	ga_ls9c_ard_3-2-1_111083_2023-06-29_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-17 11:12:08	ga_ls9c_ard_3-2-1_109071_2023-07-17_final.stac-item
2023-08-05 10:09:53	ga_ls9c_ard_3-2-1_098085_2023-08-05_final.stac-item
2023-08-09 11:18:52	ga_ls9c_ard_3-2-1_110072_2023-08-09_final.stac-item
2023-08-09 11:23:40	ga_ls9c_ard_3-2-1_110084_2023-08-09_final.stac-item
2023-08-12 10:14:05	ga_ls9c_ard_3-2-1_099080_2023-08-12_final.stac-item
2023-08-15 10:40:12	ga_ls9c_ard_3-2-1_104068_2023-08-15_final.stac-item
2023-08-18 09:39:47	ga_ls9c_ard_3-2-1_093087_2023-08-18_final.stac-item
2023-08-18 11:17:29	ga_ls9c_ard_3-2-1_109084_2023-08-18_final.stac-item
2023-10-21 11:13:58	ga_ls9c_ard_3-2-1_109074_2023-10-21_final.stac-item
2023-11-04 09:47:20	ga_ls9c_ard_3-2-1_095074_2023-11-04_final.stac-item
2023-11-15 11:06:31	ga_ls9c_ard_3-2-1_108071_2023-11-15_final.stac-item
2023-11-27 11:36:10	ga_ls9c_ard_3-2-1_112083_2023-11-27_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