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
2021-11-03 09:53:46	ga_ls9c_ard_3-2-1_096072_2021-11-03_final.stac-item
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-08 11:36:06	ga_ls9c_ard_3-2-1_113075_2021-11-08_final.stac-item
2021-11-16 10:23:54	ga_ls9c_ard_3-2-1_100082_2021-11-16_final.stac-item
2021-11-18 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-11-23 11:43:29	ga_ls9c_ard_3-2-1_114075_2021-11-23_final.stac-item
2021-12-13 10:57:29	ga_ls9c_ard_3-2-1_106079_2021-12-13_final.stac-item
2021-12-14 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-14_final.stac-item
2021-12-23 09:58:04	ga_ls9c_ard_3-2-1_096085_2021-12-23_final.stac-item
2022-01-03 09:39:07	ga_ls9c_ard_3-2-1_093084_2022-01-03_final.stac-item
2022-01-12 11:10:35	ga_ls9c_ard_3-2-1_108081_2022-01-12_final.stac-item
2022-01-22 11:46:53	ga_ls9c_ard_3-2-1_114079_2022-01-22_final.stac-item
2022-01-31 10:03:26	ga_ls9c_ard_3-2-1_097083_2022-01-31_final.stac-item
2022-01-31 11:41:31	ga_ls9c_ard_3-2-1_113081_2022-01-31_final.stac-item
2022-02-05 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-02-05_final.stac-item
2022-02-09 09:53:38	ga_ls9c_ard_3-2-1_096074_2022-02-09_final.stac-item
2022-02-09 11:35:42	ga_ls9c_ard_3-2-1_112082_2022-02-09_final.stac-item
2022-02-13 09:30:28	ga_ls9c_ard_3-2-1_092078_2022-02-13_final.stac-item
2022-02-16 11:40:14	ga_ls9c_ard_3-2-1_113078_2022-02-16_final.stac-item
2022-03-02 10:15:32	ga_ls9c_ard_3-2-1_099083_2022-03-02_final.stac-item
2022-03-03 10:54:48	ga_ls9c_ard_3-2-1_106073_2022-03-03_final.stac-item
2022-03-11 11:44:39	ga_ls9c_ard_3-2-1_114074_2022-03-11_final.stac-item
2022-04-03 10:15:27	ga_ls9c_ard_3-2-1_099083_2022-04-03_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-05 10:01:30	ga_ls9c_ard_3-2-1_097079_2022-04-05_final.stac-item
2022-04-12 11:46:30	ga_ls9c_ard_3-2-1_114079_2022-04-12_final.stac-item
2022-04-16 11:20:56	ga_ls9c_ard_3-2-1_110077_2022-04-16_final.stac-item
2022-04-21 11:41:00	ga_ls9c_ard_3-2-1_113081_2022-04-21_final.stac-item
2022-04-23 11:29:50	ga_ls9c_ard_3-2-1_111084_2022-04-23_final.stac-item
2022-05-03 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-05-03_final.stac-item
2022-05-15 10:51:23	ga_ls9c_ard_3-2-1_105081_2022-05-15_final.stac-item
2022-05-25 11:24:48	ga_ls9c_ard_3-2-1_111072_2022-05-25_final.stac-item
2022-06-04 10:24:37	ga_ls9c_ard_3-2-1_101076_2022-06-04_final.stac-item
2022-06-19 11:18:24	ga_ls9c_ard_3-2-1_110071_2022-06-19_final.stac-item
2022-06-21 09:31:37	ga_ls9c_ard_3-2-1_092082_2022-06-21_final.stac-item
2022-06-28 09:35:07	ga_ls9c_ard_3-2-1_093075_2022-06-28_final.stac-item
2022-07-07 09:31:42	ga_ls9c_ard_3-2-1_092082_2022-07-07_final.stac-item
2022-07-09 10:55:01	ga_ls9c_ard_3-2-1_106074_2022-07-09_final.stac-item
2022-07-16 11:03:34	ga_ls9c_ard_3-2-1_107080_2022-07-16_final.stac-item
2022-08-01 11:04:37	ga_ls9c_ard_3-2-1_107082_2022-08-01_final.stac-item
2022-08-26 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-08-26_final.stac-item
2022-09-05 09:58:00	ga_ls9c_ard_3-2-1_096085_2022-09-05_final.stac-item
2022-09-20 09:12:51	ga_ls9c_ard_3-2-1_089080_2022-09-19_final.stac-item
2022-09-28 09:59:55	ga_ls9c_ard_3-2-1_097074_2022-09-28_final.stac-item
2022-10-01 10:33:13	ga_ls9c_ard_3-2-1_102080_2022-10-01_final.stac-item
2022-10-11 11:11:56	ga_ls9c_ard_3-2-1_108084_2022-10-11_final.stac-item
2022-10-31 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-10-31_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-23 10:48:16	ga_ls9c_ard_3-2-1_105071_2022-11-23_final.stac-item
2022-11-28 09:31:29	ga_ls9c_ard_3-2-1_092080_2022-11-28_final.stac-item
2023-01-30 10:24:44	ga_ls9c_ard_3-2-1_101074_2023-01-30_final.stac-item
2023-02-04 10:43:43	ga_ls9c_ard_3-2-1_104075_2023-02-04_final.stac-item
2023-02-07 11:17:50	ga_ls9c_ard_3-2-1_109083_2023-02-07_final.stac-item
2023-02-10 11:46:20	ga_ls9c_ard_3-2-1_114077_2023-02-10_final.stac-item
2023-03-10 10:29:48	ga_ls9c_ard_3-2-1_102072_2023-03-10_final.stac-item
2023-03-13 09:27:01	ga_ls9c_ard_3-2-1_091085_2023-03-12_final.stac-item
2023-03-24 10:41:42	ga_ls9c_ard_3-2-1_104071_2023-03-24_final.stac-item
2023-04-09 10:40:45	ga_ls9c_ard_3-2-1_104069_2023-04-09_final.stac-item
2023-04-09 10:41:33	ga_ls9c_ard_3-2-1_104071_2023-04-09_final.stac-item
2023-04-12 11:17:12	ga_ls9c_ard_3-2-1_109083_2023-04-12_final.stac-item
2023-04-14 09:25:55	ga_ls9c_ard_3-2-1_091083_2023-04-13_final.stac-item
2023-04-16 10:48:03	ga_ls9c_ard_3-2-1_105072_2023-04-16_final.stac-item
2023-04-17 11:31:43	ga_ls9c_ard_3-2-1_112073_2023-04-17_final.stac-item
2023-04-19 11:23:21	ga_ls9c_ard_3-2-1_110083_2023-04-19_final.stac-item
2023-04-21 11:11:23	ga_ls9c_ard_3-2-1_108084_2023-04-21_final.stac-item
2023-04-26 09:47:00	ga_ls9c_ard_3-2-1_095074_2023-04-26_final.stac-item
2023-04-28 09:34:37	ga_ls9c_ard_3-2-1_093074_2023-04-28_final.stac-item
2023-04-30 10:59:30	ga_ls9c_ard_3-2-1_107070_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
2023-05-05 11:22:21	ga_ls9c_ard_3-2-1_110081_2023-05-05_final.stac-item
2023-05-06 10:23:32	ga_ls9c_ard_3-2-1_101073_2023-05-06_final.stac-item
2023-05-10 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-05-10_final.stac-item
2023-05-11 10:40:04	ga_ls9c_ard_3-2-1_104068_2023-05-11_final.stac-item
2023-05-12 11:26:31	ga_ls9c_ard_3-2-1_111076_2023-05-12_final.stac-item
2023-05-16 10:59:22	ga_ls9c_ard_3-2-1_107070_2023-05-16_final.stac-item
2023-05-19 09:51:45	ga_ls9c_ard_3-2-1_096071_2023-05-19_final.stac-item
2023-05-21 11:20:14	ga_ls9c_ard_3-2-1_110076_2023-05-21_final.stac-item
2023-05-22 10:22:36	ga_ls9c_ard_3-2-1_101071_2023-05-22_final.stac-item
2023-05-22 10:23:48	ga_ls9c_ard_3-2-1_101074_2023-05-22_final.stac-item
2023-05-23 11:05:51	ga_ls9c_ard_3-2-1_108071_2023-05-23_final.stac-item
2023-05-26 10:00:38	ga_ls9c_ard_3-2-1_097078_2023-05-26_final.stac-item
2023-05-28 11:28:21	ga_ls9c_ard_3-2-1_111081_2023-05-28_final.stac-item
2023-06-20 09:51:31	ga_ls9c_ard_3-2-1_096071_2023-06-20_final.stac-item
2023-07-04 10:08:03	ga_ls9c_ard_3-2-1_098081_2023-07-04_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-06 09:56:07	ga_ls9c_ard_3-2-1_096082_2023-07-06_final.stac-item
2023-07-10 11:05:08	ga_ls9c_ard_3-2-1_108069_2023-07-10_final.stac-item
2023-07-10 11:05:55	ga_ls9c_ard_3-2-1_108071_2023-07-10_final.stac-item
2023-09-06 11:46:13	ga_ls9c_ard_3-2-1_114078_2023-09-06_final.stac-item
2023-09-11 10:23:56	ga_ls9c_ard_3-2-1_101073_2023-09-11_final.stac-item
2023-09-15 10:03:38	ga_ls9c_ard_3-2-1_097084_2023-09-15_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-09-27 10:23:53	ga_ls9c_ard_3-2-1_101073_2023-09-27_final.stac-item
2023-09-27 10:24:17	ga_ls9c_ard_3-2-1_101074_2023-09-27_final.stac-item
2023-09-29 10:12:44	ga_ls9c_ard_3-2-1_099076_2023-09-29_final.stac-item
2023-10-02 10:44:29	ga_ls9c_ard_3-2-1_104078_2023-10-02_final.stac-item
2023-10-07 09:28:12	ga_ls9c_ard_3-2-1_091088_2023-10-06_final.stac-item
2023-10-08 10:08:16	ga_ls9c_ard_3-2-1_098080_2023-10-08_final.stac-item
2023-10-09 10:47:57	ga_ls9c_ard_3-2-1_105071_2023-10-09_final.stac-item
2023-10-10 11:35:13	ga_ls9c_ard_3-2-1_112081_2023-10-10_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years