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
2021-11-06 10:15:47	ga_ls9c_ard_3-2-1_100074_2021-11-06_final.stac-item
2021-11-08 09:56:15	ga_ls9c_ard_3-2-1_097072_2021-11-08_final.stac-item
2021-11-22 11:03:32	ga_ls9c_ard_3-2-1_107075_2021-11-22_final.stac-item
2021-12-04 09:27:41	ga_ls9c_ard_3-2-1_091086_2021-12-03_final.stac-item
2022-01-02 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-01-02_final.stac-item
2022-01-07 10:50:28	ga_ls9c_ard_3-2-1_105077_2022-01-07_final.stac-item
2022-01-19 09:35:30	ga_ls9c_ard_3-2-1_093075_2022-01-19_final.stac-item
2022-02-09 11:36:06	ga_ls9c_ard_3-2-1_112083_2022-02-09_final.stac-item
2022-02-18 09:46:10	ga_ls9c_ard_3-2-1_095071_2022-02-18_final.stac-item
2022-02-20 11:12:40	ga_ls9c_ard_3-2-1_109071_2022-02-20_final.stac-item
2022-02-20 11:13:04	ga_ls9c_ard_3-2-1_109072_2022-02-20_final.stac-item
2022-03-02 10:15:08	ga_ls9c_ard_3-2-1_099082_2022-03-02_final.stac-item
2022-03-06 11:23:43	ga_ls9c_ard_3-2-1_111068_2022-03-06_final.stac-item
2022-03-19 10:53:59	ga_ls9c_ard_3-2-1_106071_2022-03-19_final.stac-item
2022-03-21 10:42:49	ga_ls9c_ard_3-2-1_104074_2022-03-21_final.stac-item
2022-03-26 09:27:13	ga_ls9c_ard_3-2-1_091086_2022-03-25_final.stac-item
2022-04-04 10:53:56	ga_ls9c_ard_3-2-1_106071_2022-04-04_final.stac-item
2022-04-07 11:25:13	ga_ls9c_ard_3-2-1_111072_2022-04-07_final.stac-item
2022-04-11 11:02:51	ga_ls9c_ard_3-2-1_107078_2022-04-11_final.stac-item
2022-04-13 10:51:40	ga_ls9c_ard_3-2-1_105081_2022-04-13_final.stac-item
2022-04-21 10:02:31	ga_ls9c_ard_3-2-1_097082_2022-04-21_final.stac-item
2022-05-25 09:46:42	ga_ls9c_ard_3-2-1_095074_2022-05-25_final.stac-item
2022-05-27 11:12:50	ga_ls9c_ard_3-2-1_109073_2022-05-27_final.stac-item
2022-05-28 10:20:48	ga_ls9c_ard_3-2-1_100082_2022-05-28_final.stac-item
2022-06-08 10:00:42	ga_ls9c_ard_3-2-1_097078_2022-06-08_final.stac-item
2022-06-12 11:11:18	ga_ls9c_ard_3-2-1_109069_2022-06-12_final.stac-item
2022-06-19 09:40:43	ga_ls9c_ard_3-2-1_094074_2022-06-19_final.stac-item
2022-06-21 11:05:43	ga_ls9c_ard_3-2-1_108070_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
2022-06-23 09:20:07	ga_ls9c_ard_3-2-1_090084_2022-06-22_final.stac-item
2022-06-23 10:53:49	ga_ls9c_ard_3-2-1_106071_2022-06-23_final.stac-item
2022-06-26 09:50:41	ga_ls9c_ard_3-2-1_095083_2022-06-26_final.stac-item
2022-07-07 11:05:48	ga_ls9c_ard_3-2-1_108070_2022-07-07_final.stac-item
2022-07-12 11:29:29	ga_ls9c_ard_3-2-1_111083_2022-07-12_final.stac-item
2022-08-01 09:28:32	ga_ls9c_ard_3-2-1_091089_2022-07-31_final.stac-item
2022-08-10 10:54:09	ga_ls9c_ard_3-2-1_106071_2022-08-10_final.stac-item
2022-08-26 10:55:01	ga_ls9c_ard_3-2-1_106073_2022-08-26_final.stac-item
2022-08-29 09:48:14	ga_ls9c_ard_3-2-1_095076_2022-08-29_final.stac-item
2022-09-01 11:58:49	ga_ls9c_ard_3-2-1_116078_2022-09-01_final.stac-item
2022-09-02 11:04:00	ga_ls9c_ard_3-2-1_107080_2022-09-02_final.stac-item
2022-09-03 10:08:22	ga_ls9c_ard_3-2-1_098080_2022-09-03_final.stac-item
2022-09-10 10:12:09	ga_ls9c_ard_3-2-1_099074_2022-09-10_final.stac-item
2022-09-14 11:28:46	ga_ls9c_ard_3-2-1_111080_2022-09-14_final.stac-item
2022-10-09 11:21:29	ga_ls9c_ard_3-2-1_110077_2022-10-09_final.stac-item
2022-10-16 11:25:20	ga_ls9c_ard_3-2-1_111071_2022-10-16_final.stac-item
2022-10-21 10:08:59	ga_ls9c_ard_3-2-1_098081_2022-10-21_final.stac-item
2022-10-23 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-10-23_final.stac-item
2022-10-27 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-10-27_final.stac-item
2022-10-27 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-10-27_final.stac-item
2022-10-28 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-10-28_final.stac-item
2022-10-28 10:16:22	ga_ls9c_ard_3-2-1_099084_2022-10-28_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-26 09:42:40	ga_ls9c_ard_3-2-1_094077_2022-11-26_final.stac-item
2022-12-05 11:13:21	ga_ls9c_ard_3-2-1_109072_2022-12-05_final.stac-item
2022-12-24 10:03:44	ga_ls9c_ard_3-2-1_098068_2022-12-24_final.stac-item
2023-01-06 11:12:11	ga_ls9c_ard_3-2-1_109069_2023-01-06_final.stac-item
2023-01-10 10:48:15	ga_ls9c_ard_3-2-1_105071_2023-01-10_final.stac-item
2023-01-10 10:52:14	ga_ls9c_ard_3-2-1_105081_2023-01-10_final.stac-item
2023-01-15 11:11:55	ga_ls9c_ard_3-2-1_108084_2023-01-15_final.stac-item
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-02-21 09:50:20	ga_ls9c_ard_3-2-1_095081_2023-02-21_final.stac-item
2023-02-21 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-02-21_final.stac-item
2023-03-04 09:28:06	ga_ls9c_ard_3-2-1_092072_2023-03-03_final.stac-item
2023-03-04 11:10:58	ga_ls9c_ard_3-2-1_108082_2023-03-04_final.stac-item
2023-03-09 11:29:25	ga_ls9c_ard_3-2-1_111082_2023-03-09_final.stac-item
2023-03-11 11:13:04	ga_ls9c_ard_3-2-1_109072_2023-03-11_final.stac-item
2023-03-13 09:27:01	ga_ls9c_ard_3-2-1_091085_2023-03-12_final.stac-item
2023-03-14 10:03:06	ga_ls9c_ard_3-2-1_098067_2023-03-14_final.stac-item
2023-03-22 10:54:29	ga_ls9c_ard_3-2-1_106072_2023-03-22_final.stac-item
2023-04-01 11:36:13	ga_ls9c_ard_3-2-1_112084_2023-04-01_final.stac-item
2023-04-06 10:15:51	ga_ls9c_ard_3-2-1_099084_2023-04-06_final.stac-item
2023-04-17 09:51:38	ga_ls9c_ard_3-2-1_096070_2023-04-17_final.stac-item
2023-04-22 10:12:34	ga_ls9c_ard_3-2-1_099076_2023-04-22_final.stac-item
2023-05-06 10:23:08	ga_ls9c_ard_3-2-1_101072_2023-05-06_final.stac-item
2023-05-09 10:52:50	ga_ls9c_ard_3-2-1_106069_2023-05-09_final.stac-item
2023-05-16 11:00:58	ga_ls9c_ard_3-2-1_107074_2023-05-16_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-05-23 11:05:03	ga_ls9c_ard_3-2-1_108069_2023-05-23_final.stac-item
2023-05-30 11:11:12	ga_ls9c_ard_3-2-1_109069_2023-05-30_final.stac-item
2023-06-03 10:45:40	ga_ls9c_ard_3-2-1_105067_2023-06-03_final.stac-item
2023-06-05 10:37:17	ga_ls9c_ard_3-2-1_103077_2023-06-05_final.stac-item
2023-06-17 11:03:29	ga_ls9c_ard_3-2-1_107081_2023-06-17_final.stac-item
2023-06-22 09:40:21	ga_ls9c_ard_3-2-1_094074_2023-06-22_final.stac-item
2023-06-24 11:08:52	ga_ls9c_ard_3-2-1_108079_2023-06-24_final.stac-item
2023-07-18 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-07-18_final.stac-item
2023-07-20 10:03:21	ga_ls9c_ard_3-2-1_098069_2023-07-20_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-08-15 10:42:36	ga_ls9c_ard_3-2-1_104074_2023-08-15_final.stac-item
2023-08-29 09:17:49	ga_ls9c_ard_3-2-1_090078_2023-08-28_final.stac-item
2023-08-30 11:40:46	ga_ls9c_ard_3-2-1_113080_2023-08-30_final.stac-item
2023-09-06 10:07:20	ga_ls9c_ard_3-2-1_098078_2023-09-06_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-10-16 10:55:01	ga_ls9c_ard_3-2-1_106073_2023-10-16_final.stac-item
2023-10-20 10:28:43	ga_ls9c_ard_3-2-1_102069_2023-10-20_final.stac-item
2023-11-04 09:51:43	ga_ls9c_ard_3-2-1_095085_2023-11-04_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-26 09:14:25	ga_ls9c_ard_3-2-1_089084_2023-11-25_final.stac-item
2023-11-29 11:18:37	ga_ls9c_ard_3-2-1_110070_2023-11-29_final.stac-item
2023-11-29 11:21:25	ga_ls9c_ard_3-2-1_110077_2023-11-29_final.stac-item
2023-11-30 10:23:48	ga_ls9c_ard_3-2-1_101072_2023-11-30_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