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 11:38:29	ga_ls9c_ard_3-2-1_113081_2021-11-08_final.stac-item
2021-11-13 11:40:57	ga_ls9c_ard_3-2-1_113081_2021-11-13_final.stac-item
2021-11-14 10:41:51	ga_ls9c_ard_3-2-1_103080_2021-11-14_final.stac-item
2021-11-18 10:03:34	ga_ls9c_ard_3-2-1_097078_2021-11-18_final.stac-item
2021-12-06 10:50:35	ga_ls9c_ard_3-2-1_105077_2021-12-06_final.stac-item
2021-12-20 11:05:14	ga_ls9c_ard_3-2-1_107083_2021-12-20_final.stac-item
2021-12-24 10:35:20	ga_ls9c_ard_3-2-1_103070_2021-12-24_final.stac-item
2022-01-29 11:51:53	ga_ls9c_ard_3-2-1_115076_2022-01-29_final.stac-item
2022-01-30 09:20:10	ga_ls9c_ard_3-2-1_090083_2022-01-29_final.stac-item
2022-01-31 10:03:50	ga_ls9c_ard_3-2-1_097084_2022-01-31_final.stac-item
2022-02-05 10:19:10	ga_ls9c_ard_3-2-1_100076_2022-02-05_final.stac-item
2022-02-07 10:08:24	ga_ls9c_ard_3-2-1_098080_2022-02-07_final.stac-item
2022-02-07 11:45:17	ga_ls9c_ard_3-2-1_114075_2022-02-07_final.stac-item
2022-02-19 10:28:38	ga_ls9c_ard_3-2-1_102069_2022-02-19_final.stac-item
2022-02-19 10:31:49	ga_ls9c_ard_3-2-1_102077_2022-02-19_final.stac-item
2022-03-22 09:47:11	ga_ls9c_ard_3-2-1_095074_2022-03-22_final.stac-item
2022-04-02 09:30:36	ga_ls9c_ard_3-2-1_092079_2022-04-02_final.stac-item
2022-04-09 11:15:14	ga_ls9c_ard_3-2-1_109078_2022-04-09_final.stac-item
2022-05-05 11:50:31	ga_ls9c_ard_3-2-1_115074_2022-05-05_final.stac-item
2022-05-07 10:02:03	ga_ls9c_ard_3-2-1_097081_2022-05-07_final.stac-item
2022-05-15 09:12:54	ga_ls9c_ard_3-2-1_089082_2022-05-14_final.stac-item
2022-05-27 11:14:49	ga_ls9c_ard_3-2-1_109078_2022-05-27_final.stac-item
2022-06-01 09:54:54	ga_ls9c_ard_3-2-1_096079_2022-06-01_final.stac-item
2022-06-08 09:59:06	ga_ls9c_ard_3-2-1_097074_2022-06-08_final.stac-item
2022-06-13 10:16:54	ga_ls9c_ard_3-2-1_100072_2022-06-13_final.stac-item
2022-06-17 09:55:25	ga_ls9c_ard_3-2-1_096080_2022-06-17_final.stac-item
2022-06-22 10:14:07	ga_ls9c_ard_3-2-1_099080_2022-06-22_final.stac-item
2022-06-30 11:02:02	ga_ls9c_ard_3-2-1_107076_2022-06-30_final.stac-item
2022-07-02 10:46:05	ga_ls9c_ard_3-2-1_105067_2022-07-02_final.stac-item
2022-07-03 11:35:20	ga_ls9c_ard_3-2-1_112082_2022-07-03_final.stac-item
2022-07-10 09:58:12	ga_ls9c_ard_3-2-1_097071_2022-07-10_final.stac-item
2022-07-17 11:44:28	ga_ls9c_ard_3-2-1_114074_2022-07-17_final.stac-item
2022-07-22 10:25:48	ga_ls9c_ard_3-2-1_101078_2022-07-22_final.stac-item
2022-08-03 10:47:06	ga_ls9c_ard_3-2-1_105069_2022-08-03_final.stac-item
2022-08-08 09:33:35	ga_ls9c_ard_3-2-1_092086_2022-08-08_final.stac-item
2022-08-18 10:03:34	ga_ls9c_ard_3-2-1_098068_2022-08-18_final.stac-item
2022-08-20 09:52:00	ga_ls9c_ard_3-2-1_096070_2022-08-20_final.stac-item
2022-08-31 09:37:04	ga_ls9c_ard_3-2-1_093079_2022-08-31_final.stac-item
2022-08-31 09:39:28	ga_ls9c_ard_3-2-1_093085_2022-08-31_final.stac-item
2022-09-14 09:47:53	ga_ls9c_ard_3-2-1_095075_2022-09-14_final.stac-item
2022-09-22 10:34:59	ga_ls9c_ard_3-2-1_103069_2022-09-22_final.stac-item
2022-09-26 10:13:28	ga_ls9c_ard_3-2-1_099077_2022-09-26_final.stac-item
2022-09-27 09:19:03	ga_ls9c_ard_3-2-1_090080_2022-09-26_final.stac-item
2022-10-03 11:58:56	ga_ls9c_ard_3-2-1_116078_2022-10-03_final.stac-item
2022-10-13 10:54:48	ga_ls9c_ard_3-2-1_106072_2022-10-13_final.stac-item
2022-10-15 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-14_final.stac-item
2022-10-21 10:04:12	ga_ls9c_ard_3-2-1_098069_2022-10-21_final.stac-item
2022-10-31 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-10-31_final.stac-item
2022-11-02 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-11-02_final.stac-item
2022-11-05 11:00:59	ga_ls9c_ard_3-2-1_107072_2022-11-05_final.stac-item
2022-11-12 11:10:48	ga_ls9c_ard_3-2-1_108081_2022-11-12_final.stac-item
2022-11-18 10:30:32	ga_ls9c_ard_3-2-1_102073_2022-11-18_final.stac-item
2022-11-19 11:12:12	ga_ls9c_ard_3-2-1_109069_2022-11-19_final.stac-item
2022-11-19 11:13:24	ga_ls9c_ard_3-2-1_109072_2022-11-19_final.stac-item
2022-11-20 10:21:46	ga_ls9c_ard_3-2-1_100082_2022-11-20_final.stac-item
2022-11-30 09:19:55	ga_ls9c_ard_3-2-1_090082_2022-11-29_final.stac-item
2022-12-08 11:45:28	ga_ls9c_ard_3-2-1_114075_2022-12-08_final.stac-item
2022-12-16 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-12-15_final.stac-item
2022-12-22 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-12-22_final.stac-item
2022-12-30 11:11:35	ga_ls9c_ard_3-2-1_108083_2022-12-30_final.stac-item
2023-01-04 09:50:27	ga_ls9c_ard_3-2-1_095081_2023-01-04_final.stac-item
2023-01-04 09:51:39	ga_ls9c_ard_3-2-1_095084_2023-01-04_final.stac-item
2023-01-07 11:59:02	ga_ls9c_ard_3-2-1_116078_2023-01-07_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-19 09:07:03	ga_ls9c_ard_3-2-1_088081_2023-01-18_final.stac-item
2023-01-25 10:10:30	ga_ls9c_ard_3-2-1_098085_2023-01-25_final.stac-item
2023-02-02 09:19:10	ga_ls9c_ard_3-2-1_090080_2023-02-01_final.stac-item
2023-03-06 09:20:30	ga_ls9c_ard_3-2-1_090084_2023-03-05_final.stac-item
2023-03-21 11:52:55	ga_ls9c_ard_3-2-1_115079_2023-03-21_final.stac-item
2023-03-31 09:11:40	ga_ls9c_ard_3-2-1_089078_2023-03-30_final.stac-item
2023-04-08 11:40:46	ga_ls9c_ard_3-2-1_113080_2023-04-08_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-05 11:18:45	ga_ls9c_ard_3-2-1_110072_2023-05-05_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-12 09:46:50	ga_ls9c_ard_3-2-1_095074_2023-05-12_final.stac-item
2023-05-22 10:23:48	ga_ls9c_ard_3-2-1_101074_2023-05-22_final.stac-item
2023-05-29 10:28:45	ga_ls9c_ard_3-2-1_102071_2023-05-29_final.stac-item
2023-06-04 11:35:43	ga_ls9c_ard_3-2-1_112084_2023-06-04_final.stac-item
2023-06-21 10:35:34	ga_ls9c_ard_3-2-1_103073_2023-06-21_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-07-03 11:00:28	ga_ls9c_ard_3-2-1_107073_2023-07-03_final.stac-item
2023-07-08 09:40:11	ga_ls9c_ard_3-2-1_094073_2023-07-08_final.stac-item
2023-07-29 09:58:25	ga_ls9c_ard_3-2-1_097072_2023-07-29_final.stac-item
2023-07-31 09:47:17	ga_ls9c_ard_3-2-1_095075_2023-07-31_final.stac-item
2023-08-11 09:30:50	ga_ls9c_ard_3-2-1_092080_2023-08-11_final.stac-item
2023-08-20 11:03:34	ga_ls9c_ard_3-2-1_107080_2023-08-20_final.stac-item
2023-08-27 11:05:51	ga_ls9c_ard_3-2-1_108070_2023-08-27_final.stac-item
2023-08-27 11:08:15	ga_ls9c_ard_3-2-1_108076_2023-08-27_final.stac-item
2023-08-28 10:09:03	ga_ls9c_ard_3-2-1_099067_2023-08-28_final.stac-item
2023-09-04 10:18:04	ga_ls9c_ard_3-2-1_100074_2023-09-04_final.stac-item
2023-09-07 09:12:32	ga_ls9c_ard_3-2-1_089080_2023-09-06_final.stac-item
2023-10-17 10:02:36	ga_ls9c_ard_3-2-1_097081_2023-10-17_final.stac-item
2023-10-20 10:31:07	ga_ls9c_ard_3-2-1_102075_2023-10-20_final.stac-item
2023-10-23 11:04:00	ga_ls9c_ard_3-2-1_107080_2023-10-23_final.stac-item
2023-10-26 11:34:53	ga_ls9c_ard_3-2-1_112080_2023-10-26_final.stac-item
2023-10-29 10:26:04	ga_ls9c_ard_3-2-1_101078_2023-10-29_final.stac-item
2023-11-07 11:58:45	ga_ls9c_ard_3-2-1_116078_2023-11-07_final.stac-item
2023-11-09 10:03:31	ga_ls9c_ard_3-2-1_098068_2023-11-09_final.stac-item
2023-11-15 09:32:01	ga_ls9c_ard_3-2-1_092082_2023-11-15_final.stac-item
2023-11-16 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-11-16_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