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
2021-11-22 11:02:20	ga_ls9c_ard_3-2-1_107072_2021-11-22_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2022-01-07 10:51:16	ga_ls9c_ard_3-2-1_105079_2022-01-07_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-03-22 09:47:35	ga_ls9c_ard_3-2-1_095075_2022-03-22_final.stac-item
2022-04-18 11:08:33	ga_ls9c_ard_3-2-1_108077_2022-04-18_final.stac-item
2022-05-02 09:45:09	ga_ls9c_ard_3-2-1_094085_2022-05-02_final.stac-item
2022-05-04 09:31:34	ga_ls9c_ard_3-2-1_092082_2022-05-04_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-06-12 09:35:13	ga_ls9c_ard_3-2-1_093076_2022-06-12_final.stac-item
2022-08-02 10:05:25	ga_ls9c_ard_3-2-1_098073_2022-08-02_final.stac-item
2022-08-05 10:39:33	ga_ls9c_ard_3-2-1_103081_2022-08-05_final.stac-item
2022-09-19 10:07:16	ga_ls9c_ard_3-2-1_098077_2022-09-19_final.stac-item
2022-10-14 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-14_final.stac-item
2022-12-08 10:08:35	ga_ls9c_ard_3-2-1_098080_2022-12-08_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-08 09:28:55	ga_ls9c_ard_3-2-1_091089_2023-01-07_final.stac-item
2023-01-09 10:09:23	ga_ls9c_ard_3-2-1_098082_2023-01-09_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-10 10:53:02	ga_ls9c_ard_3-2-1_105083_2023-01-10_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-01-15 11:11:31	ga_ls9c_ard_3-2-1_108083_2023-01-15_final.stac-item
2023-01-22 09:33:57	ga_ls9c_ard_3-2-1_093071_2023-01-22_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-01-30 10:24:20	ga_ls9c_ard_3-2-1_101073_2023-01-30_final.stac-item
2023-02-01 10:13:59	ga_ls9c_ard_3-2-1_099078_2023-02-01_final.stac-item
2023-02-03 09:57:39	ga_ls9c_ard_3-2-1_097068_2023-02-03_final.stac-item
2023-02-04 10:41:43	ga_ls9c_ard_3-2-1_104070_2023-02-04_final.stac-item
2023-02-07 09:39:20	ga_ls9c_ard_3-2-1_093084_2023-02-07_final.stac-item
2023-04-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2023-04-23_final.stac-item
2023-04-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2023-04-23_final.stac-item
2023-04-23 10:56:13	ga_ls9c_ard_3-2-1_106077_2023-04-23_final.stac-item
2023-04-24 09:58:59	ga_ls9c_ard_3-2-1_097073_2023-04-24_final.stac-item
2023-04-25 10:41:27	ga_ls9c_ard_3-2-1_104071_2023-04-25_final.stac-item
2023-04-25 10:44:38	ga_ls9c_ard_3-2-1_104079_2023-04-25_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_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
2023-05-28 09:46:41	ga_ls9c_ard_3-2-1_095074_2023-05-28_final.stac-item
2023-07-05 10:47:44	ga_ls9c_ard_3-2-1_105072_2023-07-05_final.stac-item
2023-07-24 11:23:05	ga_ls9c_ard_3-2-1_110083_2023-07-24_final.stac-item
2023-07-25 10:23:04	ga_ls9c_ard_3-2-1_101072_2023-07-25_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-07-28 10:56:01	ga_ls9c_ard_3-2-1_106077_2023-07-28_final.stac-item
2023-07-29 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-07-29_final.stac-item
2023-07-29 09:59:37	ga_ls9c_ard_3-2-1_097075_2023-07-29_final.stac-item
2023-07-29 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-07-29_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-07-30 09:06:24	ga_ls9c_ard_3-2-1_088081_2023-07-29_final.stac-item
2023-08-02 09:38:57	ga_ls9c_ard_3-2-1_093085_2023-08-02_final.stac-item
2023-08-04 09:25:48	ga_ls9c_ard_3-2-1_091083_2023-08-03_final.stac-item
2023-08-04 11:05:05	ga_ls9c_ard_3-2-1_107084_2023-08-04_final.stac-item
2023-08-05 10:05:05	ga_ls9c_ard_3-2-1_098073_2023-08-05_final.stac-item
2023-08-05 10:05:53	ga_ls9c_ard_3-2-1_098075_2023-08-05_final.stac-item
2023-08-05 10:09:29	ga_ls9c_ard_3-2-1_098084_2023-08-05_final.stac-item
2023-10-13 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-13_final.stac-item
2023-10-15 10:10:09	ga_ls9c_ard_3-2-1_099069_2023-10-15_final.stac-item
2023-10-15 10:14:57	ga_ls9c_ard_3-2-1_099081_2023-10-15_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-16 10:54:37	ga_ls9c_ard_3-2-1_106072_2023-10-16_final.stac-item
2023-10-16 10:56:37	ga_ls9c_ard_3-2-1_106077_2023-10-16_final.stac-item
2023-10-17 09:57:49	ga_ls9c_ard_3-2-1_097069_2023-10-17_final.stac-item
2023-10-17 09:59:24	ga_ls9c_ard_3-2-1_097073_2023-10-17_final.stac-item
2023-10-17 10:01:48	ga_ls9c_ard_3-2-1_097079_2023-10-17_final.stac-item
2023-10-17 10:03:24	ga_ls9c_ard_3-2-1_097083_2023-10-17_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-23 09:25:55	ga_ls9c_ard_3-2-1_091082_2023-10-22_final.stac-item
2023-10-23 09:26:43	ga_ls9c_ard_3-2-1_091084_2023-10-22_final.stac-item
2023-10-23 11:01:12	ga_ls9c_ard_3-2-1_107073_2023-10-23_final.stac-item
2023-10-24 10:07:11	ga_ls9c_ard_3-2-1_098077_2023-10-24_final.stac-item
2023-10-24 10:07:59	ga_ls9c_ard_3-2-1_098079_2023-10-24_final.stac-item
2023-10-25 09:15:09	ga_ls9c_ard_3-2-1_089086_2023-10-24_final.stac-item
2023-10-25 10:51:14	ga_ls9c_ard_3-2-1_105079_2023-10-25_final.stac-item
2023-10-27 10:36:04	ga_ls9c_ard_3-2-1_103072_2023-10-27_final.stac-item
2023-10-28 09:41:38	ga_ls9c_ard_3-2-1_094075_2023-10-28_final.stac-item
2023-10-28 11:24:06	ga_ls9c_ard_3-2-1_110084_2023-10-28_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final.stac-item
2023-11-02 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-02 11:41:46	ga_ls9c_ard_3-2-1_113082_2023-11-02_final.stac-item
2023-11-04 09:47:44	ga_ls9c_ard_3-2-1_095075_2023-11-04_final.stac-item
2023-11-04 09:50:31	ga_ls9c_ard_3-2-1_095082_2023-11-04_final.stac-item
2023-11-05 10:30:13	ga_ls9c_ard_3-2-1_102073_2023-11-05_final.stac-item
2023-11-14 10:24:03	ga_ls9c_ard_3-2-1_101073_2023-11-14_final.stac-item
2023-11-15 09:32:49	ga_ls9c_ard_3-2-1_092084_2023-11-15_final.stac-item
2023-11-16 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-11-16_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-17 09:22:53	ga_ls9c_ard_3-2-1_090090_2023-11-16_final.stac-item
2023-11-18 09:58:58	ga_ls9c_ard_3-2-1_097072_2023-11-18_final.stac-item
2023-11-19 10:42:15	ga_ls9c_ard_3-2-1_104072_2023-11-19_final.stac-item
2023-11-20 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-11-20_final.stac-item
2023-11-20 11:29:55	ga_ls9c_ard_3-2-1_111083_2023-11-20_final.stac-item
2023-11-21 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-11-21_final.stac-item
2023-11-22 09:35:31	ga_ls9c_ard_3-2-1_093075_2023-11-22_final.stac-item
2023-11-24 11:01:39	ga_ls9c_ard_3-2-1_107074_2023-11-24_final.stac-item
2023-11-24 11:05:15	ga_ls9c_ard_3-2-1_107083_2023-11-24_final.stac-item
2023-11-24 11:05:39	ga_ls9c_ard_3-2-1_107084_2023-11-24_final.stac-item
2023-11-26 10:51:42	ga_ls9c_ard_3-2-1_105080_2023-11-26_final.stac-item
2023-11-29 11:19:49	ga_ls9c_ard_3-2-1_110073_2023-11-29_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