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
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-01-23 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-23_final.stac-item
2022-02-24 10:52:18	ga_ls9c_ard_3-2-1_105082_2022-02-24_final.stac-item
2022-03-07 10:32:29	ga_ls9c_ard_3-2-1_102079_2022-03-07_final.stac-item
2022-04-08 10:32:23	ga_ls9c_ard_3-2-1_102079_2022-04-08_final.stac-item
2022-05-29 09:23:35	ga_ls9c_ard_3-2-1_091078_2022-05-28_final.stac-item
2022-06-12 11:11:42	ga_ls9c_ard_3-2-1_109070_2022-06-12_final.stac-item
2022-07-16 09:23:54	ga_ls9c_ard_3-2-1_091078_2022-07-15_final.stac-item
2022-07-26 09:57:57	ga_ls9c_ard_3-2-1_097070_2022-07-26_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-25 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-10-25_final.stac-item
2022-10-27 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-10-27_final.stac-item
2022-11-01 11:28:06	ga_ls9c_ard_3-2-1_111078_2022-11-01_final.stac-item
2022-11-06 10:04:58	ga_ls9c_ard_3-2-1_098071_2022-11-06_final.stac-item
2022-11-28 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-11-28_final.stac-item
2022-11-30 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-11-29_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-20 10:32:53	ga_ls9c_ard_3-2-1_102079_2022-12-20_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2022-12-27 10:38:39	ga_ls9c_ard_3-2-1_103078_2022-12-27_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-20 09:48:41	ga_ls9c_ard_3-2-1_095077_2023-01-20_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-24 09:22:02	ga_ls9c_ard_3-2-1_091072_2023-01-23_final.stac-item
2023-01-26 10:50:35	ga_ls9c_ard_3-2-1_105077_2023-01-26_final.stac-item
2023-01-27 09:54:59	ga_ls9c_ard_3-2-1_096077_2023-01-27_final.stac-item
2023-01-27 11:33:04	ga_ls9c_ard_3-2-1_112075_2023-01-27_final.stac-item
2023-01-29 09:42:39	ga_ls9c_ard_3-2-1_094077_2023-01-29_final.stac-item
2023-01-29 09:43:03	ga_ls9c_ard_3-2-1_094078_2023-01-29_final.stac-item
2023-02-02 09:21:34	ga_ls9c_ard_3-2-1_090086_2023-02-01_final.stac-item
2023-02-05 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-05 11:27:23	ga_ls9c_ard_3-2-1_111076_2023-02-05_final.stac-item
2023-02-05 11:28:35	ga_ls9c_ard_3-2-1_111079_2023-02-05_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-07 11:18:13	ga_ls9c_ard_3-2-1_109084_2023-02-07_final.stac-item
2023-02-09 11:02:16	ga_ls9c_ard_3-2-1_107075_2023-02-09_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-04-23 10:53:25	ga_ls9c_ard_3-2-1_106070_2023-04-23_final.stac-item
2023-04-24 11:39:28	ga_ls9c_ard_3-2-1_113077_2023-04-24_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-04-26 11:27:05	ga_ls9c_ard_3-2-1_111077_2023-04-26_final.stac-item
2023-04-26 11:28:41	ga_ls9c_ard_3-2-1_111081_2023-04-26_final.stac-item
2023-04-27 10:31:27	ga_ls9c_ard_3-2-1_102077_2023-04-27_final.stac-item
2023-05-28 09:49:28	ga_ls9c_ard_3-2-1_095081_2023-05-28_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-07-15 11:27:17	ga_ls9c_ard_3-2-1_111078_2023-07-15_final.stac-item
2023-07-16 10:32:28	ga_ls9c_ard_3-2-1_102080_2023-07-16_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-18 10:20:06	ga_ls9c_ard_3-2-1_100080_2023-07-18_final.stac-item
2023-07-19 09:23:41	ga_ls9c_ard_3-2-1_091078_2023-07-18_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-20 11:45:49	ga_ls9c_ard_3-2-1_114078_2023-07-20_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-07-25 10:25:27	ga_ls9c_ard_3-2-1_101078_2023-07-25_final.stac-item
2023-07-26 09:29:51	ga_ls9c_ard_3-2-1_092078_2023-07-25_final.stac-item
2023-07-28 10:58:25	ga_ls9c_ard_3-2-1_106083_2023-07-28_final.stac-item
2023-07-29 09:57:37	ga_ls9c_ard_3-2-1_097070_2023-07-29_final.stac-item
2023-07-29 11:39:18	ga_ls9c_ard_3-2-1_113077_2023-07-29_final.stac-item
2023-08-02 11:12:38	ga_ls9c_ard_3-2-1_109072_2023-08-02_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-05 11:44:22	ga_ls9c_ard_3-2-1_114074_2023-08-05_final.stac-item
2023-08-05 11:45:58	ga_ls9c_ard_3-2-1_114078_2023-08-05_final.stac-item
2023-10-13 10:25:17	ga_ls9c_ard_3-2-1_101076_2023-10-13_final.stac-item
2023-10-14 11:07:22	ga_ls9c_ard_3-2-1_108073_2023-10-14_final.stac-item
2023-10-16 09:22:55	ga_ls9c_ard_3-2-1_090090_2023-10-15_final.stac-item
2023-10-19 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-10-19_final.stac-item
2023-10-19 11:29:08	ga_ls9c_ard_3-2-1_111081_2023-10-19_final.stac-item
2023-10-24 11:45:16	ga_ls9c_ard_3-2-1_114075_2023-10-24_final.stac-item
2023-10-25 09:11:33	ga_ls9c_ard_3-2-1_089077_2023-10-24_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-10-25 10:48:02	ga_ls9c_ard_3-2-1_105071_2023-10-25_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-26 11:34:53	ga_ls9c_ard_3-2-1_112080_2023-10-26_final.stac-item
2023-10-28 11:22:54	ga_ls9c_ard_3-2-1_110081_2023-10-28_final.stac-item
2023-10-29 10:25:40	ga_ls9c_ard_3-2-1_101077_2023-10-29_final.stac-item
2023-10-30 09:30:26	ga_ls9c_ard_3-2-1_092078_2023-10-30_final.stac-item
2023-11-01 09:19:38	ga_ls9c_ard_3-2-1_090082_2023-10-31_final.stac-item
2023-11-02 10:02:05	ga_ls9c_ard_3-2-1_097080_2023-11-02_final.stac-item
2023-11-04 09:47:20	ga_ls9c_ard_3-2-1_095074_2023-11-04_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_final.stac-item
2023-11-04 11:26:37	ga_ls9c_ard_3-2-1_111075_2023-11-04_final.stac-item
2023-11-04 11:29:24	ga_ls9c_ard_3-2-1_111082_2023-11-04_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-05 10:32:12	ga_ls9c_ard_3-2-1_102078_2023-11-05_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-19 10:41:03	ga_ls9c_ard_3-2-1_104069_2023-11-19_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_2023-11-20_final.stac-item
2023-11-20 11:28:19	ga_ls9c_ard_3-2-1_111079_2023-11-20_final.stac-item
2023-11-20 11:28:43	ga_ls9c_ard_3-2-1_111080_2023-11-20_final.stac-item
2023-11-21 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-11-21_final.stac-item
2023-11-21 10:32:43	ga_ls9c_ard_3-2-1_102079_2023-11-21_final.stac-item
2023-11-22 11:15:12	ga_ls9c_ard_3-2-1_109077_2023-11-22_final.stac-item
2023-11-22 11:15:36	ga_ls9c_ard_3-2-1_109078_2023-11-22_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_final.stac-item
2023-11-25 10:06:27	ga_ls9c_ard_3-2-1_098075_2023-11-25_final.stac-item
2024-02-16 10:40:04	ga_ls9c_ard_3-2-1_103082_2024-02-16_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