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
2021-12-06 10:49:00	ga_ls9c_ard_3-2-1_105073_2021-12-06_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2021-12-29 10:58:16	ga_ls9c_ard_3-2-1_106081_2021-12-29_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-06 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-06_final.stac-item
2022-01-07 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-07_final.stac-item
2022-01-14 10:58:12	ga_ls9c_ard_3-2-1_106081_2022-01-14_final.stac-item
2022-01-31 11:41:31	ga_ls9c_ard_3-2-1_113081_2022-01-31_final.stac-item
2022-02-03 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-02-03_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-11 09:45:39	ga_ls9c_ard_3-2-1_094085_2022-02-11_final.stac-item
2022-02-16 11:41:26	ga_ls9c_ard_3-2-1_113081_2022-02-16_final.stac-item
2022-02-18 09:47:46	ga_ls9c_ard_3-2-1_095075_2022-02-18_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-05-30 10:04:28	ga_ls9c_ard_3-2-1_098072_2022-05-30_final.stac-item
2022-06-02 10:34:11	ga_ls9c_ard_3-2-1_103069_2022-06-02_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-06-05 09:30:35	ga_ls9c_ard_3-2-1_092080_2022-06-05_final.stac-item
2022-06-18 10:34:18	ga_ls9c_ard_3-2-1_103069_2022-06-18_final.stac-item
2022-06-26 09:50:17	ga_ls9c_ard_3-2-1_095082_2022-06-26_final.stac-item
2022-07-04 10:34:31	ga_ls9c_ard_3-2-1_103069_2022-07-04_final.stac-item
2022-07-23 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-07-23_final.stac-item
2022-07-26 09:59:33	ga_ls9c_ard_3-2-1_097074_2022-07-26_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-08-01 11:01:26	ga_ls9c_ard_3-2-1_107074_2022-08-01_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-09-27 10:54:45	ga_ls9c_ard_3-2-1_106072_2022-09-27_final.stac-item
2022-09-27 10:55:56	ga_ls9c_ard_3-2-1_106075_2022-09-27_final.stac-item
2022-10-16 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-10-16_final.stac-item
2022-11-13 10:16:23	ga_ls9c_ard_3-2-1_099084_2022-11-13_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-10 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-12-10_final.stac-item
2022-12-14 09:34:42	ga_ls9c_ard_3-2-1_092088_2022-12-14_final.stac-item
2022-12-18 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-12-18_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2022-12-24 10:05:44	ga_ls9c_ard_3-2-1_098073_2022-12-24_final.stac-item
2022-12-24 10:09:43	ga_ls9c_ard_3-2-1_098083_2022-12-24_final.stac-item
2022-12-24 10:10:07	ga_ls9c_ard_3-2-1_098084_2022-12-24_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-13 09:44:14	ga_ls9c_ard_3-2-1_094081_2023-01-13_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-17 10:57:32	ga_ls9c_ard_3-2-1_106079_2023-01-17_final.stac-item
2023-01-27 09:56:59	ga_ls9c_ard_3-2-1_096082_2023-01-27_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-02 09:17:58	ga_ls9c_ard_3-2-1_090077_2023-02-01_final.stac-item
2023-02-02 10:53:16	ga_ls9c_ard_3-2-1_106068_2023-02-02_final.stac-item
2023-02-03 10:04:02	ga_ls9c_ard_3-2-1_097084_2023-02-03_final.stac-item
2023-02-03 11:42:07	ga_ls9c_ard_3-2-1_113082_2023-02-03_final.stac-item
2023-02-06 10:34:10	ga_ls9c_ard_3-2-1_102082_2023-02-06_final.stac-item
2023-02-07 09:38:56	ga_ls9c_ard_3-2-1_093083_2023-02-07_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-10 10:04:39	ga_ls9c_ard_3-2-1_098070_2023-02-10_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-02-14 09:46:41	ga_ls9c_ard_3-2-1_094087_2023-02-14_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-04-26 09:47:24	ga_ls9c_ard_3-2-1_095075_2023-04-26_final.stac-item
2023-05-28 11:25:34	ga_ls9c_ard_3-2-1_111074_2023-05-28_final.stac-item
2023-06-01 09:25:09	ga_ls9c_ard_3-2-1_091082_2023-05-31_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-20 10:04:33	ga_ls9c_ard_3-2-1_098072_2023-07-20_final.stac-item
2023-07-20 10:05:21	ga_ls9c_ard_3-2-1_098074_2023-07-20_final.stac-item
2023-07-20 10:05:45	ga_ls9c_ard_3-2-1_098075_2023-07-20_final.stac-item
2023-07-22 09:52:11	ga_ls9c_ard_3-2-1_096072_2023-07-22_final.stac-item
2023-07-23 10:34:14	ga_ls9c_ard_3-2-1_103069_2023-07-23_final.stac-item
2023-07-24 09:40:36	ga_ls9c_ard_3-2-1_094074_2023-07-24_final.stac-item
2023-07-24 11:23:52	ga_ls9c_ard_3-2-1_110085_2023-07-24_final.stac-item
2023-07-26 09:32:15	ga_ls9c_ard_3-2-1_092084_2023-07-26_final.stac-item
2023-07-28 10:54:25	ga_ls9c_ard_3-2-1_106073_2023-07-28_final.stac-item
2023-07-28 10:54:49	ga_ls9c_ard_3-2-1_106074_2023-07-28_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-08-04 11:04:17	ga_ls9c_ard_3-2-1_107082_2023-08-04_final.stac-item
2023-08-05 10:04:41	ga_ls9c_ard_3-2-1_098072_2023-08-05_final.stac-item
2023-08-05 10:05:29	ga_ls9c_ard_3-2-1_098074_2023-08-05_final.stac-item
2023-08-06 09:15:51	ga_ls9c_ard_3-2-1_089089_2023-08-05_final.stac-item
2023-10-14 09:29:41	ga_ls9c_ard_3-2-1_092076_2023-10-13_final.stac-item
2023-10-14 09:31:16	ga_ls9c_ard_3-2-1_092080_2023-10-14_final.stac-item
2023-10-16 09:17:44	ga_ls9c_ard_3-2-1_090077_2023-10-15_final.stac-item
2023-10-16 09:19:44	ga_ls9c_ard_3-2-1_090082_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
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-18 10:41:52	ga_ls9c_ard_3-2-1_104071_2023-10-18_final.stac-item
2023-10-18 10:42:16	ga_ls9c_ard_3-2-1_104072_2023-10-18_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-19 09:50:39	ga_ls9c_ard_3-2-1_095082_2023-10-19_final.stac-item
2023-10-19 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-10-19_final.stac-item
2023-10-21 09:35:05	ga_ls9c_ard_3-2-1_093074_2023-10-21_final.stac-item
2023-10-21 11:14:22	ga_ls9c_ard_3-2-1_109075_2023-10-21_final.stac-item
2023-10-24 10:07:35	ga_ls9c_ard_3-2-1_098078_2023-10-24_final.stac-item
2023-10-26 09:56:48	ga_ls9c_ard_3-2-1_096082_2023-10-26_final.stac-item
2023-10-27 10:34:52	ga_ls9c_ard_3-2-1_103069_2023-10-27_final.stac-item
2023-11-02 11:42:10	ga_ls9c_ard_3-2-1_113083_2023-11-02_final.stac-item
2023-11-04 09:46:56	ga_ls9c_ard_3-2-1_095073_2023-11-04_final.stac-item
2023-11-19 10:43:03	ga_ls9c_ard_3-2-1_104074_2023-11-19_final.stac-item
2023-11-20 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-11-20_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