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
2022-01-08 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-01-08_final.stac-item
2022-01-31 11:41:31	ga_ls9c_ard_3-2-1_113081_2022-01-31_final.stac-item
2022-02-01 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-02-01_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-02-20 09:34:59	ga_ls9c_ard_3-2-1_093074_2022-02-20_final.stac-item
2022-03-04 09:57:35	ga_ls9c_ard_3-2-1_097069_2022-03-04_final.stac-item
2022-03-12 09:14:32	ga_ls9c_ard_3-2-1_089085_2022-03-11_final.stac-item
2022-04-11 09:25:58	ga_ls9c_ard_3-2-1_091083_2022-04-10_final.stac-item
2022-04-27 09:23:50	ga_ls9c_ard_3-2-1_091078_2022-04-26_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-06-13 10:16:54	ga_ls9c_ard_3-2-1_100072_2022-06-13_final.stac-item
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final.stac-item
2022-06-15 10:07:45	ga_ls9c_ard_3-2-1_098080_2022-06-15_final.stac-item
2022-06-28 09:34:43	ga_ls9c_ard_3-2-1_093074_2022-06-28_final.stac-item
2022-07-10 09:59:23	ga_ls9c_ard_3-2-1_097074_2022-07-10_final.stac-item
2022-07-15 10:17:06	ga_ls9c_ard_3-2-1_100072_2022-07-15_final.stac-item
2022-07-16 09:23:30	ga_ls9c_ard_3-2-1_091077_2022-07-15_final.stac-item
2022-07-18 09:11:34	ga_ls9c_ard_3-2-1_089078_2022-07-17_final.stac-item
2022-07-31 10:21:21	ga_ls9c_ard_3-2-1_100082_2022-07-31_final.stac-item
2022-08-02 10:06:13	ga_ls9c_ard_3-2-1_098075_2022-08-02_final.stac-item
2022-08-05 10:34:45	ga_ls9c_ard_3-2-1_103069_2022-08-05_final.stac-item
2022-08-31 09:37:52	ga_ls9c_ard_3-2-1_093081_2022-08-31_final.stac-item
2022-09-04 09:11:57	ga_ls9c_ard_3-2-1_089078_2022-09-03_final.stac-item
2022-09-16 09:37:56	ga_ls9c_ard_3-2-1_093081_2022-09-16_final.stac-item
2022-10-02 09:36:00	ga_ls9c_ard_3-2-1_093076_2022-10-02_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-10 10:25:04	ga_ls9c_ard_3-2-1_101075_2022-10-10_final.stac-item
2022-10-11 11:07:09	ga_ls9c_ard_3-2-1_108072_2022-10-11_final.stac-item
2022-10-14 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-14_final.stac-item
2022-10-20 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-10-20_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-26 10:25:08	ga_ls9c_ard_3-2-1_101075_2022-10-26_final.stac-item
2022-10-31 10:41:39	ga_ls9c_ard_3-2-1_104070_2022-10-31_final.stac-item
2022-11-03 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-11-03_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-21 11:03:50	ga_ls9c_ard_3-2-1_107079_2022-11-21_final.stac-item
2022-11-23 10:48:16	ga_ls9c_ard_3-2-1_105071_2022-11-23_final.stac-item
2022-12-08 11:45:04	ga_ls9c_ard_3-2-1_114074_2022-12-08_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2022-12-20 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-20_final.stac-item
2022-12-20 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-20_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-25 10:50:36	ga_ls9c_ard_3-2-1_105077_2022-12-25_final.stac-item
2023-01-03 10:44:28	ga_ls9c_ard_3-2-1_104077_2023-01-03_final.stac-item
2023-01-13 09:45:25	ga_ls9c_ard_3-2-1_094084_2023-01-13_final.stac-item
2023-01-13 09:46:13	ga_ls9c_ard_3-2-1_094086_2023-01-13_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-15 11:11:07	ga_ls9c_ard_3-2-1_108082_2023-01-15_final.stac-item
2023-01-16 10:13:05	ga_ls9c_ard_3-2-1_099076_2023-01-16_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-26 09:14:30	ga_ls9c_ard_3-2-1_089084_2023-01-25_final.stac-item
2023-01-29 09:42:15	ga_ls9c_ard_3-2-1_094076_2023-01-29_final.stac-item
2023-01-29 11:19:08	ga_ls9c_ard_3-2-1_110071_2023-01-29_final.stac-item
2023-01-31 09:33:06	ga_ls9c_ard_3-2-1_092084_2023-01-31_final.stac-item
2023-01-31 09:34:42	ga_ls9c_ard_3-2-1_092088_2023-01-31_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-04 10:43:19	ga_ls9c_ard_3-2-1_104074_2023-02-04_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-07 11:17:50	ga_ls9c_ard_3-2-1_109083_2023-02-07_final.stac-item
2023-02-11 09:15:25	ga_ls9c_ard_3-2-1_089086_2023-02-10_final.stac-item
2023-04-22 10:14:10	ga_ls9c_ard_3-2-1_099080_2023-04-22_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-26 11:29:53	ga_ls9c_ard_3-2-1_111084_2023-04-26_final.stac-item
2023-04-28 11:17:05	ga_ls9c_ard_3-2-1_109083_2023-04-28_final.stac-item
2023-04-29 10:17:52	ga_ls9c_ard_3-2-1_100074_2023-04-29_final.stac-item
2023-07-16 10:28:52	ga_ls9c_ard_3-2-1_102071_2023-07-16_final.stac-item
2023-07-17 11:16:55	ga_ls9c_ard_3-2-1_109083_2023-07-17_final.stac-item
2023-07-18 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-07-18_final.stac-item
2023-07-26 09:29:03	ga_ls9c_ard_3-2-1_092076_2023-07-25_final.stac-item
2023-07-26 09:32:15	ga_ls9c_ard_3-2-1_092084_2023-07-26_final.stac-item
2023-07-27 10:09:57	ga_ls9c_ard_3-2-1_099070_2023-07-27_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_2023-07-27_final.stac-item
2023-07-28 10:53:37	ga_ls9c_ard_3-2-1_106071_2023-07-28_final.stac-item
2023-08-05 10:06:41	ga_ls9c_ard_3-2-1_098077_2023-08-05_final.stac-item
2023-08-05 11:44:22	ga_ls9c_ard_3-2-1_114074_2023-08-05_final.stac-item
2023-10-17 09:59:00	ga_ls9c_ard_3-2-1_097072_2023-10-17_final.stac-item
2023-10-23 09:23:55	ga_ls9c_ard_3-2-1_091077_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
2023-10-23 11:02:48	ga_ls9c_ard_3-2-1_107077_2023-10-23_final.stac-item
2023-10-24 10:03:59	ga_ls9c_ard_3-2-1_098069_2023-10-24_final.stac-item
2023-10-25 09:13:09	ga_ls9c_ard_3-2-1_089081_2023-10-24_final.stac-item
2023-10-25 09:14:21	ga_ls9c_ard_3-2-1_089084_2023-10-24_final.stac-item
2023-10-25 10:46:27	ga_ls9c_ard_3-2-1_105067_2023-10-25_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 10:51:38	ga_ls9c_ard_3-2-1_105080_2023-10-25_final.stac-item
2023-10-26 09:52:48	ga_ls9c_ard_3-2-1_096072_2023-10-26_final.stac-item
2023-11-04 09:50:31	ga_ls9c_ard_3-2-1_095082_2023-11-04_final.stac-item
2023-11-18 11:41:51	ga_ls9c_ard_3-2-1_113082_2023-11-18_final.stac-item
2023-11-19 10:41:03	ga_ls9c_ard_3-2-1_104069_2023-11-19_final.stac-item
2023-11-23 10:21:35	ga_ls9c_ard_3-2-1_100082_2023-11-23_final.stac-item
2023-11-24 11:01:16	ga_ls9c_ard_3-2-1_107073_2023-11-24_final.stac-item
2023-11-24 11:04:27	ga_ls9c_ard_3-2-1_107081_2023-11-24_final.stac-item
2023-11-25 11:45:20	ga_ls9c_ard_3-2-1_114075_2023-11-25_final.stac-item
2023-11-26 10:47:43	ga_ls9c_ard_3-2-1_105070_2023-11-26_final.stac-item
2023-11-26 10:48:31	ga_ls9c_ard_3-2-1_105072_2023-11-26_final.stac-item
2024-02-20 10:15:15	ga_ls9c_ard_3-2-1_099082_2024-02-20_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