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
2021-11-13 10:03:05	ga_ls9c_ard_3-2-1_097083_2021-11-13_final.stac-item
2021-11-17 09:23:40	ga_ls9c_ard_3-2-1_091078_2021-11-16_final.stac-item
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-12-06 09:16:30	ga_ls9c_ard_3-2-1_089089_2021-12-05_final.stac-item
2021-12-09 09:43:22	ga_ls9c_ard_3-2-1_094079_2021-12-09_final.stac-item
2021-12-18 09:36:19	ga_ls9c_ard_3-2-1_093077_2021-12-18_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2022-01-19 09:37:05	ga_ls9c_ard_3-2-1_093079_2022-01-19_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-01-31 10:02:38	ga_ls9c_ard_3-2-1_097081_2022-01-31_final.stac-item
2022-02-02 09:47:52	ga_ls9c_ard_3-2-1_095075_2022-02-02_final.stac-item
2022-02-13 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-02-13_final.stac-item
2022-02-16 10:02:33	ga_ls9c_ard_3-2-1_097081_2022-02-16_final.stac-item
2022-04-28 10:05:06	ga_ls9c_ard_3-2-1_098073_2022-04-28_final.stac-item
2022-06-09 10:41:34	ga_ls9c_ard_3-2-1_104072_2022-06-09_final.stac-item
2022-06-13 10:18:05	ga_ls9c_ard_3-2-1_100075_2022-06-13_final.stac-item
2022-06-15 10:05:22	ga_ls9c_ard_3-2-1_098074_2022-06-15_final.stac-item
2022-07-04 10:34:31	ga_ls9c_ard_3-2-1_103069_2022-07-04_final.stac-item
2022-07-24 10:11:53	ga_ls9c_ard_3-2-1_099074_2022-07-24_final.stac-item
2022-08-02 10:05:25	ga_ls9c_ard_3-2-1_098073_2022-08-02_final.stac-item
2022-08-08 09:29:36	ga_ls9c_ard_3-2-1_092076_2022-08-07_final.stac-item
2022-08-20 09:53:36	ga_ls9c_ard_3-2-1_096074_2022-08-20_final.stac-item
2022-09-01 10:18:20	ga_ls9c_ard_3-2-1_100074_2022-09-01_final.stac-item
2022-09-17 10:18:24	ga_ls9c_ard_3-2-1_100074_2022-09-17_final.stac-item
2022-10-03 10:18:04	ga_ls9c_ard_3-2-1_100073_2022-10-03_final.stac-item
2022-10-14 11:39:16	ga_ls9c_ard_3-2-1_113075_2022-10-14_final.stac-item
2022-10-14 11:41:16	ga_ls9c_ard_3-2-1_113080_2022-10-14_final.stac-item
2022-10-19 11:59:02	ga_ls9c_ard_3-2-1_116078_2022-10-19_final.stac-item
2022-11-04 10:20:54	ga_ls9c_ard_3-2-1_100080_2022-11-04_final.stac-item
2022-11-18 10:32:56	ga_ls9c_ard_3-2-1_102079_2022-11-18_final.stac-item
2022-11-26 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-11-26_final.stac-item
2022-11-28 09:30:17	ga_ls9c_ard_3-2-1_092077_2022-11-28_final.stac-item
2022-12-01 11:41:39	ga_ls9c_ard_3-2-1_113081_2022-12-01_final.stac-item
2022-12-03 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-12-03_final.stac-item
2022-12-04 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-12-04_final.stac-item
2022-12-07 09:24:55	ga_ls9c_ard_3-2-1_091079_2022-12-06_final.stac-item
2022-12-12 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-12-12_final.stac-item
2022-12-27 10:38:16	ga_ls9c_ard_3-2-1_103077_2022-12-27_final.stac-item
2023-01-02 11:40:06	ga_ls9c_ard_3-2-1_113077_2023-01-02_final.stac-item
2023-01-02 11:40:30	ga_ls9c_ard_3-2-1_113078_2023-01-02_final.stac-item
2023-01-08 09:26:07	ga_ls9c_ard_3-2-1_091082_2023-01-07_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-13 09:44:14	ga_ls9c_ard_3-2-1_094081_2023-01-13_final.stac-item
2023-01-13 09:46:37	ga_ls9c_ard_3-2-1_094087_2023-01-13_final.stac-item
2023-01-13 11:23:54	ga_ls9c_ard_3-2-1_110083_2023-01-13_final.stac-item
2023-01-14 10:26:41	ga_ls9c_ard_3-2-1_101079_2023-01-14_final.stac-item
2023-01-15 09:32:38	ga_ls9c_ard_3-2-1_092083_2023-01-15_final.stac-item
2023-01-18 11:40:22	ga_ls9c_ard_3-2-1_113078_2023-01-18_final.stac-item
2023-01-20 11:28:46	ga_ls9c_ard_3-2-1_111080_2023-01-20_final.stac-item
2023-01-27 09:54:59	ga_ls9c_ard_3-2-1_096077_2023-01-27_final.stac-item
2023-02-03 10:03:38	ga_ls9c_ard_3-2-1_097083_2023-02-03_final.stac-item
2023-02-03 11:39:44	ga_ls9c_ard_3-2-1_113076_2023-02-03_final.stac-item
2023-02-07 11:15:50	ga_ls9c_ard_3-2-1_109078_2023-02-07_final.stac-item
2023-02-14 09:42:18	ga_ls9c_ard_3-2-1_094076_2023-02-14_final.stac-item
2023-04-23 09:19:20	ga_ls9c_ard_3-2-1_090082_2023-04-22_final.stac-item
2023-04-24 10:00:59	ga_ls9c_ard_3-2-1_097078_2023-04-24_final.stac-item
2023-04-25 10:42:38	ga_ls9c_ard_3-2-1_104074_2023-04-25_final.stac-item
2023-04-25 10:45:02	ga_ls9c_ard_3-2-1_104080_2023-04-25_final.stac-item
2023-05-07 09:30:42	ga_ls9c_ard_3-2-1_092080_2023-05-07_final.stac-item
2023-05-28 09:46:41	ga_ls9c_ard_3-2-1_095074_2023-05-28_final.stac-item
2023-06-23 10:25:12	ga_ls9c_ard_3-2-1_101078_2023-06-23_final.stac-item
2023-07-05 10:49:44	ga_ls9c_ard_3-2-1_105077_2023-07-05_final.stac-item
2023-07-05 10:52:07	ga_ls9c_ard_3-2-1_105083_2023-07-05_final.stac-item
2023-07-16 10:29:16	ga_ls9c_ard_3-2-1_102072_2023-07-16_final.stac-item
2023-07-16 10:30:28	ga_ls9c_ard_3-2-1_102075_2023-07-16_final.stac-item
2023-07-16 10:33:16	ga_ls9c_ard_3-2-1_102082_2023-07-16_final.stac-item
2023-07-17 09:35:15	ga_ls9c_ard_3-2-1_093076_2023-07-17_final.stac-item
2023-07-17 09:36:03	ga_ls9c_ard_3-2-1_093078_2023-07-17_final.stac-item
2023-07-20 10:08:08	ga_ls9c_ard_3-2-1_098081_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
2023-07-23 10:34:38	ga_ls9c_ard_3-2-1_103070_2023-07-23_final.stac-item
2023-07-25 10:26:39	ga_ls9c_ard_3-2-1_101081_2023-07-25_final.stac-item
2023-07-28 10:57:37	ga_ls9c_ard_3-2-1_106081_2023-07-28_final.stac-item
2023-07-28 10:58:01	ga_ls9c_ard_3-2-1_106082_2023-07-28_final.stac-item
2023-07-29 11:39:18	ga_ls9c_ard_3-2-1_113077_2023-07-29_final.stac-item
2023-08-04 09:25:24	ga_ls9c_ard_3-2-1_091082_2023-08-03_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 11:45:34	ga_ls9c_ard_3-2-1_114077_2023-08-05_final.stac-item
2023-08-08 10:37:36	ga_ls9c_ard_3-2-1_103077_2023-08-08_final.stac-item
2023-10-13 10:22:54	ga_ls9c_ard_3-2-1_101070_2023-10-13_final.stac-item
2023-10-14 11:05:46	ga_ls9c_ard_3-2-1_108069_2023-10-14_final.stac-item
2023-10-15 10:12:57	ga_ls9c_ard_3-2-1_099076_2023-10-15_final.stac-item
2023-10-19 09:48:39	ga_ls9c_ard_3-2-1_095077_2023-10-19_final.stac-item
2023-10-19 11:26:44	ga_ls9c_ard_3-2-1_111075_2023-10-19_final.stac-item
2023-10-20 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-10-20_final.stac-item
2023-10-22 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-10-22_final.stac-item
2023-10-23 11:03:36	ga_ls9c_ard_3-2-1_107079_2023-10-23_final.stac-item
2023-10-24 10:06:47	ga_ls9c_ard_3-2-1_098076_2023-10-24_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 09:57:12	ga_ls9c_ard_3-2-1_096083_2023-10-26_final.stac-item
2023-10-27 10:37:39	ga_ls9c_ard_3-2-1_103076_2023-10-27_final.stac-item
2023-10-27 10:38:27	ga_ls9c_ard_3-2-1_103078_2023-10-27_final.stac-item
2023-10-28 09:44:01	ga_ls9c_ard_3-2-1_094081_2023-10-28_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-10-31 11:50:58	ga_ls9c_ard_3-2-1_115074_2023-10-31_final.stac-item
2023-11-02 10:02:29	ga_ls9c_ard_3-2-1_097081_2023-11-02_final.stac-item
2023-11-02 11:39:22	ga_ls9c_ard_3-2-1_113076_2023-11-02_final.stac-item
2023-11-02 11:40:10	ga_ls9c_ard_3-2-1_113078_2023-11-02_final.stac-item
2023-11-16 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-11-16_final.stac-item
2023-11-19 10:42:15	ga_ls9c_ard_3-2-1_104072_2023-11-19_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