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
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-11-25 09:46:04	ga_ls9c_ard_3-2-1_095075_2021-11-25_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-02-19 10:33:49	ga_ls9c_ard_3-2-1_102082_2022-02-19_final.stac-item
2022-04-02 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-04-02_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-05-02 09:45:09	ga_ls9c_ard_3-2-1_094085_2022-05-02_final.stac-item
2022-07-15 10:17:54	ga_ls9c_ard_3-2-1_100074_2022-07-15_final.stac-item
2022-08-13 09:47:47	ga_ls9c_ard_3-2-1_095075_2022-08-13_final.stac-item
2022-09-16 09:37:56	ga_ls9c_ard_3-2-1_093081_2022-09-16_final.stac-item
2022-09-23 09:44:57	ga_ls9c_ard_3-2-1_094083_2022-09-23_final.stac-item
2022-09-28 09:59:55	ga_ls9c_ard_3-2-1_097074_2022-09-28_final.stac-item
2022-10-14 09:59:11	ga_ls9c_ard_3-2-1_097072_2022-10-14_final.stac-item
2022-10-21 11:45:05	ga_ls9c_ard_3-2-1_114074_2022-10-21_final.stac-item
2022-10-22 10:48:40	ga_ls9c_ard_3-2-1_105072_2022-10-22_final.stac-item
2022-10-27 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-10-27_final.stac-item
2022-10-31 10:41:39	ga_ls9c_ard_3-2-1_104070_2022-10-31_final.stac-item
2022-11-01 09:51:13	ga_ls9c_ard_3-2-1_095083_2022-11-01_final.stac-item
2022-11-04 10:18:30	ga_ls9c_ard_3-2-1_100074_2022-11-04_final.stac-item
2022-11-04 10:20:30	ga_ls9c_ard_3-2-1_100079_2022-11-04_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-16 10:41:42	ga_ls9c_ard_3-2-1_104070_2022-11-16_final.stac-item
2022-11-18 10:32:56	ga_ls9c_ard_3-2-1_102079_2022-11-18_final.stac-item
2022-11-22 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-11-22_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-12-10 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-12-10_final.stac-item
2022-12-14 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-14_final.stac-item
2022-12-19 09:49:37	ga_ls9c_ard_3-2-1_095079_2022-12-19_final.stac-item
2022-12-27 10:38:39	ga_ls9c_ard_3-2-1_103078_2022-12-27_final.stac-item
2022-12-28 09:46:38	ga_ls9c_ard_3-2-1_094087_2022-12-28_final.stac-item
2022-12-30 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-30_final.stac-item
2022-12-30 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-30_final.stac-item
2023-01-11 11:35:53	ga_ls9c_ard_3-2-1_112082_2023-01-11_final.stac-item
2023-01-14 10:25:29	ga_ls9c_ard_3-2-1_101076_2023-01-14_final.stac-item
2023-01-15 11:11:31	ga_ls9c_ard_3-2-1_108083_2023-01-15_final.stac-item
2023-01-17 09:18:39	ga_ls9c_ard_3-2-1_090079_2023-01-16_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_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 11:01:19	ga_ls9c_ard_3-2-1_107073_2023-01-24_final.stac-item
2023-01-24 11:04:31	ga_ls9c_ard_3-2-1_107081_2023-01-24_final.stac-item
2023-01-27 09:58:10	ga_ls9c_ard_3-2-1_096085_2023-01-27_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-01-31 11:10:00	ga_ls9c_ard_3-2-1_108079_2023-01-31_final.stac-item
2023-02-01 11:51:16	ga_ls9c_ard_3-2-1_115074_2023-02-01_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 09:36:33	ga_ls9c_ard_3-2-1_093077_2023-02-07_final.stac-item
2023-02-09 11:04:40	ga_ls9c_ard_3-2-1_107081_2023-02-09_final.stac-item
2023-04-24 09:58:59	ga_ls9c_ard_3-2-1_097073_2023-04-24_final.stac-item
2023-04-28 11:12:42	ga_ls9c_ard_3-2-1_109072_2023-04-28_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_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
2023-04-30 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-04-30_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-07-15 11:28:53	ga_ls9c_ard_3-2-1_111082_2023-07-15_final.stac-item
2023-07-15 11:29:41	ga_ls9c_ard_3-2-1_111084_2023-07-15_final.stac-item
2023-07-16 10:28:52	ga_ls9c_ard_3-2-1_102071_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
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_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
2023-07-21 10:46:36	ga_ls9c_ard_3-2-1_105069_2023-07-21_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-24 09:43:48	ga_ls9c_ard_3-2-1_094082_2023-07-24_final.stac-item
2023-07-28 10:53:13	ga_ls9c_ard_3-2-1_106070_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 09:25:48	ga_ls9c_ard_3-2-1_091083_2023-08-03_final.stac-item
2023-08-05 11:44:46	ga_ls9c_ard_3-2-1_114075_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
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-17 09:59:48	ga_ls9c_ard_3-2-1_097074_2023-10-17_final.stac-item
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_2023-10-17_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-17 11:41:29	ga_ls9c_ard_3-2-1_113081_2023-10-17_final.stac-item
2023-10-19 11:26:44	ga_ls9c_ard_3-2-1_111075_2023-10-19_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-21 09:39:05	ga_ls9c_ard_3-2-1_093084_2023-10-21_final.stac-item
2023-10-21 11:17:34	ga_ls9c_ard_3-2-1_109083_2023-10-21_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-10-24 10:05:35	ga_ls9c_ard_3-2-1_098073_2023-10-24_final.stac-item
2023-10-25 10:50:26	ga_ls9c_ard_3-2-1_105077_2023-10-25_final.stac-item
2023-10-26 11:32:53	ga_ls9c_ard_3-2-1_112075_2023-10-26_final.stac-item
2023-10-27 10:34:28	ga_ls9c_ard_3-2-1_103068_2023-10-27_final.stac-item
2023-10-27 10:34:52	ga_ls9c_ard_3-2-1_103069_2023-10-27_final.stac-item
2023-10-27 10:38:03	ga_ls9c_ard_3-2-1_103077_2023-10-27_final.stac-item
2023-10-30 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-10-30_final.stac-item
2023-11-02 10:00:53	ga_ls9c_ard_3-2-1_097077_2023-11-02_final.stac-item
2023-11-02 10:03:17	ga_ls9c_ard_3-2-1_097083_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
2023-11-03 10:44:08	ga_ls9c_ard_3-2-1_104077_2023-11-03_final.stac-item
2023-11-15 09:32:25	ga_ls9c_ard_3-2-1_092083_2023-11-15_final.stac-item
2023-11-15 11:09:42	ga_ls9c_ard_3-2-1_108079_2023-11-15_final.stac-item
2023-11-15 11:10:30	ga_ls9c_ard_3-2-1_108081_2023-11-15_final.stac-item
2023-11-16 10:12:53	ga_ls9c_ard_3-2-1_099076_2023-11-16_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-18 11:41:51	ga_ls9c_ard_3-2-1_113082_2023-11-18_final.stac-item
2023-11-22 09:39:06	ga_ls9c_ard_3-2-1_093084_2023-11-22_final.stac-item
2023-11-23 10:21:35	ga_ls9c_ard_3-2-1_100082_2023-11-23_final.stac-item
2023-11-25 11:44:56	ga_ls9c_ard_3-2-1_114074_2023-11-25_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