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
2021-11-22 11:02:20	ga_ls9c_ard_3-2-1_107072_2021-11-22_final.stac-item
2021-12-29 10:58:16	ga_ls9c_ard_3-2-1_106081_2021-12-29_final.stac-item
2022-01-12 11:10:11	ga_ls9c_ard_3-2-1_108080_2022-01-12_final.stac-item
2022-01-14 09:22:31	ga_ls9c_ard_3-2-1_090089_2022-01-13_final.stac-item
2022-02-03 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-02-03_final.stac-item
2022-02-27 09:45:28	ga_ls9c_ard_3-2-1_094085_2022-02-27_final.stac-item
2022-03-02 10:12:44	ga_ls9c_ard_3-2-1_099076_2022-03-02_final.stac-item
2022-03-30 10:37:47	ga_ls9c_ard_3-2-1_103077_2022-03-30_final.stac-item
2022-03-31 09:45:21	ga_ls9c_ard_3-2-1_094085_2022-03-31_final.stac-item
2022-06-09 10:43:57	ga_ls9c_ard_3-2-1_104078_2022-06-09_final.stac-item
2022-06-25 10:44:18	ga_ls9c_ard_3-2-1_104078_2022-06-25_final.stac-item
2022-06-30 09:23:57	ga_ls9c_ard_3-2-1_091078_2022-06-29_final.stac-item
2022-08-05 10:34:45	ga_ls9c_ard_3-2-1_103069_2022-08-05_final.stac-item
2022-08-11 09:59:44	ga_ls9c_ard_3-2-1_097074_2022-08-11_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-08-31 11:13:10	ga_ls9c_ard_3-2-1_109072_2022-08-31_final.stac-item
2022-09-02 09:23:55	ga_ls9c_ard_3-2-1_091077_2022-09-01_final.stac-item
2022-09-23 11:23:03	ga_ls9c_ard_3-2-1_110081_2022-09-23_final.stac-item
2022-09-29 10:42:47	ga_ls9c_ard_3-2-1_104073_2022-09-29_final.stac-item
2022-09-30 09:50:45	ga_ls9c_ard_3-2-1_095082_2022-09-30_final.stac-item
2022-10-12 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-10-12_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-11-01 09:48:01	ga_ls9c_ard_3-2-1_095075_2022-11-01_final.stac-item
2022-11-10 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-10_final.stac-item
2022-11-23 10:51:04	ga_ls9c_ard_3-2-1_105078_2022-11-23_final.stac-item
2022-11-24 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-11-24_final.stac-item
2022-11-24 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-11-24_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-12-05 09:37:16	ga_ls9c_ard_3-2-1_093079_2022-12-05_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_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 10:09:19	ga_ls9c_ard_3-2-1_098082_2022-12-24_final.stac-item
2023-01-02 10:00:01	ga_ls9c_ard_3-2-1_097074_2023-01-02_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 11:04:12	ga_ls9c_ard_3-2-1_107080_2023-01-08_final.stac-item
2023-01-12 10:38:40	ga_ls9c_ard_3-2-1_103078_2023-01-12_final.stac-item
2023-01-24 11:01:19	ga_ls9c_ard_3-2-1_107073_2023-01-24_final.stac-item
2023-01-31 11:10:00	ga_ls9c_ard_3-2-1_108079_2023-01-31_final.stac-item
2023-02-02 10:57:15	ga_ls9c_ard_3-2-1_106078_2023-02-02_final.stac-item
2023-02-03 11:39:44	ga_ls9c_ard_3-2-1_113076_2023-02-03_final.stac-item
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_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
2023-04-24 11:40:16	ga_ls9c_ard_3-2-1_113079_2023-04-24_final.stac-item
2023-04-25 10:41:03	ga_ls9c_ard_3-2-1_104070_2023-04-25_final.stac-item
2023-04-26 11:28:17	ga_ls9c_ard_3-2-1_111080_2023-04-26_final.stac-item
2023-05-28 11:26:22	ga_ls9c_ard_3-2-1_111076_2023-05-28_final.stac-item
2023-05-28 11:28:45	ga_ls9c_ard_3-2-1_111082_2023-05-28_final.stac-item
2023-07-05 10:50:08	ga_ls9c_ard_3-2-1_105078_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 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-17 09:38:26	ga_ls9c_ard_3-2-1_093084_2023-07-17_final.stac-item
2023-07-19 09:25:41	ga_ls9c_ard_3-2-1_091083_2023-07-18_final.stac-item
2023-07-20 10:02:33	ga_ls9c_ard_3-2-1_098067_2023-07-20_final.stac-item
2023-07-27 10:11:32	ga_ls9c_ard_3-2-1_099074_2023-07-27_final.stac-item
2023-08-02 09:35:21	ga_ls9c_ard_3-2-1_093076_2023-08-02_final.stac-item
2023-08-02 09:38:33	ga_ls9c_ard_3-2-1_093084_2023-08-02_final.stac-item
2023-08-04 09:25:48	ga_ls9c_ard_3-2-1_091083_2023-08-03_final.stac-item
2023-08-04 11:00:18	ga_ls9c_ard_3-2-1_107072_2023-08-04_final.stac-item
2023-08-04 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-08-04_final.stac-item
2023-08-08 10:36:00	ga_ls9c_ard_3-2-1_103073_2023-08-08_final.stac-item
2023-10-13 10:24:29	ga_ls9c_ard_3-2-1_101074_2023-10-13_final.stac-item
2023-10-14 09:32:28	ga_ls9c_ard_3-2-1_092083_2023-10-14_final.stac-item
2023-10-14 11:10:57	ga_ls9c_ard_3-2-1_108082_2023-10-14_final.stac-item
2023-10-15 10:12:09	ga_ls9c_ard_3-2-1_099074_2023-10-15_final.stac-item
2023-10-16 09:20:08	ga_ls9c_ard_3-2-1_090083_2023-10-15_final.stac-item
2023-10-18 10:45:28	ga_ls9c_ard_3-2-1_104080_2023-10-18_final.stac-item
2023-10-19 09:48:39	ga_ls9c_ard_3-2-1_095077_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
2023-10-20 10:33:30	ga_ls9c_ard_3-2-1_102081_2023-10-20_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 11:46:28	ga_ls9c_ard_3-2-1_114078_2023-10-24_final.stac-item
2023-10-26 11:35:17	ga_ls9c_ard_3-2-1_112081_2023-10-26_final.stac-item
2023-10-27 10:37:15	ga_ls9c_ard_3-2-1_103075_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 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-02 10:01:17	ga_ls9c_ard_3-2-1_097078_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
2023-11-14 10:24:51	ga_ls9c_ard_3-2-1_101075_2023-11-14_final.stac-item
2023-11-15 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-11-15_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-16 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-11-16_final.stac-item
2023-11-17 09:20:29	ga_ls9c_ard_3-2-1_090084_2023-11-16_final.stac-item
2023-11-18 11:41:51	ga_ls9c_ard_3-2-1_113082_2023-11-18_final.stac-item
2023-11-20 09:49:26	ga_ls9c_ard_3-2-1_095079_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
2023-11-22 09:33:55	ga_ls9c_ard_3-2-1_093071_2023-11-22_final.stac-item
2023-11-22 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-11-22_final.stac-item
2023-11-22 09:40:18	ga_ls9c_ard_3-2-1_093087_2023-11-22_final.stac-item
2023-11-24 09:29:10	ga_ls9c_ard_3-2-1_091090_2023-11-23_final.stac-item
2023-11-24 11:03:39	ga_ls9c_ard_3-2-1_107079_2023-11-24_final.stac-item
2023-11-25 10:05:39	ga_ls9c_ard_3-2-1_098073_2023-11-25_final.stac-item
2023-11-25 10:08:50	ga_ls9c_ard_3-2-1_098081_2023-11-25_final.stac-item
2023-11-29 11:23:01	ga_ls9c_ard_3-2-1_110081_2023-11-29_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