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
2021-12-11 09:31:23	ga_ls9c_ard_3-2-1_092080_2021-12-11_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2022-01-10 09:45:40	ga_ls9c_ard_3-2-1_094085_2022-01-10_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-01-30 09:22:58	ga_ls9c_ard_3-2-1_090090_2022-01-29_final.stac-item
2022-02-06 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-02-05_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 11:38:52	ga_ls9c_ard_3-2-1_113075_2022-03-04_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-11 09:25:58	ga_ls9c_ard_3-2-1_091083_2022-04-10_final.stac-item
2022-05-11 11:12:58	ga_ls9c_ard_3-2-1_109073_2022-05-11_final.stac-item
2022-05-15 09:16:06	ga_ls9c_ard_3-2-1_089090_2022-05-14_final.stac-item
2022-06-08 10:02:41	ga_ls9c_ard_3-2-1_097083_2022-06-08_final.stac-item
2022-06-28 11:12:01	ga_ls9c_ard_3-2-1_109070_2022-06-28_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-09-14 09:50:40	ga_ls9c_ard_3-2-1_095082_2022-09-14_final.stac-item
2022-09-16 09:35:56	ga_ls9c_ard_3-2-1_093076_2022-09-16_final.stac-item
2022-09-25 09:32:12	ga_ls9c_ard_3-2-1_092082_2022-09-25_final.stac-item
2022-10-02 09:37:12	ga_ls9c_ard_3-2-1_093079_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
2022-10-05 11:46:34	ga_ls9c_ard_3-2-1_114078_2022-10-05_final.stac-item
2022-10-11 09:35:27	ga_ls9c_ard_3-2-1_092090_2022-10-11_final.stac-item
2022-10-11 11:07:09	ga_ls9c_ard_3-2-1_108072_2022-10-11_final.stac-item
2022-10-24 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-10-24_final.stac-item
2022-10-25 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-10-25_final.stac-item
2022-11-03 09:35:15	ga_ls9c_ard_3-2-1_093074_2022-11-03_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-17 09:51:40	ga_ls9c_ard_3-2-1_095084_2022-11-17_final.stac-item
2022-11-19 09:37:18	ga_ls9c_ard_3-2-1_093079_2022-11-19_final.stac-item
2022-11-24 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-11-24_final.stac-item
2022-12-09 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-12-09_final.stac-item
2022-12-09 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-12-09_final.stac-item
2022-12-10 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-12-10_final.stac-item
2022-12-11 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-12-11_final.stac-item
2022-12-11 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-12-11_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-29 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-12-29_final.stac-item
2023-01-04 09:46:28	ga_ls9c_ard_3-2-1_095071_2023-01-04_final.stac-item
2023-01-06 11:15:23	ga_ls9c_ard_3-2-1_109077_2023-01-06_final.stac-item
2023-01-12 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-12_final.stac-item
2023-01-12 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-12_final.stac-item
2023-01-13 09:45:25	ga_ls9c_ard_3-2-1_094084_2023-01-13_final.stac-item
2023-01-18 10:02:41	ga_ls9c_ard_3-2-1_097081_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
2023-01-22 09:36:21	ga_ls9c_ard_3-2-1_093077_2023-01-22_final.stac-item
2023-01-22 09:39:56	ga_ls9c_ard_3-2-1_093086_2023-01-22_final.stac-item
2023-01-22 11:15:38	ga_ls9c_ard_3-2-1_109078_2023-01-22_final.stac-item
2023-01-24 09:25:37	ga_ls9c_ard_3-2-1_091081_2023-01-23_final.stac-item
2023-01-24 09:28:25	ga_ls9c_ard_3-2-1_091088_2023-01-23_final.stac-item
2023-01-26 09:14:30	ga_ls9c_ard_3-2-1_089084_2023-01-25_final.stac-item
2023-01-27 09:53:47	ga_ls9c_ard_3-2-1_096074_2023-01-27_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 11:34:40	ga_ls9c_ard_3-2-1_112079_2023-01-27_final.stac-item
2023-01-28 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-28_final.stac-item
2023-01-31 11:10:48	ga_ls9c_ard_3-2-1_108081_2023-01-31_final.stac-item
2023-02-02 09:19:34	ga_ls9c_ard_3-2-1_090081_2023-02-01_final.stac-item
2023-02-03 10:02:02	ga_ls9c_ard_3-2-1_097079_2023-02-03_final.stac-item
2023-02-03 11:41:43	ga_ls9c_ard_3-2-1_113081_2023-02-03_final.stac-item
2023-02-10 11:47:56	ga_ls9c_ard_3-2-1_114081_2023-02-10_final.stac-item
2023-02-11 09:14:37	ga_ls9c_ard_3-2-1_089084_2023-02-10_final.stac-item
2023-02-11 10:52:18	ga_ls9c_ard_3-2-1_105081_2023-02-11_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-26 11:23:30	ga_ls9c_ard_3-2-1_111068_2023-04-26_final.stac-item
2023-04-28 09:38:12	ga_ls9c_ard_3-2-1_093083_2023-04-28_final.stac-item
2023-04-30 09:25:01	ga_ls9c_ard_3-2-1_091081_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
2023-04-30 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-04-30_final.stac-item
2023-05-03 11:31:33	ga_ls9c_ard_3-2-1_112073_2023-05-03_final.stac-item
2023-05-03 11:35:56	ga_ls9c_ard_3-2-1_112084_2023-05-03_final.stac-item
2023-06-27 11:40:36	ga_ls9c_ard_3-2-1_113081_2023-06-27_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_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
2023-07-20 10:04:33	ga_ls9c_ard_3-2-1_098072_2023-07-20_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-07-24 09:40:36	ga_ls9c_ard_3-2-1_094074_2023-07-24_final.stac-item
2023-07-25 10:24:39	ga_ls9c_ard_3-2-1_101076_2023-07-25_final.stac-item
2023-08-04 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-08-04_final.stac-item
2023-08-05 11:44:22	ga_ls9c_ard_3-2-1_114074_2023-08-05_final.stac-item
2023-08-06 09:14:16	ga_ls9c_ard_3-2-1_089085_2023-08-05_final.stac-item
2023-10-13 10:23:18	ga_ls9c_ard_3-2-1_101071_2023-10-13_final.stac-item
2023-10-16 09:18:08	ga_ls9c_ard_3-2-1_090078_2023-10-15_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-24 10:08:22	ga_ls9c_ard_3-2-1_098080_2023-10-24_final.stac-item
2023-10-24 11:46:04	ga_ls9c_ard_3-2-1_114077_2023-10-24_final.stac-item
2023-10-25 10:48:26	ga_ls9c_ard_3-2-1_105072_2023-10-25_final.stac-item
2023-10-26 09:52:25	ga_ls9c_ard_3-2-1_096071_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
2023-10-27 10:36:28	ga_ls9c_ard_3-2-1_103073_2023-10-27_final.stac-item
2023-11-02 11:40:58	ga_ls9c_ard_3-2-1_113080_2023-11-02_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-15 11:10:54	ga_ls9c_ard_3-2-1_108082_2023-11-15_final.stac-item
2023-11-18 11:39:03	ga_ls9c_ard_3-2-1_113075_2023-11-18_final.stac-item
2023-11-21 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-11-21_final.stac-item
2023-11-22 09:37:06	ga_ls9c_ard_3-2-1_093079_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

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