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
2021-11-05 09:37:25	ga_ls9c_ard_3-2-1_093078_2021-11-05_final.stac-item
2022-01-05 09:26:45	ga_ls9c_ard_3-2-1_091084_2022-01-04_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-02-04 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-02-04_final.stac-item
2022-02-08 09:13:34	ga_ls9c_ard_3-2-1_089082_2022-02-07_final.stac-item
2022-04-06 10:45:09	ga_ls9c_ard_3-2-1_104080_2022-04-06_final.stac-item
2022-06-14 09:23:41	ga_ls9c_ard_3-2-1_091078_2022-06-13_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-07-06 10:26:08	ga_ls9c_ard_3-2-1_101079_2022-07-06_final.stac-item
2022-07-07 09:34:06	ga_ls9c_ard_3-2-1_092088_2022-07-07_final.stac-item
2022-07-14 11:11:56	ga_ls9c_ard_3-2-1_109070_2022-07-14_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-08-06 09:44:44	ga_ls9c_ard_3-2-1_094083_2022-08-06_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-17 09:25:05	ga_ls9c_ard_3-2-1_091080_2022-08-16_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_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 10:45:59	ga_ls9c_ard_3-2-1_104081_2022-09-29_final.stac-item
2022-10-06 10:51:21	ga_ls9c_ard_3-2-1_105079_2022-10-06_final.stac-item
2022-10-14 11:40:04	ga_ls9c_ard_3-2-1_113077_2022-10-14_final.stac-item
2022-10-21 11:47:29	ga_ls9c_ard_3-2-1_114080_2022-10-21_final.stac-item
2022-10-25 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-10-25_final.stac-item
2022-10-28 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-10-28_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-09 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-11-09_final.stac-item
2022-11-10 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-11-10_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-12-01 11:39:39	ga_ls9c_ard_3-2-1_113076_2022-12-01_final.stac-item
2022-12-03 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-12-03_final.stac-item
2022-12-05 09:36:04	ga_ls9c_ard_3-2-1_093076_2022-12-05_final.stac-item
2022-12-14 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-14_final.stac-item
2022-12-18 10:43:39	ga_ls9c_ard_3-2-1_104075_2022-12-18_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2023-01-17 09:22:38	ga_ls9c_ard_3-2-1_090089_2023-01-16_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-28 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-28_final.stac-item
2023-02-03 11:41:20	ga_ls9c_ard_3-2-1_113080_2023-02-03_final.stac-item
2023-02-05 09:48:54	ga_ls9c_ard_3-2-1_095077_2023-02-05_final.stac-item
2023-02-05 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-05 11:27:23	ga_ls9c_ard_3-2-1_111076_2023-02-05_final.stac-item
2023-02-05 11:28:35	ga_ls9c_ard_3-2-1_111079_2023-02-05_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-07 11:16:14	ga_ls9c_ard_3-2-1_109079_2023-02-07_final.stac-item
2023-02-08 10:17:25	ga_ls9c_ard_3-2-1_100071_2023-02-08_final.stac-item
2023-02-14 09:42:42	ga_ls9c_ard_3-2-1_094077_2023-02-14_final.stac-item
2023-04-22 11:51:27	ga_ls9c_ard_3-2-1_115076_2023-04-22_final.stac-item
2023-04-26 11:29:05	ga_ls9c_ard_3-2-1_111082_2023-04-26_final.stac-item
2023-04-27 10:31:51	ga_ls9c_ard_3-2-1_102078_2023-04-27_final.stac-item
2023-04-28 09:36:37	ga_ls9c_ard_3-2-1_093079_2023-04-28_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-04-30 09:24:37	ga_ls9c_ard_3-2-1_091080_2023-04-29_final.stac-item
2023-04-30 09:27:48	ga_ls9c_ard_3-2-1_091088_2023-04-29_final.stac-item
2023-05-28 09:49:28	ga_ls9c_ard_3-2-1_095081_2023-05-28_final.stac-item
2023-05-28 11:27:57	ga_ls9c_ard_3-2-1_111080_2023-05-28_final.stac-item
2023-07-15 11:27:41	ga_ls9c_ard_3-2-1_111079_2023-07-15_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-15 11:28:29	ga_ls9c_ard_3-2-1_111081_2023-07-15_final.stac-item
2023-07-15 11:28:53	ga_ls9c_ard_3-2-1_111082_2023-07-15_final.stac-item
2023-07-16 10:29:40	ga_ls9c_ard_3-2-1_102073_2023-07-16_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-21 10:46:12	ga_ls9c_ard_3-2-1_105068_2023-07-21_final.stac-item
2023-07-25 10:25:51	ga_ls9c_ard_3-2-1_101079_2023-07-25_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 09:12:40	ga_ls9c_ard_3-2-1_089081_2023-08-05_final.stac-item
2023-08-08 10:38:24	ga_ls9c_ard_3-2-1_103079_2023-08-08_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_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 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-10-15 10:13:21	ga_ls9c_ard_3-2-1_099077_2023-10-15_final.stac-item
2023-10-15 11:53:02	ga_ls9c_ard_3-2-1_115079_2023-10-15_final.stac-item
2023-10-17 11:39:53	ga_ls9c_ard_3-2-1_113077_2023-10-17_final.stac-item
2023-10-19 11:27:08	ga_ls9c_ard_3-2-1_111076_2023-10-19_final.stac-item
2023-10-21 11:12:23	ga_ls9c_ard_3-2-1_109070_2023-10-21_final.stac-item
2023-10-21 11:13:11	ga_ls9c_ard_3-2-1_109072_2023-10-21_final.stac-item
2023-10-24 11:46:28	ga_ls9c_ard_3-2-1_114078_2023-10-24_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-10-26 09:56:00	ga_ls9c_ard_3-2-1_096080_2023-10-26_final.stac-item
2023-10-26 11:32:53	ga_ls9c_ard_3-2-1_112075_2023-10-26_final.stac-item
2023-10-26 11:34:05	ga_ls9c_ard_3-2-1_112078_2023-10-26_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_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 10:04:05	ga_ls9c_ard_3-2-1_097085_2023-11-02_final.stac-item
2023-11-03 10:43:44	ga_ls9c_ard_3-2-1_104076_2023-11-03_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 11:08:55	ga_ls9c_ard_3-2-1_108077_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
2023-11-17 09:22:29	ga_ls9c_ard_3-2-1_090089_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 11:39:27	ga_ls9c_ard_3-2-1_113076_2023-11-18_final.stac-item
2023-11-21 10:32:43	ga_ls9c_ard_3-2-1_102079_2023-11-21_final.stac-item
2023-11-22 11:15:59	ga_ls9c_ard_3-2-1_109079_2023-11-22_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_final.stac-item
2023-11-25 11:45:20	ga_ls9c_ard_3-2-1_114075_2023-11-25_final.stac-item
2023-11-25 11:45:44	ga_ls9c_ard_3-2-1_114076_2023-11-25_final.stac-item
2023-11-26 09:13:13	ga_ls9c_ard_3-2-1_089081_2023-11-25_final.stac-item
2023-11-26 10:46:55	ga_ls9c_ard_3-2-1_105068_2023-11-26_final.stac-item
2024-02-19 11:09:42	ga_ls9c_ard_3-2-1_108079_2024-02-19_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