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 10:05:33	ga_ls9c_ard_3-2-1_097083_2021-11-18_final.stac-item
2021-12-04 11:00:11	ga_ls9c_ard_3-2-1_107070_2021-12-04_final.stac-item
2021-12-04 11:02:10	ga_ls9c_ard_3-2-1_107075_2021-12-04_final.stac-item
2021-12-09 11:23:51	ga_ls9c_ard_3-2-1_110083_2021-12-09_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-12 09:34:05	ga_ls9c_ard_3-2-1_092087_2022-01-12_final.stac-item
2022-01-12 11:10:11	ga_ls9c_ard_3-2-1_108080_2022-01-12_final.stac-item
2022-01-31 11:41:31	ga_ls9c_ard_3-2-1_113081_2022-01-31_final.stac-item
2022-02-20 11:15:28	ga_ls9c_ard_3-2-1_109078_2022-02-20_final.stac-item
2022-02-27 09:43:04	ga_ls9c_ard_3-2-1_094079_2022-02-27_final.stac-item
2022-03-28 09:13:15	ga_ls9c_ard_3-2-1_089082_2022-03-27_final.stac-item
2022-05-09 09:49:16	ga_ls9c_ard_3-2-1_095080_2022-05-09_final.stac-item
2022-05-10 10:33:19	ga_ls9c_ard_3-2-1_102082_2022-05-10_final.stac-item
2022-07-09 10:57:01	ga_ls9c_ard_3-2-1_106079_2022-07-09_final.stac-item
2022-07-30 11:12:58	ga_ls9c_ard_3-2-1_109072_2022-07-30_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-11-14 09:18:22	ga_ls9c_ard_3-2-1_090078_2022-11-13_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-11-26 11:23:56	ga_ls9c_ard_3-2-1_110083_2022-11-26_final.stac-item
2022-11-29 11:51:14	ga_ls9c_ard_3-2-1_115074_2022-11-29_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2023-01-17 09:19:03	ga_ls9c_ard_3-2-1_090080_2023-01-16_final.stac-item
2023-01-20 09:49:29	ga_ls9c_ard_3-2-1_095079_2023-01-20_final.stac-item
2023-01-27 11:34:40	ga_ls9c_ard_3-2-1_112079_2023-01-27_final.stac-item
2023-01-29 11:21:56	ga_ls9c_ard_3-2-1_110078_2023-01-29_final.stac-item
2023-01-30 10:24:44	ga_ls9c_ard_3-2-1_101074_2023-01-30_final.stac-item
2023-02-02 10:56:51	ga_ls9c_ard_3-2-1_106077_2023-02-02_final.stac-item
2023-02-02 10:58:27	ga_ls9c_ard_3-2-1_106081_2023-02-02_final.stac-item
2023-02-05 09:51:18	ga_ls9c_ard_3-2-1_095083_2023-02-05_final.stac-item
2023-02-09 11:04:16	ga_ls9c_ard_3-2-1_107080_2023-02-09_final.stac-item
2023-04-21 09:32:30	ga_ls9c_ard_3-2-1_092084_2023-04-21_final.stac-item
2023-04-22 10:14:33	ga_ls9c_ard_3-2-1_099081_2023-04-22_final.stac-item
2023-04-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2023-04-23_final.stac-item
2023-04-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2023-04-23_final.stac-item
2023-04-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2023-04-23_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-04-26 09:47:48	ga_ls9c_ard_3-2-1_095076_2023-04-26_final.stac-item
2023-04-26 11:27:29	ga_ls9c_ard_3-2-1_111078_2023-04-26_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 11:15:06	ga_ls9c_ard_3-2-1_109078_2023-04-28_final.stac-item
2023-04-29 10:20:39	ga_ls9c_ard_3-2-1_100081_2023-04-29_final.stac-item
2023-05-28 11:26:46	ga_ls9c_ard_3-2-1_111077_2023-05-28_final.stac-item
2023-07-24 09:40:12	ga_ls9c_ard_3-2-1_094073_2023-07-24_final.stac-item
2023-07-26 11:09:32	ga_ls9c_ard_3-2-1_108080_2023-07-26_final.stac-item
2023-07-28 10:54:49	ga_ls9c_ard_3-2-1_106074_2023-07-28_final.stac-item
2023-07-28 10:56:49	ga_ls9c_ard_3-2-1_106079_2023-07-28_final.stac-item
2023-08-02 09:36:33	ga_ls9c_ard_3-2-1_093079_2023-08-02_final.stac-item
2023-08-04 11:04:41	ga_ls9c_ard_3-2-1_107083_2023-08-04_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-14 11:11:21	ga_ls9c_ard_3-2-1_108083_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
2023-10-17 10:01:48	ga_ls9c_ard_3-2-1_097079_2023-10-17_final.stac-item
2023-10-17 10:02:36	ga_ls9c_ard_3-2-1_097081_2023-10-17_final.stac-item
2023-10-17 11:39:05	ga_ls9c_ard_3-2-1_113075_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
2023-10-18 10:45:04	ga_ls9c_ard_3-2-1_104079_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
2023-10-19 09:50:15	ga_ls9c_ard_3-2-1_095081_2023-10-19_final.stac-item
2023-10-19 09:51:27	ga_ls9c_ard_3-2-1_095084_2023-10-19_final.stac-item
2023-10-19 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-10-19_final.stac-item
2023-10-19 11:29:56	ga_ls9c_ard_3-2-1_111083_2023-10-19_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-22 10:17:09	ga_ls9c_ard_3-2-1_100071_2023-10-22_final.stac-item
2023-10-23 09:24:19	ga_ls9c_ard_3-2-1_091078_2023-10-22_final.stac-item
2023-10-23 09:27:55	ga_ls9c_ard_3-2-1_091087_2023-10-22_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 11:01:36	ga_ls9c_ard_3-2-1_107074_2023-10-23_final.stac-item
2023-10-25 10:49:14	ga_ls9c_ard_3-2-1_105074_2023-10-25_final.stac-item
2023-10-26 09:54:00	ga_ls9c_ard_3-2-1_096075_2023-10-26_final.stac-item
2023-10-26 09:56:48	ga_ls9c_ard_3-2-1_096082_2023-10-26_final.stac-item
2023-10-26 11:34:29	ga_ls9c_ard_3-2-1_112079_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 09:41:14	ga_ls9c_ard_3-2-1_094074_2023-10-28_final.stac-item
2023-10-28 09:45:13	ga_ls9c_ard_3-2-1_094084_2023-10-28_final.stac-item
2023-10-30 09:34:02	ga_ls9c_ard_3-2-1_092087_2023-10-30_final.stac-item
2023-10-30 11:10:55	ga_ls9c_ard_3-2-1_108082_2023-10-30_final.stac-item
2023-10-31 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-10-31_final.stac-item
2023-10-31 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-10-31_final.stac-item
2023-11-01 10:55:44	ga_ls9c_ard_3-2-1_106075_2023-11-01_final.stac-item
2023-11-02 11:38:58	ga_ls9c_ard_3-2-1_113075_2023-11-02_final.stac-item
2023-11-04 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-11-04_final.stac-item
2023-11-04 09:50:55	ga_ls9c_ard_3-2-1_095083_2023-11-04_final.stac-item
2023-11-04 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-11-04_final.stac-item
2023-11-05 10:29:01	ga_ls9c_ard_3-2-1_102070_2023-11-05_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-15 11:10:06	ga_ls9c_ard_3-2-1_108080_2023-11-15_final.stac-item
2023-11-20 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-11-20_final.stac-item
2023-11-20 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-11-20_final.stac-item
2023-11-20 11:25:56	ga_ls9c_ard_3-2-1_111073_2023-11-20_final.stac-item
2023-11-21 10:30:43	ga_ls9c_ard_3-2-1_102074_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
2023-11-22 11:16:47	ga_ls9c_ard_3-2-1_109081_2023-11-22_final.stac-item
2023-11-24 09:28:22	ga_ls9c_ard_3-2-1_091088_2023-11-23_final.stac-item
2023-11-27 11:34:34	ga_ls9c_ard_3-2-1_112079_2023-11-27_final.stac-item
2023-11-29 11:21:49	ga_ls9c_ard_3-2-1_110078_2023-11-29_final.stac-item
2024-02-17 09:45:37	ga_ls9c_ard_3-2-1_094085_2024-02-17_final.stac-item
2024-02-18 10:27:40	ga_ls9c_ard_3-2-1_101082_2024-02-18_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