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

76 results

Time (local)	Label
2021-11-09 10:39:23	ga_ls9c_ard_3-2-1_103080_2021-11-09_final.stac-item
2021-11-11 10:20:39	ga_ls9c_ard_3-2-1_100080_2021-11-11_final.stac-item
2021-11-15 09:39:34	ga_ls9c_ard_3-2-1_094071_2021-11-15_final.stac-item
2021-11-15 09:44:21	ga_ls9c_ard_3-2-1_094083_2021-11-15_final.stac-item
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2021-12-18 09:33:55	ga_ls9c_ard_3-2-1_093071_2021-12-18_final.stac-item
2022-03-19 10:55:35	ga_ls9c_ard_3-2-1_106075_2022-03-19_final.stac-item
2022-03-26 09:24:49	ga_ls9c_ard_3-2-1_091080_2022-03-25_final.stac-item
2022-04-03 11:52:21	ga_ls9c_ard_3-2-1_115078_2022-04-03_final.stac-item
2022-04-10 11:58:29	ga_ls9c_ard_3-2-1_116078_2022-04-10_final.stac-item
2022-06-12 09:33:37	ga_ls9c_ard_3-2-1_093072_2022-06-12_final.stac-item
2022-06-25 10:42:19	ga_ls9c_ard_3-2-1_104073_2022-06-25_final.stac-item
2022-07-08 10:13:46	ga_ls9c_ard_3-2-1_099079_2022-07-08_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-07-18 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-18_final.stac-item
2022-08-09 10:13:16	ga_ls9c_ard_3-2-1_099077_2022-08-09_final.stac-item
2022-08-17 09:29:04	ga_ls9c_ard_3-2-1_091090_2022-08-16_final.stac-item
2022-08-30 10:33:30	ga_ls9c_ard_3-2-1_102081_2022-08-30_final.stac-item
2022-09-18 09:23:12	ga_ls9c_ard_3-2-1_091075_2022-09-17_final.stac-item
2022-10-05 10:04:06	ga_ls9c_ard_3-2-1_098069_2022-10-05_final.stac-item
2022-10-28 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-10-28_final.stac-item
2022-10-29 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-10-28_final.stac-item
2022-10-30 10:02:00	ga_ls9c_ard_3-2-1_097079_2022-10-30_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-03 09:38:50	ga_ls9c_ard_3-2-1_093083_2022-11-03_final.stac-item
2022-11-23 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-11-23_final.stac-item
2022-12-11 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-12-11_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2022-12-21 11:13:20	ga_ls9c_ard_3-2-1_109072_2022-12-21_final.stac-item
2023-01-01 10:53:14	ga_ls9c_ard_3-2-1_106068_2023-01-01_final.stac-item
2023-01-07 10:19:45	ga_ls9c_ard_3-2-1_100077_2023-01-07_final.stac-item
2023-01-09 10:04:11	ga_ls9c_ard_3-2-1_098069_2023-01-09_final.stac-item
2023-01-28 10:34:40	ga_ls9c_ard_3-2-1_103068_2023-01-28_final.stac-item
2023-02-08 11:58:42	ga_ls9c_ard_3-2-1_116077_2023-02-08_final.stac-item
2023-02-22 10:28:23	ga_ls9c_ard_3-2-1_102068_2023-02-22_final.stac-item
2023-03-28 10:19:17	ga_ls9c_ard_3-2-1_100077_2023-03-28_final.stac-item
2023-04-26 09:46:12	ga_ls9c_ard_3-2-1_095072_2023-04-26_final.stac-item
2023-05-16 09:22:29	ga_ls9c_ard_3-2-1_091075_2023-05-15_final.stac-item
2023-05-22 10:27:00	ga_ls9c_ard_3-2-1_101082_2023-05-22_final.stac-item
2023-06-16 11:57:30	ga_ls9c_ard_3-2-1_116077_2023-06-16_final.stac-item
2023-06-27 09:56:08	ga_ls9c_ard_3-2-1_097067_2023-06-27_final.stac-item
2023-07-04 10:03:40	ga_ls9c_ard_3-2-1_098070_2023-07-04_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-08-04 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-08-04_final.stac-item
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final.stac-item
2023-08-19 10:19:29	ga_ls9c_ard_3-2-1_100078_2023-08-19_final.stac-item
2023-08-22 09:11:09	ga_ls9c_ard_3-2-1_089077_2023-08-21_final.stac-item
2023-08-25 09:40:06	ga_ls9c_ard_3-2-1_094072_2023-08-25_final.stac-item
2023-08-31 09:06:40	ga_ls9c_ard_3-2-1_088081_2023-08-30_final.stac-item
2023-09-13 10:10:24	ga_ls9c_ard_3-2-1_099070_2023-09-13_final.stac-item
2023-09-22 10:03:49	ga_ls9c_ard_3-2-1_098069_2023-09-22_final.stac-item
2023-09-23 09:16:34	ga_ls9c_ard_3-2-1_089090_2023-09-22_final.stac-item
2023-09-23 10:51:51	ga_ls9c_ard_3-2-1_105081_2023-09-23_final.stac-item
2023-09-29 10:10:20	ga_ls9c_ard_3-2-1_099070_2023-09-29_final.stac-item
2023-10-02 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-10-02_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-11-01 10:53:44	ga_ls9c_ard_3-2-1_106070_2023-11-01_final.stac-item
2023-11-09 10:03:55	ga_ls9c_ard_3-2-1_098069_2023-11-09_final.stac-item
2023-12-24 09:37:11	ga_ls9c_ard_3-2-1_093079_2023-12-24_final.stac-item
2024-01-04 09:16:57	ga_ls9c_ard_3-2-1_090075_2024-01-03_final.stac-item
2024-01-18 09:30:32	ga_ls9c_ard_3-2-1_092078_2024-01-18_final.stac-item
2024-02-01 09:40:31	ga_ls9c_ard_3-2-1_094072_2024-02-01_final.stac-item
2024-02-06 09:57:05	ga_ls9c_ard_3-2-1_097067_2024-02-06_final.stac-item
2024-02-14 09:15:58	ga_ls9c_ard_3-2-1_089088_2024-02-13_final.stac-item
2024-02-18 10:24:04	ga_ls9c_ard_3-2-1_101073_2024-02-18_final.stac-item
2024-03-02 11:32:26	ga_ls9c_ard_3-2-1_112074_2024-03-02_final.stac-item
2024-03-10 09:06:31	ga_ls9c_ard_3-2-1_088080_2024-03-09_final.stac-item
2024-03-24 09:22:48	ga_ls9c_ard_3-2-1_090090_2024-03-23_final.stac-item
2024-04-17 10:04:00	ga_ls9c_ard_3-2-1_098070_2024-04-17_final.stac-item
2024-04-28 11:23:43	ga_ls9c_ard_3-2-1_111069_2024-04-28_final.stac-item
2024-05-02 09:22:05	ga_ls9c_ard_3-2-1_091074_2024-05-01_final.stac-item
2024-05-08 10:24:17	ga_ls9c_ard_3-2-1_101075_2024-05-08_final.stac-item
2024-05-13 09:06:42	ga_ls9c_ard_3-2-1_088082_2024-05-12_nrt.stac-item
2024-05-18 09:21:33	ga_ls9c_ard_3-2-1_091073_2024-05-17_nrt.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