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
2021-11-25 09:50:27	ga_ls9c_ard_3-2-1_095086_2021-11-25_final.stac-item
2022-01-09 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-01-09_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-08 10:49:39	ga_ls9c_ard_3-2-1_105075_2022-02-08_final.stac-item
2022-02-22 09:23:24	ga_ls9c_ard_3-2-1_091076_2022-02-21_final.stac-item
2022-02-22 09:25:00	ga_ls9c_ard_3-2-1_091080_2022-02-21_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-29 11:31:25	ga_ls9c_ard_3-2-1_112072_2022-03-29_final.stac-item
2022-04-14 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-04-14_final.stac-item
2022-04-18 11:07:21	ga_ls9c_ard_3-2-1_108074_2022-04-18_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-05-23 11:40:21	ga_ls9c_ard_3-2-1_113080_2022-05-23_final.stac-item
2022-06-05 09:29:24	ga_ls9c_ard_3-2-1_092077_2022-06-04_final.stac-item
2022-06-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-06-23_final.stac-item
2022-07-08 11:51:03	ga_ls9c_ard_3-2-1_115075_2022-07-08_final.stac-item
2022-07-12 11:26:18	ga_ls9c_ard_3-2-1_111075_2022-07-12_final.stac-item
2022-08-02 10:07:01	ga_ls9c_ard_3-2-1_098077_2022-08-02_final.stac-item
2022-09-10 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-09-10_final.stac-item
2022-09-19 11:46:33	ga_ls9c_ard_3-2-1_114078_2022-09-19_final.stac-item
2022-09-20 09:10:51	ga_ls9c_ard_3-2-1_089075_2022-09-19_final.stac-item
2022-09-25 09:29:25	ga_ls9c_ard_3-2-1_092075_2022-09-24_final.stac-item
2022-10-04 11:03:43	ga_ls9c_ard_3-2-1_107079_2022-10-04_final.stac-item
2022-10-15 09:07:58	ga_ls9c_ard_3-2-1_088083_2022-10-14_final.stac-item
2022-10-20 11:00:13	ga_ls9c_ard_3-2-1_107070_2022-10-20_final.stac-item
2022-10-22 10:49:52	ga_ls9c_ard_3-2-1_105075_2022-10-22_final.stac-item
2022-10-24 10:39:54	ga_ls9c_ard_3-2-1_103081_2022-10-24_final.stac-item
2022-11-03 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-11-03_final.stac-item
2022-11-12 09:33:07	ga_ls9c_ard_3-2-1_092084_2022-11-12_final.stac-item
2022-11-20 10:18:10	ga_ls9c_ard_3-2-1_100073_2022-11-20_final.stac-item
2022-11-26 09:46:15	ga_ls9c_ard_3-2-1_094086_2022-11-26_final.stac-item
2022-12-01 11:38:51	ga_ls9c_ard_3-2-1_113074_2022-12-01_final.stac-item
2022-12-17 11:42:05	ga_ls9c_ard_3-2-1_113082_2022-12-17_final.stac-item
2022-12-21 11:16:56	ga_ls9c_ard_3-2-1_109081_2022-12-21_final.stac-item
2022-12-28 09:46:14	ga_ls9c_ard_3-2-1_094086_2022-12-28_final.stac-item
2023-01-15 11:06:20	ga_ls9c_ard_3-2-1_108070_2023-01-15_final.stac-item
2023-02-09 11:01:05	ga_ls9c_ard_3-2-1_107072_2023-02-09_final.stac-item
2023-02-16 09:29:30	ga_ls9c_ard_3-2-1_092075_2023-02-15_final.stac-item
2023-03-06 09:22:06	ga_ls9c_ard_3-2-1_090088_2023-03-05_final.stac-item
2023-03-08 09:07:42	ga_ls9c_ard_3-2-1_088083_2023-03-07_final.stac-item
2023-03-13 10:59:55	ga_ls9c_ard_3-2-1_107070_2023-03-13_final.stac-item
2023-03-22 10:53:17	ga_ls9c_ard_3-2-1_106069_2023-03-22_final.stac-item
2023-03-25 09:46:51	ga_ls9c_ard_3-2-1_095073_2023-03-25_final.stac-item
2023-03-30 10:04:30	ga_ls9c_ard_3-2-1_098071_2023-03-30_final.stac-item
2023-04-14 11:00:01	ga_ls9c_ard_3-2-1_107071_2023-04-14_final.stac-item
2023-05-22 10:22:12	ga_ls9c_ard_3-2-1_101070_2023-05-22_final.stac-item
2023-05-24 10:08:37	ga_ls9c_ard_3-2-1_099067_2023-05-24_final.stac-item
2023-05-27 10:45:29	ga_ls9c_ard_3-2-1_104082_2023-05-27_final.stac-item
2023-06-01 09:27:08	ga_ls9c_ard_3-2-1_091087_2023-05-31_final.stac-item
2023-06-06 11:19:45	ga_ls9c_ard_3-2-1_110075_2023-06-06_final.stac-item
2023-06-17 09:26:35	ga_ls9c_ard_3-2-1_091086_2023-06-16_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-08-13 10:55:21	ga_ls9c_ard_3-2-1_106075_2023-08-13_final.stac-item
2023-08-29 09:21:49	ga_ls9c_ard_3-2-1_090088_2023-08-28_final.stac-item
2023-09-14 09:22:22	ga_ls9c_ard_3-2-1_090089_2023-09-13_final.stac-item
2023-09-22 10:09:48	ga_ls9c_ard_3-2-1_098084_2023-09-22_final.stac-item
2023-09-30 10:56:01	ga_ls9c_ard_3-2-1_106076_2023-09-30_final.stac-item
2023-10-05 11:11:50	ga_ls9c_ard_3-2-1_109069_2023-10-05_final.stac-item
2023-10-31 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-10-31_final.stac-item
2023-11-26 10:48:55	ga_ls9c_ard_3-2-1_105073_2023-11-26_final.stac-item
2023-12-04 10:01:26	ga_ls9c_ard_3-2-1_097078_2023-12-04_final.stac-item
2023-12-08 11:11:57	ga_ls9c_ard_3-2-1_109069_2023-12-08_final.stac-item
2023-12-17 11:07:28	ga_ls9c_ard_3-2-1_108073_2023-12-17_final.stac-item
2023-12-21 10:43:10	ga_ls9c_ard_3-2-1_104074_2023-12-21_final.stac-item
2023-12-22 11:26:26	ga_ls9c_ard_3-2-1_111074_2023-12-22_final.stac-item
2024-02-11 10:19:12	ga_ls9c_ard_3-2-1_100076_2024-02-11_final.stac-item
2024-02-23 09:06:24	ga_ls9c_ard_3-2-1_088080_2024-02-22_final.stac-item
2024-02-29 10:03:30	ga_ls9c_ard_3-2-1_098068_2024-02-29_final.stac-item
2024-02-29 11:47:34	ga_ls9c_ard_3-2-1_114081_2024-02-29_final.stac-item
2024-03-02 11:35:13	ga_ls9c_ard_3-2-1_112081_2024-03-02_final.stac-item
2024-03-17 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-03-16_final.stac-item
2024-03-29 11:11:44	ga_ls9c_ard_3-2-1_109069_2024-03-29_final.stac-item
2024-04-25 09:22:18	ga_ls9c_ard_3-2-1_090090_2024-04-24_final.stac-item
2024-04-30 09:37:39	ga_ls9c_ard_3-2-1_093082_2024-04-30_final.stac-item
2024-05-03 10:03:20	ga_ls9c_ard_3-2-1_098069_2024-05-03_final.stac-item
2024-05-03 10:03:44	ga_ls9c_ard_3-2-1_098070_2024-05-03_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