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
2021-12-16 09:46:41	ga_ls9c_ard_3-2-1_095072_2021-12-16_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2021-12-29 09:17:47	ga_ls9c_ard_3-2-1_090077_2021-12-28_final.stac-item
2021-12-29 10:57:28	ga_ls9c_ard_3-2-1_106079_2021-12-29_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-01-01_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-21 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-21_final.stac-item
2022-01-24 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-24_final.stac-item
2022-02-08 10:49:15	ga_ls9c_ard_3-2-1_105074_2022-02-08_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-12 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-02-12_final.stac-item
2022-02-14 11:51:25	ga_ls9c_ard_3-2-1_115075_2022-02-14_final.stac-item
2022-02-20 09:36:11	ga_ls9c_ard_3-2-1_093077_2022-02-20_final.stac-item
2022-02-20 11:12:17	ga_ls9c_ard_3-2-1_109070_2022-02-20_final.stac-item
2022-04-13 09:12:47	ga_ls9c_ard_3-2-1_089081_2022-04-12_final.stac-item
2022-04-17 10:27:42	ga_ls9c_ard_3-2-1_101083_2022-04-17_final.stac-item
2022-04-19 10:13:43	ga_ls9c_ard_3-2-1_099079_2022-04-19_final.stac-item
2022-04-27 09:27:25	ga_ls9c_ard_3-2-1_091087_2022-04-26_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-05-17 10:33:49	ga_ls9c_ard_3-2-1_103068_2022-05-17_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-06-22 11:52:12	ga_ls9c_ard_3-2-1_115078_2022-06-22_final.stac-item
2022-07-02 10:49:16	ga_ls9c_ard_3-2-1_105075_2022-07-02_final.stac-item
2022-08-03 10:49:05	ga_ls9c_ard_3-2-1_105074_2022-08-03_final.stac-item
2022-08-08 09:33:35	ga_ls9c_ard_3-2-1_092086_2022-08-08_final.stac-item
2022-08-11 11:38:37	ga_ls9c_ard_3-2-1_113074_2022-08-11_final.stac-item
2022-08-28 10:46:15	ga_ls9c_ard_3-2-1_104082_2022-08-28_final.stac-item
2022-09-04 09:12:21	ga_ls9c_ard_3-2-1_089079_2022-09-03_final.stac-item
2022-09-07 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-09-07_final.stac-item
2022-09-09 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-09-08_final.stac-item
2022-09-11 10:53:26	ga_ls9c_ard_3-2-1_106069_2022-09-11_final.stac-item
2022-09-14 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-09-14_final.stac-item
2022-09-26 10:11:05	ga_ls9c_ard_3-2-1_099071_2022-09-26_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-05 10:03:42	ga_ls9c_ard_3-2-1_098068_2022-10-05_final.stac-item
2022-10-05 10:04:30	ga_ls9c_ard_3-2-1_098070_2022-10-05_final.stac-item
2022-10-13 10:53:13	ga_ls9c_ard_3-2-1_106068_2022-10-13_final.stac-item
2022-10-20 11:00:13	ga_ls9c_ard_3-2-1_107070_2022-10-20_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-10-28 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-10-28_final.stac-item
2022-11-05 09:24:05	ga_ls9c_ard_3-2-1_091077_2022-11-04_final.stac-item
2022-11-05 09:28:05	ga_ls9c_ard_3-2-1_091087_2022-11-04_final.stac-item
2022-11-07 09:11:45	ga_ls9c_ard_3-2-1_089077_2022-11-06_final.stac-item
2022-11-12 11:08:01	ga_ls9c_ard_3-2-1_108074_2022-11-12_final.stac-item
2022-11-15 09:58:02	ga_ls9c_ard_3-2-1_097069_2022-11-15_final.stac-item
2022-11-23 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-11-22_final.stac-item
2022-11-23 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-11-23_final.stac-item
2022-11-28 11:07:59	ga_ls9c_ard_3-2-1_108074_2022-11-28_final.stac-item
2022-11-29 10:16:20	ga_ls9c_ard_3-2-1_099084_2022-11-29_final.stac-item
2022-11-30 10:53:36	ga_ls9c_ard_3-2-1_106069_2022-11-30_final.stac-item
2022-12-03 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-12-03_final.stac-item
2022-12-05 09:34:04	ga_ls9c_ard_3-2-1_093071_2022-12-05_final.stac-item
2022-12-06 10:17:20	ga_ls9c_ard_3-2-1_100071_2022-12-06_final.stac-item
2022-12-09 09:16:33	ga_ls9c_ard_3-2-1_089089_2022-12-08_final.stac-item
2022-12-09 10:47:03	ga_ls9c_ard_3-2-1_105068_2022-12-09_final.stac-item
2022-12-16 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-12-15_final.stac-item
2022-12-23 11:00:58	ga_ls9c_ard_3-2-1_107072_2022-12-23_final.stac-item
2022-12-25 09:13:43	ga_ls9c_ard_3-2-1_089082_2022-12-24_final.stac-item
2022-12-31 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-31_final.stac-item
2023-01-03 10:44:05	ga_ls9c_ard_3-2-1_104076_2023-01-03_final.stac-item
2023-01-16 10:14:17	ga_ls9c_ard_3-2-1_099079_2023-01-16_final.stac-item
2023-01-16 10:15:53	ga_ls9c_ard_3-2-1_099083_2023-01-16_final.stac-item
2023-01-19 09:07:27	ga_ls9c_ard_3-2-1_088082_2023-01-18_final.stac-item
2023-01-24 11:00:31	ga_ls9c_ard_3-2-1_107071_2023-01-24_final.stac-item
2023-01-26 09:14:54	ga_ls9c_ard_3-2-1_089085_2023-01-25_final.stac-item
2023-01-27 09:52:59	ga_ls9c_ard_3-2-1_096072_2023-01-27_final.stac-item
2023-01-30 10:28:19	ga_ls9c_ard_3-2-1_101083_2023-01-30_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-02-01 11:53:16	ga_ls9c_ard_3-2-1_115079_2023-02-01_final.stac-item
2023-02-02 10:55:16	ga_ls9c_ard_3-2-1_106073_2023-02-02_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-10 10:04:15	ga_ls9c_ard_3-2-1_098069_2023-02-10_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-02-18 09:23:06	ga_ls9c_ard_3-2-1_090090_2023-02-17_final.stac-item
2023-02-18 10:55:59	ga_ls9c_ard_3-2-1_106075_2023-02-18_final.stac-item
2023-03-21 10:14:02	ga_ls9c_ard_3-2-1_099079_2023-03-21_final.stac-item
2023-04-12 09:35:07	ga_ls9c_ard_3-2-1_093075_2023-04-12_final.stac-item
2023-04-16 09:10:22	ga_ls9c_ard_3-2-1_089075_2023-04-15_final.stac-item
2023-04-19 11:17:46	ga_ls9c_ard_3-2-1_110069_2023-04-19_final.stac-item
2023-04-19 11:19:45	ga_ls9c_ard_3-2-1_110074_2023-04-19_final.stac-item
2023-04-20 10:27:44	ga_ls9c_ard_3-2-1_101083_2023-04-20_final.stac-item
2023-04-21 11:05:48	ga_ls9c_ard_3-2-1_108070_2023-04-21_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-05-07 09:28:43	ga_ls9c_ard_3-2-1_092075_2023-05-06_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-23 11:07:03	ga_ls9c_ard_3-2-1_108074_2023-05-23_final.stac-item
2023-05-30 11:14:00	ga_ls9c_ard_3-2-1_109076_2023-05-30_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-08 09:31:16	ga_ls9c_ard_3-2-1_092082_2023-06-08_final.stac-item
2023-06-18 10:09:03	ga_ls9c_ard_3-2-1_098084_2023-06-18_final.stac-item
2023-06-29 09:51:48	ga_ls9c_ard_3-2-1_095087_2023-06-29_final.stac-item
2023-06-29 11:24:42	ga_ls9c_ard_3-2-1_111072_2023-06-29_final.stac-item
2023-09-05 11:01:45	ga_ls9c_ard_3-2-1_107075_2023-09-05_final.stac-item
2023-09-06 11:47:25	ga_ls9c_ard_3-2-1_114081_2023-09-06_final.stac-item
2023-09-22 10:09:48	ga_ls9c_ard_3-2-1_098084_2023-09-22_final.stac-item
2023-09-23 09:12:34	ga_ls9c_ard_3-2-1_089080_2023-09-22_final.stac-item
2023-09-25 10:39:28	ga_ls9c_ard_3-2-1_103081_2023-09-25_final.stac-item
2023-10-01 11:41:18	ga_ls9c_ard_3-2-1_113081_2023-10-01_final.stac-item
2023-10-14 11:06:10	ga_ls9c_ard_3-2-1_108070_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

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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years