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
2021-11-02 09:16:59	ga_ls9c_ard_3-2-1_090080_2021-11-01_final.stac-item
2021-11-03 11:33:13	ga_ls9c_ard_3-2-1_112074_2021-11-03_final.stac-item
2021-11-12 10:55:49	ga_ls9c_ard_3-2-1_106068_2021-11-12_final.stac-item
2021-11-13 11:37:23	ga_ls9c_ard_3-2-1_113072_2021-11-13_final.stac-item
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-12-05 11:46:13	ga_ls9c_ard_3-2-1_114077_2021-12-05_final.stac-item
2021-12-16 11:24:22	ga_ls9c_ard_3-2-1_111069_2021-12-16_final.stac-item
2021-12-22 09:11:36	ga_ls9c_ard_3-2-1_089077_2021-12-21_final.stac-item
2021-12-28 11:51:06	ga_ls9c_ard_3-2-1_115074_2021-12-28_final.stac-item
2022-01-07 10:47:16	ga_ls9c_ard_3-2-1_105069_2022-01-07_final.stac-item
2022-01-15 10:04:11	ga_ls9c_ard_3-2-1_097085_2022-01-15_final.stac-item
2022-01-20 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-01-20_final.stac-item
2022-01-25 10:36:55	ga_ls9c_ard_3-2-1_103074_2022-01-25_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-02-03 10:29:56	ga_ls9c_ard_3-2-1_102072_2022-02-03_final.stac-item
2022-02-07 11:44:53	ga_ls9c_ard_3-2-1_114074_2022-02-07_final.stac-item
2022-02-12 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-02-12_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-02-18 11:25:27	ga_ls9c_ard_3-2-1_111072_2022-02-18_final.stac-item
2022-02-20 11:13:04	ga_ls9c_ard_3-2-1_109072_2022-02-20_final.stac-item
2022-03-06 11:24:31	ga_ls9c_ard_3-2-1_111070_2022-03-06_final.stac-item
2022-03-21 10:42:49	ga_ls9c_ard_3-2-1_104074_2022-03-21_final.stac-item
2022-03-31 09:45:45	ga_ls9c_ard_3-2-1_094086_2022-03-31_final.stac-item
2022-04-02 09:32:36	ga_ls9c_ard_3-2-1_092084_2022-04-02_final.stac-item
2022-04-05 10:02:17	ga_ls9c_ard_3-2-1_097081_2022-04-05_final.stac-item
2022-04-05 10:03:29	ga_ls9c_ard_3-2-1_097084_2022-04-05_final.stac-item
2022-05-05 11:51:43	ga_ls9c_ard_3-2-1_115077_2022-05-05_final.stac-item
2022-05-11 11:14:34	ga_ls9c_ard_3-2-1_109077_2022-05-11_final.stac-item
2022-05-12 10:18:32	ga_ls9c_ard_3-2-1_100076_2022-05-12_final.stac-item
2022-06-16 10:52:14	ga_ls9c_ard_3-2-1_105083_2022-06-16_final.stac-item
2022-06-17 09:57:49	ga_ls9c_ard_3-2-1_096086_2022-06-17_final.stac-item
2022-06-21 11:08:30	ga_ls9c_ard_3-2-1_108077_2022-06-21_final.stac-item
2022-07-01 11:44:30	ga_ls9c_ard_3-2-1_114074_2022-07-01_final.stac-item
2022-07-10 10:02:11	ga_ls9c_ard_3-2-1_097081_2022-07-10_final.stac-item
2022-07-14 11:16:43	ga_ls9c_ard_3-2-1_109082_2022-07-14_final.stac-item
2022-07-18 10:52:03	ga_ls9c_ard_3-2-1_105082_2022-07-18_final.stac-item
2022-07-22 10:24:36	ga_ls9c_ard_3-2-1_101075_2022-07-22_final.stac-item
2022-07-23 11:11:05	ga_ls9c_ard_3-2-1_108083_2022-07-23_final.stac-item
2022-07-27 10:42:49	ga_ls9c_ard_3-2-1_104074_2022-07-27_final.stac-item
2022-08-10 10:54:33	ga_ls9c_ard_3-2-1_106072_2022-08-10_final.stac-item
2022-08-17 09:25:05	ga_ls9c_ard_3-2-1_091080_2022-08-16_final.stac-item
2022-08-24 11:07:46	ga_ls9c_ard_3-2-1_108074_2022-08-24_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 11:05:46	ga_ls9c_ard_3-2-1_108069_2022-09-09_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-16 11:14:49	ga_ls9c_ard_3-2-1_109076_2022-09-16_final.stac-item
2022-09-19 11:47:21	ga_ls9c_ard_3-2-1_114080_2022-09-19_final.stac-item
2022-09-22 10:39:47	ga_ls9c_ard_3-2-1_103081_2022-09-22_final.stac-item
2022-09-30 09:52:21	ga_ls9c_ard_3-2-1_095086_2022-09-30_final.stac-item
2022-10-12 10:14:20	ga_ls9c_ard_3-2-1_099079_2022-10-12_final.stac-item
2022-10-12 10:16:43	ga_ls9c_ard_3-2-1_099085_2022-10-12_final.stac-item
2022-10-14 10:02:47	ga_ls9c_ard_3-2-1_097081_2022-10-14_final.stac-item
2022-10-18 11:18:10	ga_ls9c_ard_3-2-1_109084_2022-10-18_final.stac-item
2022-10-26 10:25:56	ga_ls9c_ard_3-2-1_101077_2022-10-26_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-10-31 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-10-31_final.stac-item
2022-11-05 09:28:29	ga_ls9c_ard_3-2-1_091088_2022-11-04_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-12 09:33:55	ga_ls9c_ard_3-2-1_092086_2022-11-12_final.stac-item
2022-11-13 10:15:59	ga_ls9c_ard_3-2-1_099083_2022-11-13_final.stac-item
2022-11-17 11:27:45	ga_ls9c_ard_3-2-1_111077_2022-11-17_final.stac-item
2022-11-19 09:38:54	ga_ls9c_ard_3-2-1_093083_2022-11-19_final.stac-item
2022-11-21 09:25:20	ga_ls9c_ard_3-2-1_091080_2022-11-20_final.stac-item
2022-11-28 11:08:22	ga_ls9c_ard_3-2-1_108075_2022-11-28_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2022-12-07 09:26:07	ga_ls9c_ard_3-2-1_091082_2022-12-06_final.stac-item
2022-12-07 09:27:43	ga_ls9c_ard_3-2-1_091086_2022-12-06_final.stac-item
2022-12-08 11:45:04	ga_ls9c_ard_3-2-1_114074_2022-12-08_final.stac-item
2022-12-25 09:12:31	ga_ls9c_ard_3-2-1_089079_2022-12-24_final.stac-item
2023-01-08 11:01:01	ga_ls9c_ard_3-2-1_107072_2023-01-08_final.stac-item
2023-01-14 10:28:16	ga_ls9c_ard_3-2-1_101083_2023-01-14_final.stac-item
2023-01-17 10:53:32	ga_ls9c_ard_3-2-1_106069_2023-01-17_final.stac-item
2023-01-27 11:32:16	ga_ls9c_ard_3-2-1_112073_2023-01-27_final.stac-item
2023-02-02 10:54:52	ga_ls9c_ard_3-2-1_106072_2023-02-02_final.stac-item
2023-02-10 10:05:27	ga_ls9c_ard_3-2-1_098072_2023-02-10_final.stac-item
2023-02-25 11:02:02	ga_ls9c_ard_3-2-1_107075_2023-02-25_final.stac-item
2023-02-26 11:44:54	ga_ls9c_ard_3-2-1_114074_2023-02-26_final.stac-item
2023-03-13 11:05:30	ga_ls9c_ard_3-2-1_107084_2023-03-13_final.stac-item
2023-03-31 09:11:16	ga_ls9c_ard_3-2-1_089077_2023-03-30_final.stac-item
2023-03-31 10:46:58	ga_ls9c_ard_3-2-1_105069_2023-03-31_final.stac-item
2023-03-31 10:50:09	ga_ls9c_ard_3-2-1_105077_2023-03-31_final.stac-item
2023-04-10 11:26:48	ga_ls9c_ard_3-2-1_111076_2023-04-10_final.stac-item
2023-04-16 09:11:58	ga_ls9c_ard_3-2-1_089079_2023-04-15_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-06-01 09:26:44	ga_ls9c_ard_3-2-1_091086_2023-05-31_final.stac-item
2023-06-01 11:03:14	ga_ls9c_ard_3-2-1_107080_2023-06-01_final.stac-item
2023-06-03 10:46:28	ga_ls9c_ard_3-2-1_105069_2023-06-03_final.stac-item
2023-06-19 10:45:32	ga_ls9c_ard_3-2-1_105067_2023-06-19_final.stac-item
2023-07-08 11:20:40	ga_ls9c_ard_3-2-1_110077_2023-07-08_final.stac-item
2023-07-11 11:51:59	ga_ls9c_ard_3-2-1_115078_2023-07-11_final.stac-item
2023-07-15 11:24:53	ga_ls9c_ard_3-2-1_111072_2023-07-15_final.stac-item
2023-07-16 10:33:16	ga_ls9c_ard_3-2-1_102082_2023-07-16_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-08-06 09:13:52	ga_ls9c_ard_3-2-1_089084_2023-08-05_final.stac-item
2023-08-11 11:05:19	ga_ls9c_ard_3-2-1_108069_2023-08-11_final.stac-item
2023-10-14 11:07:46	ga_ls9c_ard_3-2-1_108074_2023-10-14_final.stac-item
2023-10-19 11:30:20	ga_ls9c_ard_3-2-1_111084_2023-10-19_final.stac-item
2023-11-01 10:53:44	ga_ls9c_ard_3-2-1_106070_2023-11-01_final.stac-item
2023-11-16 11:52:34	ga_ls9c_ard_3-2-1_115078_2023-11-16_final.stac-item
2023-11-19 09:06:57	ga_ls9c_ard_3-2-1_088081_2023-11-18_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