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
2021-12-28 10:09:25	ga_ls9c_ard_3-2-1_099067_2021-12-28_final.stac-item
2021-12-28 10:09:49	ga_ls9c_ard_3-2-1_099068_2021-12-28_final.stac-item
2021-12-28 10:10:37	ga_ls9c_ard_3-2-1_099070_2021-12-28_final.stac-item
2021-12-30 09:57:03	ga_ls9c_ard_3-2-1_097067_2021-12-30_final.stac-item
2021-12-30 09:57:27	ga_ls9c_ard_3-2-1_097068_2021-12-30_final.stac-item
2021-12-30 09:57:51	ga_ls9c_ard_3-2-1_097069_2021-12-30_final.stac-item
2022-01-16 10:44:40	ga_ls9c_ard_3-2-1_104078_2022-01-16_final.stac-item
2022-01-17 11:23:56	ga_ls9c_ard_3-2-1_111068_2022-01-17_final.stac-item
2022-02-01 10:44:42	ga_ls9c_ard_3-2-1_104078_2022-02-01_final.stac-item
2022-02-03 10:30:20	ga_ls9c_ard_3-2-1_102073_2022-02-03_final.stac-item
2022-02-04 09:35:07	ga_ls9c_ard_3-2-1_093074_2022-02-04_final.stac-item
2022-02-23 10:03:28	ga_ls9c_ard_3-2-1_098068_2022-02-23_final.stac-item
2022-03-27 10:03:17	ga_ls9c_ard_3-2-1_098068_2022-03-27_final.stac-item
2022-04-19 10:08:55	ga_ls9c_ard_3-2-1_099067_2022-04-19_final.stac-item
2022-04-25 09:35:24	ga_ls9c_ard_3-2-1_093076_2022-04-25_final.stac-item
2022-04-25 09:36:35	ga_ls9c_ard_3-2-1_093079_2022-04-25_final.stac-item
2022-04-27 09:25:50	ga_ls9c_ard_3-2-1_091083_2022-04-26_final.stac-item
2022-04-27 09:26:13	ga_ls9c_ard_3-2-1_091084_2022-04-26_final.stac-item
2022-05-11 09:34:05	ga_ls9c_ard_3-2-1_093073_2022-05-11_final.stac-item
2022-05-11 09:34:29	ga_ls9c_ard_3-2-1_093074_2022-05-11_final.stac-item
2022-05-11 09:35:17	ga_ls9c_ard_3-2-1_093076_2022-05-11_final.stac-item
2022-05-11 09:36:53	ga_ls9c_ard_3-2-1_093080_2022-05-11_final.stac-item
2022-05-11 09:37:17	ga_ls9c_ard_3-2-1_093081_2022-05-11_final.stac-item
2022-05-13 09:23:18	ga_ls9c_ard_3-2-1_091077_2022-05-12_final.stac-item
2022-06-18 10:39:06	ga_ls9c_ard_3-2-1_103081_2022-06-18_final.stac-item
2022-06-19 09:44:18	ga_ls9c_ard_3-2-1_094083_2022-06-19_final.stac-item
2022-06-19 09:44:42	ga_ls9c_ard_3-2-1_094084_2022-06-19_final.stac-item
2022-07-01 10:06:49	ga_ls9c_ard_3-2-1_098077_2022-07-01_final.stac-item
2022-07-02 09:11:35	ga_ls9c_ard_3-2-1_089078_2022-07-01_final.stac-item
2022-08-12 09:07:18	ga_ls9c_ard_3-2-1_088082_2022-08-11_final.stac-item
2022-09-01 10:19:56	ga_ls9c_ard_3-2-1_100078_2022-09-01_final.stac-item
2022-09-02 09:25:07	ga_ls9c_ard_3-2-1_091080_2022-09-01_final.stac-item
2022-09-04 10:52:50	ga_ls9c_ard_3-2-1_105083_2022-09-04_final.stac-item
2022-10-01 10:32:25	ga_ls9c_ard_3-2-1_102078_2022-10-01_final.stac-item
2022-10-03 10:21:39	ga_ls9c_ard_3-2-1_100082_2022-10-03_final.stac-item
2022-10-10 10:28:16	ga_ls9c_ard_3-2-1_101083_2022-10-10_final.stac-item
2022-10-12 10:15:32	ga_ls9c_ard_3-2-1_099082_2022-10-12_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-22 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-10-21_final.stac-item
2022-10-22 09:16:34	ga_ls9c_ard_3-2-1_089089_2022-10-21_final.stac-item
2022-10-22 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-10-21_final.stac-item
2022-10-23 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-10-23_final.stac-item
2022-10-23 09:58:14	ga_ls9c_ard_3-2-1_096085_2022-10-23_final.stac-item
2022-10-23 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-10-23_final.stac-item
2022-10-30 10:02:47	ga_ls9c_ard_3-2-1_097081_2022-10-30_final.stac-item
2022-11-14 09:22:45	ga_ls9c_ard_3-2-1_090089_2022-11-13_final.stac-item
2022-11-14 09:23:09	ga_ls9c_ard_3-2-1_090090_2022-11-13_final.stac-item
2022-11-19 09:39:42	ga_ls9c_ard_3-2-1_093085_2022-11-19_final.stac-item
2022-11-30 09:18:43	ga_ls9c_ard_3-2-1_090079_2022-11-29_final.stac-item
2022-12-21 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-12-21_final.stac-item
2022-12-23 09:25:40	ga_ls9c_ard_3-2-1_091081_2022-12-22_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2022-12-27 10:35:04	ga_ls9c_ard_3-2-1_103069_2022-12-27_final.stac-item
2022-12-28 11:19:08	ga_ls9c_ard_3-2-1_110071_2022-12-28_final.stac-item
2022-12-28 11:19:32	ga_ls9c_ard_3-2-1_110072_2022-12-28_final.stac-item
2022-12-31 10:09:58	ga_ls9c_ard_3-2-1_099068_2022-12-31_final.stac-item
2023-01-04 11:25:21	ga_ls9c_ard_3-2-1_111071_2023-01-04_final.stac-item
2023-01-04 11:25:45	ga_ls9c_ard_3-2-1_111072_2023-01-04_final.stac-item
2023-01-04 11:26:09	ga_ls9c_ard_3-2-1_111073_2023-01-04_final.stac-item
2023-01-04 11:26:32	ga_ls9c_ard_3-2-1_111074_2023-01-04_final.stac-item
2023-01-05 10:28:32	ga_ls9c_ard_3-2-1_102068_2023-01-05_final.stac-item
2023-01-06 11:13:23	ga_ls9c_ard_3-2-1_109072_2023-01-06_final.stac-item
2023-01-15 09:29:27	ga_ls9c_ard_3-2-1_092075_2023-01-14_final.stac-item
2023-01-28 10:39:51	ga_ls9c_ard_3-2-1_103081_2023-01-28_final.stac-item
2023-01-29 09:45:27	ga_ls9c_ard_3-2-1_094084_2023-01-29_final.stac-item
2023-01-29 09:45:51	ga_ls9c_ard_3-2-1_094085_2023-01-29_final.stac-item
2023-01-30 10:25:08	ga_ls9c_ard_3-2-1_101075_2023-01-30_final.stac-item
2023-01-30 10:25:31	ga_ls9c_ard_3-2-1_101076_2023-01-30_final.stac-item
2023-02-03 10:00:03	ga_ls9c_ard_3-2-1_097074_2023-02-03_final.stac-item
2023-02-07 09:34:09	ga_ls9c_ard_3-2-1_093071_2023-02-07_final.stac-item
2023-02-09 09:22:12	ga_ls9c_ard_3-2-1_091072_2023-02-08_final.stac-item
2023-02-09 09:22:36	ga_ls9c_ard_3-2-1_091073_2023-02-08_final.stac-item
2023-02-09 09:23:00	ga_ls9c_ard_3-2-1_091074_2023-02-08_final.stac-item
2023-02-09 09:25:23	ga_ls9c_ard_3-2-1_091080_2023-02-08_final.stac-item
2023-02-16 09:35:30	ga_ls9c_ard_3-2-1_092090_2023-02-16_final.stac-item
2023-02-22 10:29:35	ga_ls9c_ard_3-2-1_102071_2023-02-22_final.stac-item
2023-04-25 10:40:15	ga_ls9c_ard_3-2-1_104068_2023-04-25_final.stac-item
2023-04-30 09:22:13	ga_ls9c_ard_3-2-1_091074_2023-04-29_final.stac-item
2023-06-20 11:31:59	ga_ls9c_ard_3-2-1_112075_2023-06-20_final.stac-item
2023-06-26 10:55:42	ga_ls9c_ard_3-2-1_106077_2023-06-26_final.stac-item
2023-06-26 10:56:06	ga_ls9c_ard_3-2-1_106078_2023-06-26_final.stac-item
2023-06-27 10:01:43	ga_ls9c_ard_3-2-1_097081_2023-06-27_final.stac-item
2023-06-27 10:02:07	ga_ls9c_ard_3-2-1_097082_2023-06-27_final.stac-item
2023-06-27 10:02:31	ga_ls9c_ard_3-2-1_097083_2023-06-27_final.stac-item
2023-06-27 10:02:55	ga_ls9c_ard_3-2-1_097084_2023-06-27_final.stac-item
2023-06-27 10:03:18	ga_ls9c_ard_3-2-1_097085_2023-06-27_final.stac-item
2023-06-28 09:06:55	ga_ls9c_ard_3-2-1_088083_2023-06-27_final.stac-item
2023-06-30 10:30:43	ga_ls9c_ard_3-2-1_102076_2023-06-30_final.stac-item
2023-06-30 10:31:06	ga_ls9c_ard_3-2-1_102077_2023-06-30_final.stac-item
2023-07-02 10:17:59	ga_ls9c_ard_3-2-1_100075_2023-07-02_final.stac-item
2023-07-02 10:18:23	ga_ls9c_ard_3-2-1_100076_2023-07-02_final.stac-item
2023-07-02 10:19:11	ga_ls9c_ard_3-2-1_100078_2023-07-02_final.stac-item
2023-07-03 09:23:11	ga_ls9c_ard_3-2-1_091077_2023-07-02_final.stac-item
2023-07-03 09:23:35	ga_ls9c_ard_3-2-1_091078_2023-07-02_final.stac-item
2023-08-04 09:27:48	ga_ls9c_ard_3-2-1_091088_2023-08-03_final.stac-item
2023-08-04 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-08-03_final.stac-item
2023-08-04 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-08-03_final.stac-item
2023-11-03 10:43:20	ga_ls9c_ard_3-2-1_104075_2023-11-03_final.stac-item
2023-11-24 09:25:58	ga_ls9c_ard_3-2-1_091082_2023-11-23_final.stac-item
2023-11-24 09:26:22	ga_ls9c_ard_3-2-1_091083_2023-11-23_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