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
2021-11-07 09:21:28	ga_ls9c_ard_3-2-1_090085_2021-11-06_final.stac-item
2021-12-10 10:28:13	ga_ls9c_ard_3-2-1_101083_2021-12-10_final.stac-item
2021-12-17 10:33:55	ga_ls9c_ard_3-2-1_102082_2021-12-17_final.stac-item
2021-12-21 11:46:06	ga_ls9c_ard_3-2-1_114077_2021-12-21_final.stac-item
2021-12-25 11:23:23	ga_ls9c_ard_3-2-1_110082_2021-12-25_final.stac-item
2021-12-27 09:32:57	ga_ls9c_ard_3-2-1_092084_2021-12-27_final.stac-item
2022-01-03 09:35:07	ga_ls9c_ard_3-2-1_093074_2022-01-03_final.stac-item
2022-01-03 11:13:12	ga_ls9c_ard_3-2-1_109072_2022-01-03_final.stac-item
2022-01-05 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-01-05_final.stac-item
2022-01-15 10:02:35	ga_ls9c_ard_3-2-1_097081_2022-01-15_final.stac-item
2022-01-16 10:41:28	ga_ls9c_ard_3-2-1_104070_2022-01-16_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-01-23 10:48:52	ga_ls9c_ard_3-2-1_105073_2022-01-23_final.stac-item
2022-01-26 09:45:41	ga_ls9c_ard_3-2-1_094085_2022-01-26_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-04 11:17:11	ga_ls9c_ard_3-2-1_109082_2022-02-04_final.stac-item
2022-02-06 09:27:08	ga_ls9c_ard_3-2-1_091085_2022-02-05_final.stac-item
2022-02-08 10:50:03	ga_ls9c_ard_3-2-1_105076_2022-02-08_final.stac-item
2022-02-10 10:34:53	ga_ls9c_ard_3-2-1_103069_2022-02-10_final.stac-item
2022-02-16 11:37:50	ga_ls9c_ard_3-2-1_113072_2022-02-16_final.stac-item
2022-02-17 09:06:55	ga_ls9c_ard_3-2-1_088081_2022-02-16_final.stac-item
2022-03-22 09:50:46	ga_ls9c_ard_3-2-1_095083_2022-03-22_final.stac-item
2022-03-22 11:27:40	ga_ls9c_ard_3-2-1_111078_2022-03-22_final.stac-item
2022-04-05 10:02:17	ga_ls9c_ard_3-2-1_097081_2022-04-05_final.stac-item
2022-04-10 10:21:12	ga_ls9c_ard_3-2-1_100082_2022-04-10_final.stac-item
2022-04-28 10:03:06	ga_ls9c_ard_3-2-1_098068_2022-04-28_final.stac-item
2022-05-07 11:41:20	ga_ls9c_ard_3-2-1_113082_2022-05-07_final.stac-item
2022-05-12 10:18:32	ga_ls9c_ard_3-2-1_100076_2022-05-12_final.stac-item
2022-05-22 09:21:00	ga_ls9c_ard_3-2-1_090087_2022-05-21_final.stac-item
2022-06-03 11:17:50	ga_ls9c_ard_3-2-1_110070_2022-06-03_final.stac-item
2022-06-05 09:30:59	ga_ls9c_ard_3-2-1_092081_2022-06-05_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-08 11:37:11	ga_ls9c_ard_3-2-1_113072_2022-06-08_final.stac-item
2022-06-14 09:24:29	ga_ls9c_ard_3-2-1_091080_2022-06-13_final.stac-item
2022-06-18 10:37:54	ga_ls9c_ard_3-2-1_103078_2022-06-18_final.stac-item
2022-06-25 09:06:37	ga_ls9c_ard_3-2-1_088081_2022-06-24_final.stac-item
2022-07-11 10:43:03	ga_ls9c_ard_3-2-1_104075_2022-07-11_final.stac-item
2022-08-04 09:58:16	ga_ls9c_ard_3-2-1_096086_2022-08-04_final.stac-item
2022-08-17 09:23:53	ga_ls9c_ard_3-2-1_091077_2022-08-16_final.stac-item
2022-08-19 09:10:44	ga_ls9c_ard_3-2-1_089075_2022-08-18_final.stac-item
2022-08-19 09:13:32	ga_ls9c_ard_3-2-1_089082_2022-08-18_final.stac-item
2022-08-26 10:53:25	ga_ls9c_ard_3-2-1_106069_2022-08-26_final.stac-item
2022-08-27 10:03:23	ga_ls9c_ard_3-2-1_097083_2022-08-27_final.stac-item
2022-08-29 09:47:26	ga_ls9c_ard_3-2-1_095074_2022-08-29_final.stac-item
2022-09-04 10:48:50	ga_ls9c_ard_3-2-1_105073_2022-09-04_final.stac-item
2022-09-10 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-09-10_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-23 09:41:22	ga_ls9c_ard_3-2-1_094074_2022-09-23_final.stac-item
2022-10-02 09:35:12	ga_ls9c_ard_3-2-1_093074_2022-10-02_final.stac-item
2022-10-14 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-10-14_final.stac-item
2022-10-21 11:46:17	ga_ls9c_ard_3-2-1_114077_2022-10-21_final.stac-item
2022-10-22 10:47:28	ga_ls9c_ard_3-2-1_105069_2022-10-22_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-26 11:18:45	ga_ls9c_ard_3-2-1_110070_2022-11-26_final.stac-item
2022-12-07 09:25:19	ga_ls9c_ard_3-2-1_091080_2022-12-06_final.stac-item
2022-12-19 11:29:18	ga_ls9c_ard_3-2-1_111081_2022-12-19_final.stac-item
2023-01-22 11:14:50	ga_ls9c_ard_3-2-1_109076_2023-01-22_final.stac-item
2023-01-26 09:14:54	ga_ls9c_ard_3-2-1_089085_2023-01-25_final.stac-item
2023-01-26 10:52:11	ga_ls9c_ard_3-2-1_105081_2023-01-26_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-12 09:52:17	ga_ls9c_ard_3-2-1_096070_2023-02-12_final.stac-item
2023-02-16 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-02-16_final.stac-item
2023-02-16 11:11:35	ga_ls9c_ard_3-2-1_108083_2023-02-16_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-03-11 09:39:46	ga_ls9c_ard_3-2-1_093086_2023-03-11_final.stac-item
2023-03-15 09:13:52	ga_ls9c_ard_3-2-1_089083_2023-03-14_final.stac-item
2023-03-15 10:46:22	ga_ls9c_ard_3-2-1_105067_2023-03-15_final.stac-item
2023-03-20 11:07:16	ga_ls9c_ard_3-2-1_108073_2023-03-20_final.stac-item
2023-04-07 10:53:32	ga_ls9c_ard_3-2-1_106070_2023-04-07_final.stac-item
2023-04-07 10:53:56	ga_ls9c_ard_3-2-1_106071_2023-04-07_final.stac-item
2023-04-14 09:22:20	ga_ls9c_ard_3-2-1_091074_2023-04-13_final.stac-item
2023-04-28 09:37:24	ga_ls9c_ard_3-2-1_093081_2023-04-28_final.stac-item
2023-05-10 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-05-10_final.stac-item
2023-06-10 10:52:35	ga_ls9c_ard_3-2-1_106069_2023-06-10_final.stac-item
2023-06-10 10:55:47	ga_ls9c_ard_3-2-1_106077_2023-06-10_final.stac-item
2023-06-17 10:59:05	ga_ls9c_ard_3-2-1_107070_2023-06-17_final.stac-item
2023-06-25 10:09:38	ga_ls9c_ard_3-2-1_099070_2023-06-25_final.stac-item
2023-07-01 09:39:54	ga_ls9c_ard_3-2-1_093088_2023-07-01_final.stac-item
2023-07-01 11:16:23	ga_ls9c_ard_3-2-1_109082_2023-07-01_final.stac-item
2023-07-03 09:21:11	ga_ls9c_ard_3-2-1_091072_2023-07-02_final.stac-item
2023-07-11 11:51:59	ga_ls9c_ard_3-2-1_115078_2023-07-11_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-07-12 10:57:58	ga_ls9c_ard_3-2-1_106082_2023-07-12_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_2023-07-27_final.stac-item
2023-07-31 11:29:22	ga_ls9c_ard_3-2-1_111083_2023-07-31_final.stac-item
2023-08-18 11:17:05	ga_ls9c_ard_3-2-1_109083_2023-08-18_final.stac-item
2023-08-21 10:09:09	ga_ls9c_ard_3-2-1_098083_2023-08-21_final.stac-item
2023-08-25 09:44:53	ga_ls9c_ard_3-2-1_094084_2023-08-25_final.stac-item
2023-08-28 11:52:19	ga_ls9c_ard_3-2-1_115078_2023-08-28_final.stac-item
2023-09-03 09:34:00	ga_ls9c_ard_3-2-1_093072_2023-09-03_final.stac-item
2023-09-23 09:12:10	ga_ls9c_ard_3-2-1_089079_2023-09-22_final.stac-item
2023-10-04 10:28:58	ga_ls9c_ard_3-2-1_102070_2023-10-04_final.stac-item
2023-10-05 11:17:49	ga_ls9c_ard_3-2-1_109084_2023-10-05_final.stac-item
2023-10-07 09:27:48	ga_ls9c_ard_3-2-1_091087_2023-10-06_final.stac-item
2023-10-11 10:34:50	ga_ls9c_ard_3-2-1_103069_2023-10-11_final.stac-item
2023-11-08 09:29:02	ga_ls9c_ard_3-2-1_091090_2023-11-07_final.stac-item
2023-11-20 09:50:38	ga_ls9c_ard_3-2-1_095082_2023-11-20_final.stac-item
2023-11-24 09:23:58	ga_ls9c_ard_3-2-1_091077_2023-11-23_final.stac-item
2023-11-25 10:08:26	ga_ls9c_ard_3-2-1_098080_2023-11-25_final.stac-item
2023-12-10 11:04:00	ga_ls9c_ard_3-2-1_107080_2023-12-10_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