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 10:55:39	ga_ls9c_ard_3-2-1_106080_2021-11-02_final.stac-item
2021-11-13 10:03:29	ga_ls9c_ard_3-2-1_097084_2021-11-13_final.stac-item
2021-11-17 09:22:04	ga_ls9c_ard_3-2-1_091074_2021-11-16_final.stac-item
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final.stac-item
2021-12-05 10:10:08	ga_ls9c_ard_3-2-1_098084_2021-12-05_final.stac-item
2021-12-06 10:49:24	ga_ls9c_ard_3-2-1_105074_2021-12-06_final.stac-item
2021-12-28 11:53:05	ga_ls9c_ard_3-2-1_115079_2021-12-28_final.stac-item
2022-01-07 10:49:16	ga_ls9c_ard_3-2-1_105074_2022-01-07_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-09 10:34:30	ga_ls9c_ard_3-2-1_103068_2022-01-09_final.stac-item
2022-01-10 09:40:04	ga_ls9c_ard_3-2-1_094071_2022-01-10_final.stac-item
2022-01-10 11:24:09	ga_ls9c_ard_3-2-1_110084_2022-01-10_final.stac-item
2022-01-13 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-01-13_final.stac-item
2022-01-13 11:53:02	ga_ls9c_ard_3-2-1_115079_2022-01-13_final.stac-item
2022-01-26 11:19:23	ga_ls9c_ard_3-2-1_110072_2022-01-26_final.stac-item
2022-01-28 11:08:13	ga_ls9c_ard_3-2-1_108075_2022-01-28_final.stac-item
2022-02-06 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-02-06_final.stac-item
2022-02-20 09:34:11	ga_ls9c_ard_3-2-1_093072_2022-02-20_final.stac-item
2022-04-03 11:52:45	ga_ls9c_ard_3-2-1_115079_2022-04-03_final.stac-item
2022-04-18 11:07:45	ga_ls9c_ard_3-2-1_108075_2022-04-18_final.stac-item
2022-05-04 11:10:27	ga_ls9c_ard_3-2-1_108082_2022-05-04_final.stac-item
2022-05-09 11:25:21	ga_ls9c_ard_3-2-1_111073_2022-05-09_final.stac-item
2022-05-18 11:23:26	ga_ls9c_ard_3-2-1_110084_2022-05-18_final.stac-item
2022-05-23 09:56:17	ga_ls9c_ard_3-2-1_097067_2022-05-23_final.stac-item
2022-05-29 09:27:35	ga_ls9c_ard_3-2-1_091088_2022-05-28_final.stac-item
2022-06-18 10:35:30	ga_ls9c_ard_3-2-1_103072_2022-06-18_final.stac-item
2022-07-02 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-07-02_final.stac-item
2022-07-12 11:24:18	ga_ls9c_ard_3-2-1_111070_2022-07-12_final.stac-item
2022-07-21 09:46:07	ga_ls9c_ard_3-2-1_094087_2022-07-21_final.stac-item
2022-07-31 10:16:57	ga_ls9c_ard_3-2-1_100071_2022-07-31_final.stac-item
2022-08-17 09:21:53	ga_ls9c_ard_3-2-1_091072_2022-08-16_final.stac-item
2022-08-18 10:03:10	ga_ls9c_ard_3-2-1_098067_2022-08-18_final.stac-item
2022-08-18 11:47:38	ga_ls9c_ard_3-2-1_114081_2022-08-18_final.stac-item
2022-09-02 09:27:54	ga_ls9c_ard_3-2-1_091087_2022-09-01_final.stac-item
2022-09-03 10:03:35	ga_ls9c_ard_3-2-1_098068_2022-09-03_final.stac-item
2022-09-14 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-09-14_final.stac-item
2022-09-14 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-09-14_final.stac-item
2022-09-20 10:49:44	ga_ls9c_ard_3-2-1_105075_2022-09-20_final.stac-item
2022-09-25 11:08:18	ga_ls9c_ard_3-2-1_108075_2022-09-25_final.stac-item
2022-09-27 09:17:51	ga_ls9c_ard_3-2-1_090077_2022-09-26_final.stac-item
2022-09-27 10:53:09	ga_ls9c_ard_3-2-1_106068_2022-09-27_final.stac-item
2022-10-01 10:28:26	ga_ls9c_ard_3-2-1_102068_2022-10-01_final.stac-item
2022-10-02 11:17:17	ga_ls9c_ard_3-2-1_109082_2022-10-02_final.stac-item
2022-10-03 11:58:09	ga_ls9c_ard_3-2-1_116076_2022-10-03_final.stac-item
2022-10-06 10:49:45	ga_ls9c_ard_3-2-1_105075_2022-10-06_final.stac-item
2022-10-09 09:45:47	ga_ls9c_ard_3-2-1_094085_2022-10-09_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-05 11:00:11	ga_ls9c_ard_3-2-1_107070_2022-11-05_final.stac-item
2022-11-08 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-11-08_final.stac-item
2022-11-10 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-11-10_final.stac-item
2022-11-13 10:13:59	ga_ls9c_ard_3-2-1_099078_2022-11-13_final.stac-item
2022-11-20 10:17:46	ga_ls9c_ard_3-2-1_100072_2022-11-20_final.stac-item
2022-11-22 10:10:36	ga_ls9c_ard_3-2-1_098085_2022-11-22_final.stac-item
2022-11-26 09:41:28	ga_ls9c_ard_3-2-1_094074_2022-11-26_final.stac-item
2022-11-26 11:19:33	ga_ls9c_ard_3-2-1_110072_2022-11-26_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-20 10:33:41	ga_ls9c_ard_3-2-1_102081_2022-12-20_final.stac-item
2022-12-23 09:22:05	ga_ls9c_ard_3-2-1_091072_2022-12-22_final.stac-item
2022-12-23 09:23:40	ga_ls9c_ard_3-2-1_091076_2022-12-22_final.stac-item
2023-01-04 09:52:51	ga_ls9c_ard_3-2-1_095087_2023-01-04_final.stac-item
2023-01-06 11:12:59	ga_ls9c_ard_3-2-1_109071_2023-01-06_final.stac-item
2023-01-18 09:57:54	ga_ls9c_ard_3-2-1_097069_2023-01-18_final.stac-item
2023-01-23 10:17:14	ga_ls9c_ard_3-2-1_100071_2023-01-23_final.stac-item
2023-01-26 09:11:42	ga_ls9c_ard_3-2-1_089077_2023-01-25_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-01-28 10:36:16	ga_ls9c_ard_3-2-1_103072_2023-01-28_final.stac-item
2023-02-03 09:57:39	ga_ls9c_ard_3-2-1_097068_2023-02-03_final.stac-item
2023-02-04 09:07:37	ga_ls9c_ard_3-2-1_088082_2023-02-03_final.stac-item
2023-02-08 10:17:49	ga_ls9c_ard_3-2-1_100072_2023-02-08_final.stac-item
2023-02-11 09:11:49	ga_ls9c_ard_3-2-1_089077_2023-02-10_final.stac-item
2023-02-11 09:12:13	ga_ls9c_ard_3-2-1_089078_2023-02-10_final.stac-item
2023-02-27 09:10:47	ga_ls9c_ard_3-2-1_089075_2023-02-26_final.stac-item
2023-03-11 11:13:52	ga_ls9c_ard_3-2-1_109074_2023-03-11_final.stac-item
2023-03-14 10:09:53	ga_ls9c_ard_3-2-1_098084_2023-03-14_final.stac-item
2023-04-05 11:07:54	ga_ls9c_ard_3-2-1_108075_2023-04-05_final.stac-item
2023-04-06 10:10:16	ga_ls9c_ard_3-2-1_099070_2023-04-06_final.stac-item
2023-04-12 11:13:36	ga_ls9c_ard_3-2-1_109074_2023-04-12_final.stac-item
2023-04-15 10:07:11	ga_ls9c_ard_3-2-1_098078_2023-04-15_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-04-29 10:16:40	ga_ls9c_ard_3-2-1_100071_2023-04-29_final.stac-item
2023-05-02 10:48:42	ga_ls9c_ard_3-2-1_105074_2023-05-02_final.stac-item
2023-05-21 11:19:26	ga_ls9c_ard_3-2-1_110074_2023-05-21_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-05-28 09:51:52	ga_ls9c_ard_3-2-1_095087_2023-05-28_final.stac-item
2023-06-01 09:27:56	ga_ls9c_ard_3-2-1_091089_2023-05-31_final.stac-item
2023-06-25 10:08:27	ga_ls9c_ard_3-2-1_099067_2023-06-25_final.stac-item
2023-07-03 09:21:11	ga_ls9c_ard_3-2-1_091072_2023-07-02_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-05 10:50:32	ga_ls9c_ard_3-2-1_105079_2023-07-05_final.stac-item
2023-07-15 11:23:18	ga_ls9c_ard_3-2-1_111068_2023-07-15_final.stac-item
2023-07-15 11:24:06	ga_ls9c_ard_3-2-1_111070_2023-07-15_final.stac-item
2023-07-30 09:06:48	ga_ls9c_ard_3-2-1_088082_2023-07-29_final.stac-item
2023-08-05 10:07:05	ga_ls9c_ard_3-2-1_098078_2023-08-05_final.stac-item
2023-08-08 10:34:01	ga_ls9c_ard_3-2-1_103068_2023-08-08_final.stac-item
2023-08-11 09:33:37	ga_ls9c_ard_3-2-1_092087_2023-08-11_final.stac-item
2023-08-16 09:51:45	ga_ls9c_ard_3-2-1_095086_2023-08-16_final.stac-item
2023-10-15 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-10-15_final.stac-item
2023-10-31 10:14:05	ga_ls9c_ard_3-2-1_099079_2023-10-31_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_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