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
2021-11-05 09:38:13	ga_ls9c_ard_3-2-1_093080_2021-11-05_final.stac-item
2021-12-07 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-12 10:15:26	ga_ls9c_ard_3-2-1_099082_2021-12-12_final.stac-item
2021-12-14 11:41:08	ga_ls9c_ard_3-2-1_113080_2021-12-14_final.stac-item
2021-12-18 09:36:19	ga_ls9c_ard_3-2-1_093077_2021-12-18_final.stac-item
2021-12-18 11:12:48	ga_ls9c_ard_3-2-1_109071_2021-12-18_final.stac-item
2021-12-20 09:23:34	ga_ls9c_ard_3-2-1_091076_2021-12-19_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2022-01-03 09:36:19	ga_ls9c_ard_3-2-1_093077_2022-01-03_final.stac-item
2022-01-05 09:23:33	ga_ls9c_ard_3-2-1_091076_2022-01-04_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-18 10:29:07	ga_ls9c_ard_3-2-1_102070_2022-01-18_final.stac-item
2022-01-19 09:36:18	ga_ls9c_ard_3-2-1_093077_2022-01-19_final.stac-item
2022-01-21 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-01-20_final.stac-item
2022-01-25 10:38:55	ga_ls9c_ard_3-2-1_103079_2022-01-25_final.stac-item
2022-02-02 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-02-02_final.stac-item
2022-02-08 09:15:10	ga_ls9c_ard_3-2-1_089086_2022-02-07_final.stac-item
2022-02-11 09:42:27	ga_ls9c_ard_3-2-1_094077_2022-02-11_final.stac-item
2022-02-11 09:43:39	ga_ls9c_ard_3-2-1_094080_2022-02-11_final.stac-item
2022-02-15 09:17:18	ga_ls9c_ard_3-2-1_090076_2022-02-14_final.stac-item
2022-02-15 09:22:05	ga_ls9c_ard_3-2-1_090088_2022-02-14_final.stac-item
2022-02-17 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-02-17_final.stac-item
2022-02-17 10:45:00	ga_ls9c_ard_3-2-1_104079_2022-02-17_final.stac-item
2022-02-18 09:47:22	ga_ls9c_ard_3-2-1_095074_2022-02-18_final.stac-item
2022-02-18 09:50:58	ga_ls9c_ard_3-2-1_095083_2022-02-18_final.stac-item
2022-03-03 09:17:07	ga_ls9c_ard_3-2-1_090076_2022-03-02_final.stac-item
2022-03-03 09:19:31	ga_ls9c_ard_3-2-1_090082_2022-03-02_final.stac-item
2022-03-04 10:02:47	ga_ls9c_ard_3-2-1_097082_2022-03-04_final.stac-item
2022-03-05 10:44:51	ga_ls9c_ard_3-2-1_104079_2022-03-05_final.stac-item
2022-03-06 09:47:14	ga_ls9c_ard_3-2-1_095074_2022-03-06_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-03-12 10:47:26	ga_ls9c_ard_3-2-1_105070_2022-03-12_final.stac-item
2022-03-21 10:42:25	ga_ls9c_ard_3-2-1_104073_2022-03-21_final.stac-item
2022-04-04 09:17:02	ga_ls9c_ard_3-2-1_090076_2022-04-03_final.stac-item
2022-04-09 09:37:09	ga_ls9c_ard_3-2-1_093080_2022-04-09_final.stac-item
2022-04-09 11:16:26	ga_ls9c_ard_3-2-1_109081_2022-04-09_final.stac-item
2022-04-11 09:25:10	ga_ls9c_ard_3-2-1_091081_2022-04-10_final.stac-item
2022-04-13 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-04-13_final.stac-item
2022-04-18 09:28:28	ga_ls9c_ard_3-2-1_092074_2022-04-17_final.stac-item
2022-04-21 10:00:55	ga_ls9c_ard_3-2-1_097078_2022-04-21_final.stac-item
2022-04-23 11:28:38	ga_ls9c_ard_3-2-1_111081_2022-04-23_final.stac-item
2022-04-25 11:16:16	ga_ls9c_ard_3-2-1_109081_2022-04-25_final.stac-item
2022-04-30 09:51:56	ga_ls9c_ard_3-2-1_096071_2022-04-30_final.stac-item
2022-05-04 09:31:58	ga_ls9c_ard_3-2-1_092083_2022-05-04_final.stac-item
2022-05-04 11:08:52	ga_ls9c_ard_3-2-1_108078_2022-05-04_final.stac-item
2022-05-06 10:54:05	ga_ls9c_ard_3-2-1_106072_2022-05-06_final.stac-item
2022-05-07 09:59:39	ga_ls9c_ard_3-2-1_097075_2022-05-07_final.stac-item
2022-05-08 10:42:30	ga_ls9c_ard_3-2-1_104074_2022-05-08_final.stac-item
2022-05-09 11:28:33	ga_ls9c_ard_3-2-1_111081_2022-05-09_final.stac-item
2022-05-13 09:24:54	ga_ls9c_ard_3-2-1_091081_2022-05-12_final.stac-item
2022-05-14 10:06:09	ga_ls9c_ard_3-2-1_098076_2022-05-14_final.stac-item
2022-05-20 09:31:46	ga_ls9c_ard_3-2-1_092083_2022-05-20_final.stac-item
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final.stac-item
2022-05-25 11:26:23	ga_ls9c_ard_3-2-1_111076_2022-05-25_final.stac-item
2022-05-25 11:28:23	ga_ls9c_ard_3-2-1_111081_2022-05-25_final.stac-item
2022-05-30 10:06:04	ga_ls9c_ard_3-2-1_098076_2022-05-30_final.stac-item
2022-06-01 09:51:43	ga_ls9c_ard_3-2-1_096071_2022-06-01_final.stac-item
2022-06-01 11:35:23	ga_ls9c_ard_3-2-1_112083_2022-06-01_final.stac-item
2022-06-05 11:08:40	ga_ls9c_ard_3-2-1_108078_2022-06-05_final.stac-item
2022-06-07 10:53:55	ga_ls9c_ard_3-2-1_106072_2022-06-07_final.stac-item
2022-06-10 11:26:26	ga_ls9c_ard_3-2-1_111076_2022-06-10_final.stac-item
2022-06-12 09:35:37	ga_ls9c_ard_3-2-1_093077_2022-06-12_final.stac-item
2022-06-17 11:35:30	ga_ls9c_ard_3-2-1_112083_2022-06-17_final.stac-item
2022-06-21 11:08:54	ga_ls9c_ard_3-2-1_108078_2022-06-21_final.stac-item
2022-06-23 10:54:13	ga_ls9c_ard_3-2-1_106072_2022-06-23_final.stac-item
2022-06-26 11:24:46	ga_ls9c_ard_3-2-1_111071_2022-06-26_final.stac-item
2022-06-26 11:26:46	ga_ls9c_ard_3-2-1_111076_2022-06-26_final.stac-item
2022-06-27 10:28:21	ga_ls9c_ard_3-2-1_102069_2022-06-27_final.stac-item
2022-07-01 10:06:25	ga_ls9c_ard_3-2-1_098076_2022-07-01_final.stac-item
2022-07-03 11:35:43	ga_ls9c_ard_3-2-1_112083_2022-07-03_final.stac-item
2022-07-05 09:43:16	ga_ls9c_ard_3-2-1_094080_2022-07-05_final.stac-item
2022-07-07 11:08:59	ga_ls9c_ard_3-2-1_108078_2022-07-07_final.stac-item
2022-07-09 10:56:37	ga_ls9c_ard_3-2-1_106078_2022-07-09_final.stac-item
2022-07-12 11:24:42	ga_ls9c_ard_3-2-1_111071_2022-07-12_final.stac-item
2022-07-17 11:46:51	ga_ls9c_ard_3-2-1_114080_2022-07-17_final.stac-item
2022-07-18 10:46:52	ga_ls9c_ard_3-2-1_105069_2022-07-18_final.stac-item
2022-07-20 10:38:32	ga_ls9c_ard_3-2-1_103079_2022-07-20_final.stac-item
2022-07-21 09:43:19	ga_ls9c_ard_3-2-1_094080_2022-07-21_final.stac-item
2022-07-21 11:20:13	ga_ls9c_ard_3-2-1_110075_2022-07-21_final.stac-item
2022-07-22 10:27:24	ga_ls9c_ard_3-2-1_101082_2022-07-22_final.stac-item
2022-07-23 11:10:41	ga_ls9c_ard_3-2-1_108082_2022-07-23_final.stac-item
2022-07-25 10:56:45	ga_ls9c_ard_3-2-1_106078_2022-07-25_final.stac-item
2022-08-02 10:06:37	ga_ls9c_ard_3-2-1_098076_2022-08-02_final.stac-item
2022-08-06 09:43:32	ga_ls9c_ard_3-2-1_094080_2022-08-06_final.stac-item
2022-08-06 11:20:25	ga_ls9c_ard_3-2-1_110075_2022-08-06_final.stac-item
2022-08-17 11:02:22	ga_ls9c_ard_3-2-1_107076_2022-08-17_final.stac-item
2022-08-22 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-08-22_final.stac-item
2022-08-24 11:10:58	ga_ls9c_ard_3-2-1_108082_2022-08-24_final.stac-item
2022-09-03 10:08:46	ga_ls9c_ard_3-2-1_098081_2022-09-03_final.stac-item
2022-09-07 09:42:50	ga_ls9c_ard_3-2-1_094078_2022-09-07_final.stac-item
2022-09-07 11:24:07	ga_ls9c_ard_3-2-1_110084_2022-09-07_final.stac-item
2022-09-11 09:16:33	ga_ls9c_ard_3-2-1_090074_2022-09-10_final.stac-item
2022-09-11 09:22:32	ga_ls9c_ard_3-2-1_090089_2022-09-10_final.stac-item
2022-09-11 10:57:02	ga_ls9c_ard_3-2-1_106078_2022-09-11_final.stac-item
2022-09-12 09:59:25	ga_ls9c_ard_3-2-1_097073_2022-09-12_final.stac-item
2022-09-14 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-09-14_final.stac-item
2022-09-15 10:32:21	ga_ls9c_ard_3-2-1_102078_2022-09-15_final.stac-item
2022-09-21 09:54:31	ga_ls9c_ard_3-2-1_096076_2022-09-21_final.stac-item
2022-09-23 11:20:39	ga_ls9c_ard_3-2-1_110075_2022-09-23_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