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
2021-11-06 10:15:47	ga_ls9c_ard_3-2-1_100074_2021-11-06_final.stac-item
2021-11-13 11:41:21	ga_ls9c_ard_3-2-1_113082_2021-11-13_final.stac-item
2021-11-22 11:02:44	ga_ls9c_ard_3-2-1_107073_2021-11-22_final.stac-item
2021-11-23 10:03:38	ga_ls9c_ard_3-2-1_098072_2021-11-23_final.stac-item
2021-11-24 10:45:34	ga_ls9c_ard_3-2-1_104077_2021-11-24_final.stac-item
2021-12-06 10:48:12	ga_ls9c_ard_3-2-1_105071_2021-12-06_final.stac-item
2021-12-30 10:02:39	ga_ls9c_ard_3-2-1_097081_2021-12-30_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-01-09 10:35:18	ga_ls9c_ard_3-2-1_103070_2022-01-09_final.stac-item
2022-01-12 09:31:18	ga_ls9c_ard_3-2-1_092080_2022-01-12_final.stac-item
2022-01-19 09:39:05	ga_ls9c_ard_3-2-1_093084_2022-01-19_final.stac-item
2022-01-29 10:15:23	ga_ls9c_ard_3-2-1_099082_2022-01-29_final.stac-item
2022-02-14 11:53:01	ga_ls9c_ard_3-2-1_115079_2022-02-14_final.stac-item
2022-03-03 09:19:07	ga_ls9c_ard_3-2-1_090081_2022-03-02_final.stac-item
2022-03-24 09:34:48	ga_ls9c_ard_3-2-1_093074_2022-03-24_final.stac-item
2022-03-30 10:38:35	ga_ls9c_ard_3-2-1_103079_2022-03-30_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-04-16 09:46:03	ga_ls9c_ard_3-2-1_094087_2022-04-16_final.stac-item
2022-04-30 11:35:36	ga_ls9c_ard_3-2-1_112083_2022-04-30_final.stac-item
2022-05-07 11:40:56	ga_ls9c_ard_3-2-1_113081_2022-05-07_final.stac-item
2022-05-23 09:57:52	ga_ls9c_ard_3-2-1_097071_2022-05-23_final.stac-item
2022-05-23 09:58:16	ga_ls9c_ard_3-2-1_097072_2022-05-23_final.stac-item
2022-05-23 10:00:40	ga_ls9c_ard_3-2-1_097078_2022-05-23_final.stac-item
2022-05-27 09:35:09	ga_ls9c_ard_3-2-1_093076_2022-05-27_final.stac-item
2022-06-22 10:14:55	ga_ls9c_ard_3-2-1_099082_2022-06-22_final.stac-item
2022-06-26 09:50:17	ga_ls9c_ard_3-2-1_095082_2022-06-26_final.stac-item
2022-08-02 10:06:13	ga_ls9c_ard_3-2-1_098075_2022-08-02_final.stac-item
2022-08-03 09:13:00	ga_ls9c_ard_3-2-1_089081_2022-08-02_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-18 10:08:21	ga_ls9c_ard_3-2-1_098080_2022-08-18_final.stac-item
2022-08-18 11:47:14	ga_ls9c_ard_3-2-1_114080_2022-08-18_final.stac-item
2022-08-27 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-08-27_final.stac-item
2022-09-23 09:44:57	ga_ls9c_ard_3-2-1_094083_2022-09-23_final.stac-item
2022-10-02 09:38:00	ga_ls9c_ard_3-2-1_093081_2022-10-02_final.stac-item
2022-10-04 09:24:02	ga_ls9c_ard_3-2-1_091077_2022-10-03_final.stac-item
2022-10-21 10:09:23	ga_ls9c_ard_3-2-1_098082_2022-10-21_final.stac-item
2022-11-11 10:24:45	ga_ls9c_ard_3-2-1_101074_2022-11-11_final.stac-item
2022-11-15 10:02:50	ga_ls9c_ard_3-2-1_097081_2022-11-15_final.stac-item
2022-11-19 09:36:54	ga_ls9c_ard_3-2-1_093078_2022-11-19_final.stac-item
2022-11-22 11:46:17	ga_ls9c_ard_3-2-1_114077_2022-11-22_final.stac-item
2022-11-24 09:53:50	ga_ls9c_ard_3-2-1_096074_2022-11-24_final.stac-item
2022-11-25 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-11-25_final.stac-item
2022-11-28 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-11-28_final.stac-item
2022-12-07 09:28:30	ga_ls9c_ard_3-2-1_091088_2022-12-06_final.stac-item
2022-12-12 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-12-12_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-27 10:37:28	ga_ls9c_ard_3-2-1_103075_2022-12-27_final.stac-item
2023-01-02 10:00:49	ga_ls9c_ard_3-2-1_097076_2023-01-02_final.stac-item
2023-01-04 09:49:39	ga_ls9c_ard_3-2-1_095079_2023-01-04_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-16 10:12:41	ga_ls9c_ard_3-2-1_099075_2023-01-16_final.stac-item
2023-01-22 09:39:08	ga_ls9c_ard_3-2-1_093084_2023-01-22_final.stac-item
2023-01-24 09:28:25	ga_ls9c_ard_3-2-1_091088_2023-01-23_final.stac-item
2023-01-31 09:32:18	ga_ls9c_ard_3-2-1_092082_2023-01-31_final.stac-item
2023-02-02 10:57:15	ga_ls9c_ard_3-2-1_106078_2023-02-02_final.stac-item
2023-02-05 09:51:18	ga_ls9c_ard_3-2-1_095083_2023-02-05_final.stac-item
2023-02-10 10:07:03	ga_ls9c_ard_3-2-1_098076_2023-02-10_final.stac-item
2023-02-10 11:45:56	ga_ls9c_ard_3-2-1_114076_2023-02-10_final.stac-item
2023-03-13 09:28:13	ga_ls9c_ard_3-2-1_091088_2023-03-12_final.stac-item
2023-04-01 09:52:32	ga_ls9c_ard_3-2-1_096072_2023-04-01_final.stac-item
2023-04-03 09:46:10	ga_ls9c_ard_3-2-1_094087_2023-04-03_final.stac-item
2023-04-24 09:59:23	ga_ls9c_ard_3-2-1_097074_2023-04-24_final.stac-item
2023-05-02 09:14:13	ga_ls9c_ard_3-2-1_089085_2023-05-01_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-03 09:52:40	ga_ls9c_ard_3-2-1_096073_2023-05-03_final.stac-item
2023-05-10 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-05-10_final.stac-item
2023-06-22 09:45:32	ga_ls9c_ard_3-2-1_094087_2023-06-22_final.stac-item
2023-06-24 09:28:23	ga_ls9c_ard_3-2-1_092075_2023-06-23_final.stac-item
2023-06-24 09:31:10	ga_ls9c_ard_3-2-1_092082_2023-06-24_final.stac-item
2023-06-25 10:10:50	ga_ls9c_ard_3-2-1_099073_2023-06-25_final.stac-item
2023-06-26 09:18:25	ga_ls9c_ard_3-2-1_090081_2023-06-25_final.stac-item
2023-06-28 10:40:13	ga_ls9c_ard_3-2-1_104069_2023-06-28_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-07-01 09:34:43	ga_ls9c_ard_3-2-1_093075_2023-07-01_final.stac-item
2023-07-15 11:29:41	ga_ls9c_ard_3-2-1_111084_2023-07-15_final.stac-item
2023-07-17 11:17:19	ga_ls9c_ard_3-2-1_109084_2023-07-17_final.stac-item
2023-07-18 10:20:06	ga_ls9c_ard_3-2-1_100080_2023-07-18_final.stac-item
2023-07-19 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-07-19_final.stac-item
2023-07-24 09:40:12	ga_ls9c_ard_3-2-1_094073_2023-07-24_final.stac-item
2023-07-25 10:23:51	ga_ls9c_ard_3-2-1_101074_2023-07-25_final.stac-item
2023-07-26 11:05:57	ga_ls9c_ard_3-2-1_108071_2023-07-26_final.stac-item
2023-08-03 10:17:50	ga_ls9c_ard_3-2-1_100074_2023-08-03_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-10-17 10:03:48	ga_ls9c_ard_3-2-1_097084_2023-10-17_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-19 11:27:08	ga_ls9c_ard_3-2-1_111076_2023-10-19_final.stac-item
2023-10-21 09:39:05	ga_ls9c_ard_3-2-1_093084_2023-10-21_final.stac-item
2023-10-25 10:48:26	ga_ls9c_ard_3-2-1_105072_2023-10-25_final.stac-item
2023-10-28 11:23:18	ga_ls9c_ard_3-2-1_110082_2023-10-28_final.stac-item
2023-10-30 09:32:02	ga_ls9c_ard_3-2-1_092082_2023-10-30_final.stac-item
2023-11-01 09:20:26	ga_ls9c_ard_3-2-1_090084_2023-10-31_final.stac-item
2023-11-04 09:51:43	ga_ls9c_ard_3-2-1_095085_2023-11-04_final.stac-item
2023-11-15 09:32:25	ga_ls9c_ard_3-2-1_092083_2023-11-15_final.stac-item
2023-11-17 09:19:17	ga_ls9c_ard_3-2-1_090081_2023-11-16_final.stac-item
2023-11-18 11:41:03	ga_ls9c_ard_3-2-1_113080_2023-11-18_final.stac-item
2023-11-20 09:51:02	ga_ls9c_ard_3-2-1_095083_2023-11-20_final.stac-item
2023-11-21 10:31:31	ga_ls9c_ard_3-2-1_102076_2023-11-21_final.stac-item
2023-11-23 10:17:59	ga_ls9c_ard_3-2-1_100073_2023-11-23_final.stac-item
2023-11-24 09:28:46	ga_ls9c_ard_3-2-1_091089_2023-11-23_final.stac-item
2023-11-25 10:05:39	ga_ls9c_ard_3-2-1_098073_2023-11-25_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