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
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-28 11:10:13	ga_ls9c_ard_3-2-1_108080_2022-01-28_final.stac-item
2022-01-30 10:58:15	ga_ls9c_ard_3-2-1_106081_2022-01-30_final.stac-item
2022-02-27 09:43:04	ga_ls9c_ard_3-2-1_094079_2022-02-27_final.stac-item
2022-03-08 09:36:52	ga_ls9c_ard_3-2-1_093079_2022-03-08_final.stac-item
2022-03-28 10:50:56	ga_ls9c_ard_3-2-1_105079_2022-03-28_final.stac-item
2022-04-02 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-04-02_final.stac-item
2022-04-06 10:45:09	ga_ls9c_ard_3-2-1_104080_2022-04-06_final.stac-item
2022-04-09 09:37:09	ga_ls9c_ard_3-2-1_093080_2022-04-09_final.stac-item
2022-04-15 10:38:05	ga_ls9c_ard_3-2-1_103078_2022-04-15_final.stac-item
2022-05-09 09:49:16	ga_ls9c_ard_3-2-1_095080_2022-05-09_final.stac-item
2022-05-16 09:53:21	ga_ls9c_ard_3-2-1_096075_2022-05-16_final.stac-item
2022-05-18 09:42:34	ga_ls9c_ard_3-2-1_094079_2022-05-18_final.stac-item
2022-05-24 10:41:32	ga_ls9c_ard_3-2-1_104072_2022-05-24_final.stac-item
2022-05-26 10:33:10	ga_ls9c_ard_3-2-1_102082_2022-05-26_final.stac-item
2022-06-09 10:43:57	ga_ls9c_ard_3-2-1_104078_2022-06-09_final.stac-item
2022-06-21 09:30:49	ga_ls9c_ard_3-2-1_092080_2022-06-21_final.stac-item
2022-06-21 11:08:30	ga_ls9c_ard_3-2-1_108077_2022-06-21_final.stac-item
2022-06-28 11:11:37	ga_ls9c_ard_3-2-1_109069_2022-06-28_final.stac-item
2022-07-06 10:26:08	ga_ls9c_ard_3-2-1_101079_2022-07-06_final.stac-item
2022-07-07 11:10:11	ga_ls9c_ard_3-2-1_108081_2022-07-07_final.stac-item
2022-07-11 10:43:27	ga_ls9c_ard_3-2-1_104076_2022-07-11_final.stac-item
2022-07-16 09:23:54	ga_ls9c_ard_3-2-1_091078_2022-07-15_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-07-23 09:30:36	ga_ls9c_ard_3-2-1_092079_2022-07-23_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-08-12 10:43:48	ga_ls9c_ard_3-2-1_104076_2022-08-12_final.stac-item
2022-09-13 10:42:18	ga_ls9c_ard_3-2-1_104072_2022-09-13_final.stac-item
2022-09-22 10:38:35	ga_ls9c_ard_3-2-1_103078_2022-09-22_final.stac-item
2022-09-27 09:20:15	ga_ls9c_ard_3-2-1_090083_2022-09-26_final.stac-item
2022-10-06 10:51:21	ga_ls9c_ard_3-2-1_105079_2022-10-06_final.stac-item
2022-10-23 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-10-23_final.stac-item
2022-10-31 10:42:03	ga_ls9c_ard_3-2-1_104071_2022-10-31_final.stac-item
2022-11-01 11:28:06	ga_ls9c_ard_3-2-1_111078_2022-11-01_final.stac-item
2022-11-03 11:16:31	ga_ls9c_ard_3-2-1_109080_2022-11-03_final.stac-item
2022-11-05 11:02:58	ga_ls9c_ard_3-2-1_107077_2022-11-05_final.stac-item
2022-11-09 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-09_final.stac-item
2022-11-11 10:27:08	ga_ls9c_ard_3-2-1_101080_2022-11-11_final.stac-item
2022-11-11 10:27:32	ga_ls9c_ard_3-2-1_101081_2022-11-11_final.stac-item
2022-11-19 09:38:30	ga_ls9c_ard_3-2-1_093082_2022-11-19_final.stac-item
2022-11-19 11:16:35	ga_ls9c_ard_3-2-1_109080_2022-11-19_final.stac-item
2022-11-21 11:04:13	ga_ls9c_ard_3-2-1_107080_2022-11-21_final.stac-item
2022-11-24 09:56:14	ga_ls9c_ard_3-2-1_096080_2022-11-24_final.stac-item
2022-11-26 11:21:57	ga_ls9c_ard_3-2-1_110078_2022-11-26_final.stac-item
2022-12-03 09:50:00	ga_ls9c_ard_3-2-1_095080_2022-12-03_final.stac-item
2022-12-04 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-12-04_final.stac-item
2022-12-04 10:33:17	ga_ls9c_ard_3-2-1_102080_2022-12-04_final.stac-item
2022-12-10 11:35:07	ga_ls9c_ard_3-2-1_112080_2022-12-10_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2023-01-13 09:46:37	ga_ls9c_ard_3-2-1_094087_2023-01-13_final.stac-item
2023-01-27 09:55:47	ga_ls9c_ard_3-2-1_096079_2023-01-27_final.stac-item
2023-01-29 11:22:20	ga_ls9c_ard_3-2-1_110079_2023-01-29_final.stac-item
2023-02-07 11:16:38	ga_ls9c_ard_3-2-1_109080_2023-02-07_final.stac-item
2023-02-14 09:43:30	ga_ls9c_ard_3-2-1_094079_2023-02-14_final.stac-item
2023-02-14 11:22:23	ga_ls9c_ard_3-2-1_110079_2023-02-14_final.stac-item
2023-04-22 10:14:57	ga_ls9c_ard_3-2-1_099082_2023-04-22_final.stac-item
2023-04-24 11:40:40	ga_ls9c_ard_3-2-1_113080_2023-04-24_final.stac-item
2023-04-26 09:50:36	ga_ls9c_ard_3-2-1_095083_2023-04-26_final.stac-item
2023-04-26 11:26:41	ga_ls9c_ard_3-2-1_111076_2023-04-26_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 09:36:37	ga_ls9c_ard_3-2-1_093079_2023-04-28_final.stac-item
2023-05-30 09:37:31	ga_ls9c_ard_3-2-1_093082_2023-05-30_final.stac-item
2023-06-01 09:23:33	ga_ls9c_ard_3-2-1_091078_2023-05-31_final.stac-item
2023-07-15 09:47:36	ga_ls9c_ard_3-2-1_095076_2023-07-15_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-19 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-07-19_final.stac-item
2023-07-19 11:03:46	ga_ls9c_ard_3-2-1_107081_2023-07-19_final.stac-item
2023-07-23 10:35:02	ga_ls9c_ard_3-2-1_103071_2023-07-23_final.stac-item
2023-07-23 10:35:50	ga_ls9c_ard_3-2-1_103073_2023-07-23_final.stac-item
2023-07-23 10:36:38	ga_ls9c_ard_3-2-1_103075_2023-07-23_final.stac-item
2023-07-24 11:20:41	ga_ls9c_ard_3-2-1_110077_2023-07-24_final.stac-item
2023-07-24 11:23:52	ga_ls9c_ard_3-2-1_110085_2023-07-24_final.stac-item
2023-07-25 10:26:39	ga_ls9c_ard_3-2-1_101081_2023-07-25_final.stac-item
2023-07-26 09:30:39	ga_ls9c_ard_3-2-1_092080_2023-07-26_final.stac-item
2023-07-27 10:11:56	ga_ls9c_ard_3-2-1_099075_2023-07-27_final.stac-item
2023-07-28 09:18:20	ga_ls9c_ard_3-2-1_090080_2023-07-27_final.stac-item
2023-08-04 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-08-04_final.stac-item
2023-08-04 11:03:53	ga_ls9c_ard_3-2-1_107081_2023-08-04_final.stac-item
2023-08-05 10:08:17	ga_ls9c_ard_3-2-1_098081_2023-08-05_final.stac-item
2023-08-08 10:35:13	ga_ls9c_ard_3-2-1_103071_2023-08-08_final.stac-item
2023-10-13 10:26:29	ga_ls9c_ard_3-2-1_101079_2023-10-13_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-15 10:14:57	ga_ls9c_ard_3-2-1_099081_2023-10-15_final.stac-item
2023-10-16 10:56:37	ga_ls9c_ard_3-2-1_106077_2023-10-16_final.stac-item
2023-10-17 11:40:41	ga_ls9c_ard_3-2-1_113079_2023-10-17_final.stac-item
2023-10-18 10:43:28	ga_ls9c_ard_3-2-1_104075_2023-10-18_final.stac-item
2023-10-19 09:50:15	ga_ls9c_ard_3-2-1_095081_2023-10-19_final.stac-item
2023-10-21 09:37:05	ga_ls9c_ard_3-2-1_093079_2023-10-21_final.stac-item
2023-10-22 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-10-22_final.stac-item
2023-10-25 10:51:38	ga_ls9c_ard_3-2-1_105080_2023-10-25_final.stac-item
2023-10-26 11:34:29	ga_ls9c_ard_3-2-1_112079_2023-10-26_final.stac-item
2023-10-27 10:38:51	ga_ls9c_ard_3-2-1_103079_2023-10-27_final.stac-item
2023-10-28 09:44:01	ga_ls9c_ard_3-2-1_094081_2023-10-28_final.stac-item
2023-10-30 09:31:38	ga_ls9c_ard_3-2-1_092081_2023-10-30_final.stac-item
2023-11-02 10:00:29	ga_ls9c_ard_3-2-1_097076_2023-11-02_final.stac-item
2023-11-04 09:48:08	ga_ls9c_ard_3-2-1_095076_2023-11-04_final.stac-item
2023-11-04 09:49:43	ga_ls9c_ard_3-2-1_095080_2023-11-04_final.stac-item
2023-11-05 10:31:00	ga_ls9c_ard_3-2-1_102075_2023-11-05_final.stac-item
2023-11-20 09:48:38	ga_ls9c_ard_3-2-1_095077_2023-11-20_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