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
2021-11-18 10:05:33	ga_ls9c_ard_3-2-1_097083_2021-11-18_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-14 10:03:27	ga_ls9c_ard_3-2-1_097083_2021-12-14_final.stac-item
2021-12-22 10:51:17	ga_ls9c_ard_3-2-1_105079_2021-12-22_final.stac-item
2022-01-14 10:58:12	ga_ls9c_ard_3-2-1_106081_2022-01-14_final.stac-item
2022-01-30 10:58:15	ga_ls9c_ard_3-2-1_106081_2022-01-30_final.stac-item
2022-02-20 09:36:59	ga_ls9c_ard_3-2-1_093079_2022-02-20_final.stac-item
2022-03-02 10:14:44	ga_ls9c_ard_3-2-1_099081_2022-03-02_final.stac-item
2022-03-24 09:37:12	ga_ls9c_ard_3-2-1_093080_2022-03-24_final.stac-item
2022-03-31 09:43:46	ga_ls9c_ard_3-2-1_094081_2022-03-31_final.stac-item
2022-04-14 09:56:26	ga_ls9c_ard_3-2-1_096082_2022-04-14_final.stac-item
2022-07-10 11:38:40	ga_ls9c_ard_3-2-1_113075_2022-07-10_final.stac-item
2022-07-20 10:34:32	ga_ls9c_ard_3-2-1_103069_2022-07-20_final.stac-item
2022-07-26 10:00:45	ga_ls9c_ard_3-2-1_097077_2022-07-26_final.stac-item
2022-07-26 11:38:50	ga_ls9c_ard_3-2-1_113075_2022-07-26_final.stac-item
2022-08-05 10:35:33	ga_ls9c_ard_3-2-1_103071_2022-08-05_final.stac-item
2022-08-11 11:39:01	ga_ls9c_ard_3-2-1_113075_2022-08-11_final.stac-item
2022-08-16 10:18:42	ga_ls9c_ard_3-2-1_100075_2022-08-16_final.stac-item
2022-08-20 09:55:12	ga_ls9c_ard_3-2-1_096078_2022-08-20_final.stac-item
2022-08-21 10:35:40	ga_ls9c_ard_3-2-1_103071_2022-08-21_final.stac-item
2022-08-21 10:38:28	ga_ls9c_ard_3-2-1_103078_2022-08-21_final.stac-item
2022-09-14 09:49:52	ga_ls9c_ard_3-2-1_095080_2022-09-14_final.stac-item
2022-09-18 09:24:23	ga_ls9c_ard_3-2-1_091078_2022-09-17_final.stac-item
2022-10-12 10:12:44	ga_ls9c_ard_3-2-1_099075_2022-10-12_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-10-25 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-10-25_final.stac-item
2022-10-30 11:40:53	ga_ls9c_ard_3-2-1_113079_2022-10-30_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
2022-11-20 10:20:58	ga_ls9c_ard_3-2-1_100080_2022-11-20_final.stac-item
2022-11-28 09:30:41	ga_ls9c_ard_3-2-1_092078_2022-11-28_final.stac-item
2022-12-07 11:03:24	ga_ls9c_ard_3-2-1_107078_2022-12-07_final.stac-item
2022-12-12 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-12-12_final.stac-item
2022-12-13 10:24:44	ga_ls9c_ard_3-2-1_101074_2022-12-13_final.stac-item
2022-12-14 11:09:35	ga_ls9c_ard_3-2-1_108078_2022-12-14_final.stac-item
2022-12-17 10:03:12	ga_ls9c_ard_3-2-1_097082_2022-12-17_final.stac-item
2022-12-17 10:03:36	ga_ls9c_ard_3-2-1_097083_2022-12-17_final.stac-item
2022-12-19 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-19_final.stac-item
2022-12-27 10:39:03	ga_ls9c_ard_3-2-1_103079_2022-12-27_final.stac-item
2023-01-12 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-12_final.stac-item
2023-01-13 09:46:37	ga_ls9c_ard_3-2-1_094087_2023-01-13_final.stac-item
2023-01-20 11:27:58	ga_ls9c_ard_3-2-1_111078_2023-01-20_final.stac-item
2023-01-27 11:33:52	ga_ls9c_ard_3-2-1_112077_2023-01-27_final.stac-item
2023-01-31 09:33:06	ga_ls9c_ard_3-2-1_092084_2023-01-31_final.stac-item
2023-02-02 10:58:27	ga_ls9c_ard_3-2-1_106081_2023-02-02_final.stac-item
2023-02-07 09:37:45	ga_ls9c_ard_3-2-1_093080_2023-02-07_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-02-13 10:36:44	ga_ls9c_ard_3-2-1_103073_2023-02-13_final.stac-item
2023-02-14 09:43:54	ga_ls9c_ard_3-2-1_094080_2023-02-14_final.stac-item
2023-03-05 10:14:56	ga_ls9c_ard_3-2-1_099081_2023-03-05_final.stac-item
2023-04-23 10:56:37	ga_ls9c_ard_3-2-1_106078_2023-04-23_final.stac-item
2023-04-26 09:49:00	ga_ls9c_ard_3-2-1_095079_2023-04-26_final.stac-item
2023-04-28 09:35:49	ga_ls9c_ard_3-2-1_093077_2023-04-28_final.stac-item
2023-04-29 11:57:56	ga_ls9c_ard_3-2-1_116077_2023-04-29_final.stac-item
2023-05-01 10:08:15	ga_ls9c_ard_3-2-1_098081_2023-05-01_final.stac-item
2023-05-01 10:08:39	ga_ls9c_ard_3-2-1_098082_2023-05-01_final.stac-item
2023-05-04 10:36:42	ga_ls9c_ard_3-2-1_103075_2023-05-04_final.stac-item
2023-05-04 10:37:06	ga_ls9c_ard_3-2-1_103076_2023-05-04_final.stac-item
2023-05-05 11:20:45	ga_ls9c_ard_3-2-1_110077_2023-05-05_final.stac-item
2023-05-07 09:31:54	ga_ls9c_ard_3-2-1_092083_2023-05-07_final.stac-item
2023-05-07 11:06:24	ga_ls9c_ard_3-2-1_108072_2023-05-07_final.stac-item
2023-05-08 10:11:34	ga_ls9c_ard_3-2-1_099074_2023-05-08_final.stac-item
2023-05-09 09:18:21	ga_ls9c_ard_3-2-1_090080_2023-05-08_final.stac-item
2023-05-09 10:56:02	ga_ls9c_ard_3-2-1_106077_2023-05-09_final.stac-item
2023-06-22 09:41:09	ga_ls9c_ard_3-2-1_094076_2023-06-22_final.stac-item
2023-06-22 11:20:26	ga_ls9c_ard_3-2-1_110077_2023-06-22_final.stac-item
2023-06-23 10:25:36	ga_ls9c_ard_3-2-1_101079_2023-06-23_final.stac-item
2023-06-27 11:38:12	ga_ls9c_ard_3-2-1_113075_2023-06-27_final.stac-item
2023-06-27 11:39:48	ga_ls9c_ard_3-2-1_113079_2023-06-27_final.stac-item
2023-07-06 09:52:55	ga_ls9c_ard_3-2-1_096074_2023-07-06_final.stac-item
2023-07-06 09:55:43	ga_ls9c_ard_3-2-1_096081_2023-07-06_final.stac-item
2023-07-06 11:35:24	ga_ls9c_ard_3-2-1_112083_2023-07-06_final.stac-item
2023-07-17 11:14:56	ga_ls9c_ard_3-2-1_109078_2023-07-17_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-21 10:50:12	ga_ls9c_ard_3-2-1_105078_2023-07-21_final.stac-item
2023-07-22 09:54:34	ga_ls9c_ard_3-2-1_096078_2023-07-22_final.stac-item
2023-07-24 09:41:00	ga_ls9c_ard_3-2-1_094075_2023-07-24_final.stac-item
2023-07-25 10:23:04	ga_ls9c_ard_3-2-1_101072_2023-07-25_final.stac-item
2023-07-25 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-25_final.stac-item
2023-07-28 09:19:32	ga_ls9c_ard_3-2-1_090083_2023-07-27_final.stac-item
2023-08-04 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-08-03_final.stac-item
2023-08-04 11:03:53	ga_ls9c_ard_3-2-1_107081_2023-08-04_final.stac-item
2023-08-08 10:37:12	ga_ls9c_ard_3-2-1_103076_2023-08-08_final.stac-item
2023-08-08 10:38:00	ga_ls9c_ard_3-2-1_103078_2023-08-08_final.stac-item
2023-10-14 09:30:52	ga_ls9c_ard_3-2-1_092079_2023-10-14_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-14 11:10:09	ga_ls9c_ard_3-2-1_108080_2023-10-14_final.stac-item
2023-10-17 09:59:24	ga_ls9c_ard_3-2-1_097073_2023-10-17_final.stac-item
2023-10-19 09:50:15	ga_ls9c_ard_3-2-1_095081_2023-10-19_final.stac-item
2023-10-19 09:51:27	ga_ls9c_ard_3-2-1_095084_2023-10-19_final.stac-item
2023-10-21 09:36:41	ga_ls9c_ard_3-2-1_093078_2023-10-21_final.stac-item
2023-10-26 09:55:12	ga_ls9c_ard_3-2-1_096078_2023-10-26_final.stac-item
2023-10-31 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-10-31_final.stac-item
2023-11-02 10:03:17	ga_ls9c_ard_3-2-1_097083_2023-11-02_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_final.stac-item
2023-11-04 09:51:19	ga_ls9c_ard_3-2-1_095084_2023-11-04_final.stac-item
2023-11-05 10:32:12	ga_ls9c_ard_3-2-1_102078_2023-11-05_final.stac-item
2023-11-05 10:32:36	ga_ls9c_ard_3-2-1_102079_2023-11-05_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_final.stac-item
2023-11-20 09:50:14	ga_ls9c_ard_3-2-1_095081_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