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
2021-11-07 10:57:20	ga_ls9c_ard_3-2-1_106078_2021-11-07_final.stac-item
2021-11-20 11:20:41	ga_ls9c_ard_3-2-1_110071_2021-11-20_final.stac-item
2021-12-09 09:43:22	ga_ls9c_ard_3-2-1_094079_2021-12-09_final.stac-item
2021-12-16 09:49:28	ga_ls9c_ard_3-2-1_095079_2021-12-16_final.stac-item
2021-12-19 10:20:46	ga_ls9c_ard_3-2-1_100080_2021-12-19_final.stac-item
2021-12-23 09:53:40	ga_ls9c_ard_3-2-1_096074_2021-12-23_final.stac-item
2022-01-12 11:10:11	ga_ls9c_ard_3-2-1_108080_2022-01-12_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-02-06 09:24:20	ga_ls9c_ard_3-2-1_091078_2022-02-05_final.stac-item
2022-02-06 09:26:20	ga_ls9c_ard_3-2-1_091083_2022-02-05_final.stac-item
2022-02-14 11:51:01	ga_ls9c_ard_3-2-1_115074_2022-02-14_final.stac-item
2022-02-27 09:44:16	ga_ls9c_ard_3-2-1_094082_2022-02-27_final.stac-item
2022-03-04 09:57:35	ga_ls9c_ard_3-2-1_097069_2022-03-04_final.stac-item
2022-03-07 10:30:53	ga_ls9c_ard_3-2-1_102075_2022-03-07_final.stac-item
2022-03-26 09:26:01	ga_ls9c_ard_3-2-1_091083_2022-03-25_final.stac-item
2022-03-31 11:19:51	ga_ls9c_ard_3-2-1_110074_2022-03-31_final.stac-item
2022-05-09 09:51:16	ga_ls9c_ard_3-2-1_095085_2022-05-09_final.stac-item
2022-05-21 10:15:49	ga_ls9c_ard_3-2-1_099085_2022-05-21_final.stac-item
2022-05-30 11:45:21	ga_ls9c_ard_3-2-1_114077_2022-05-30_final.stac-item
2022-06-08 09:58:18	ga_ls9c_ard_3-2-1_097072_2022-06-08_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-06-26 11:26:46	ga_ls9c_ard_3-2-1_111076_2022-06-26_final.stac-item
2022-07-09 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-07-09_final.stac-item
2022-07-19 09:52:51	ga_ls9c_ard_3-2-1_096073_2022-07-19_final.stac-item
2022-07-30 11:12:34	ga_ls9c_ard_3-2-1_109071_2022-07-30_final.stac-item
2022-07-31 10:20:57	ga_ls9c_ard_3-2-1_100081_2022-07-31_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-20 09:53:12	ga_ls9c_ard_3-2-1_096073_2022-08-20_final.stac-item
2022-08-27 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-08-27_final.stac-item
2022-09-15 10:29:57	ga_ls9c_ard_3-2-1_102072_2022-09-15_final.stac-item
2022-10-11 11:11:08	ga_ls9c_ard_3-2-1_108082_2022-10-11_final.stac-item
2022-10-18 11:12:35	ga_ls9c_ard_3-2-1_109070_2022-10-18_final.stac-item
2022-10-19 10:18:09	ga_ls9c_ard_3-2-1_100073_2022-10-19_final.stac-item
2022-10-22 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-10-22_final.stac-item
2022-11-03 11:13:20	ga_ls9c_ard_3-2-1_109072_2022-11-03_final.stac-item
2022-11-17 11:28:09	ga_ls9c_ard_3-2-1_111078_2022-11-17_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-11-28 09:32:41	ga_ls9c_ard_3-2-1_092083_2022-11-28_final.stac-item
2022-11-29 10:12:45	ga_ls9c_ard_3-2-1_099075_2022-11-29_final.stac-item
2022-12-01 11:39:39	ga_ls9c_ard_3-2-1_113076_2022-12-01_final.stac-item
2022-12-02 10:42:50	ga_ls9c_ard_3-2-1_104073_2022-12-02_final.stac-item
2022-12-05 09:36:04	ga_ls9c_ard_3-2-1_093076_2022-12-05_final.stac-item
2022-12-05 11:12:33	ga_ls9c_ard_3-2-1_109070_2022-12-05_final.stac-item
2022-12-07 11:03:48	ga_ls9c_ard_3-2-1_107079_2022-12-07_final.stac-item
2022-12-09 09:16:57	ga_ls9c_ard_3-2-1_089090_2022-12-08_final.stac-item
2022-12-19 09:50:01	ga_ls9c_ard_3-2-1_095080_2022-12-19_final.stac-item
2022-12-20 10:31:41	ga_ls9c_ard_3-2-1_102076_2022-12-20_final.stac-item
2022-12-22 10:18:54	ga_ls9c_ard_3-2-1_100075_2022-12-22_final.stac-item
2022-12-23 11:03:45	ga_ls9c_ard_3-2-1_107079_2022-12-23_final.stac-item
2022-12-30 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-30_final.stac-item
2023-01-04 09:51:39	ga_ls9c_ard_3-2-1_095084_2023-01-04_final.stac-item
2023-01-08 11:03:48	ga_ls9c_ard_3-2-1_107079_2023-01-08_final.stac-item
2023-01-15 09:33:02	ga_ls9c_ard_3-2-1_092084_2023-01-15_final.stac-item
2023-01-15 11:11:07	ga_ls9c_ard_3-2-1_108082_2023-01-15_final.stac-item
2023-02-08 10:20:37	ga_ls9c_ard_3-2-1_100079_2023-02-08_final.stac-item
2023-02-24 10:17:58	ga_ls9c_ard_3-2-1_100073_2023-02-24_final.stac-item
2023-02-27 10:52:52	ga_ls9c_ard_3-2-1_105083_2023-02-27_final.stac-item
2023-03-06 09:19:18	ga_ls9c_ard_3-2-1_090081_2023-03-05_final.stac-item
2023-03-11 09:38:58	ga_ls9c_ard_3-2-1_093084_2023-03-11_final.stac-item
2023-03-12 10:17:51	ga_ls9c_ard_3-2-1_100073_2023-03-12_final.stac-item
2023-03-13 11:00:43	ga_ls9c_ard_3-2-1_107072_2023-03-13_final.stac-item
2023-03-16 09:53:08	ga_ls9c_ard_3-2-1_096073_2023-03-16_final.stac-item
2023-03-17 10:36:23	ga_ls9c_ard_3-2-1_103073_2023-03-17_final.stac-item
2023-03-25 09:51:15	ga_ls9c_ard_3-2-1_095084_2023-03-25_final.stac-item
2023-03-25 11:27:44	ga_ls9c_ard_3-2-1_111078_2023-03-25_final.stac-item
2023-03-30 10:05:41	ga_ls9c_ard_3-2-1_098074_2023-03-30_final.stac-item
2023-04-01 09:52:56	ga_ls9c_ard_3-2-1_096073_2023-04-01_final.stac-item
2023-04-01 09:53:20	ga_ls9c_ard_3-2-1_096074_2023-04-01_final.stac-item
2023-04-03 09:45:46	ga_ls9c_ard_3-2-1_094086_2023-04-03_final.stac-item
2023-04-06 10:11:28	ga_ls9c_ard_3-2-1_099073_2023-04-06_final.stac-item
2023-04-08 09:59:30	ga_ls9c_ard_3-2-1_097074_2023-04-08_final.stac-item
2023-04-12 11:15:12	ga_ls9c_ard_3-2-1_109078_2023-04-12_final.stac-item
2023-04-24 09:58:59	ga_ls9c_ard_3-2-1_097073_2023-04-24_final.stac-item
2023-04-26 09:49:24	ga_ls9c_ard_3-2-1_095080_2023-04-26_final.stac-item
2023-05-09 09:17:57	ga_ls9c_ard_3-2-1_090079_2023-05-08_final.stac-item
2023-05-12 09:50:26	ga_ls9c_ard_3-2-1_095083_2023-05-12_final.stac-item
2023-05-15 10:20:31	ga_ls9c_ard_3-2-1_100081_2023-05-15_final.stac-item
2023-05-20 10:34:12	ga_ls9c_ard_3-2-1_103069_2023-05-20_final.stac-item
2023-05-22 10:25:48	ga_ls9c_ard_3-2-1_101079_2023-05-22_final.stac-item
2023-06-01 11:03:38	ga_ls9c_ard_3-2-1_107081_2023-06-01_final.stac-item
2023-06-02 10:05:13	ga_ls9c_ard_3-2-1_098074_2023-06-02_final.stac-item
2023-06-05 10:38:05	ga_ls9c_ard_3-2-1_103079_2023-06-05_final.stac-item
2023-06-26 09:17:37	ga_ls9c_ard_3-2-1_090079_2023-06-25_final.stac-item
2023-06-27 09:57:43	ga_ls9c_ard_3-2-1_097071_2023-06-27_final.stac-item
2023-07-01 11:15:59	ga_ls9c_ard_3-2-1_109081_2023-07-01_final.stac-item
2023-07-15 09:47:36	ga_ls9c_ard_3-2-1_095076_2023-07-15_final.stac-item
2023-07-26 11:07:56	ga_ls9c_ard_3-2-1_108076_2023-07-26_final.stac-item
2023-07-31 09:50:05	ga_ls9c_ard_3-2-1_095082_2023-07-31_final.stac-item
2023-07-31 09:50:29	ga_ls9c_ard_3-2-1_095083_2023-07-31_final.stac-item
2023-08-02 09:35:21	ga_ls9c_ard_3-2-1_093076_2023-08-02_final.stac-item
2023-08-04 09:24:13	ga_ls9c_ard_3-2-1_091079_2023-08-03_final.stac-item
2023-08-13 09:18:52	ga_ls9c_ard_3-2-1_090081_2023-08-12_final.stac-item
2023-08-17 10:30:14	ga_ls9c_ard_3-2-1_102074_2023-08-17_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-16 09:19:44	ga_ls9c_ard_3-2-1_090082_2023-10-15_final.stac-item
2023-10-24 11:45:40	ga_ls9c_ard_3-2-1_114076_2023-10-24_final.stac-item
2023-11-02 09:59:17	ga_ls9c_ard_3-2-1_097073_2023-11-02_final.stac-item
2023-11-03 10:43:44	ga_ls9c_ard_3-2-1_104076_2023-11-03_final.stac-item
2023-11-15 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-11-15_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_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