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
2021-11-12 10:59:24	ga_ls9c_ard_3-2-1_106077_2021-11-12_final.stac-item
2021-11-18 10:05:09	ga_ls9c_ard_3-2-1_097082_2021-11-18_final.stac-item
2021-11-25 09:48:03	ga_ls9c_ard_3-2-1_095080_2021-11-25_final.stac-item
2021-12-10 10:24:38	ga_ls9c_ard_3-2-1_101074_2021-12-10_final.stac-item
2021-12-21 10:08:49	ga_ls9c_ard_3-2-1_098081_2021-12-21_final.stac-item
2021-12-23 09:55:40	ga_ls9c_ard_3-2-1_096079_2021-12-23_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2021-12-26 10:25:22	ga_ls9c_ard_3-2-1_101076_2021-12-26_final.stac-item
2021-12-29 10:58:16	ga_ls9c_ard_3-2-1_106081_2021-12-29_final.stac-item
2022-01-08 09:55:38	ga_ls9c_ard_3-2-1_096079_2022-01-08_final.stac-item
2022-01-14 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-01-13_final.stac-item
2022-02-09 09:54:02	ga_ls9c_ard_3-2-1_096075_2022-02-09_final.stac-item
2022-02-11 09:43:39	ga_ls9c_ard_3-2-1_094080_2022-02-11_final.stac-item
2022-02-25 09:53:28	ga_ls9c_ard_3-2-1_096074_2022-02-25_final.stac-item
2022-02-25 11:31:57	ga_ls9c_ard_3-2-1_112073_2022-02-25_final.stac-item
2022-04-24 10:31:49	ga_ls9c_ard_3-2-1_102078_2022-04-24_final.stac-item
2022-05-16 09:53:21	ga_ls9c_ard_3-2-1_096075_2022-05-16_final.stac-item
2022-05-21 10:14:37	ga_ls9c_ard_3-2-1_099082_2022-05-21_final.stac-item
2022-05-31 09:14:26	ga_ls9c_ard_3-2-1_089086_2022-05-30_final.stac-item
2022-05-31 10:48:08	ga_ls9c_ard_3-2-1_105073_2022-05-31_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-07-02 10:48:29	ga_ls9c_ard_3-2-1_105073_2022-07-02_final.stac-item
2022-07-07 09:29:42	ga_ls9c_ard_3-2-1_092077_2022-07-06_final.stac-item
2022-07-17 10:06:23	ga_ls9c_ard_3-2-1_098076_2022-07-17_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-07-28 11:24:54	ga_ls9c_ard_3-2-1_111071_2022-07-28_final.stac-item
2022-08-01 11:01:02	ga_ls9c_ard_3-2-1_107073_2022-08-01_final.stac-item
2022-08-01 11:04:13	ga_ls9c_ard_3-2-1_107081_2022-08-01_final.stac-item
2022-08-03 10:48:42	ga_ls9c_ard_3-2-1_105073_2022-08-03_final.stac-item
2022-08-04 09:53:29	ga_ls9c_ard_3-2-1_096074_2022-08-04_final.stac-item
2022-08-12 10:43:48	ga_ls9c_ard_3-2-1_104076_2022-08-12_final.stac-item
2022-08-19 10:52:49	ga_ls9c_ard_3-2-1_105083_2022-08-19_final.stac-item
2022-09-05 09:53:13	ga_ls9c_ard_3-2-1_096073_2022-09-05_final.stac-item
2022-09-06 10:35:40	ga_ls9c_ard_3-2-1_103071_2022-09-06_final.stac-item
2022-09-30 11:27:15	ga_ls9c_ard_3-2-1_111076_2022-09-30_final.stac-item
2022-10-06 10:52:56	ga_ls9c_ard_3-2-1_105083_2022-10-06_final.stac-item
2022-10-14 10:03:11	ga_ls9c_ard_3-2-1_097082_2022-10-14_final.stac-item
2022-10-17 10:34:06	ga_ls9c_ard_3-2-1_102082_2022-10-17_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-27 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-10-27_final.stac-item
2022-10-27 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-10-27_final.stac-item
2022-10-30 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-10-30_final.stac-item
2022-11-03 11:12:56	ga_ls9c_ard_3-2-1_109071_2022-11-03_final.stac-item
2022-11-10 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-10_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-11 10:26:44	ga_ls9c_ard_3-2-1_101079_2022-11-11_final.stac-item
2022-11-26 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-11-26_final.stac-item
2022-11-26 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-11-26_final.stac-item
2022-12-01 11:41:39	ga_ls9c_ard_3-2-1_113081_2022-12-01_final.stac-item
2022-12-07 11:05:00	ga_ls9c_ard_3-2-1_107082_2022-12-07_final.stac-item
2022-12-19 11:29:42	ga_ls9c_ard_3-2-1_111082_2022-12-19_final.stac-item
2022-12-23 11:03:21	ga_ls9c_ard_3-2-1_107078_2022-12-23_final.stac-item
2022-12-28 11:22:20	ga_ls9c_ard_3-2-1_110079_2022-12-28_final.stac-item
2022-12-30 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-30_final.stac-item
2023-01-02 11:40:06	ga_ls9c_ard_3-2-1_113077_2023-01-02_final.stac-item
2023-01-13 09:44:14	ga_ls9c_ard_3-2-1_094081_2023-01-13_final.stac-item
2023-01-14 10:26:41	ga_ls9c_ard_3-2-1_101079_2023-01-14_final.stac-item
2023-01-17 09:18:39	ga_ls9c_ard_3-2-1_090079_2023-01-16_final.stac-item
2023-01-22 09:38:21	ga_ls9c_ard_3-2-1_093082_2023-01-22_final.stac-item
2023-01-25 10:09:18	ga_ls9c_ard_3-2-1_098082_2023-01-25_final.stac-item
2023-01-27 09:55:47	ga_ls9c_ard_3-2-1_096079_2023-01-27_final.stac-item
2023-01-27 11:34:16	ga_ls9c_ard_3-2-1_112078_2023-01-27_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-07 09:39:20	ga_ls9c_ard_3-2-1_093084_2023-02-07_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-03-06 10:56:35	ga_ls9c_ard_3-2-1_106077_2023-03-06_final.stac-item
2023-03-08 10:43:47	ga_ls9c_ard_3-2-1_104076_2023-03-08_final.stac-item
2023-03-13 11:03:30	ga_ls9c_ard_3-2-1_107079_2023-03-13_final.stac-item
2023-04-06 11:52:45	ga_ls9c_ard_3-2-1_115079_2023-04-06_final.stac-item
2023-04-24 10:02:11	ga_ls9c_ard_3-2-1_097081_2023-04-24_final.stac-item
2023-04-24 11:39:28	ga_ls9c_ard_3-2-1_113077_2023-04-24_final.stac-item
2023-04-28 11:14:42	ga_ls9c_ard_3-2-1_109077_2023-04-28_final.stac-item
2023-05-03 09:54:39	ga_ls9c_ard_3-2-1_096078_2023-05-03_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-11 10:41:16	ga_ls9c_ard_3-2-1_104071_2023-05-11_final.stac-item
2023-05-14 09:36:52	ga_ls9c_ard_3-2-1_093080_2023-05-14_final.stac-item
2023-05-14 09:38:27	ga_ls9c_ard_3-2-1_093084_2023-05-14_final.stac-item
2023-05-17 10:05:44	ga_ls9c_ard_3-2-1_098075_2023-05-17_final.stac-item
2023-05-20 10:35:48	ga_ls9c_ard_3-2-1_103073_2023-05-20_final.stac-item
2023-05-28 11:27:09	ga_ls9c_ard_3-2-1_111078_2023-05-28_final.stac-item
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final.stac-item
2023-06-25 10:11:38	ga_ls9c_ard_3-2-1_099075_2023-06-25_final.stac-item
2023-07-01 09:35:30	ga_ls9c_ard_3-2-1_093077_2023-07-01_final.stac-item
2023-07-17 09:37:14	ga_ls9c_ard_3-2-1_093081_2023-07-17_final.stac-item
2023-07-29 10:00:01	ga_ls9c_ard_3-2-1_097076_2023-07-29_final.stac-item
2023-07-30 10:43:17	ga_ls9c_ard_3-2-1_104076_2023-07-30_final.stac-item
2023-08-10 10:24:27	ga_ls9c_ard_3-2-1_101075_2023-08-10_final.stac-item
2023-08-10 10:26:03	ga_ls9c_ard_3-2-1_101079_2023-08-10_final.stac-item
2023-08-11 11:08:31	ga_ls9c_ard_3-2-1_108077_2023-08-11_final.stac-item
2023-08-12 10:12:06	ga_ls9c_ard_3-2-1_099075_2023-08-12_final.stac-item
2023-08-13 09:19:16	ga_ls9c_ard_3-2-1_090082_2023-08-12_final.stac-item
2023-08-14 11:39:25	ga_ls9c_ard_3-2-1_113077_2023-08-14_final.stac-item
2023-08-14 11:40:13	ga_ls9c_ard_3-2-1_113079_2023-08-14_final.stac-item
2023-10-18 10:45:28	ga_ls9c_ard_3-2-1_104080_2023-10-18_final.stac-item
2023-10-27 10:35:40	ga_ls9c_ard_3-2-1_103071_2023-10-27_final.stac-item
2023-10-30 11:11:19	ga_ls9c_ard_3-2-1_108083_2023-10-30_final.stac-item
2023-11-02 11:39:22	ga_ls9c_ard_3-2-1_113076_2023-11-02_final.stac-item
2023-11-04 09:50:31	ga_ls9c_ard_3-2-1_095082_2023-11-04_final.stac-item
2023-11-15 11:10:06	ga_ls9c_ard_3-2-1_108080_2023-11-15_final.stac-item
2023-11-21 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-11-21_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