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 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-11-20 11:22:17	ga_ls9c_ard_3-2-1_110075_2021-11-20_final.stac-item
2021-12-07 09:56:33	ga_ls9c_ard_3-2-1_096081_2021-12-07_final.stac-item
2021-12-09 09:44:34	ga_ls9c_ard_3-2-1_094082_2021-12-09_final.stac-item
2021-12-11 11:05:53	ga_ls9c_ard_3-2-1_108069_2021-12-11_final.stac-item
2021-12-18 09:36:19	ga_ls9c_ard_3-2-1_093077_2021-12-18_final.stac-item
2021-12-18 09:39:54	ga_ls9c_ard_3-2-1_093086_2021-12-18_final.stac-item
2021-12-26 10:24:58	ga_ls9c_ard_3-2-1_101075_2021-12-26_final.stac-item
2022-01-01 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-01-01_final.stac-item
2022-01-05 09:24:21	ga_ls9c_ard_3-2-1_091078_2022-01-04_final.stac-item
2022-01-30 09:20:34	ga_ls9c_ard_3-2-1_090084_2022-01-29_final.stac-item
2022-02-02 09:47:52	ga_ls9c_ard_3-2-1_095075_2022-02-02_final.stac-item
2022-02-06 11:04:25	ga_ls9c_ard_3-2-1_107081_2022-02-06_final.stac-item
2022-02-08 10:52:03	ga_ls9c_ard_3-2-1_105081_2022-02-08_final.stac-item
2022-03-03 09:18:43	ga_ls9c_ard_3-2-1_090080_2022-03-02_final.stac-item
2022-03-05 10:43:15	ga_ls9c_ard_3-2-1_104075_2022-03-05_final.stac-item
2022-03-12 10:47:26	ga_ls9c_ard_3-2-1_105070_2022-03-12_final.stac-item
2022-03-25 10:20:51	ga_ls9c_ard_3-2-1_100081_2022-03-25_final.stac-item
2022-03-26 09:27:13	ga_ls9c_ard_3-2-1_091086_2022-03-25_final.stac-item
2022-05-09 09:50:28	ga_ls9c_ard_3-2-1_095083_2022-05-09_final.stac-item
2022-05-18 11:22:14	ga_ls9c_ard_3-2-1_110081_2022-05-18_final.stac-item
2022-05-25 09:47:06	ga_ls9c_ard_3-2-1_095075_2022-05-25_final.stac-item
2022-05-30 10:06:04	ga_ls9c_ard_3-2-1_098076_2022-05-30_final.stac-item
2022-06-13 10:20:29	ga_ls9c_ard_3-2-1_100081_2022-06-13_final.stac-item
2022-06-30 11:02:26	ga_ls9c_ard_3-2-1_107077_2022-06-30_final.stac-item
2022-07-07 09:31:18	ga_ls9c_ard_3-2-1_092081_2022-07-07_final.stac-item
2022-07-07 11:06:36	ga_ls9c_ard_3-2-1_108072_2022-07-07_final.stac-item
2022-07-11 10:40:15	ga_ls9c_ard_3-2-1_104068_2022-07-11_final.stac-item
2022-07-27 10:40:26	ga_ls9c_ard_3-2-1_104068_2022-07-27_final.stac-item
2022-08-06 09:44:20	ga_ls9c_ard_3-2-1_094082_2022-08-06_final.stac-item
2022-08-10 09:21:39	ga_ls9c_ard_3-2-1_090087_2022-08-09_final.stac-item
2022-08-15 11:13:07	ga_ls9c_ard_3-2-1_109072_2022-08-15_final.stac-item
2022-08-20 11:35:41	ga_ls9c_ard_3-2-1_112082_2022-08-20_final.stac-item
2022-09-14 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-09-14_final.stac-item
2022-09-30 09:50:45	ga_ls9c_ard_3-2-1_095082_2022-09-30_final.stac-item
2022-09-30 09:52:45	ga_ls9c_ard_3-2-1_095087_2022-09-30_final.stac-item
2022-10-10 10:25:28	ga_ls9c_ard_3-2-1_101076_2022-10-10_final.stac-item
2022-10-12 11:51:13	ga_ls9c_ard_3-2-1_115074_2022-10-12_final.stac-item
2022-10-20 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-10-20_final.stac-item
2022-10-28 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-10-28_final.stac-item
2022-11-03 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-11-03_final.stac-item
2022-11-07 10:51:50	ga_ls9c_ard_3-2-1_105080_2022-11-07_final.stac-item
2022-11-10 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-11-10_final.stac-item
2022-11-10 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-11-10_final.stac-item
2022-11-16 10:45:41	ga_ls9c_ard_3-2-1_104080_2022-11-16_final.stac-item
2022-11-18 10:32:56	ga_ls9c_ard_3-2-1_102079_2022-11-18_final.stac-item
2022-11-18 10:33:20	ga_ls9c_ard_3-2-1_102080_2022-11-18_final.stac-item
2022-11-26 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-26_final.stac-item
2022-11-30 10:57:36	ga_ls9c_ard_3-2-1_106079_2022-11-30_final.stac-item
2022-12-05 09:37:40	ga_ls9c_ard_3-2-1_093080_2022-12-05_final.stac-item
2022-12-10 11:33:31	ga_ls9c_ard_3-2-1_112076_2022-12-10_final.stac-item
2023-01-04 09:48:03	ga_ls9c_ard_3-2-1_095075_2023-01-04_final.stac-item
2023-01-11 11:35:29	ga_ls9c_ard_3-2-1_112081_2023-01-11_final.stac-item
2023-01-17 10:56:44	ga_ls9c_ard_3-2-1_106077_2023-01-17_final.stac-item
2023-01-17 10:57:32	ga_ls9c_ard_3-2-1_106079_2023-01-17_final.stac-item
2023-01-25 11:45:48	ga_ls9c_ard_3-2-1_114076_2023-01-25_final.stac-item
2023-01-28 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-28_final.stac-item
2023-01-29 09:44:15	ga_ls9c_ard_3-2-1_094081_2023-01-29_final.stac-item
2023-01-31 11:10:00	ga_ls9c_ard_3-2-1_108079_2023-01-31_final.stac-item
2023-02-01 10:15:11	ga_ls9c_ard_3-2-1_099081_2023-02-01_final.stac-item
2023-02-08 10:21:24	ga_ls9c_ard_3-2-1_100081_2023-02-08_final.stac-item
2023-02-10 11:45:56	ga_ls9c_ard_3-2-1_114076_2023-02-10_final.stac-item
2023-03-06 09:19:42	ga_ls9c_ard_3-2-1_090082_2023-03-05_final.stac-item
2023-03-16 11:32:01	ga_ls9c_ard_3-2-1_112073_2023-03-16_final.stac-item
2023-03-29 11:05:19	ga_ls9c_ard_3-2-1_107084_2023-03-29_final.stac-item
2023-04-05 11:05:30	ga_ls9c_ard_3-2-1_108069_2023-04-05_final.stac-item
2023-04-05 11:05:54	ga_ls9c_ard_3-2-1_108070_2023-04-05_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-05-02 10:52:18	ga_ls9c_ard_3-2-1_105083_2023-05-02_final.stac-item
2023-05-03 11:31:33	ga_ls9c_ard_3-2-1_112073_2023-05-03_final.stac-item
2023-05-05 11:21:09	ga_ls9c_ard_3-2-1_110078_2023-05-05_final.stac-item
2023-05-08 10:14:46	ga_ls9c_ard_3-2-1_099082_2023-05-08_final.stac-item
2023-05-10 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-05-10_final.stac-item
2023-05-19 09:56:32	ga_ls9c_ard_3-2-1_096083_2023-05-19_final.stac-item
2023-05-28 11:26:22	ga_ls9c_ard_3-2-1_111076_2023-05-28_final.stac-item
2023-05-29 10:28:45	ga_ls9c_ard_3-2-1_102071_2023-05-29_final.stac-item
2023-05-30 11:15:36	ga_ls9c_ard_3-2-1_109080_2023-05-30_final.stac-item
2023-06-03 10:46:52	ga_ls9c_ard_3-2-1_105070_2023-06-03_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-20 11:44:38	ga_ls9c_ard_3-2-1_114075_2023-07-20_final.stac-item
2023-07-28 09:17:56	ga_ls9c_ard_3-2-1_090079_2023-07-27_final.stac-item
2023-08-02 11:11:50	ga_ls9c_ard_3-2-1_109070_2023-08-02_final.stac-item
2023-08-02 11:15:02	ga_ls9c_ard_3-2-1_109078_2023-08-02_final.stac-item
2023-08-05 11:46:22	ga_ls9c_ard_3-2-1_114079_2023-08-05_final.stac-item
2023-08-06 10:47:57	ga_ls9c_ard_3-2-1_105072_2023-08-06_final.stac-item
2023-08-11 09:31:14	ga_ls9c_ard_3-2-1_092081_2023-08-11_final.stac-item
2023-08-13 10:54:10	ga_ls9c_ard_3-2-1_106072_2023-08-13_final.stac-item
2023-10-13 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-13_final.stac-item
2023-10-19 11:26:44	ga_ls9c_ard_3-2-1_111075_2023-10-19_final.stac-item
2023-10-22 10:17:57	ga_ls9c_ard_3-2-1_100073_2023-10-22_final.stac-item
2023-10-22 10:18:21	ga_ls9c_ard_3-2-1_100074_2023-10-22_final.stac-item
2023-10-30 11:10:31	ga_ls9c_ard_3-2-1_108081_2023-10-30_final.stac-item
2023-11-15 11:09:42	ga_ls9c_ard_3-2-1_108079_2023-11-15_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-19 10:45:27	ga_ls9c_ard_3-2-1_104080_2023-11-19_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-11-20 11:27:55	ga_ls9c_ard_3-2-1_111078_2023-11-20_final.stac-item
2023-11-22 09:33:55	ga_ls9c_ard_3-2-1_093071_2023-11-22_final.stac-item
2023-11-22 11:12:24	ga_ls9c_ard_3-2-1_109070_2023-11-22_final.stac-item
2023-11-24 09:29:10	ga_ls9c_ard_3-2-1_091090_2023-11-23_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