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
2021-10-31 11:11:12	ga_ls9c_ard_3-2-1_109072_2021-10-31_final.stac-item
2021-11-02 10:52:28	ga_ls9c_ard_3-2-1_106072_2021-11-02_final.stac-item
2021-11-08 09:58:38	ga_ls9c_ard_3-2-1_097078_2021-11-08_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-11-23 11:43:53	ga_ls9c_ard_3-2-1_114076_2021-11-23_final.stac-item
2021-12-06 10:48:36	ga_ls9c_ard_3-2-1_105072_2021-12-06_final.stac-item
2021-12-18 09:33:55	ga_ls9c_ard_3-2-1_093071_2021-12-18_final.stac-item
2021-12-20 09:27:33	ga_ls9c_ard_3-2-1_091086_2021-12-19_final.stac-item
2021-12-25 09:44:30	ga_ls9c_ard_3-2-1_094082_2021-12-25_final.stac-item
2021-12-27 11:08:38	ga_ls9c_ard_3-2-1_108076_2021-12-27_final.stac-item
2021-12-30 11:42:20	ga_ls9c_ard_3-2-1_113083_2021-12-30_final.stac-item
2022-01-07 10:47:40	ga_ls9c_ard_3-2-1_105070_2022-01-07_final.stac-item
2022-01-24 11:32:56	ga_ls9c_ard_3-2-1_112075_2022-01-24_final.stac-item
2022-02-02 11:29:57	ga_ls9c_ard_3-2-1_111083_2022-02-02_final.stac-item
2022-02-16 11:37:50	ga_ls9c_ard_3-2-1_113072_2022-02-16_final.stac-item
2022-03-04 10:01:35	ga_ls9c_ard_3-2-1_097079_2022-03-04_final.stac-item
2022-03-09 10:20:56	ga_ls9c_ard_3-2-1_100081_2022-03-09_final.stac-item
2022-03-31 09:39:46	ga_ls9c_ard_3-2-1_094071_2022-03-31_final.stac-item
2022-04-02 09:32:36	ga_ls9c_ard_3-2-1_092084_2022-04-02_final.stac-item
2022-04-09 09:39:56	ga_ls9c_ard_3-2-1_093087_2022-04-09_final.stac-item
2022-04-09 11:17:14	ga_ls9c_ard_3-2-1_109083_2022-04-09_final.stac-item
2022-05-07 11:40:08	ga_ls9c_ard_3-2-1_113079_2022-05-07_final.stac-item
2022-05-09 11:29:21	ga_ls9c_ard_3-2-1_111083_2022-05-09_final.stac-item
2022-05-14 10:02:33	ga_ls9c_ard_3-2-1_098067_2022-05-14_final.stac-item
2022-05-27 11:17:13	ga_ls9c_ard_3-2-1_109084_2022-05-27_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-06-03_final.stac-item
2022-06-12 11:16:06	ga_ls9c_ard_3-2-1_109081_2022-06-12_final.stac-item
2022-06-18 10:37:06	ga_ls9c_ard_3-2-1_103076_2022-06-18_final.stac-item
2022-06-21 11:06:07	ga_ls9c_ard_3-2-1_108071_2022-06-21_final.stac-item
2022-06-21 11:11:18	ga_ls9c_ard_3-2-1_108084_2022-06-21_final.stac-item
2022-06-25 10:44:18	ga_ls9c_ard_3-2-1_104078_2022-06-25_final.stac-item
2022-07-12 09:50:13	ga_ls9c_ard_3-2-1_095082_2022-07-12_final.stac-item
2022-07-18 10:46:04	ga_ls9c_ard_3-2-1_105067_2022-07-18_final.stac-item
2022-07-26 09:59:09	ga_ls9c_ard_3-2-1_097073_2022-07-26_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-06 09:43:32	ga_ls9c_ard_3-2-1_094080_2022-08-06_final.stac-item
2022-08-17 09:27:05	ga_ls9c_ard_3-2-1_091085_2022-08-16_final.stac-item
2022-08-18 11:47:14	ga_ls9c_ard_3-2-1_114080_2022-08-18_final.stac-item
2022-09-04 09:16:44	ga_ls9c_ard_3-2-1_089090_2022-09-03_final.stac-item
2022-09-12 09:59:49	ga_ls9c_ard_3-2-1_097074_2022-09-12_final.stac-item
2022-09-13 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-09-13_final.stac-item
2022-09-19 11:45:21	ga_ls9c_ard_3-2-1_114075_2022-09-19_final.stac-item
2022-09-28 10:02:43	ga_ls9c_ard_3-2-1_097081_2022-09-28_final.stac-item
2022-09-29 10:43:11	ga_ls9c_ard_3-2-1_104074_2022-09-29_final.stac-item
2022-10-03 10:18:51	ga_ls9c_ard_3-2-1_100075_2022-10-03_final.stac-item
2022-10-16 09:50:26	ga_ls9c_ard_3-2-1_095081_2022-10-16_final.stac-item
2022-10-21 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-10-21_final.stac-item
2022-10-27 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-10-27_final.stac-item
2022-10-29 09:19:08	ga_ls9c_ard_3-2-1_090080_2022-10-28_final.stac-item
2022-11-02 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-11-02_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-19 11:15:24	ga_ls9c_ard_3-2-1_109077_2022-11-19_final.stac-item
2022-11-28 11:09:58	ga_ls9c_ard_3-2-1_108079_2022-11-28_final.stac-item
2022-11-29 10:15:08	ga_ls9c_ard_3-2-1_099081_2022-11-29_final.stac-item
2022-12-01 10:02:46	ga_ls9c_ard_3-2-1_097081_2022-12-01_final.stac-item
2022-12-09 10:48:39	ga_ls9c_ard_3-2-1_105072_2022-12-09_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-14 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-12-14_final.stac-item
2022-12-26 09:56:35	ga_ls9c_ard_3-2-1_096081_2022-12-26_final.stac-item
2022-12-30 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-12-30_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-07 10:21:21	ga_ls9c_ard_3-2-1_100081_2023-01-07_final.stac-item
2023-01-12 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-12_final.stac-item
2023-01-16 10:12:41	ga_ls9c_ard_3-2-1_099075_2023-01-16_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_final.stac-item
2023-02-09 09:28:59	ga_ls9c_ard_3-2-1_091089_2023-02-08_final.stac-item
2023-02-11 10:53:06	ga_ls9c_ard_3-2-1_105083_2023-02-11_final.stac-item
2023-02-14 11:22:23	ga_ls9c_ard_3-2-1_110079_2023-02-14_final.stac-item
2023-02-25 09:27:32	ga_ls9c_ard_3-2-1_091086_2023-02-24_final.stac-item
2023-03-11 09:35:23	ga_ls9c_ard_3-2-1_093075_2023-03-11_final.stac-item
2023-03-25 09:47:39	ga_ls9c_ard_3-2-1_095075_2023-03-25_final.stac-item
2023-03-28 10:18:29	ga_ls9c_ard_3-2-1_100075_2023-03-28_final.stac-item
2023-03-31 10:48:33	ga_ls9c_ard_3-2-1_105073_2023-03-31_final.stac-item
2023-04-12 11:14:48	ga_ls9c_ard_3-2-1_109077_2023-04-12_final.stac-item
2023-05-07 11:06:00	ga_ls9c_ard_3-2-1_108071_2023-05-07_final.stac-item
2023-05-10 10:00:48	ga_ls9c_ard_3-2-1_097078_2023-05-10_final.stac-item
2023-05-12 09:48:02	ga_ls9c_ard_3-2-1_095077_2023-05-12_final.stac-item
2023-05-17 11:44:37	ga_ls9c_ard_3-2-1_114075_2023-05-17_final.stac-item
2023-05-23 09:28:34	ga_ls9c_ard_3-2-1_092075_2023-05-22_final.stac-item
2023-06-05 10:35:42	ga_ls9c_ard_3-2-1_103073_2023-06-05_final.stac-item
2023-07-05 10:45:44	ga_ls9c_ard_3-2-1_105067_2023-07-05_final.stac-item
2023-07-06 09:52:31	ga_ls9c_ard_3-2-1_096073_2023-07-06_final.stac-item
2023-07-06 09:54:55	ga_ls9c_ard_3-2-1_096079_2023-07-06_final.stac-item
2023-07-06 09:56:07	ga_ls9c_ard_3-2-1_096082_2023-07-06_final.stac-item
2023-07-17 11:16:55	ga_ls9c_ard_3-2-1_109083_2023-07-17_final.stac-item
2023-08-13 10:57:21	ga_ls9c_ard_3-2-1_106080_2023-08-13_final.stac-item
2023-08-14 10:00:32	ga_ls9c_ard_3-2-1_097077_2023-08-14_final.stac-item
2023-08-18 11:11:30	ga_ls9c_ard_3-2-1_109069_2023-08-18_final.stac-item
2023-08-18 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-08-18_final.stac-item
2023-10-18 10:44:40	ga_ls9c_ard_3-2-1_104078_2023-10-18_final.stac-item
2023-10-24 10:06:23	ga_ls9c_ard_3-2-1_098075_2023-10-24_final.stac-item
2023-10-25 10:46:27	ga_ls9c_ard_3-2-1_105067_2023-10-25_final.stac-item
2023-10-26 09:53:12	ga_ls9c_ard_3-2-1_096073_2023-10-26_final.stac-item
2023-10-31 10:09:18	ga_ls9c_ard_3-2-1_099067_2023-10-31_final.stac-item
2023-11-16 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-11-16_final.stac-item
2023-11-19 10:44:39	ga_ls9c_ard_3-2-1_104078_2023-11-19_final.stac-item
2023-11-26 10:49:43	ga_ls9c_ard_3-2-1_105075_2023-11-26_final.stac-item
2023-11-27 09:56:29	ga_ls9c_ard_3-2-1_096081_2023-11-27_final.stac-item
2024-02-16 10:40:04	ga_ls9c_ard_3-2-1_103082_2024-02-16_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