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
2021-11-08 09:59:02	ga_ls9c_ard_3-2-1_097079_2021-11-08_final.stac-item
2021-11-08 11:39:17	ga_ls9c_ard_3-2-1_113083_2021-11-08_final.stac-item
2021-12-14 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-14_final.stac-item
2021-12-14 11:37:57	ga_ls9c_ard_3-2-1_113072_2021-12-14_final.stac-item
2021-12-14 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-14_final.stac-item
2021-12-27 11:09:50	ga_ls9c_ard_3-2-1_108079_2021-12-27_final.stac-item
2022-01-01 11:29:58	ga_ls9c_ard_3-2-1_111083_2022-01-01_final.stac-item
2022-01-02 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-01-02_final.stac-item
2022-01-12 09:29:42	ga_ls9c_ard_3-2-1_092076_2022-01-11_final.stac-item
2022-01-14 10:57:01	ga_ls9c_ard_3-2-1_106078_2022-01-14_final.stac-item
2022-01-21 11:04:25	ga_ls9c_ard_3-2-1_107081_2022-01-21_final.stac-item
2022-02-04 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-02-04_final.stac-item
2022-02-05 11:58:51	ga_ls9c_ard_3-2-1_116078_2022-02-05_final.stac-item
2022-02-08 10:47:39	ga_ls9c_ard_3-2-1_105070_2022-02-08_final.stac-item
2022-02-15 09:20:29	ga_ls9c_ard_3-2-1_090084_2022-02-14_final.stac-item
2022-03-29 11:35:48	ga_ls9c_ard_3-2-1_112083_2022-03-29_final.stac-item
2022-04-09 09:39:56	ga_ls9c_ard_3-2-1_093087_2022-04-09_final.stac-item
2022-04-11 09:24:22	ga_ls9c_ard_3-2-1_091079_2022-04-10_final.stac-item
2022-04-18 09:29:16	ga_ls9c_ard_3-2-1_092076_2022-04-17_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-04-27 10:59:31	ga_ls9c_ard_3-2-1_107070_2022-04-27_final.stac-item
2022-04-27 11:01:55	ga_ls9c_ard_3-2-1_107076_2022-04-27_final.stac-item
2022-04-30 09:56:43	ga_ls9c_ard_3-2-1_096083_2022-04-30_final.stac-item
2022-05-03 10:24:48	ga_ls9c_ard_3-2-1_101076_2022-05-03_final.stac-item
2022-05-04 11:05:16	ga_ls9c_ard_3-2-1_108069_2022-05-04_final.stac-item
2022-05-23 09:59:52	ga_ls9c_ard_3-2-1_097076_2022-05-23_final.stac-item
2022-05-29 09:24:23	ga_ls9c_ard_3-2-1_091080_2022-05-28_final.stac-item
2022-05-31 09:13:38	ga_ls9c_ard_3-2-1_089084_2022-05-30_final.stac-item
2022-06-11 10:28:50	ga_ls9c_ard_3-2-1_102071_2022-06-11_final.stac-item
2022-06-11 10:30:25	ga_ls9c_ard_3-2-1_102075_2022-06-11_final.stac-item
2022-06-12 09:35:37	ga_ls9c_ard_3-2-1_093077_2022-06-12_final.stac-item
2022-06-12 11:12:06	ga_ls9c_ard_3-2-1_109071_2022-06-12_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-06-22 10:12:31	ga_ls9c_ard_3-2-1_099076_2022-06-22_final.stac-item
2022-06-25 10:44:18	ga_ls9c_ard_3-2-1_104078_2022-06-25_final.stac-item
2022-06-26 11:29:10	ga_ls9c_ard_3-2-1_111082_2022-06-26_final.stac-item
2022-07-16 11:03:34	ga_ls9c_ard_3-2-1_107080_2022-07-16_final.stac-item
2022-07-18 09:12:22	ga_ls9c_ard_3-2-1_089080_2022-07-17_final.stac-item
2022-07-26 10:01:56	ga_ls9c_ard_3-2-1_097080_2022-07-26_final.stac-item
2022-07-27 10:40:50	ga_ls9c_ard_3-2-1_104069_2022-07-27_final.stac-item
2022-07-30 09:38:52	ga_ls9c_ard_3-2-1_093084_2022-07-30_final.stac-item
2022-07-31 10:18:33	ga_ls9c_ard_3-2-1_100075_2022-07-31_final.stac-item
2022-08-15 11:17:07	ga_ls9c_ard_3-2-1_109082_2022-08-15_final.stac-item
2022-08-17 11:02:46	ga_ls9c_ard_3-2-1_107077_2022-08-17_final.stac-item
2022-08-26 09:20:08	ga_ls9c_ard_3-2-1_090083_2022-08-25_final.stac-item
2022-08-27 10:01:47	ga_ls9c_ard_3-2-1_097079_2022-08-27_final.stac-item
2022-09-01 11:58:01	ga_ls9c_ard_3-2-1_116076_2022-09-01_final.stac-item
2022-09-11 09:20:56	ga_ls9c_ard_3-2-1_090085_2022-09-10_final.stac-item
2022-09-13 10:45:29	ga_ls9c_ard_3-2-1_104080_2022-09-13_final.stac-item
2022-09-14 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-09-14_final.stac-item
2022-09-21 09:53:19	ga_ls9c_ard_3-2-1_096073_2022-09-21_final.stac-item
2022-10-21 10:08:12	ga_ls9c_ard_3-2-1_098079_2022-10-21_final.stac-item
2022-10-28 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-10-28_final.stac-item
2022-10-30 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-10-30_final.stac-item
2022-11-13 11:51:17	ga_ls9c_ard_3-2-1_115074_2022-11-13_final.stac-item
2022-11-18 10:33:20	ga_ls9c_ard_3-2-1_102080_2022-11-18_final.stac-item
2022-11-20 10:20:34	ga_ls9c_ard_3-2-1_100079_2022-11-20_final.stac-item
2022-12-15 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-12-15_final.stac-item
2022-12-23 11:01:21	ga_ls9c_ard_3-2-1_107073_2022-12-23_final.stac-item
2022-12-31 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-12-31_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-20 11:30:22	ga_ls9c_ard_3-2-1_111084_2023-01-20_final.stac-item
2023-01-28 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-28_final.stac-item
2023-02-02 09:19:34	ga_ls9c_ard_3-2-1_090081_2023-02-01_final.stac-item
2023-02-19 10:02:44	ga_ls9c_ard_3-2-1_097081_2023-02-19_final.stac-item
2023-03-07 10:03:20	ga_ls9c_ard_3-2-1_097083_2023-03-07_final.stac-item
2023-04-14 11:04:01	ga_ls9c_ard_3-2-1_107081_2023-04-14_final.stac-item
2023-04-15 11:46:28	ga_ls9c_ard_3-2-1_114079_2023-04-15_final.stac-item
2023-04-19 09:43:40	ga_ls9c_ard_3-2-1_094081_2023-04-19_final.stac-item
2023-04-26 09:47:00	ga_ls9c_ard_3-2-1_095074_2023-04-26_final.stac-item
2023-04-29 10:19:51	ga_ls9c_ard_3-2-1_100079_2023-04-29_final.stac-item
2023-05-07 11:09:11	ga_ls9c_ard_3-2-1_108079_2023-05-07_final.stac-item
2023-05-16 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-05-16_final.stac-item
2023-05-25 10:56:39	ga_ls9c_ard_3-2-1_106079_2023-05-25_final.stac-item
2023-06-06 11:20:33	ga_ls9c_ard_3-2-1_110077_2023-06-06_final.stac-item
2023-06-13 09:50:33	ga_ls9c_ard_3-2-1_095084_2023-06-13_final.stac-item
2023-06-17 09:25:23	ga_ls9c_ard_3-2-1_091083_2023-06-16_final.stac-item
2023-06-27 11:41:00	ga_ls9c_ard_3-2-1_113082_2023-06-27_final.stac-item
2023-06-28 10:44:36	ga_ls9c_ard_3-2-1_104080_2023-06-28_final.stac-item
2023-07-01 09:34:19	ga_ls9c_ard_3-2-1_093074_2023-07-01_final.stac-item
2023-07-04 11:46:08	ga_ls9c_ard_3-2-1_114079_2023-07-04_final.stac-item
2023-07-16 10:30:28	ga_ls9c_ard_3-2-1_102075_2023-07-16_final.stac-item
2023-07-19 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-07-18_final.stac-item
2023-07-19 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-07-19_final.stac-item
2023-07-28 10:53:13	ga_ls9c_ard_3-2-1_106070_2023-07-28_final.stac-item
2023-07-29 09:58:01	ga_ls9c_ard_3-2-1_097071_2023-07-29_final.stac-item
2023-08-04 09:24:36	ga_ls9c_ard_3-2-1_091080_2023-08-03_final.stac-item
2023-08-10 10:22:27	ga_ls9c_ard_3-2-1_101070_2023-08-10_final.stac-item
2023-08-14 10:03:19	ga_ls9c_ard_3-2-1_097084_2023-08-14_final.stac-item
2023-08-14 11:41:01	ga_ls9c_ard_3-2-1_113081_2023-08-14_final.stac-item
2023-08-16 09:46:58	ga_ls9c_ard_3-2-1_095074_2023-08-16_final.stac-item
2023-08-18 09:35:00	ga_ls9c_ard_3-2-1_093075_2023-08-18_final.stac-item
2023-10-19 09:50:39	ga_ls9c_ard_3-2-1_095082_2023-10-19_final.stac-item
2023-10-25 09:14:21	ga_ls9c_ard_3-2-1_089084_2023-10-24_final.stac-item
2023-10-29 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-29_final.stac-item
2023-10-30 11:09:19	ga_ls9c_ard_3-2-1_108078_2023-10-30_final.stac-item
2023-10-30 11:10:07	ga_ls9c_ard_3-2-1_108080_2023-10-30_final.stac-item
2023-11-04 09:50:55	ga_ls9c_ard_3-2-1_095083_2023-11-04_final.stac-item
2023-11-15 09:32:01	ga_ls9c_ard_3-2-1_092082_2023-11-15_final.stac-item
2023-11-22 11:12:48	ga_ls9c_ard_3-2-1_109071_2023-11-22_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