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
2021-12-15 10:41:07	ga_ls9c_ard_3-2-1_104069_2021-12-15_final.stac-item
2021-12-22 10:48:29	ga_ls9c_ard_3-2-1_105072_2021-12-22_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2021-12-25 09:46:06	ga_ls9c_ard_3-2-1_094086_2021-12-25_final.stac-item
2021-12-28 10:12:37	ga_ls9c_ard_3-2-1_099075_2021-12-28_final.stac-item
2022-01-08 11:35:43	ga_ls9c_ard_3-2-1_112082_2022-01-08_final.stac-item
2022-02-09 09:56:01	ga_ls9c_ard_3-2-1_096080_2022-02-09_final.stac-item
2022-02-14 11:51:01	ga_ls9c_ard_3-2-1_115074_2022-02-14_final.stac-item
2022-02-16 10:02:57	ga_ls9c_ard_3-2-1_097082_2022-02-16_final.stac-item
2022-02-16 11:41:50	ga_ls9c_ard_3-2-1_113082_2022-02-16_final.stac-item
2022-02-26 10:39:06	ga_ls9c_ard_3-2-1_103080_2022-02-26_final.stac-item
2022-03-04 11:41:40	ga_ls9c_ard_3-2-1_113082_2022-03-04_final.stac-item
2022-03-05 10:42:27	ga_ls9c_ard_3-2-1_104073_2022-03-05_final.stac-item
2022-03-08 09:35:40	ga_ls9c_ard_3-2-1_093076_2022-03-08_final.stac-item
2022-04-12 10:07:37	ga_ls9c_ard_3-2-1_098079_2022-04-12_final.stac-item
2022-04-21 10:00:07	ga_ls9c_ard_3-2-1_097076_2022-04-21_final.stac-item
2022-05-03 10:24:01	ga_ls9c_ard_3-2-1_101074_2022-05-03_final.stac-item
2022-05-16 09:52:10	ga_ls9c_ard_3-2-1_096072_2022-05-16_final.stac-item
2022-05-17 10:35:48	ga_ls9c_ard_3-2-1_103073_2022-05-17_final.stac-item
2022-05-18 09:42:34	ga_ls9c_ard_3-2-1_094079_2022-05-18_final.stac-item
2022-06-01 09:52:31	ga_ls9c_ard_3-2-1_096073_2022-06-01_final.stac-item
2022-06-01 09:56:30	ga_ls9c_ard_3-2-1_096083_2022-06-01_final.stac-item
2022-06-18 10:35:54	ga_ls9c_ard_3-2-1_103073_2022-06-18_final.stac-item
2022-06-29 10:17:35	ga_ls9c_ard_3-2-1_100073_2022-06-29_final.stac-item
2022-07-04 10:36:06	ga_ls9c_ard_3-2-1_103073_2022-07-04_final.stac-item
2022-07-11 10:40:15	ga_ls9c_ard_3-2-1_104068_2022-07-11_final.stac-item
2022-07-19 09:55:39	ga_ls9c_ard_3-2-1_096080_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
2022-08-02 10:03:02	ga_ls9c_ard_3-2-1_098067_2022-08-02_final.stac-item
2022-08-11 11:41:24	ga_ls9c_ard_3-2-1_113081_2022-08-11_final.stac-item
2022-08-15 11:13:31	ga_ls9c_ard_3-2-1_109073_2022-08-15_final.stac-item
2022-08-26 09:19:20	ga_ls9c_ard_3-2-1_090081_2022-08-25_final.stac-item
2022-09-09 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-09-09_final.stac-item
2022-09-23 09:44:57	ga_ls9c_ard_3-2-1_094083_2022-09-23_final.stac-item
2022-10-18 11:12:59	ga_ls9c_ard_3-2-1_109071_2022-10-18_final.stac-item
2022-10-21 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-10-21_final.stac-item
2022-10-31 10:42:51	ga_ls9c_ard_3-2-1_104073_2022-10-31_final.stac-item
2022-11-07 10:48:38	ga_ls9c_ard_3-2-1_105072_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
2022-11-24 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-11-24_final.stac-item
2022-12-06 10:20:56	ga_ls9c_ard_3-2-1_100080_2022-12-06_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-07 11:01:00	ga_ls9c_ard_3-2-1_107072_2022-12-07_final.stac-item
2022-12-08 11:45:52	ga_ls9c_ard_3-2-1_114076_2022-12-08_final.stac-item
2022-12-09 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-12-09_final.stac-item
2022-12-15 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-15_final.stac-item
2022-12-24 11:47:25	ga_ls9c_ard_3-2-1_114080_2022-12-24_final.stac-item
2023-01-08 09:29:19	ga_ls9c_ard_3-2-1_091090_2023-01-07_final.stac-item
2023-01-12 10:39:04	ga_ls9c_ard_3-2-1_103079_2023-01-12_final.stac-item
2023-02-01 11:51:16	ga_ls9c_ard_3-2-1_115074_2023-02-01_final.stac-item
2023-02-01 11:52:28	ga_ls9c_ard_3-2-1_115077_2023-02-01_final.stac-item
2023-02-05 11:28:59	ga_ls9c_ard_3-2-1_111080_2023-02-05_final.stac-item
2023-02-11 10:49:07	ga_ls9c_ard_3-2-1_105073_2023-02-11_final.stac-item
2023-02-18 09:18:18	ga_ls9c_ard_3-2-1_090078_2023-02-17_final.stac-item
2023-02-22 10:29:35	ga_ls9c_ard_3-2-1_102071_2023-02-22_final.stac-item
2023-02-25 09:24:44	ga_ls9c_ard_3-2-1_091079_2023-02-24_final.stac-item
2023-03-01 10:38:30	ga_ls9c_ard_3-2-1_103078_2023-03-01_final.stac-item
2023-03-04 09:31:41	ga_ls9c_ard_3-2-1_092081_2023-03-04_final.stac-item
2023-03-08 10:42:11	ga_ls9c_ard_3-2-1_104072_2023-03-08_final.stac-item
2023-04-02 10:39:48	ga_ls9c_ard_3-2-1_103082_2023-04-02_final.stac-item
2023-04-05 11:06:18	ga_ls9c_ard_3-2-1_108071_2023-04-05_final.stac-item
2023-04-23 10:57:01	ga_ls9c_ard_3-2-1_106079_2023-04-23_final.stac-item
2023-04-26 09:49:48	ga_ls9c_ard_3-2-1_095081_2023-04-26_final.stac-item
2023-04-27 10:30:15	ga_ls9c_ard_3-2-1_102074_2023-04-27_final.stac-item
2023-04-27 10:31:27	ga_ls9c_ard_3-2-1_102077_2023-04-27_final.stac-item
2023-05-06 10:24:20	ga_ls9c_ard_3-2-1_101075_2023-05-06_final.stac-item
2023-05-07 09:29:30	ga_ls9c_ard_3-2-1_092077_2023-05-06_final.stac-item
2023-05-19 11:34:37	ga_ls9c_ard_3-2-1_112081_2023-05-19_final.stac-item
2023-05-20 10:36:12	ga_ls9c_ard_3-2-1_103074_2023-05-20_final.stac-item
2023-05-27 10:39:54	ga_ls9c_ard_3-2-1_104068_2023-05-27_final.stac-item
2023-06-03 10:48:04	ga_ls9c_ard_3-2-1_105073_2023-06-03_final.stac-item
2023-06-03 10:50:28	ga_ls9c_ard_3-2-1_105079_2023-06-03_final.stac-item
2023-06-08 09:28:53	ga_ls9c_ard_3-2-1_092076_2023-06-07_final.stac-item
2023-06-15 11:15:50	ga_ls9c_ard_3-2-1_109081_2023-06-15_final.stac-item
2023-07-09 10:23:51	ga_ls9c_ard_3-2-1_101074_2023-07-09_final.stac-item
2023-07-15 11:26:29	ga_ls9c_ard_3-2-1_111076_2023-07-15_final.stac-item
2023-07-22 11:35:03	ga_ls9c_ard_3-2-1_112082_2023-07-22_final.stac-item
2023-07-23 10:35:50	ga_ls9c_ard_3-2-1_103073_2023-07-23_final.stac-item
2023-08-03 10:21:49	ga_ls9c_ard_3-2-1_100084_2023-08-03_final.stac-item
2023-08-09 11:18:29	ga_ls9c_ard_3-2-1_110071_2023-08-09_final.stac-item
2023-08-16 09:50:58	ga_ls9c_ard_3-2-1_095084_2023-08-16_final.stac-item
2023-08-22 09:12:21	ga_ls9c_ard_3-2-1_089080_2023-08-21_final.stac-item
2023-08-22 10:46:03	ga_ls9c_ard_3-2-1_105067_2023-08-22_final.stac-item
2023-08-27 09:31:45	ga_ls9c_ard_3-2-1_092082_2023-08-27_final.stac-item
2023-09-11 10:23:56	ga_ls9c_ard_3-2-1_101073_2023-09-11_final.stac-item
2023-09-17 09:50:05	ga_ls9c_ard_3-2-1_095081_2023-09-17_final.stac-item
2023-09-22 11:45:05	ga_ls9c_ard_3-2-1_114075_2023-09-22_final.stac-item
2023-09-25 10:36:40	ga_ls9c_ard_3-2-1_103074_2023-09-25_final.stac-item
2023-10-03 09:47:41	ga_ls9c_ard_3-2-1_095075_2023-10-03_final.stac-item
2023-10-25 10:46:27	ga_ls9c_ard_3-2-1_105067_2023-10-25_final.stac-item
2023-10-29 10:25:16	ga_ls9c_ard_3-2-1_101076_2023-10-29_final.stac-item
2023-11-04 09:50:07	ga_ls9c_ard_3-2-1_095081_2023-11-04_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 09:19:17	ga_ls9c_ard_3-2-1_090081_2023-11-16_final.stac-item
2023-11-18 11:41:27	ga_ls9c_ard_3-2-1_113081_2023-11-18_final.stac-item
2023-11-19 10:44:15	ga_ls9c_ard_3-2-1_104077_2023-11-19_final.stac-item
2023-11-30 10:25:23	ga_ls9c_ard_3-2-1_101076_2023-11-30_final.stac-item
2023-12-11 11:45:41	ga_ls9c_ard_3-2-1_114076_2023-12-11_final.stac-item
2023-12-13 09:54:04	ga_ls9c_ard_3-2-1_096075_2023-12-13_final.stac-item
2023-12-22 11:28:25	ga_ls9c_ard_3-2-1_111079_2023-12-22_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