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 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_2021-12-19_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-02-20 09:34:59	ga_ls9c_ard_3-2-1_093074_2022-02-20_final.stac-item
2022-02-23 10:07:27	ga_ls9c_ard_3-2-1_098078_2022-02-23_final.stac-item
2022-03-09 10:17:20	ga_ls9c_ard_3-2-1_100072_2022-03-09_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-10 10:57:20	ga_ls9c_ard_3-2-1_106079_2022-08-10_final.stac-item
2022-09-27 10:57:32	ga_ls9c_ard_3-2-1_106079_2022-09-27_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2023-01-01 10:57:38	ga_ls9c_ard_3-2-1_106079_2023-01-01_final.stac-item
2023-01-12 10:38:40	ga_ls9c_ard_3-2-1_103078_2023-01-12_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-27 09:54:35	ga_ls9c_ard_3-2-1_096076_2023-01-27_final.stac-item
2023-01-29 11:20:44	ga_ls9c_ard_3-2-1_110075_2023-01-29_final.stac-item
2023-02-02 09:21:58	ga_ls9c_ard_3-2-1_090087_2023-02-01_final.stac-item
2023-02-08 10:17:49	ga_ls9c_ard_3-2-1_100072_2023-02-08_final.stac-item
2023-02-10 10:09:27	ga_ls9c_ard_3-2-1_098082_2023-02-10_final.stac-item
2023-04-23 09:17:20	ga_ls9c_ard_3-2-1_090077_2023-04-22_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-24 10:00:35	ga_ls9c_ard_3-2-1_097077_2023-04-24_final.stac-item
2023-04-24 11:41:52	ga_ls9c_ard_3-2-1_113083_2023-04-24_final.stac-item
2023-04-25 10:43:50	ga_ls9c_ard_3-2-1_104077_2023-04-25_final.stac-item
2023-04-26 09:48:12	ga_ls9c_ard_3-2-1_095077_2023-04-26_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-04-26 11:25:05	ga_ls9c_ard_3-2-1_111072_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
2023-04-28 11:17:29	ga_ls9c_ard_3-2-1_109084_2023-04-28_final.stac-item
2023-04-29 10:21:03	ga_ls9c_ard_3-2-1_100082_2023-04-29_final.stac-item
2023-04-30 11:01:30	ga_ls9c_ard_3-2-1_107075_2023-04-30_final.stac-item
2023-05-28 09:45:53	ga_ls9c_ard_3-2-1_095072_2023-05-28_final.stac-item
2023-07-05 10:50:08	ga_ls9c_ard_3-2-1_105078_2023-07-05_final.stac-item
2023-07-28 10:52:49	ga_ls9c_ard_3-2-1_106069_2023-07-28_final.stac-item
2023-07-29 11:40:06	ga_ls9c_ard_3-2-1_113079_2023-07-29_final.stac-item
2023-10-13 10:24:53	ga_ls9c_ard_3-2-1_101075_2023-10-13_final.stac-item
2023-10-13 10:25:17	ga_ls9c_ard_3-2-1_101076_2023-10-13_final.stac-item
2023-10-14 11:06:58	ga_ls9c_ard_3-2-1_108072_2023-10-14_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-15 10:12:33	ga_ls9c_ard_3-2-1_099075_2023-10-15_final.stac-item
2023-10-15 10:15:45	ga_ls9c_ard_3-2-1_099083_2023-10-15_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-16 09:18:08	ga_ls9c_ard_3-2-1_090078_2023-10-15_final.stac-item
2023-10-16 10:59:01	ga_ls9c_ard_3-2-1_106083_2023-10-16_final.stac-item
2023-10-17 10:02:36	ga_ls9c_ard_3-2-1_097081_2023-10-17_final.stac-item
2023-10-17 11:40:17	ga_ls9c_ard_3-2-1_113078_2023-10-17_final.stac-item
2023-10-17 11:41:05	ga_ls9c_ard_3-2-1_113080_2023-10-17_final.stac-item
2023-10-18 10:43:52	ga_ls9c_ard_3-2-1_104076_2023-10-18_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-19 09:49:03	ga_ls9c_ard_3-2-1_095078_2023-10-19_final.stac-item
2023-10-19 11:29:08	ga_ls9c_ard_3-2-1_111081_2023-10-19_final.stac-item
2023-10-19 11:29:32	ga_ls9c_ard_3-2-1_111082_2023-10-19_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-10-21 09:37:05	ga_ls9c_ard_3-2-1_093079_2023-10-21_final.stac-item
2023-10-22 10:18:45	ga_ls9c_ard_3-2-1_100075_2023-10-22_final.stac-item
2023-10-22 10:20:45	ga_ls9c_ard_3-2-1_100080_2023-10-22_final.stac-item
2023-10-23 09:25:07	ga_ls9c_ard_3-2-1_091080_2023-10-22_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-10-23 11:03:36	ga_ls9c_ard_3-2-1_107079_2023-10-23_final.stac-item
2023-10-24 10:04:23	ga_ls9c_ard_3-2-1_098070_2023-10-24_final.stac-item
2023-10-25 10:47:14	ga_ls9c_ard_3-2-1_105069_2023-10-25_final.stac-item
2023-10-26 09:52:01	ga_ls9c_ard_3-2-1_096070_2023-10-26_final.stac-item
2023-10-26 09:53:36	ga_ls9c_ard_3-2-1_096074_2023-10-26_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_2023-10-27_final.stac-item
2023-10-27 10:37:39	ga_ls9c_ard_3-2-1_103076_2023-10-27_final.stac-item
2023-10-27 10:40:03	ga_ls9c_ard_3-2-1_103082_2023-10-27_final.stac-item
2023-10-28 09:43:13	ga_ls9c_ard_3-2-1_094079_2023-10-28_final.stac-item
2023-10-30 09:33:38	ga_ls9c_ard_3-2-1_092086_2023-10-30_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final.stac-item
2023-11-01 09:19:14	ga_ls9c_ard_3-2-1_090081_2023-10-31_final.stac-item
2023-11-01 09:20:26	ga_ls9c_ard_3-2-1_090084_2023-10-31_final.stac-item
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-11-02 09:58:06	ga_ls9c_ard_3-2-1_097070_2023-11-02_final.stac-item
2023-11-04 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-11-04_final.stac-item
2023-11-04 09:49:43	ga_ls9c_ard_3-2-1_095080_2023-11-04_final.stac-item
2023-11-14 10:26:51	ga_ls9c_ard_3-2-1_101080_2023-11-14_final.stac-item
2023-11-15 09:30:49	ga_ls9c_ard_3-2-1_092079_2023-11-15_final.stac-item
2023-11-16 10:12:29	ga_ls9c_ard_3-2-1_099075_2023-11-16_final.stac-item
2023-11-16 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-11-16_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-16 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-11-16_final.stac-item
2023-11-17 09:18:29	ga_ls9c_ard_3-2-1_090079_2023-11-16_final.stac-item
2023-11-18 10:02:34	ga_ls9c_ard_3-2-1_097081_2023-11-18_final.stac-item
2023-11-18 11:40:39	ga_ls9c_ard_3-2-1_113079_2023-11-18_final.stac-item
2023-11-19 10:41:03	ga_ls9c_ard_3-2-1_104069_2023-11-19_final.stac-item
2023-11-19 10:44:15	ga_ls9c_ard_3-2-1_104077_2023-11-19_final.stac-item
2023-11-20 09:49:50	ga_ls9c_ard_3-2-1_095080_2023-11-20_final.stac-item
2023-11-21 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-11-21_final.stac-item
2023-11-22 09:37:30	ga_ls9c_ard_3-2-1_093080_2023-11-22_final.stac-item
2023-11-22 11:17:35	ga_ls9c_ard_3-2-1_109083_2023-11-22_final.stac-item
2023-11-23 10:21:35	ga_ls9c_ard_3-2-1_100082_2023-11-23_final.stac-item
2023-11-24 11:04:51	ga_ls9c_ard_3-2-1_107082_2023-11-24_final.stac-item
2023-11-25 10:08:26	ga_ls9c_ard_3-2-1_098080_2023-11-25_final.stac-item
2023-11-25 10:09:38	ga_ls9c_ard_3-2-1_098083_2023-11-25_final.stac-item
2024-02-16 10:36:28	ga_ls9c_ard_3-2-1_103073_2024-02-16_final.stac-item
2024-02-16 10:37:40	ga_ls9c_ard_3-2-1_103076_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