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
2021-12-04 11:02:10	ga_ls9c_ard_3-2-1_107075_2021-12-04_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-02-01 10:41:30	ga_ls9c_ard_3-2-1_104070_2022-02-01_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-04-17 10:26:54	ga_ls9c_ard_3-2-1_101081_2022-04-17_final.stac-item
2022-04-22 10:44:58	ga_ls9c_ard_3-2-1_104080_2022-04-22_final.stac-item
2022-06-12 11:11:42	ga_ls9c_ard_3-2-1_109070_2022-06-12_final.stac-item
2022-06-26 09:47:29	ga_ls9c_ard_3-2-1_095075_2022-06-26_final.stac-item
2022-08-15 11:13:07	ga_ls9c_ard_3-2-1_109072_2022-08-15_final.stac-item
2022-08-25 10:12:09	ga_ls9c_ard_3-2-1_099074_2022-08-25_final.stac-item
2022-09-17 10:18:24	ga_ls9c_ard_3-2-1_100074_2022-09-17_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_final.stac-item
2022-09-29 10:43:59	ga_ls9c_ard_3-2-1_104076_2022-09-29_final.stac-item
2022-10-05 11:45:22	ga_ls9c_ard_3-2-1_114075_2022-10-05_final.stac-item
2022-10-25 11:23:09	ga_ls9c_ard_3-2-1_110081_2022-10-25_final.stac-item
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final.stac-item
2022-12-06 10:20:32	ga_ls9c_ard_3-2-1_100079_2022-12-06_final.stac-item
2022-12-10 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-12-10_final.stac-item
2022-12-26 09:56:35	ga_ls9c_ard_3-2-1_096081_2022-12-26_final.stac-item
2023-01-08 09:29:19	ga_ls9c_ard_3-2-1_091090_2023-01-07_final.stac-item
2023-01-09 10:09:23	ga_ls9c_ard_3-2-1_098082_2023-01-09_final.stac-item
2023-01-10 10:53:02	ga_ls9c_ard_3-2-1_105083_2023-01-10_final.stac-item
2023-01-15 09:32:38	ga_ls9c_ard_3-2-1_092083_2023-01-15_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-26 10:52:59	ga_ls9c_ard_3-2-1_105083_2023-01-26_final.stac-item
2023-02-01 11:52:28	ga_ls9c_ard_3-2-1_115077_2023-02-01_final.stac-item
2023-02-02 10:56:51	ga_ls9c_ard_3-2-1_106077_2023-02-02_final.stac-item
2023-02-03 10:02:50	ga_ls9c_ard_3-2-1_097081_2023-02-03_final.stac-item
2023-02-04 10:44:31	ga_ls9c_ard_3-2-1_104077_2023-02-04_final.stac-item
2023-02-05 09:50:30	ga_ls9c_ard_3-2-1_095081_2023-02-05_final.stac-item
2023-02-05 11:28:11	ga_ls9c_ard_3-2-1_111078_2023-02-05_final.stac-item
2023-02-07 09:36:09	ga_ls9c_ard_3-2-1_093076_2023-02-07_final.stac-item
2023-02-07 09:40:08	ga_ls9c_ard_3-2-1_093086_2023-02-07_final.stac-item
2023-02-07 11:15:26	ga_ls9c_ard_3-2-1_109077_2023-02-07_final.stac-item
2023-02-10 11:47:08	ga_ls9c_ard_3-2-1_114079_2023-02-10_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-04-21 09:32:30	ga_ls9c_ard_3-2-1_092084_2023-04-21_final.stac-item
2023-04-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2023-04-22_final.stac-item
2023-04-24 10:00:59	ga_ls9c_ard_3-2-1_097078_2023-04-24_final.stac-item
2023-04-27 10:31:27	ga_ls9c_ard_3-2-1_102077_2023-04-27_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-04-30 09:23:25	ga_ls9c_ard_3-2-1_091077_2023-04-29_final.stac-item
2023-04-30 11:00:42	ga_ls9c_ard_3-2-1_107073_2023-04-30_final.stac-item
2023-04-30 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-04-30_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-07-15 09:50:24	ga_ls9c_ard_3-2-1_095083_2023-07-15_final.stac-item
2023-07-15 09:51:12	ga_ls9c_ard_3-2-1_095085_2023-07-15_final.stac-item
2023-07-15 11:28:53	ga_ls9c_ard_3-2-1_111082_2023-07-15_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 11:00:10	ga_ls9c_ard_3-2-1_107072_2023-07-19_final.stac-item
2023-07-21 09:12:31	ga_ls9c_ard_3-2-1_089081_2023-07-20_final.stac-item
2023-07-26 09:31:27	ga_ls9c_ard_3-2-1_092082_2023-07-26_final.stac-item
2023-07-27 10:12:20	ga_ls9c_ard_3-2-1_099076_2023-07-27_final.stac-item
2023-07-28 10:53:13	ga_ls9c_ard_3-2-1_106070_2023-07-28_final.stac-item
2023-07-28 10:58:01	ga_ls9c_ard_3-2-1_106082_2023-07-28_final.stac-item
2023-07-29 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-07-29_final.stac-item
2023-08-05 11:44:46	ga_ls9c_ard_3-2-1_114075_2023-08-05_final.stac-item
2023-08-05 11:45:10	ga_ls9c_ard_3-2-1_114076_2023-08-05_final.stac-item
2023-08-08 10:34:25	ga_ls9c_ard_3-2-1_103069_2023-08-08_final.stac-item
2023-10-14 11:10:33	ga_ls9c_ard_3-2-1_108081_2023-10-14_final.stac-item
2023-10-15 11:53:26	ga_ls9c_ard_3-2-1_115080_2023-10-15_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-17 10:03:24	ga_ls9c_ard_3-2-1_097083_2023-10-17_final.stac-item
2023-10-20 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-10-20_final.stac-item
2023-10-20 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-10-20_final.stac-item
2023-10-22 10:18:21	ga_ls9c_ard_3-2-1_100074_2023-10-22_final.stac-item
2023-10-24 10:06:23	ga_ls9c_ard_3-2-1_098075_2023-10-24_final.stac-item
2023-10-24 11:45:40	ga_ls9c_ard_3-2-1_114076_2023-10-24_final.stac-item
2023-10-25 09:14:21	ga_ls9c_ard_3-2-1_089084_2023-10-24_final.stac-item
2023-10-26 09:52:48	ga_ls9c_ard_3-2-1_096072_2023-10-26_final.stac-item
2023-10-27 10:36:28	ga_ls9c_ard_3-2-1_103073_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
2023-10-29 10:24:29	ga_ls9c_ard_3-2-1_101074_2023-10-29_final.stac-item
2023-10-30 11:06:55	ga_ls9c_ard_3-2-1_108072_2023-10-30_final.stac-item
2023-11-01 09:20:02	ga_ls9c_ard_3-2-1_090083_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
2023-11-03 10:43:44	ga_ls9c_ard_3-2-1_104076_2023-11-03_final.stac-item
2023-11-03 10:44:32	ga_ls9c_ard_3-2-1_104078_2023-11-03_final.stac-item
2023-11-03 10:45:20	ga_ls9c_ard_3-2-1_104080_2023-11-03_final.stac-item
2023-11-05 10:31:24	ga_ls9c_ard_3-2-1_102076_2023-11-05_final.stac-item
2023-11-15 09:30:49	ga_ls9c_ard_3-2-1_092079_2023-11-15_final.stac-item
2023-11-15 09:32:25	ga_ls9c_ard_3-2-1_092083_2023-11-15_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 09:18:29	ga_ls9c_ard_3-2-1_090079_2023-11-16_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-20 09:51:02	ga_ls9c_ard_3-2-1_095083_2023-11-20_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-11-22 09:36:18	ga_ls9c_ard_3-2-1_093077_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
2023-11-25 10:09:14	ga_ls9c_ard_3-2-1_098082_2023-11-25_final.stac-item
2024-02-16 10:37:40	ga_ls9c_ard_3-2-1_103076_2024-02-16_final.stac-item
2024-02-16 10:39:16	ga_ls9c_ard_3-2-1_103080_2024-02-16_final.stac-item
2024-02-17 11:21:19	ga_ls9c_ard_3-2-1_110077_2024-02-17_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