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
2021-11-12 09:21:56	ga_ls9c_ard_3-2-1_091080_2021-11-11_final.stac-item
2022-01-28 09:31:20	ga_ls9c_ard_3-2-1_092080_2022-01-28_final.stac-item
2022-03-04 09:58:23	ga_ls9c_ard_3-2-1_097071_2022-03-04_final.stac-item
2022-03-04 10:02:47	ga_ls9c_ard_3-2-1_097082_2022-03-04_final.stac-item
2022-03-04 11:38:52	ga_ls9c_ard_3-2-1_113075_2022-03-04_final.stac-item
2022-03-26 09:27:13	ga_ls9c_ard_3-2-1_091086_2022-03-25_final.stac-item
2022-04-17 10:26:54	ga_ls9c_ard_3-2-1_101081_2022-04-17_final.stac-item
2022-04-21 11:41:24	ga_ls9c_ard_3-2-1_113082_2022-04-21_final.stac-item
2022-04-22 10:44:58	ga_ls9c_ard_3-2-1_104080_2022-04-22_final.stac-item
2022-04-27 09:23:50	ga_ls9c_ard_3-2-1_091078_2022-04-26_final.stac-item
2022-05-10 10:33:19	ga_ls9c_ard_3-2-1_102082_2022-05-10_final.stac-item
2022-05-14 10:04:57	ga_ls9c_ard_3-2-1_098073_2022-05-14_final.stac-item
2022-06-12 11:11:42	ga_ls9c_ard_3-2-1_109070_2022-06-12_final.stac-item
2022-07-07 09:29:18	ga_ls9c_ard_3-2-1_092076_2022-07-06_final.stac-item
2022-07-15 10:17:54	ga_ls9c_ard_3-2-1_100074_2022-07-15_final.stac-item
2022-07-16 09:23:30	ga_ls9c_ard_3-2-1_091077_2022-07-15_final.stac-item
2022-08-11 09:59:44	ga_ls9c_ard_3-2-1_097074_2022-08-11_final.stac-item
2022-09-12 11:41:54	ga_ls9c_ard_3-2-1_113082_2022-09-12_final.stac-item
2022-09-19 10:06:28	ga_ls9c_ard_3-2-1_098075_2022-09-19_final.stac-item
2022-10-02 09:37:12	ga_ls9c_ard_3-2-1_093079_2022-10-02_final.stac-item
2022-10-15 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-10-15_final.stac-item
2022-10-17 10:30:54	ga_ls9c_ard_3-2-1_102074_2022-10-17_final.stac-item
2022-10-17 10:31:18	ga_ls9c_ard_3-2-1_102075_2022-10-17_final.stac-item
2022-10-18 09:40:05	ga_ls9c_ard_3-2-1_093086_2022-10-18_final.stac-item
2022-10-21 11:47:29	ga_ls9c_ard_3-2-1_114080_2022-10-21_final.stac-item
2022-10-29 10:57:37	ga_ls9c_ard_3-2-1_106079_2022-10-29_final.stac-item
2022-10-30 11:40:53	ga_ls9c_ard_3-2-1_113079_2022-10-30_final.stac-item
2022-11-04 10:20:30	ga_ls9c_ard_3-2-1_100079_2022-11-04_final.stac-item
2022-11-04 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-11-04_final.stac-item
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final.stac-item
2022-11-06 10:06:58	ga_ls9c_ard_3-2-1_098076_2022-11-06_final.stac-item
2022-11-14 10:57:15	ga_ls9c_ard_3-2-1_106078_2022-11-14_final.stac-item
2022-11-17 09:48:52	ga_ls9c_ard_3-2-1_095077_2022-11-17_final.stac-item
2022-11-24 09:55:50	ga_ls9c_ard_3-2-1_096079_2022-11-24_final.stac-item
2022-12-05 11:16:57	ga_ls9c_ard_3-2-1_109081_2022-12-05_final.stac-item
2022-12-12 09:43:52	ga_ls9c_ard_3-2-1_094080_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
2022-12-17 11:39:41	ga_ls9c_ard_3-2-1_113076_2022-12-17_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-30 09:31:54	ga_ls9c_ard_3-2-1_092081_2022-12-30_final.stac-item
2023-01-02 10:01:37	ga_ls9c_ard_3-2-1_097078_2023-01-02_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-06 11:16:58	ga_ls9c_ard_3-2-1_109081_2023-01-06_final.stac-item
2023-01-09 10:06:11	ga_ls9c_ard_3-2-1_098074_2023-01-09_final.stac-item
2023-01-12 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-12_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-18 10:02:41	ga_ls9c_ard_3-2-1_097081_2023-01-18_final.stac-item
2023-01-20 09:51:05	ga_ls9c_ard_3-2-1_095083_2023-01-20_final.stac-item
2023-01-25 10:08:06	ga_ls9c_ard_3-2-1_098079_2023-01-25_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-01-31 11:10:24	ga_ls9c_ard_3-2-1_108080_2023-01-31_final.stac-item
2023-02-03 09:58:51	ga_ls9c_ard_3-2-1_097071_2023-02-03_final.stac-item
2023-02-04 10:44:55	ga_ls9c_ard_3-2-1_104078_2023-02-04_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-06 10:30:10	ga_ls9c_ard_3-2-1_102072_2023-02-06_final.stac-item
2023-02-06 10:32:10	ga_ls9c_ard_3-2-1_102077_2023-02-06_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-09 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-10 10:08:39	ga_ls9c_ard_3-2-1_098080_2023-02-10_final.stac-item
2023-02-11 10:48:43	ga_ls9c_ard_3-2-1_105072_2023-02-11_final.stac-item
2023-02-16 09:33:54	ga_ls9c_ard_3-2-1_092086_2023-02-16_final.stac-item
2023-03-02 09:45:40	ga_ls9c_ard_3-2-1_094085_2023-03-02_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 10:54:13	ga_ls9c_ard_3-2-1_106072_2023-04-23_final.stac-item
2023-04-26 11:29:53	ga_ls9c_ard_3-2-1_111084_2023-04-26_final.stac-item
2023-05-08 10:14:46	ga_ls9c_ard_3-2-1_099082_2023-05-08_final.stac-item
2023-05-09 09:18:45	ga_ls9c_ard_3-2-1_090081_2023-05-08_final.stac-item
2023-05-10 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-05-10_final.stac-item
2023-05-10 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-05-10_final.stac-item
2023-06-26 09:19:13	ga_ls9c_ard_3-2-1_090083_2023-06-25_final.stac-item
2023-06-28 10:41:25	ga_ls9c_ard_3-2-1_104072_2023-06-28_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 09:54:31	ga_ls9c_ard_3-2-1_096078_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
2023-07-15 09:46:48	ga_ls9c_ard_3-2-1_095074_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
2023-07-17 11:11:44	ga_ls9c_ard_3-2-1_109070_2023-07-17_final.stac-item
2023-07-19 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-07-18_final.stac-item
2023-07-20 11:45:02	ga_ls9c_ard_3-2-1_114076_2023-07-20_final.stac-item
2023-07-25 10:23:28	ga_ls9c_ard_3-2-1_101073_2023-07-25_final.stac-item
2023-07-26 11:06:21	ga_ls9c_ard_3-2-1_108072_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
2023-07-29 09:58:49	ga_ls9c_ard_3-2-1_097073_2023-07-29_final.stac-item
2023-08-06 09:12:16	ga_ls9c_ard_3-2-1_089080_2023-08-05_final.stac-item
2023-10-14 09:32:04	ga_ls9c_ard_3-2-1_092082_2023-10-14_final.stac-item
2023-10-14 09:32:28	ga_ls9c_ard_3-2-1_092083_2023-10-14_final.stac-item
2023-10-19 11:29:08	ga_ls9c_ard_3-2-1_111081_2023-10-19_final.stac-item
2023-10-20 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-10-20_final.stac-item
2023-10-23 11:02:48	ga_ls9c_ard_3-2-1_107077_2023-10-23_final.stac-item
2023-10-24 11:45:40	ga_ls9c_ard_3-2-1_114076_2023-10-24_final.stac-item
2023-10-27 10:36:52	ga_ls9c_ard_3-2-1_103074_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
2023-10-31 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-10-31_final.stac-item
2023-11-01 10:57:19	ga_ls9c_ard_3-2-1_106079_2023-11-01_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-22 09:39:06	ga_ls9c_ard_3-2-1_093084_2023-11-22_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-11-24 09:27:34	ga_ls9c_ard_3-2-1_091086_2023-11-23_final.stac-item
2024-02-16 10:37:40	ga_ls9c_ard_3-2-1_103076_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