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
2021-11-24 10:45:34	ga_ls9c_ard_3-2-1_104077_2021-11-24_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-01-14 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-01-13_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-18 09:47:46	ga_ls9c_ard_3-2-1_095075_2022-02-18_final.stac-item
2022-02-19 10:33:49	ga_ls9c_ard_3-2-1_102082_2022-02-19_final.stac-item
2022-04-11 09:25:10	ga_ls9c_ard_3-2-1_091081_2022-04-10_final.stac-item
2022-04-13 09:09:59	ga_ls9c_ard_3-2-1_089074_2022-04-12_final.stac-item
2022-04-16 09:40:51	ga_ls9c_ard_3-2-1_094074_2022-04-16_final.stac-item
2022-05-27 09:35:09	ga_ls9c_ard_3-2-1_093076_2022-05-27_final.stac-item
2022-06-20 10:25:13	ga_ls9c_ard_3-2-1_101077_2022-06-20_final.stac-item
2022-06-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2022-06-23_final.stac-item
2022-07-26 09:57:57	ga_ls9c_ard_3-2-1_097070_2022-07-26_final.stac-item
2022-07-31 10:21:21	ga_ls9c_ard_3-2-1_100082_2022-07-31_final.stac-item
2022-08-31 09:37:04	ga_ls9c_ard_3-2-1_093079_2022-08-31_final.stac-item
2022-10-02 09:36:00	ga_ls9c_ard_3-2-1_093076_2022-10-02_final.stac-item
2022-10-11 11:09:32	ga_ls9c_ard_3-2-1_108078_2022-10-11_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-22 10:48:16	ga_ls9c_ard_3-2-1_105071_2022-10-22_final.stac-item
2022-11-05 09:26:29	ga_ls9c_ard_3-2-1_091083_2022-11-04_final.stac-item
2022-11-07 09:16:56	ga_ls9c_ard_3-2-1_089090_2022-11-06_final.stac-item
2022-11-15 10:02:50	ga_ls9c_ard_3-2-1_097081_2022-11-15_final.stac-item
2022-11-22 10:04:13	ga_ls9c_ard_3-2-1_098069_2022-11-22_final.stac-item
2022-11-22 11:45:29	ga_ls9c_ard_3-2-1_114075_2022-11-22_final.stac-item
2022-11-30 09:20:42	ga_ls9c_ard_3-2-1_090084_2022-11-29_final.stac-item
2022-12-03 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-12-03_final.stac-item
2022-12-09 09:14:10	ga_ls9c_ard_3-2-1_089083_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
2022-12-11 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-12-11_final.stac-item
2022-12-21 11:17:20	ga_ls9c_ard_3-2-1_109082_2022-12-21_final.stac-item
2022-12-23 11:05:21	ga_ls9c_ard_3-2-1_107083_2022-12-23_final.stac-item
2022-12-31 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-31_final.stac-item
2023-01-04 09:46:28	ga_ls9c_ard_3-2-1_095071_2023-01-04_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-08 09:25:43	ga_ls9c_ard_3-2-1_091081_2023-01-07_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-10 10:48:15	ga_ls9c_ard_3-2-1_105071_2023-01-10_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 11:29:10	ga_ls9c_ard_3-2-1_111081_2023-01-20_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-01-27 09:57:47	ga_ls9c_ard_3-2-1_096084_2023-01-27_final.stac-item
2023-01-29 09:42:15	ga_ls9c_ard_3-2-1_094076_2023-01-29_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-02 10:56:27	ga_ls9c_ard_3-2-1_106076_2023-02-02_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-05 09:50:54	ga_ls9c_ard_3-2-1_095082_2023-02-05_final.stac-item
2023-02-05 11:29:47	ga_ls9c_ard_3-2-1_111082_2023-02-05_final.stac-item
2023-02-07 09:39:44	ga_ls9c_ard_3-2-1_093085_2023-02-07_final.stac-item
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final.stac-item
2023-04-21 11:11:23	ga_ls9c_ard_3-2-1_108084_2023-04-21_final.stac-item
2023-04-22 11:52:15	ga_ls9c_ard_3-2-1_115078_2023-04-22_final.stac-item
2023-04-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2023-04-23_final.stac-item
2023-04-23 10:58:13	ga_ls9c_ard_3-2-1_106082_2023-04-23_final.stac-item
2023-04-24 11:39:52	ga_ls9c_ard_3-2-1_113078_2023-04-24_final.stac-item
2023-04-27 10:30:39	ga_ls9c_ard_3-2-1_102075_2023-04-27_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_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 09:23:01	ga_ls9c_ard_3-2-1_091076_2023-04-29_final.stac-item
2023-04-30 09:25:25	ga_ls9c_ard_3-2-1_091082_2023-04-29_final.stac-item
2023-07-15 11:26:05	ga_ls9c_ard_3-2-1_111075_2023-07-15_final.stac-item
2023-07-17 11:16:31	ga_ls9c_ard_3-2-1_109082_2023-07-17_final.stac-item
2023-07-18 10:16:55	ga_ls9c_ard_3-2-1_100072_2023-07-18_final.stac-item
2023-07-18 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-07-18_final.stac-item
2023-07-18 10:19:42	ga_ls9c_ard_3-2-1_100079_2023-07-18_final.stac-item
2023-07-18 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-07-18_final.stac-item
2023-07-19 11:03:46	ga_ls9c_ard_3-2-1_107081_2023-07-19_final.stac-item
2023-07-21 09:14:30	ga_ls9c_ard_3-2-1_089086_2023-07-20_final.stac-item
2023-07-24 09:40:36	ga_ls9c_ard_3-2-1_094074_2023-07-24_final.stac-item
2023-07-24 11:18:17	ga_ls9c_ard_3-2-1_110071_2023-07-24_final.stac-item
2023-07-27 10:13:08	ga_ls9c_ard_3-2-1_099078_2023-07-27_final.stac-item
2023-07-29 09:57:37	ga_ls9c_ard_3-2-1_097070_2023-07-29_final.stac-item
2023-08-04 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-08-04_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-17 09:58:12	ga_ls9c_ard_3-2-1_097070_2023-10-17_final.stac-item
2023-10-24 10:03:59	ga_ls9c_ard_3-2-1_098069_2023-10-24_final.stac-item
2023-10-29 10:28:04	ga_ls9c_ard_3-2-1_101083_2023-10-29_final.stac-item
2023-10-30 09:29:38	ga_ls9c_ard_3-2-1_092076_2023-10-29_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 10:58:31	ga_ls9c_ard_3-2-1_106082_2023-11-01_final.stac-item
2023-11-03 10:40:56	ga_ls9c_ard_3-2-1_104069_2023-11-03_final.stac-item
2023-11-04 09:46:56	ga_ls9c_ard_3-2-1_095073_2023-11-04_final.stac-item
2023-11-04 09:47:20	ga_ls9c_ard_3-2-1_095074_2023-11-04_final.stac-item
2023-11-14 10:23:39	ga_ls9c_ard_3-2-1_101072_2023-11-14_final.stac-item
2023-11-14 10:28:03	ga_ls9c_ard_3-2-1_101083_2023-11-14_final.stac-item
2023-11-15 09:32:49	ga_ls9c_ard_3-2-1_092084_2023-11-15_final.stac-item
2023-11-16 10:15:17	ga_ls9c_ard_3-2-1_099082_2023-11-16_final.stac-item
2023-11-18 10:01:22	ga_ls9c_ard_3-2-1_097078_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 10:45:27	ga_ls9c_ard_3-2-1_104080_2023-11-19_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-21 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-11-21_final.stac-item
2023-11-21 10:29:55	ga_ls9c_ard_3-2-1_102072_2023-11-21_final.stac-item
2023-11-25 10:03:39	ga_ls9c_ard_3-2-1_098068_2023-11-25_final.stac-item
2023-11-26 09:14:25	ga_ls9c_ard_3-2-1_089084_2023-11-25_final.stac-item
2023-11-26 09:14:49	ga_ls9c_ard_3-2-1_089085_2023-11-25_final.stac-item
2023-11-26 10:47:19	ga_ls9c_ard_3-2-1_105069_2023-11-26_final.stac-item
2023-11-26 10:47:43	ga_ls9c_ard_3-2-1_105070_2023-11-26_final.stac-item
2023-11-26 10:48:55	ga_ls9c_ard_3-2-1_105073_2023-11-26_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