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
2021-11-22 11:07:07	ga_ls9c_ard_3-2-1_107084_2021-11-22_final.stac-item
2021-12-27 09:30:33	ga_ls9c_ard_3-2-1_092078_2021-12-27_final.stac-item
2022-01-12 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-01-12_final.stac-item
2022-01-14 09:18:31	ga_ls9c_ard_3-2-1_090079_2022-01-13_final.stac-item
2022-01-30 09:18:34	ga_ls9c_ard_3-2-1_090079_2022-01-29_final.stac-item
2022-02-07 10:04:00	ga_ls9c_ard_3-2-1_098069_2022-02-07_final.stac-item
2022-02-22 11:03:53	ga_ls9c_ard_3-2-1_107080_2022-02-22_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-04 10:01:35	ga_ls9c_ard_3-2-1_097079_2022-03-04_final.stac-item
2022-05-05 11:52:07	ga_ls9c_ard_3-2-1_115078_2022-05-05_final.stac-item
2022-05-14 10:04:33	ga_ls9c_ard_3-2-1_098072_2022-05-14_final.stac-item
2022-05-16 09:54:09	ga_ls9c_ard_3-2-1_096077_2022-05-16_final.stac-item
2022-06-08 09:58:42	ga_ls9c_ard_3-2-1_097073_2022-06-08_final.stac-item
2022-06-08 10:03:05	ga_ls9c_ard_3-2-1_097084_2022-06-08_final.stac-item
2022-06-14 11:03:22	ga_ls9c_ard_3-2-1_107080_2022-06-14_final.stac-item
2022-06-28 11:16:48	ga_ls9c_ard_3-2-1_109082_2022-06-28_final.stac-item
2022-07-05 11:18:34	ga_ls9c_ard_3-2-1_110071_2022-07-05_final.stac-item
2022-07-09 10:53:02	ga_ls9c_ard_3-2-1_106069_2022-07-09_final.stac-item
2022-07-16 11:03:34	ga_ls9c_ard_3-2-1_107080_2022-07-16_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-07-23 09:27:48	ga_ls9c_ard_3-2-1_092072_2022-07-22_final.stac-item
2022-08-05 10:39:57	ga_ls9c_ard_3-2-1_103082_2022-08-05_final.stac-item
2022-08-20 09:52:00	ga_ls9c_ard_3-2-1_096070_2022-08-20_final.stac-item
2022-08-20 11:31:41	ga_ls9c_ard_3-2-1_112072_2022-08-20_final.stac-item
2022-08-29 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-08-29_final.stac-item
2022-09-01 10:22:20	ga_ls9c_ard_3-2-1_100084_2022-09-01_final.stac-item
2022-09-02 11:04:00	ga_ls9c_ard_3-2-1_107080_2022-09-02_final.stac-item
2022-09-20 10:48:08	ga_ls9c_ard_3-2-1_105071_2022-09-20_final.stac-item
2022-09-28 10:01:55	ga_ls9c_ard_3-2-1_097079_2022-09-28_final.stac-item
2022-09-28 11:42:24	ga_ls9c_ard_3-2-1_113083_2022-09-28_final.stac-item
2022-09-29 10:41:35	ga_ls9c_ard_3-2-1_104070_2022-09-29_final.stac-item
2022-10-01 10:29:38	ga_ls9c_ard_3-2-1_102071_2022-10-01_final.stac-item
2022-10-06 10:48:33	ga_ls9c_ard_3-2-1_105072_2022-10-06_final.stac-item
2022-10-13 10:54:48	ga_ls9c_ard_3-2-1_106072_2022-10-13_final.stac-item
2022-10-20 11:05:25	ga_ls9c_ard_3-2-1_107083_2022-10-20_final.stac-item
2022-11-05 11:00:59	ga_ls9c_ard_3-2-1_107072_2022-11-05_final.stac-item
2022-11-05 11:05:46	ga_ls9c_ard_3-2-1_107084_2022-11-05_final.stac-item
2022-11-28 09:31:29	ga_ls9c_ard_3-2-1_092080_2022-11-28_final.stac-item
2023-02-21 09:51:32	ga_ls9c_ard_3-2-1_095084_2023-02-21_final.stac-item
2023-02-25 11:04:25	ga_ls9c_ard_3-2-1_107081_2023-02-25_final.stac-item
2023-03-10 10:30:59	ga_ls9c_ard_3-2-1_102075_2023-03-10_final.stac-item
2023-05-02 10:45:55	ga_ls9c_ard_3-2-1_105067_2023-05-02_final.stac-item
2023-05-05 09:45:03	ga_ls9c_ard_3-2-1_094085_2023-05-05_final.stac-item
2023-05-05 11:17:33	ga_ls9c_ard_3-2-1_110069_2023-05-05_final.stac-item
2023-05-06 10:22:44	ga_ls9c_ard_3-2-1_101071_2023-05-06_final.stac-item
2023-05-07 09:29:07	ga_ls9c_ard_3-2-1_092076_2023-05-06_final.stac-item
2023-05-08 11:51:15	ga_ls9c_ard_3-2-1_115076_2023-05-08_final.stac-item
2023-05-09 10:53:38	ga_ls9c_ard_3-2-1_106071_2023-05-09_final.stac-item
2023-05-10 11:38:30	ga_ls9c_ard_3-2-1_113075_2023-05-10_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-12 11:26:31	ga_ls9c_ard_3-2-1_111076_2023-05-12_final.stac-item
2023-05-13 10:28:30	ga_ls9c_ard_3-2-1_102070_2023-05-13_final.stac-item
2023-05-13 10:33:17	ga_ls9c_ard_3-2-1_102082_2023-05-13_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-16 09:24:53	ga_ls9c_ard_3-2-1_091081_2023-05-15_final.stac-item
2023-05-16 11:00:58	ga_ls9c_ard_3-2-1_107074_2023-05-16_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-05-17 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-05-17_final.stac-item
2023-05-18 10:48:11	ga_ls9c_ard_3-2-1_105073_2023-05-18_final.stac-item
2023-05-19 11:35:49	ga_ls9c_ard_3-2-1_112084_2023-05-19_final.stac-item
2023-05-21 09:40:33	ga_ls9c_ard_3-2-1_094074_2023-05-21_final.stac-item
2023-05-23 09:28:34	ga_ls9c_ard_3-2-1_092075_2023-05-22_final.stac-item
2023-07-08 11:21:52	ga_ls9c_ard_3-2-1_110080_2023-07-08_final.stac-item
2023-07-10 11:06:19	ga_ls9c_ard_3-2-1_108072_2023-07-10_final.stac-item
2023-09-04 10:17:16	ga_ls9c_ard_3-2-1_100072_2023-09-04_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-06 10:09:20	ga_ls9c_ard_3-2-1_098083_2023-09-06_final.stac-item
2023-09-08 09:57:48	ga_ls9c_ard_3-2-1_096085_2023-09-08_final.stac-item
2023-09-08 11:36:17	ga_ls9c_ard_3-2-1_112084_2023-09-08_final.stac-item
2023-09-10 09:45:03	ga_ls9c_ard_3-2-1_094084_2023-09-10_final.stac-item
2023-09-10 11:20:45	ga_ls9c_ard_3-2-1_110076_2023-09-10_final.stac-item
2023-09-11 10:23:56	ga_ls9c_ard_3-2-1_101073_2023-09-11_final.stac-item
2023-09-13 11:51:17	ga_ls9c_ard_3-2-1_115075_2023-09-13_final.stac-item
2023-09-17 09:47:17	ga_ls9c_ard_3-2-1_095074_2023-09-17_final.stac-item
2023-09-18 10:33:44	ga_ls9c_ard_3-2-1_102082_2023-09-18_final.stac-item
2023-09-19 11:13:24	ga_ls9c_ard_3-2-1_109073_2023-09-19_final.stac-item
2023-09-20 10:20:10	ga_ls9c_ard_3-2-1_100079_2023-09-20_final.stac-item
2023-09-20 10:21:22	ga_ls9c_ard_3-2-1_100082_2023-09-20_final.stac-item
2023-09-21 09:25:21	ga_ls9c_ard_3-2-1_091081_2023-09-20_final.stac-item
2023-09-21 11:02:14	ga_ls9c_ard_3-2-1_107076_2023-09-21_final.stac-item
2023-09-21 11:03:50	ga_ls9c_ard_3-2-1_107080_2023-09-21_final.stac-item
2023-09-22 10:08:12	ga_ls9c_ard_3-2-1_098080_2023-09-22_final.stac-item
2023-09-23 09:13:46	ga_ls9c_ard_3-2-1_089083_2023-09-22_final.stac-item
2023-09-23 10:48:39	ga_ls9c_ard_3-2-1_105073_2023-09-23_final.stac-item
2023-09-25 10:36:17	ga_ls9c_ard_3-2-1_103073_2023-09-25_final.stac-item
2023-09-26 11:18:43	ga_ls9c_ard_3-2-1_110071_2023-09-26_final.stac-item
2023-09-28 09:29:27	ga_ls9c_ard_3-2-1_092076_2023-09-27_final.stac-item
2023-09-28 11:11:32	ga_ls9c_ard_3-2-1_108084_2023-09-28_final.stac-item
2023-09-29 10:14:20	ga_ls9c_ard_3-2-1_099080_2023-09-29_final.stac-item
2023-10-05 11:17:02	ga_ls9c_ard_3-2-1_109082_2023-10-05_final.stac-item
2023-10-07 09:26:12	ga_ls9c_ard_3-2-1_091083_2023-10-06_final.stac-item
2023-10-07 09:27:24	ga_ls9c_ard_3-2-1_091086_2023-10-06_final.stac-item
2023-10-07 11:05:29	ga_ls9c_ard_3-2-1_107084_2023-10-07_final.stac-item
2023-10-08 10:03:05	ga_ls9c_ard_3-2-1_098067_2023-10-08_final.stac-item
2023-10-08 10:08:16	ga_ls9c_ard_3-2-1_098080_2023-10-08_final.stac-item
2023-10-10 09:53:08	ga_ls9c_ard_3-2-1_096073_2023-10-10_final.stac-item
2023-10-10 11:35:37	ga_ls9c_ard_3-2-1_112082_2023-10-10_final.stac-item
2023-10-11 10:34:50	ga_ls9c_ard_3-2-1_103069_2023-10-11_final.stac-item
2023-10-12 11:23:41	ga_ls9c_ard_3-2-1_110083_2023-10-12_final.stac-item
2023-10-13 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-13_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years