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
2021-10-31 11:10:24	ga_ls9c_ard_3-2-1_109070_2021-10-31_final.stac-item
2021-11-10 09:40:17	ga_ls9c_ard_3-2-1_094079_2021-11-10_final.stac-item
2021-11-14 10:40:16	ga_ls9c_ard_3-2-1_103076_2021-11-14_final.stac-item
2021-12-25 11:20:12	ga_ls9c_ard_3-2-1_110074_2021-12-25_final.stac-item
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-20 10:17:34	ga_ls9c_ard_3-2-1_100072_2022-01-20_final.stac-item
2022-02-03 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-02-03_final.stac-item
2022-02-19 10:32:37	ga_ls9c_ard_3-2-1_102079_2022-02-19_final.stac-item
2022-02-24 10:52:18	ga_ls9c_ard_3-2-1_105082_2022-02-24_final.stac-item
2022-03-24 09:36:48	ga_ls9c_ard_3-2-1_093079_2022-03-24_final.stac-item
2022-04-02 09:29:48	ga_ls9c_ard_3-2-1_092077_2022-04-01_final.stac-item
2022-04-03 10:10:16	ga_ls9c_ard_3-2-1_099070_2022-04-03_final.stac-item
2022-04-04 09:22:38	ga_ls9c_ard_3-2-1_090090_2022-04-03_final.stac-item
2022-04-22 10:44:58	ga_ls9c_ard_3-2-1_104080_2022-04-22_final.stac-item
2022-05-30 10:07:39	ga_ls9c_ard_3-2-1_098080_2022-05-30_final.stac-item
2022-06-16 10:45:51	ga_ls9c_ard_3-2-1_105067_2022-06-16_final.stac-item
2022-06-20 10:25:13	ga_ls9c_ard_3-2-1_101077_2022-06-20_final.stac-item
2022-06-29 10:21:34	ga_ls9c_ard_3-2-1_100083_2022-06-29_final.stac-item
2022-09-25 09:34:36	ga_ls9c_ard_3-2-1_092088_2022-09-25_final.stac-item
2022-10-03 10:19:15	ga_ls9c_ard_3-2-1_100076_2022-10-03_final.stac-item
2022-10-12 10:11:08	ga_ls9c_ard_3-2-1_099071_2022-10-12_final.stac-item
2022-10-15 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-14_final.stac-item
2022-10-19 11:58:38	ga_ls9c_ard_3-2-1_116077_2022-10-19_final.stac-item
2022-10-21 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-10-21_final.stac-item
2022-10-28 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-10-28_final.stac-item
2022-10-30 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-10-30_final.stac-item
2022-11-03 09:37:14	ga_ls9c_ard_3-2-1_093079_2022-11-03_final.stac-item
2022-11-12 09:30:43	ga_ls9c_ard_3-2-1_092078_2022-11-12_final.stac-item
2022-11-13 10:11:12	ga_ls9c_ard_3-2-1_099071_2022-11-13_final.stac-item
2022-11-15 10:04:25	ga_ls9c_ard_3-2-1_097085_2022-11-15_final.stac-item
2022-11-16 10:46:05	ga_ls9c_ard_3-2-1_104081_2022-11-16_final.stac-item
2022-11-20 10:18:10	ga_ls9c_ard_3-2-1_100073_2022-11-20_final.stac-item
2022-11-21 09:24:57	ga_ls9c_ard_3-2-1_091079_2022-11-20_final.stac-item
2022-11-22 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-11-22_final.stac-item
2022-11-23 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-11-22_final.stac-item
2022-11-28 09:30:17	ga_ls9c_ard_3-2-1_092077_2022-11-28_final.stac-item
2022-12-03 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-12-03_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-08 11:45:04	ga_ls9c_ard_3-2-1_114074_2022-12-08_final.stac-item
2022-12-16 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-12-16_final.stac-item
2022-12-19 11:27:43	ga_ls9c_ard_3-2-1_111077_2022-12-19_final.stac-item
2022-12-24 10:04:32	ga_ls9c_ard_3-2-1_098070_2022-12-24_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_2022-12-28_final.stac-item
2023-01-09 11:46:40	ga_ls9c_ard_3-2-1_114078_2023-01-09_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_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
2023-01-16 10:11:30	ga_ls9c_ard_3-2-1_099072_2023-01-16_final.stac-item
2023-01-16 10:12:41	ga_ls9c_ard_3-2-1_099075_2023-01-16_final.stac-item
2023-01-18 11:39:34	ga_ls9c_ard_3-2-1_113076_2023-01-18_final.stac-item
2023-01-18 11:39:58	ga_ls9c_ard_3-2-1_113077_2023-01-18_final.stac-item
2023-01-23 10:19:14	ga_ls9c_ard_3-2-1_100076_2023-01-23_final.stac-item
2023-01-25 11:46:36	ga_ls9c_ard_3-2-1_114078_2023-01-25_final.stac-item
2023-01-28 10:36:16	ga_ls9c_ard_3-2-1_103072_2023-01-28_final.stac-item
2023-01-29 09:42:39	ga_ls9c_ard_3-2-1_094077_2023-01-29_final.stac-item
2023-02-04 10:43:19	ga_ls9c_ard_3-2-1_104074_2023-02-04_final.stac-item
2023-02-05 11:27:47	ga_ls9c_ard_3-2-1_111077_2023-02-05_final.stac-item
2023-02-07 09:37:21	ga_ls9c_ard_3-2-1_093079_2023-02-07_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-03-03 10:25:43	ga_ls9c_ard_3-2-1_101077_2023-03-03_final.stac-item
2023-03-03 10:28:07	ga_ls9c_ard_3-2-1_101083_2023-03-03_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-04-26 11:26:41	ga_ls9c_ard_3-2-1_111076_2023-04-26_final.stac-item
2023-04-26 11:28:17	ga_ls9c_ard_3-2-1_111080_2023-04-26_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-04-30 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-04-29_final.stac-item
2023-05-01 11:46:20	ga_ls9c_ard_3-2-1_114079_2023-05-01_final.stac-item
2023-05-05 11:20:45	ga_ls9c_ard_3-2-1_110077_2023-05-05_final.stac-item
2023-05-06 10:22:20	ga_ls9c_ard_3-2-1_101070_2023-05-06_final.stac-item
2023-05-12 11:26:31	ga_ls9c_ard_3-2-1_111076_2023-05-12_final.stac-item
2023-06-29 11:26:18	ga_ls9c_ard_3-2-1_111076_2023-06-29_final.stac-item
2023-07-02 11:58:04	ga_ls9c_ard_3-2-1_116078_2023-07-02_final.stac-item
2023-07-15 11:26:29	ga_ls9c_ard_3-2-1_111076_2023-07-15_final.stac-item
2023-07-16 10:30:52	ga_ls9c_ard_3-2-1_102076_2023-07-16_final.stac-item
2023-07-16 10:31:16	ga_ls9c_ard_3-2-1_102077_2023-07-16_final.stac-item
2023-07-18 10:18:30	ga_ls9c_ard_3-2-1_100076_2023-07-18_final.stac-item
2023-07-18 10:21:18	ga_ls9c_ard_3-2-1_100083_2023-07-18_final.stac-item
2023-07-20 11:44:14	ga_ls9c_ard_3-2-1_114074_2023-07-20_final.stac-item
2023-07-24 11:20:41	ga_ls9c_ard_3-2-1_110077_2023-07-24_final.stac-item
2023-07-26 11:07:32	ga_ls9c_ard_3-2-1_108075_2023-07-26_final.stac-item
2023-07-26 11:09:32	ga_ls9c_ard_3-2-1_108080_2023-07-26_final.stac-item
2023-08-02 11:14:14	ga_ls9c_ard_3-2-1_109076_2023-08-02_final.stac-item
2023-08-05 11:45:34	ga_ls9c_ard_3-2-1_114077_2023-08-05_final.stac-item
2023-10-16 10:58:37	ga_ls9c_ard_3-2-1_106082_2023-10-16_final.stac-item
2023-10-29 10:27:40	ga_ls9c_ard_3-2-1_101082_2023-10-29_final.stac-item
2023-11-01 09:19:38	ga_ls9c_ard_3-2-1_090082_2023-10-31_final.stac-item
2023-11-02 11:39:46	ga_ls9c_ard_3-2-1_113077_2023-11-02_final.stac-item
2023-11-05 10:31:48	ga_ls9c_ard_3-2-1_102077_2023-11-05_final.stac-item
2023-11-05 10:32:36	ga_ls9c_ard_3-2-1_102079_2023-11-05_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-16 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-11-16_final.stac-item
2023-11-18 10:02:10	ga_ls9c_ard_3-2-1_097080_2023-11-18_final.stac-item
2023-11-18 10:04:10	ga_ls9c_ard_3-2-1_097085_2023-11-18_final.stac-item
2023-11-19 10:45:50	ga_ls9c_ard_3-2-1_104081_2023-11-19_final.stac-item
2023-11-20 11:27:31	ga_ls9c_ard_3-2-1_111077_2023-11-20_final.stac-item
2023-11-25 10:10:02	ga_ls9c_ard_3-2-1_098084_2023-11-25_final.stac-item
2023-11-25 11:44:56	ga_ls9c_ard_3-2-1_114074_2023-11-25_final.stac-item
2023-11-25 11:46:08	ga_ls9c_ard_3-2-1_114077_2023-11-25_final.stac-item
2023-11-26 10:49:19	ga_ls9c_ard_3-2-1_105074_2023-11-26_final.stac-item
2023-11-27 11:34:10	ga_ls9c_ard_3-2-1_112078_2023-11-27_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