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 09:23:08	ga_ls9c_ard_3-2-1_091083_2021-11-11_final.stac-item
2021-11-13 09:59:07	ga_ls9c_ard_3-2-1_097073_2021-11-13_final.stac-item
2021-11-13 11:41:21	ga_ls9c_ard_3-2-1_113082_2021-11-13_final.stac-item
2021-12-19 10:18:47	ga_ls9c_ard_3-2-1_100075_2021-12-19_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2021-12-28 10:14:36	ga_ls9c_ard_3-2-1_099080_2021-12-28_final.stac-item
2021-12-29 09:19:23	ga_ls9c_ard_3-2-1_090081_2021-12-28_final.stac-item
2021-12-29 09:21:47	ga_ls9c_ard_3-2-1_090087_2021-12-28_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-03 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-01-03_final.stac-item
2022-01-07 10:49:40	ga_ls9c_ard_3-2-1_105075_2022-01-07_final.stac-item
2022-01-08 11:31:44	ga_ls9c_ard_3-2-1_112072_2022-01-08_final.stac-item
2022-01-14 09:17:44	ga_ls9c_ard_3-2-1_090077_2022-01-13_final.stac-item
2022-01-15 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-01-15_final.stac-item
2022-01-19 11:13:35	ga_ls9c_ard_3-2-1_109073_2022-01-19_final.stac-item
2022-01-29 10:13:24	ga_ls9c_ard_3-2-1_099077_2022-01-29_final.stac-item
2022-02-09 09:58:01	ga_ls9c_ard_3-2-1_096085_2022-02-09_final.stac-item
2022-02-22 09:23:24	ga_ls9c_ard_3-2-1_091076_2022-02-21_final.stac-item
2022-02-22 10:59:53	ga_ls9c_ard_3-2-1_107070_2022-02-22_final.stac-item
2022-03-02 11:52:01	ga_ls9c_ard_3-2-1_115077_2022-03-02_final.stac-item
2022-03-05 09:07:09	ga_ls9c_ard_3-2-1_088082_2022-03-04_final.stac-item
2022-03-05 10:42:27	ga_ls9c_ard_3-2-1_104073_2022-03-05_final.stac-item
2022-03-31 11:23:03	ga_ls9c_ard_3-2-1_110082_2022-03-31_final.stac-item
2022-04-02 11:06:18	ga_ls9c_ard_3-2-1_108071_2022-04-02_final.stac-item
2022-04-20 10:57:45	ga_ls9c_ard_3-2-1_106081_2022-04-20_final.stac-item
2022-05-24 10:41:56	ga_ls9c_ard_3-2-1_104073_2022-05-24_final.stac-item
2022-05-25 09:45:55	ga_ls9c_ard_3-2-1_095072_2022-05-25_final.stac-item
2022-05-27 09:33:09	ga_ls9c_ard_3-2-1_093071_2022-05-27_final.stac-item
2022-05-28 11:58:06	ga_ls9c_ard_3-2-1_116078_2022-05-28_final.stac-item
2022-05-29 09:23:12	ga_ls9c_ard_3-2-1_091077_2022-05-28_final.stac-item
2022-05-29 09:27:59	ga_ls9c_ard_3-2-1_091089_2022-05-28_final.stac-item
2022-05-30 10:09:39	ga_ls9c_ard_3-2-1_098085_2022-05-30_final.stac-item
2022-06-09 09:06:16	ga_ls9c_ard_3-2-1_088081_2022-06-08_final.stac-item
2022-06-16 09:11:45	ga_ls9c_ard_3-2-1_089079_2022-06-15_final.stac-item
2022-06-16 10:52:14	ga_ls9c_ard_3-2-1_105083_2022-06-16_final.stac-item
2022-06-26 09:46:41	ga_ls9c_ard_3-2-1_095073_2022-06-26_final.stac-item
2022-07-17 10:07:34	ga_ls9c_ard_3-2-1_098079_2022-07-17_final.stac-item
2022-07-30 09:40:04	ga_ls9c_ard_3-2-1_093087_2022-07-30_final.stac-item
2022-07-30 11:13:22	ga_ls9c_ard_3-2-1_109073_2022-07-30_final.stac-item
2022-08-03 10:50:17	ga_ls9c_ard_3-2-1_105077_2022-08-03_final.stac-item
2022-08-04 11:35:10	ga_ls9c_ard_3-2-1_112081_2022-08-04_final.stac-item
2022-08-08 09:33:59	ga_ls9c_ard_3-2-1_092087_2022-08-08_final.stac-item
2022-08-11 11:38:37	ga_ls9c_ard_3-2-1_113074_2022-08-11_final.stac-item
2022-08-17 09:25:05	ga_ls9c_ard_3-2-1_091080_2022-08-16_final.stac-item
2022-08-28 09:06:58	ga_ls9c_ard_3-2-1_088081_2022-08-27_final.stac-item
2022-09-09 09:34:52	ga_ls9c_ard_3-2-1_092089_2022-09-09_final.stac-item
2022-09-18 09:28:23	ga_ls9c_ard_3-2-1_091088_2022-09-17_final.stac-item
2022-09-19 10:08:27	ga_ls9c_ard_3-2-1_098080_2022-09-19_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-10-03 11:58:09	ga_ls9c_ard_3-2-1_116076_2022-10-03_final.stac-item
2022-10-06 10:52:08	ga_ls9c_ard_3-2-1_105081_2022-10-06_final.stac-item
2022-10-12 10:11:08	ga_ls9c_ard_3-2-1_099071_2022-10-12_final.stac-item
2022-10-20 09:29:19	ga_ls9c_ard_3-2-1_091090_2022-10-19_final.stac-item
2022-10-25 11:20:46	ga_ls9c_ard_3-2-1_110075_2022-10-25_final.stac-item
2022-10-29 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-10-28_final.stac-item
2022-10-30 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-10-30_final.stac-item
2022-11-01 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-11-01_final.stac-item
2022-11-13 11:52:52	ga_ls9c_ard_3-2-1_115078_2022-11-13_final.stac-item
2022-11-21 09:28:32	ga_ls9c_ard_3-2-1_091088_2022-11-20_final.stac-item
2022-11-28 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-11-28_final.stac-item
2022-11-29 10:10:21	ga_ls9c_ard_3-2-1_099069_2022-11-29_final.stac-item
2022-12-03 09:48:01	ga_ls9c_ard_3-2-1_095075_2022-12-03_final.stac-item
2022-12-07 11:01:48	ga_ls9c_ard_3-2-1_107074_2022-12-07_final.stac-item
2022-12-09 10:49:27	ga_ls9c_ard_3-2-1_105074_2022-12-09_final.stac-item
2022-12-11 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-12-11_final.stac-item
2022-12-14 11:06:24	ga_ls9c_ard_3-2-1_108070_2022-12-14_final.stac-item
2022-12-21 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-12-21_final.stac-item
2022-12-21 09:40:27	ga_ls9c_ard_3-2-1_093087_2022-12-21_final.stac-item
2022-12-23 09:22:52	ga_ls9c_ard_3-2-1_091074_2022-12-22_final.stac-item
2022-12-23 11:02:33	ga_ls9c_ard_3-2-1_107076_2022-12-23_final.stac-item
2022-12-24 10:04:08	ga_ls9c_ard_3-2-1_098069_2022-12-24_final.stac-item
2022-12-24 10:10:07	ga_ls9c_ard_3-2-1_098084_2022-12-24_final.stac-item
2022-12-25 09:14:07	ga_ls9c_ard_3-2-1_089083_2022-12-24_final.stac-item
2023-01-06 09:39:41	ga_ls9c_ard_3-2-1_093085_2023-01-06_final.stac-item
2023-01-25 10:10:30	ga_ls9c_ard_3-2-1_098085_2023-01-25_final.stac-item
2023-02-09 11:01:29	ga_ls9c_ard_3-2-1_107073_2023-02-09_final.stac-item
2023-02-10 10:04:39	ga_ls9c_ard_3-2-1_098070_2023-02-10_final.stac-item
2023-03-18 09:40:46	ga_ls9c_ard_3-2-1_094073_2023-03-18_final.stac-item
2023-03-29 09:23:38	ga_ls9c_ard_3-2-1_091077_2023-03-28_final.stac-item
2023-04-03 11:20:40	ga_ls9c_ard_3-2-1_110076_2023-04-03_final.stac-item
2023-04-09 10:42:21	ga_ls9c_ard_3-2-1_104073_2023-04-09_final.stac-item
2023-04-14 11:04:48	ga_ls9c_ard_3-2-1_107083_2023-04-14_final.stac-item
2023-04-26 11:23:54	ga_ls9c_ard_3-2-1_111069_2023-04-26_final.stac-item
2023-04-26 11:24:18	ga_ls9c_ard_3-2-1_111070_2023-04-26_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-26 09:57:50	ga_ls9c_ard_3-2-1_097071_2023-05-26_final.stac-item
2023-05-26 10:01:02	ga_ls9c_ard_3-2-1_097079_2023-05-26_final.stac-item
2023-06-01 09:21:33	ga_ls9c_ard_3-2-1_091073_2023-05-31_final.stac-item
2023-06-08 11:06:58	ga_ls9c_ard_3-2-1_108074_2023-06-08_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-11 09:57:21	ga_ls9c_ard_3-2-1_097070_2023-06-11_final.stac-item
2023-07-01 09:39:30	ga_ls9c_ard_3-2-1_093087_2023-07-01_final.stac-item
2023-07-20 10:03:21	ga_ls9c_ard_3-2-1_098069_2023-07-20_final.stac-item
2023-07-27 10:08:45	ga_ls9c_ard_3-2-1_099067_2023-07-27_final.stac-item
2023-08-11 11:11:18	ga_ls9c_ard_3-2-1_108084_2023-08-11_final.stac-item
2023-10-25 09:16:20	ga_ls9c_ard_3-2-1_089089_2023-10-24_final.stac-item
2023-11-04 11:28:37	ga_ls9c_ard_3-2-1_111080_2023-11-04_final.stac-item
2023-11-05 10:30:13	ga_ls9c_ard_3-2-1_102073_2023-11-05_final.stac-item
2023-11-16 11:51:47	ga_ls9c_ard_3-2-1_115076_2023-11-16_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_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