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
2021-11-02 10:54:27	ga_ls9c_ard_3-2-1_106077_2021-11-02_final.stac-item
2021-11-16 10:21:31	ga_ls9c_ard_3-2-1_100076_2021-11-16_final.stac-item
2021-12-06 10:47:48	ga_ls9c_ard_3-2-1_105070_2021-12-06_final.stac-item
2021-12-11 11:08:41	ga_ls9c_ard_3-2-1_108076_2021-12-11_final.stac-item
2021-12-12 10:15:02	ga_ls9c_ard_3-2-1_099081_2021-12-12_final.stac-item
2021-12-16 09:47:52	ga_ls9c_ard_3-2-1_095075_2021-12-16_final.stac-item
2022-01-01 11:30:22	ga_ls9c_ard_3-2-1_111084_2022-01-01_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-03-05 10:42:27	ga_ls9c_ard_3-2-1_104073_2022-03-05_final.stac-item
2022-03-08 09:40:27	ga_ls9c_ard_3-2-1_093088_2022-03-08_final.stac-item
2022-03-10 09:28:06	ga_ls9c_ard_3-2-1_091088_2022-03-09_final.stac-item
2022-03-11 10:10:10	ga_ls9c_ard_3-2-1_098085_2022-03-11_final.stac-item
2022-03-20 11:41:14	ga_ls9c_ard_3-2-1_113081_2022-03-20_final.stac-item
2022-03-21 10:42:25	ga_ls9c_ard_3-2-1_104073_2022-03-21_final.stac-item
2022-03-28 10:47:21	ga_ls9c_ard_3-2-1_105070_2022-03-28_final.stac-item
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final.stac-item
2022-03-31 09:40:58	ga_ls9c_ard_3-2-1_094074_2022-03-31_final.stac-item
2022-04-02 11:05:54	ga_ls9c_ard_3-2-1_108070_2022-04-02_final.stac-item
2022-04-06 09:07:04	ga_ls9c_ard_3-2-1_088082_2022-04-05_final.stac-item
2022-04-11 09:26:22	ga_ls9c_ard_3-2-1_091084_2022-04-10_final.stac-item
2022-05-02 09:40:45	ga_ls9c_ard_3-2-1_094074_2022-05-02_final.stac-item
2022-05-04 11:05:16	ga_ls9c_ard_3-2-1_108069_2022-05-04_final.stac-item
2022-05-19 10:24:12	ga_ls9c_ard_3-2-1_101075_2022-05-19_final.stac-item
2022-05-29 10:59:41	ga_ls9c_ard_3-2-1_107071_2022-05-29_final.stac-item
2022-06-07 09:18:38	ga_ls9c_ard_3-2-1_090081_2022-06-06_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-15 10:07:45	ga_ls9c_ard_3-2-1_098080_2022-06-15_final.stac-item
2022-06-26 11:29:34	ga_ls9c_ard_3-2-1_111083_2022-06-26_final.stac-item
2022-07-08 10:10:58	ga_ls9c_ard_3-2-1_099072_2022-07-08_final.stac-item
2022-08-07 10:23:13	ga_ls9c_ard_3-2-1_101071_2022-08-07_final.stac-item
2022-08-24 09:29:41	ga_ls9c_ard_3-2-1_092076_2022-08-23_final.stac-item
2022-09-04 10:48:50	ga_ls9c_ard_3-2-1_105073_2022-09-04_final.stac-item
2022-09-28 09:58:20	ga_ls9c_ard_3-2-1_097070_2022-09-28_final.stac-item
2022-09-30 11:26:27	ga_ls9c_ard_3-2-1_111074_2022-09-30_final.stac-item
2022-10-02 09:35:36	ga_ls9c_ard_3-2-1_093075_2022-10-02_final.stac-item
2022-10-07 09:52:08	ga_ls9c_ard_3-2-1_096070_2022-10-07_final.stac-item
2022-10-13 09:19:07	ga_ls9c_ard_3-2-1_090080_2022-10-12_final.stac-item
2022-10-18 09:37:17	ga_ls9c_ard_3-2-1_093079_2022-10-18_final.stac-item
2022-10-18 11:12:35	ga_ls9c_ard_3-2-1_109070_2022-10-18_final.stac-item
2022-10-28 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-10-28_final.stac-item
2022-11-04 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-11-04_final.stac-item
2022-11-15 10:04:01	ga_ls9c_ard_3-2-1_097084_2022-11-15_final.stac-item
2022-11-21 11:03:50	ga_ls9c_ard_3-2-1_107079_2022-11-21_final.stac-item
2022-11-23 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-11-23_final.stac-item
2022-11-24 09:57:26	ga_ls9c_ard_3-2-1_096083_2022-11-24_final.stac-item
2022-11-27 10:25:55	ga_ls9c_ard_3-2-1_101077_2022-11-27_final.stac-item
2022-11-29 11:52:26	ga_ls9c_ard_3-2-1_115077_2022-11-29_final.stac-item
2022-12-05 11:15:21	ga_ls9c_ard_3-2-1_109077_2022-12-05_final.stac-item
2022-12-14 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-14_final.stac-item
2022-12-15 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-12-15_final.stac-item
2022-12-17 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-12-17_final.stac-item
2022-12-18 10:42:52	ga_ls9c_ard_3-2-1_104073_2022-12-18_final.stac-item
2022-12-21 09:38:51	ga_ls9c_ard_3-2-1_093083_2022-12-21_final.stac-item
2022-12-22 10:18:30	ga_ls9c_ard_3-2-1_100074_2022-12-22_final.stac-item
2022-12-24 10:08:08	ga_ls9c_ard_3-2-1_098079_2022-12-24_final.stac-item
2022-12-24 11:45:01	ga_ls9c_ard_3-2-1_114074_2022-12-24_final.stac-item
2022-12-28 09:46:38	ga_ls9c_ard_3-2-1_094087_2022-12-28_final.stac-item
2022-12-31 10:16:45	ga_ls9c_ard_3-2-1_099085_2022-12-31_final.stac-item
2023-01-06 09:36:30	ga_ls9c_ard_3-2-1_093077_2023-01-06_final.stac-item
2023-01-07 10:22:33	ga_ls9c_ard_3-2-1_100084_2023-01-07_final.stac-item
2023-01-09 11:46:40	ga_ls9c_ard_3-2-1_114078_2023-01-09_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-01-19 10:41:56	ga_ls9c_ard_3-2-1_104071_2023-01-19_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-07 09:37:21	ga_ls9c_ard_3-2-1_093079_2023-02-07_final.stac-item
2023-02-14 11:24:22	ga_ls9c_ard_3-2-1_110084_2023-02-14_final.stac-item
2023-03-06 10:54:59	ga_ls9c_ard_3-2-1_106073_2023-03-06_final.stac-item
2023-03-06 10:58:35	ga_ls9c_ard_3-2-1_106082_2023-03-06_final.stac-item
2023-03-07 10:01:21	ga_ls9c_ard_3-2-1_097078_2023-03-07_final.stac-item
2023-03-07 10:01:45	ga_ls9c_ard_3-2-1_097079_2023-03-07_final.stac-item
2023-03-14 11:45:35	ga_ls9c_ard_3-2-1_114076_2023-03-14_final.stac-item
2023-05-03 11:35:08	ga_ls9c_ard_3-2-1_112082_2023-05-03_final.stac-item
2023-05-09 10:52:50	ga_ls9c_ard_3-2-1_106069_2023-05-09_final.stac-item
2023-05-13 10:30:30	ga_ls9c_ard_3-2-1_102075_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
2023-05-19 11:35:01	ga_ls9c_ard_3-2-1_112082_2023-05-19_final.stac-item
2023-05-20 10:33:48	ga_ls9c_ard_3-2-1_103068_2023-05-20_final.stac-item
2023-05-21 11:22:38	ga_ls9c_ard_3-2-1_110082_2023-05-21_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-06-02 10:07:36	ga_ls9c_ard_3-2-1_098080_2023-06-02_final.stac-item
2023-06-04 09:51:38	ga_ls9c_ard_3-2-1_096071_2023-06-04_final.stac-item
2023-06-18 10:07:28	ga_ls9c_ard_3-2-1_098080_2023-06-18_final.stac-item
2023-06-18 10:09:27	ga_ls9c_ard_3-2-1_098085_2023-06-18_final.stac-item
2023-06-19 10:45:32	ga_ls9c_ard_3-2-1_105067_2023-06-19_final.stac-item
2023-06-19 10:46:20	ga_ls9c_ard_3-2-1_105069_2023-06-19_final.stac-item
2023-07-19 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-07-19_final.stac-item
2023-07-21 10:51:24	ga_ls9c_ard_3-2-1_105081_2023-07-21_final.stac-item
2023-07-28 10:54:49	ga_ls9c_ard_3-2-1_106074_2023-07-28_final.stac-item
2023-08-06 09:13:52	ga_ls9c_ard_3-2-1_089084_2023-08-05_final.stac-item
2023-08-09 09:45:35	ga_ls9c_ard_3-2-1_094086_2023-08-09_final.stac-item
2023-08-13 10:58:09	ga_ls9c_ard_3-2-1_106082_2023-08-13_final.stac-item
2023-10-15 10:11:21	ga_ls9c_ard_3-2-1_099072_2023-10-15_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-10-20 10:33:30	ga_ls9c_ard_3-2-1_102081_2023-10-20_final.stac-item
2023-10-23 09:27:07	ga_ls9c_ard_3-2-1_091085_2023-10-22_final.stac-item
2023-10-28 09:44:25	ga_ls9c_ard_3-2-1_094082_2023-10-28_final.stac-item
2023-11-03 10:41:20	ga_ls9c_ard_3-2-1_104070_2023-11-03_final.stac-item
2023-11-20 09:47:50	ga_ls9c_ard_3-2-1_095075_2023-11-20_final.stac-item
2023-11-23 10:21:35	ga_ls9c_ard_3-2-1_100082_2023-11-23_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