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
2021-11-03 09:52:58	ga_ls9c_ard_3-2-1_096070_2021-11-03_final.stac-item
2021-11-03 09:55:45	ga_ls9c_ard_3-2-1_096077_2021-11-03_final.stac-item
2021-11-07 10:59:20	ga_ls9c_ard_3-2-1_106083_2021-11-07_final.stac-item
2021-11-09 10:40:11	ga_ls9c_ard_3-2-1_103082_2021-11-09_final.stac-item
2021-11-18 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-11-19 09:06:51	ga_ls9c_ard_3-2-1_088083_2021-11-18_final.stac-item
2021-11-20 09:42:01	ga_ls9c_ard_3-2-1_094071_2021-11-20_final.stac-item
2021-11-23 10:02:50	ga_ls9c_ard_3-2-1_098070_2021-11-23_final.stac-item
2021-11-24 10:47:34	ga_ls9c_ard_3-2-1_104082_2021-11-24_final.stac-item
2021-12-05 10:04:33	ga_ls9c_ard_3-2-1_098070_2021-12-05_final.stac-item
2021-12-06 10:48:12	ga_ls9c_ard_3-2-1_105071_2021-12-06_final.stac-item
2021-12-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2021-12-08_final.stac-item
2021-12-12 10:16:14	ga_ls9c_ard_3-2-1_099084_2021-12-12_final.stac-item
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_final.stac-item
2021-12-19 10:19:35	ga_ls9c_ard_3-2-1_100077_2021-12-19_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2021-12-30 10:03:50	ga_ls9c_ard_3-2-1_097084_2021-12-30_final.stac-item
2021-12-31 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-31_final.stac-item
2022-01-02 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-01-02_final.stac-item
2022-01-06 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-06_final.stac-item
2022-01-07 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-07_final.stac-item
2022-01-12 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-01-12_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-01-23 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-23_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-01-24 09:54:51	ga_ls9c_ard_3-2-1_096077_2022-01-24_final.stac-item
2022-01-29 10:15:47	ga_ls9c_ard_3-2-1_099083_2022-01-29_final.stac-item
2022-01-30 10:59:03	ga_ls9c_ard_3-2-1_106083_2022-01-30_final.stac-item
2022-02-01 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-02-01_final.stac-item
2022-02-07 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-02-07_final.stac-item
2022-02-08 10:50:03	ga_ls9c_ard_3-2-1_105076_2022-02-08_final.stac-item
2022-02-11 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-02-11_final.stac-item
2022-02-13 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-02-13_final.stac-item
2022-02-14 10:16:07	ga_ls9c_ard_3-2-1_099084_2022-02-14_final.stac-item
2022-02-17 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-02-17 10:46:12	ga_ls9c_ard_3-2-1_104082_2022-02-17_final.stac-item
2022-02-23 11:45:32	ga_ls9c_ard_3-2-1_114076_2022-02-23_final.stac-item
2022-03-01 09:33:05	ga_ls9c_ard_3-2-1_092085_2022-03-01_final.stac-item
2022-03-04 10:03:34	ga_ls9c_ard_3-2-1_097084_2022-03-04_final.stac-item
2022-03-06 09:51:37	ga_ls9c_ard_3-2-1_095085_2022-03-06_final.stac-item
2022-03-08 11:14:57	ga_ls9c_ard_3-2-1_109077_2022-03-08_final.stac-item
2022-03-11 11:45:27	ga_ls9c_ard_3-2-1_114076_2022-03-11_final.stac-item
2022-03-20 10:03:33	ga_ls9c_ard_3-2-1_097084_2022-03-20_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-03-23 10:31:14	ga_ls9c_ard_3-2-1_102076_2022-03-23_final.stac-item
2022-03-28 10:49:45	ga_ls9c_ard_3-2-1_105076_2022-03-28_final.stac-item
2022-03-31 09:39:46	ga_ls9c_ard_3-2-1_094071_2022-03-31_final.stac-item
2022-04-14 09:51:39	ga_ls9c_ard_3-2-1_096070_2022-04-14_final.stac-item
2022-04-16 11:23:44	ga_ls9c_ard_3-2-1_110084_2022-04-16_final.stac-item
2022-04-23 09:51:21	ga_ls9c_ard_3-2-1_095085_2022-04-23_final.stac-item
2022-04-24 10:31:01	ga_ls9c_ard_3-2-1_102076_2022-04-24_final.stac-item
2022-04-30 09:51:32	ga_ls9c_ard_3-2-1_096070_2022-04-30_final.stac-item
2022-04-30 09:54:19	ga_ls9c_ard_3-2-1_096077_2022-04-30_final.stac-item
2022-05-06 10:58:29	ga_ls9c_ard_3-2-1_106083_2022-05-06_final.stac-item
2022-05-07 10:03:15	ga_ls9c_ard_3-2-1_097084_2022-05-07_final.stac-item
2022-05-14 10:03:45	ga_ls9c_ard_3-2-1_098070_2022-05-14_final.stac-item
2022-05-16 09:51:22	ga_ls9c_ard_3-2-1_096070_2022-05-16_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-18 09:39:22	ga_ls9c_ard_3-2-1_094071_2022-05-18_final.stac-item
2022-05-18 11:23:26	ga_ls9c_ard_3-2-1_110084_2022-05-18_final.stac-item
2022-05-24 10:45:31	ga_ls9c_ard_3-2-1_104082_2022-05-24_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-30 11:44:57	ga_ls9c_ard_3-2-1_114076_2022-05-30_final.stac-item
2022-05-31 10:49:19	ga_ls9c_ard_3-2-1_105076_2022-05-31_final.stac-item
2022-06-02 10:39:22	ga_ls9c_ard_3-2-1_103082_2022-06-02_final.stac-item
2022-06-03 09:39:21	ga_ls9c_ard_3-2-1_094071_2022-06-03_final.stac-item
2022-06-03 11:23:26	ga_ls9c_ard_3-2-1_110084_2022-06-03_final.stac-item
2022-06-07 10:58:19	ga_ls9c_ard_3-2-1_106083_2022-06-07_final.stac-item
2022-06-13 10:18:53	ga_ls9c_ard_3-2-1_100077_2022-06-13_final.stac-item
2022-06-14 10:59:22	ga_ls9c_ard_3-2-1_107070_2022-06-14_final.stac-item
2022-06-15 10:03:46	ga_ls9c_ard_3-2-1_098070_2022-06-15_final.stac-item
2022-06-15 11:45:03	ga_ls9c_ard_3-2-1_114076_2022-06-15_final.stac-item
2022-06-19 11:23:35	ga_ls9c_ard_3-2-1_110084_2022-06-19_final.stac-item
2022-06-22 10:15:43	ga_ls9c_ard_3-2-1_099084_2022-06-22_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-28 11:14:48	ga_ls9c_ard_3-2-1_109077_2022-06-28_final.stac-item
2022-06-29 11:58:04	ga_ls9c_ard_3-2-1_116077_2022-06-29_final.stac-item
2022-07-02 10:47:41	ga_ls9c_ard_3-2-1_105071_2022-07-02_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-07-17 11:45:16	ga_ls9c_ard_3-2-1_114076_2022-07-17_final.stac-item
2022-07-18 10:49:39	ga_ls9c_ard_3-2-1_105076_2022-07-18_final.stac-item
2022-07-21 09:41:44	ga_ls9c_ard_3-2-1_094076_2022-07-21_final.stac-item
2022-07-25 09:20:16	ga_ls9c_ard_3-2-1_090084_2022-07-24_final.stac-item
2022-07-25 10:58:45	ga_ls9c_ard_3-2-1_106083_2022-07-25_final.stac-item
2022-08-05 10:39:57	ga_ls9c_ard_3-2-1_103082_2022-08-05_final.stac-item
2022-08-10 10:58:56	ga_ls9c_ard_3-2-1_106083_2022-08-10_final.stac-item
2022-08-11 09:56:56	ga_ls9c_ard_3-2-1_097067_2022-08-11_final.stac-item
2022-08-14 10:31:27	ga_ls9c_ard_3-2-1_102076_2022-08-14_final.stac-item
2022-08-15 11:11:56	ga_ls9c_ard_3-2-1_109069_2022-08-15_final.stac-item
2022-08-18 11:45:38	ga_ls9c_ard_3-2-1_114076_2022-08-18_final.stac-item
2022-08-21 10:40:03	ga_ls9c_ard_3-2-1_103082_2022-08-21_final.stac-item
2022-08-24 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-08-24_final.stac-item
2022-08-27 09:57:00	ga_ls9c_ard_3-2-1_097067_2022-08-27_final.stac-item
2022-08-29 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-08-29_final.stac-item
2022-09-03 11:45:39	ga_ls9c_ard_3-2-1_114076_2022-09-03_final.stac-item
2022-09-19 11:45:45	ga_ls9c_ard_3-2-1_114076_2022-09-19_final.stac-item
2022-09-25 09:33:24	ga_ls9c_ard_3-2-1_092085_2022-09-25_final.stac-item
2022-09-25 11:11:53	ga_ls9c_ard_3-2-1_108084_2022-09-25_final.stac-item
2022-09-29 09:07:30	ga_ls9c_ard_3-2-1_088082_2022-09-28_final.stac-item
2022-09-29 10:41:11	ga_ls9c_ard_3-2-1_104069_2022-09-29_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