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
2021-11-20 11:23:05	ga_ls9c_ard_3-2-1_110077_2021-11-20_final.stac-item
2021-11-23 11:43:53	ga_ls9c_ard_3-2-1_114076_2021-11-23_final.stac-item
2021-12-07 09:52:58	ga_ls9c_ard_3-2-1_096072_2021-12-07_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2021-12-27 09:34:56	ga_ls9c_ard_3-2-1_092089_2021-12-27_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2022-01-07 10:48:04	ga_ls9c_ard_3-2-1_105071_2022-01-07_final.stac-item
2022-01-26 09:41:42	ga_ls9c_ard_3-2-1_094075_2022-01-26_final.stac-item
2022-01-27 10:25:21	ga_ls9c_ard_3-2-1_101076_2022-01-27_final.stac-item
2022-02-03 10:33:32	ga_ls9c_ard_3-2-1_102081_2022-02-03_final.stac-item
2022-02-12 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-02-12_final.stac-item
2022-02-14 11:52:37	ga_ls9c_ard_3-2-1_115078_2022-02-14_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-04-01 10:27:49	ga_ls9c_ard_3-2-1_101083_2022-04-01_final.stac-item
2022-04-02 09:33:00	ga_ls9c_ard_3-2-1_092085_2022-04-02_final.stac-item
2022-04-09 11:17:37	ga_ls9c_ard_3-2-1_109084_2022-04-09_final.stac-item
2022-04-11 09:27:34	ga_ls9c_ard_3-2-1_091087_2022-04-10_final.stac-item
2022-04-12 11:45:18	ga_ls9c_ard_3-2-1_114076_2022-04-12_final.stac-item
2022-04-21 10:01:19	ga_ls9c_ard_3-2-1_097079_2022-04-21_final.stac-item
2022-05-07 09:58:51	ga_ls9c_ard_3-2-1_097073_2022-05-07_final.stac-item
2022-05-14 11:45:02	ga_ls9c_ard_3-2-1_114076_2022-05-14_final.stac-item
2022-05-21 11:51:55	ga_ls9c_ard_3-2-1_115078_2022-05-21_final.stac-item
2022-05-23 10:01:04	ga_ls9c_ard_3-2-1_097079_2022-05-23_final.stac-item
2022-05-25 09:51:54	ga_ls9c_ard_3-2-1_095087_2022-05-25_final.stac-item
2022-05-25 11:29:11	ga_ls9c_ard_3-2-1_111083_2022-05-25_final.stac-item
2022-05-26 10:32:46	ga_ls9c_ard_3-2-1_102081_2022-05-26_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_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
2022-06-06 10:11:04	ga_ls9c_ard_3-2-1_099073_2022-06-06_final.stac-item
2022-06-10 09:45:57	ga_ls9c_ard_3-2-1_095072_2022-06-10_final.stac-item
2022-06-22 10:12:55	ga_ls9c_ard_3-2-1_099077_2022-06-22_final.stac-item
2022-06-23 09:20:07	ga_ls9c_ard_3-2-1_090084_2022-06-22_final.stac-item
2022-06-24 10:01:25	ga_ls9c_ard_3-2-1_097079_2022-06-24_final.stac-item
2022-06-28 09:35:07	ga_ls9c_ard_3-2-1_093075_2022-06-28_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-07 11:05:24	ga_ls9c_ard_3-2-1_108069_2022-07-07_final.stac-item
2022-07-08 11:52:15	ga_ls9c_ard_3-2-1_115078_2022-07-08_final.stac-item
2022-07-09 09:18:08	ga_ls9c_ard_3-2-1_090079_2022-07-08_final.stac-item
2022-07-10 10:01:23	ga_ls9c_ard_3-2-1_097079_2022-07-10_final.stac-item
2022-07-24 10:11:29	ga_ls9c_ard_3-2-1_099073_2022-07-24_final.stac-item
2022-07-25 09:18:16	ga_ls9c_ard_3-2-1_090079_2022-07-24_final.stac-item
2022-08-04 09:57:04	ga_ls9c_ard_3-2-1_096083_2022-08-04_final.stac-item
2022-09-03 10:05:11	ga_ls9c_ard_3-2-1_098072_2022-09-03_final.stac-item
2022-09-13 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-09-13_final.stac-item
2022-09-21 09:52:55	ga_ls9c_ard_3-2-1_096072_2022-09-21_final.stac-item
2022-10-05 11:45:46	ga_ls9c_ard_3-2-1_114076_2022-10-05_final.stac-item
2022-10-29 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-10-28_final.stac-item
2023-02-12 11:36:21	ga_ls9c_ard_3-2-1_112083_2023-02-12_final.stac-item
2023-02-25 09:28:20	ga_ls9c_ard_3-2-1_091088_2023-02-24_final.stac-item
2023-02-26 10:06:25	ga_ls9c_ard_3-2-1_098075_2023-02-26_final.stac-item
2023-03-15 09:14:40	ga_ls9c_ard_3-2-1_089085_2023-03-14_final.stac-item
2023-05-01 10:04:40	ga_ls9c_ard_3-2-1_098072_2023-05-01_final.stac-item
2023-05-08 11:51:15	ga_ls9c_ard_3-2-1_115076_2023-05-08_final.stac-item
2023-05-08 11:51:39	ga_ls9c_ard_3-2-1_115077_2023-05-08_final.stac-item
2023-05-09 09:18:45	ga_ls9c_ard_3-2-1_090081_2023-05-08_final.stac-item
2023-05-09 10:57:38	ga_ls9c_ard_3-2-1_106081_2023-05-09_final.stac-item
2023-05-10 09:56:25	ga_ls9c_ard_3-2-1_097067_2023-05-10_final.stac-item
2023-05-10 09:58:25	ga_ls9c_ard_3-2-1_097072_2023-05-10_final.stac-item
2023-05-12 11:24:08	ga_ls9c_ard_3-2-1_111070_2023-05-12_final.stac-item
2023-05-14 09:34:28	ga_ls9c_ard_3-2-1_093074_2023-05-14_final.stac-item
2023-05-14 09:39:39	ga_ls9c_ard_3-2-1_093087_2023-05-14_final.stac-item
2023-05-18 09:14:29	ga_ls9c_ard_3-2-1_089086_2023-05-17_final.stac-item
2023-05-18 10:45:47	ga_ls9c_ard_3-2-1_105067_2023-05-18_final.stac-item
2023-05-18 10:46:11	ga_ls9c_ard_3-2-1_105068_2023-05-18_final.stac-item
2023-05-19 11:35:01	ga_ls9c_ard_3-2-1_112082_2023-05-19_final.stac-item
2023-07-10 09:28:38	ga_ls9c_ard_3-2-1_092075_2023-07-09_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-09-04 10:17:16	ga_ls9c_ard_3-2-1_100072_2023-09-04_final.stac-item
2023-09-05 09:26:27	ga_ls9c_ard_3-2-1_091084_2023-09-04_final.stac-item
2023-09-06 10:04:56	ga_ls9c_ard_3-2-1_098072_2023-09-06_final.stac-item
2023-09-06 11:46:13	ga_ls9c_ard_3-2-1_114078_2023-09-06_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-09-07 09:16:07	ga_ls9c_ard_3-2-1_089089_2023-09-06_final.stac-item
2023-09-07 10:46:13	ga_ls9c_ard_3-2-1_105067_2023-09-07_final.stac-item
2023-09-08 09:52:36	ga_ls9c_ard_3-2-1_096072_2023-09-08_final.stac-item
2023-09-10 11:19:09	ga_ls9c_ard_3-2-1_110072_2023-09-10_final.stac-item
2023-09-11 10:23:32	ga_ls9c_ard_3-2-1_101072_2023-09-11_final.stac-item
2023-09-12 11:06:01	ga_ls9c_ard_3-2-1_108070_2023-09-12_final.stac-item
2023-09-13 10:11:12	ga_ls9c_ard_3-2-1_099072_2023-09-13_final.stac-item
2023-09-13 11:52:28	ga_ls9c_ard_3-2-1_115078_2023-09-13_final.stac-item
2023-09-14 10:56:03	ga_ls9c_ard_3-2-1_106076_2023-09-14_final.stac-item
2023-09-15 09:58:51	ga_ls9c_ard_3-2-1_097072_2023-09-15_final.stac-item
2023-09-17 11:30:09	ga_ls9c_ard_3-2-1_111084_2023-09-17_final.stac-item
2023-09-18 10:28:33	ga_ls9c_ard_3-2-1_102069_2023-09-18_final.stac-item
2023-09-19 11:12:36	ga_ls9c_ard_3-2-1_109071_2023-09-19_final.stac-item
2023-09-21 09:26:08	ga_ls9c_ard_3-2-1_091083_2023-09-20_final.stac-item
2023-09-21 10:59:50	ga_ls9c_ard_3-2-1_107070_2023-09-21_final.stac-item
2023-09-22 10:07:00	ga_ls9c_ard_3-2-1_098077_2023-09-22_final.stac-item
2023-09-22 10:07:48	ga_ls9c_ard_3-2-1_098079_2023-09-22_final.stac-item
2023-09-22 11:46:41	ga_ls9c_ard_3-2-1_114079_2023-09-22_final.stac-item
2023-09-23 09:13:22	ga_ls9c_ard_3-2-1_089082_2023-09-22_final.stac-item
2023-09-26 11:23:55	ga_ls9c_ard_3-2-1_110084_2023-09-26_final.stac-item
2023-09-29 10:12:44	ga_ls9c_ard_3-2-1_099076_2023-09-29_final.stac-item
2023-09-30 09:18:20	ga_ls9c_ard_3-2-1_090079_2023-09-29_final.stac-item
2023-10-05 09:34:57	ga_ls9c_ard_3-2-1_093074_2023-10-05_final.stac-item
2023-10-07 09:23:48	ga_ls9c_ard_3-2-1_091077_2023-10-06_final.stac-item
2023-10-07 09:28:12	ga_ls9c_ard_3-2-1_091088_2023-10-06_final.stac-item
2023-10-08 10:05:52	ga_ls9c_ard_3-2-1_098074_2023-10-08_final.stac-item
2023-10-08 11:46:21	ga_ls9c_ard_3-2-1_114078_2023-10-08_final.stac-item
2023-10-10 11:35:13	ga_ls9c_ard_3-2-1_112081_2023-10-10_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