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
2021-11-10 11:16:57	ga_ls9c_ard_3-2-1_110074_2021-11-10_final.stac-item
2021-12-08 10:37:49	ga_ls9c_ard_3-2-1_103076_2021-12-08_final.stac-item
2021-12-13 10:56:41	ga_ls9c_ard_3-2-1_106077_2021-12-13_final.stac-item
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2021-12-31 10:41:31	ga_ls9c_ard_3-2-1_104070_2021-12-31_final.stac-item
2022-02-13 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-02-13_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-03-06 09:47:38	ga_ls9c_ard_3-2-1_095075_2022-03-06_final.stac-item
2022-04-02 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-04-02_final.stac-item
2022-04-06 10:41:57	ga_ls9c_ard_3-2-1_104072_2022-04-06_final.stac-item
2022-05-02 09:40:45	ga_ls9c_ard_3-2-1_094074_2022-05-02_final.stac-item
2022-05-22 10:54:18	ga_ls9c_ard_3-2-1_106073_2022-05-22_final.stac-item
2022-05-30 10:04:52	ga_ls9c_ard_3-2-1_098073_2022-05-30_final.stac-item
2022-06-23 09:19:43	ga_ls9c_ard_3-2-1_090083_2022-06-22_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-07-23 09:29:00	ga_ls9c_ard_3-2-1_092075_2022-07-22_final.stac-item
2022-08-06 11:22:49	ga_ls9c_ard_3-2-1_110081_2022-08-06_final.stac-item
2022-08-26 10:55:01	ga_ls9c_ard_3-2-1_106073_2022-08-26_final.stac-item
2022-09-18 11:01:41	ga_ls9c_ard_3-2-1_107074_2022-09-18_final.stac-item
2022-10-07 09:53:44	ga_ls9c_ard_3-2-1_096074_2022-10-07_final.stac-item
2022-10-31 10:44:51	ga_ls9c_ard_3-2-1_104078_2022-10-31_final.stac-item
2022-11-05 11:04:34	ga_ls9c_ard_3-2-1_107081_2022-11-05_final.stac-item
2022-11-08 11:33:06	ga_ls9c_ard_3-2-1_112075_2022-11-08_final.stac-item
2022-11-21 11:04:37	ga_ls9c_ard_3-2-1_107081_2022-11-21_final.stac-item
2022-12-07 11:02:12	ga_ls9c_ard_3-2-1_107075_2022-12-07_final.stac-item
2022-12-09 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-12-09_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-20 10:32:29	ga_ls9c_ard_3-2-1_102078_2022-12-20_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2023-01-18 09:59:54	ga_ls9c_ard_3-2-1_097074_2023-01-18_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-01-28 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-28_final.stac-item
2023-01-29 11:24:20	ga_ls9c_ard_3-2-1_110084_2023-01-29_final.stac-item
2023-01-31 09:34:42	ga_ls9c_ard_3-2-1_092088_2023-01-31_final.stac-item
2023-01-31 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-01-31_final.stac-item
2023-02-02 10:57:15	ga_ls9c_ard_3-2-1_106078_2023-02-02_final.stac-item
2023-02-05 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-06 10:30:10	ga_ls9c_ard_3-2-1_102072_2023-02-06_final.stac-item
2023-04-23 10:53:49	ga_ls9c_ard_3-2-1_106071_2023-04-23_final.stac-item
2023-04-24 11:40:16	ga_ls9c_ard_3-2-1_113079_2023-04-24_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-04-26 11:25:53	ga_ls9c_ard_3-2-1_111074_2023-04-26_final.stac-item
2023-04-26 11:29:29	ga_ls9c_ard_3-2-1_111083_2023-04-26_final.stac-item
2023-04-29 10:21:03	ga_ls9c_ard_3-2-1_100082_2023-04-29_final.stac-item
2023-04-30 10:59:54	ga_ls9c_ard_3-2-1_107071_2023-04-30_final.stac-item
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-28 10:54:25	ga_ls9c_ard_3-2-1_106073_2023-07-28_final.stac-item
2023-07-29 09:58:25	ga_ls9c_ard_3-2-1_097072_2023-07-29_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-08-02 11:11:27	ga_ls9c_ard_3-2-1_109069_2023-08-02_final.stac-item
2023-08-03 10:21:25	ga_ls9c_ard_3-2-1_100083_2023-08-03_final.stac-item
2023-08-05 11:44:22	ga_ls9c_ard_3-2-1_114074_2023-08-05_final.stac-item
2023-10-14 11:05:46	ga_ls9c_ard_3-2-1_108069_2023-10-14_final.stac-item
2023-10-14 11:11:21	ga_ls9c_ard_3-2-1_108083_2023-10-14_final.stac-item
2023-10-16 10:57:49	ga_ls9c_ard_3-2-1_106080_2023-10-16_final.stac-item
2023-10-17 09:59:48	ga_ls9c_ard_3-2-1_097074_2023-10-17_final.stac-item
2023-10-17 10:01:24	ga_ls9c_ard_3-2-1_097078_2023-10-17_final.stac-item
2023-10-18 10:41:28	ga_ls9c_ard_3-2-1_104070_2023-10-18_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-19 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-10-19_final.stac-item
2023-10-21 09:33:54	ga_ls9c_ard_3-2-1_093071_2023-10-21_final.stac-item
2023-10-21 09:35:05	ga_ls9c_ard_3-2-1_093074_2023-10-21_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-21 11:13:11	ga_ls9c_ard_3-2-1_109072_2023-10-21_final.stac-item
2023-10-22 10:17:57	ga_ls9c_ard_3-2-1_100073_2023-10-22_final.stac-item
2023-10-24 10:05:35	ga_ls9c_ard_3-2-1_098073_2023-10-24_final.stac-item
2023-10-24 10:06:47	ga_ls9c_ard_3-2-1_098076_2023-10-24_final.stac-item
2023-10-25 10:48:26	ga_ls9c_ard_3-2-1_105072_2023-10-25_final.stac-item
2023-10-26 09:53:12	ga_ls9c_ard_3-2-1_096073_2023-10-26_final.stac-item
2023-10-28 09:46:25	ga_ls9c_ard_3-2-1_094087_2023-10-28_final.stac-item
2023-10-28 11:21:42	ga_ls9c_ard_3-2-1_110078_2023-10-28_final.stac-item
2023-10-28 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-10-29 10:24:52	ga_ls9c_ard_3-2-1_101075_2023-10-29_final.stac-item
2023-10-29 10:26:04	ga_ls9c_ard_3-2-1_101078_2023-10-29_final.stac-item
2023-11-01 09:18:27	ga_ls9c_ard_3-2-1_090079_2023-10-31_final.stac-item
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final.stac-item
2023-11-02 10:02:05	ga_ls9c_ard_3-2-1_097080_2023-11-02_final.stac-item
2023-11-02 11:39:46	ga_ls9c_ard_3-2-1_113077_2023-11-02_final.stac-item
2023-11-03 10:43:20	ga_ls9c_ard_3-2-1_104075_2023-11-03_final.stac-item
2023-11-03 10:44:08	ga_ls9c_ard_3-2-1_104077_2023-11-03_final.stac-item
2023-11-05 10:30:36	ga_ls9c_ard_3-2-1_102074_2023-11-05_final.stac-item
2023-11-05 10:31:24	ga_ls9c_ard_3-2-1_102076_2023-11-05_final.stac-item
2023-11-14 10:24:51	ga_ls9c_ard_3-2-1_101075_2023-11-14_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-17 10:55:46	ga_ls9c_ard_3-2-1_106075_2023-11-17_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-18 10:01:46	ga_ls9c_ard_3-2-1_097079_2023-11-18_final.stac-item
2023-11-18 11:39:27	ga_ls9c_ard_3-2-1_113076_2023-11-18_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-20 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-11-20_final.stac-item
2023-11-20 11:27:07	ga_ls9c_ard_3-2-1_111076_2023-11-20_final.stac-item
2023-11-23 10:20:23	ga_ls9c_ard_3-2-1_100079_2023-11-23_final.stac-item
2023-11-23 10:21:35	ga_ls9c_ard_3-2-1_100082_2023-11-23_final.stac-item
2023-11-24 09:28:22	ga_ls9c_ard_3-2-1_091088_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