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
2021-11-11 10:19:51	ga_ls9c_ard_3-2-1_100078_2021-11-11_final.stac-item
2021-11-17 09:23:16	ga_ls9c_ard_3-2-1_091077_2021-11-16_final.stac-item
2021-11-20 11:19:54	ga_ls9c_ard_3-2-1_110069_2021-11-20_final.stac-item
2021-12-05 10:05:21	ga_ls9c_ard_3-2-1_098072_2021-12-05_final.stac-item
2021-12-12 11:52:20	ga_ls9c_ard_3-2-1_115077_2021-12-12_final.stac-item
2021-12-16 11:26:45	ga_ls9c_ard_3-2-1_111075_2021-12-16_final.stac-item
2022-01-02 10:31:56	ga_ls9c_ard_3-2-1_102077_2022-01-02_final.stac-item
2022-01-03 11:12:48	ga_ls9c_ard_3-2-1_109071_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
2022-01-13 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-01-13_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-02-20 11:14:16	ga_ls9c_ard_3-2-1_109075_2022-02-20_final.stac-item
2022-03-02 11:51:37	ga_ls9c_ard_3-2-1_115076_2022-03-02_final.stac-item
2022-03-03 09:18:19	ga_ls9c_ard_3-2-1_090079_2022-03-02_final.stac-item
2022-03-26 09:23:14	ga_ls9c_ard_3-2-1_091076_2022-03-25_final.stac-item
2022-04-12 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-04-12_final.stac-item
2022-04-21 10:00:55	ga_ls9c_ard_3-2-1_097078_2022-04-21_final.stac-item
2022-04-22 10:42:10	ga_ls9c_ard_3-2-1_104073_2022-04-22_final.stac-item
2022-04-29 10:49:33	ga_ls9c_ard_3-2-1_105076_2022-04-29_final.stac-item
2022-05-05 11:51:19	ga_ls9c_ard_3-2-1_115076_2022-05-05_final.stac-item
2022-05-07 10:00:51	ga_ls9c_ard_3-2-1_097078_2022-05-07_final.stac-item
2022-05-20 09:32:09	ga_ls9c_ard_3-2-1_092084_2022-05-20_final.stac-item
2022-05-22 10:55:06	ga_ls9c_ard_3-2-1_106075_2022-05-22_final.stac-item
2022-05-23 09:56:17	ga_ls9c_ard_3-2-1_097067_2022-05-23_final.stac-item
2022-05-29 09:27:35	ga_ls9c_ard_3-2-1_091088_2022-05-28_final.stac-item
2022-06-01 09:51:19	ga_ls9c_ard_3-2-1_096070_2022-06-01_final.stac-item
2022-06-05 09:29:00	ga_ls9c_ard_3-2-1_092076_2022-06-04_final.stac-item
2022-06-07 09:18:38	ga_ls9c_ard_3-2-1_090081_2022-06-06_final.stac-item
2022-06-07 09:20:14	ga_ls9c_ard_3-2-1_090085_2022-06-06_final.stac-item
2022-06-07 10:52:20	ga_ls9c_ard_3-2-1_106068_2022-06-07_final.stac-item
2022-06-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2022-06-23_final.stac-item
2022-07-08 10:10:58	ga_ls9c_ard_3-2-1_099072_2022-07-08_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-07-19 11:35:44	ga_ls9c_ard_3-2-1_112083_2022-07-19_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-18 11:46:50	ga_ls9c_ard_3-2-1_114079_2022-08-18_final.stac-item
2022-08-22 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-08-22_final.stac-item
2022-08-25 10:12:57	ga_ls9c_ard_3-2-1_099076_2022-08-25_final.stac-item
2022-08-29 09:48:14	ga_ls9c_ard_3-2-1_095076_2022-08-29_final.stac-item
2022-08-29 11:29:55	ga_ls9c_ard_3-2-1_111083_2022-08-29_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-16 11:17:37	ga_ls9c_ard_3-2-1_109083_2022-09-16_final.stac-item
2022-09-19 11:46:57	ga_ls9c_ard_3-2-1_114079_2022-09-19_final.stac-item
2022-09-20 09:12:51	ga_ls9c_ard_3-2-1_089080_2022-09-19_final.stac-item
2022-09-21 09:53:43	ga_ls9c_ard_3-2-1_096074_2022-09-21_final.stac-item
2022-10-23 09:52:39	ga_ls9c_ard_3-2-1_096071_2022-10-23_final.stac-item
2022-10-27 11:07:12	ga_ls9c_ard_3-2-1_108072_2022-10-27_final.stac-item
2022-10-29 10:59:13	ga_ls9c_ard_3-2-1_106083_2022-10-29_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-11-03_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-15 09:58:02	ga_ls9c_ard_3-2-1_097069_2022-11-15_final.stac-item
2022-11-15 11:42:31	ga_ls9c_ard_3-2-1_113083_2022-11-15_final.stac-item
2022-11-19 09:34:31	ga_ls9c_ard_3-2-1_093072_2022-11-19_final.stac-item
2022-11-21 09:28:32	ga_ls9c_ard_3-2-1_091088_2022-11-20_final.stac-item
2022-11-29 11:52:02	ga_ls9c_ard_3-2-1_115076_2022-11-29_final.stac-item
2022-12-07 09:25:19	ga_ls9c_ard_3-2-1_091080_2022-12-06_final.stac-item
2022-12-15 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-15_final.stac-item
2022-12-20 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-20_final.stac-item
2023-01-04 09:46:28	ga_ls9c_ard_3-2-1_095071_2023-01-04_final.stac-item
2023-01-09 10:05:23	ga_ls9c_ard_3-2-1_098072_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 11:52:22	ga_ls9c_ard_3-2-1_115077_2023-01-16_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-01-18 11:39:11	ga_ls9c_ard_3-2-1_113075_2023-01-18_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-24 09:22:50	ga_ls9c_ard_3-2-1_091074_2023-01-23_final.stac-item
2023-01-24 11:00:07	ga_ls9c_ard_3-2-1_107070_2023-01-24_final.stac-item
2023-01-28 10:38:15	ga_ls9c_ard_3-2-1_103077_2023-01-28_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-16 11:07:59	ga_ls9c_ard_3-2-1_108074_2023-02-16_final.stac-item
2023-03-09 09:47:21	ga_ls9c_ard_3-2-1_095074_2023-03-09_final.stac-item
2023-03-11 11:12:16	ga_ls9c_ard_3-2-1_109070_2023-03-11_final.stac-item
2023-03-13 09:22:14	ga_ls9c_ard_3-2-1_091073_2023-03-12_final.stac-item
2023-03-25 09:46:51	ga_ls9c_ard_3-2-1_095073_2023-03-25_final.stac-item
2023-04-06 10:15:04	ga_ls9c_ard_3-2-1_099082_2023-04-06_final.stac-item
2023-04-14 09:27:55	ga_ls9c_ard_3-2-1_091088_2023-04-13_final.stac-item
2023-05-14 09:39:15	ga_ls9c_ard_3-2-1_093086_2023-05-14_final.stac-item
2023-05-18 09:11:42	ga_ls9c_ard_3-2-1_089079_2023-05-17_final.stac-item
2023-05-28 11:23:58	ga_ls9c_ard_3-2-1_111070_2023-05-28_final.stac-item
2023-05-29 10:29:32	ga_ls9c_ard_3-2-1_102073_2023-05-29_final.stac-item
2023-06-08 09:31:16	ga_ls9c_ard_3-2-1_092082_2023-06-08_final.stac-item
2023-07-13 09:57:58	ga_ls9c_ard_3-2-1_097071_2023-07-13_final.stac-item
2023-07-14 10:42:25	ga_ls9c_ard_3-2-1_104074_2023-07-14_final.stac-item
2023-07-19 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-07-19_final.stac-item
2023-08-04 09:27:00	ga_ls9c_ard_3-2-1_091086_2023-08-03_final.stac-item
2023-08-05 10:04:17	ga_ls9c_ard_3-2-1_098071_2023-08-05_final.stac-item
2023-08-07 09:51:57	ga_ls9c_ard_3-2-1_096071_2023-08-07_final.stac-item
2023-08-15 10:40:12	ga_ls9c_ard_3-2-1_104068_2023-08-15_final.stac-item
2023-10-21 09:34:18	ga_ls9c_ard_3-2-1_093072_2023-10-21_final.stac-item
2023-10-21 11:12:23	ga_ls9c_ard_3-2-1_109070_2023-10-21_final.stac-item
2023-10-21 11:12:47	ga_ls9c_ard_3-2-1_109071_2023-10-21_final.stac-item
2023-10-23 11:00:49	ga_ls9c_ard_3-2-1_107072_2023-10-23_final.stac-item
2023-10-31 11:51:22	ga_ls9c_ard_3-2-1_115075_2023-10-31_final.stac-item
2023-11-03 10:43:20	ga_ls9c_ard_3-2-1_104075_2023-11-03_final.stac-item
2023-11-17 10:53:23	ga_ls9c_ard_3-2-1_106069_2023-11-17_final.stac-item
2023-11-24 09:29:10	ga_ls9c_ard_3-2-1_091090_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