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
2021-11-07 09:17:29	ga_ls9c_ard_3-2-1_090075_2021-11-06_final.stac-item
2021-11-07 09:18:16	ga_ls9c_ard_3-2-1_090077_2021-11-06_final.stac-item
2021-11-12 10:58:37	ga_ls9c_ard_3-2-1_106075_2021-11-12_final.stac-item
2021-12-22 09:13:12	ga_ls9c_ard_3-2-1_089081_2021-12-21_final.stac-item
2022-01-19 09:39:29	ga_ls9c_ard_3-2-1_093085_2022-01-19_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-02-02 11:23:58	ga_ls9c_ard_3-2-1_111068_2022-02-02_final.stac-item
2022-02-03 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-02-03_final.stac-item
2022-02-11 09:46:27	ga_ls9c_ard_3-2-1_094087_2022-02-11_final.stac-item
2022-04-02 09:31:00	ga_ls9c_ard_3-2-1_092080_2022-04-02_final.stac-item
2022-04-03 10:10:16	ga_ls9c_ard_3-2-1_099070_2022-04-03_final.stac-item
2022-04-03 11:51:57	ga_ls9c_ard_3-2-1_115077_2022-04-03_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-05-09 11:24:57	ga_ls9c_ard_3-2-1_111072_2022-05-09_final.stac-item
2022-05-13 11:02:11	ga_ls9c_ard_3-2-1_107077_2022-05-13_final.stac-item
2022-05-20 11:05:27	ga_ls9c_ard_3-2-1_108070_2022-05-20_final.stac-item
2022-05-29 09:21:12	ga_ls9c_ard_3-2-1_091072_2022-05-28_final.stac-item
2022-05-29 09:26:47	ga_ls9c_ard_3-2-1_091086_2022-05-28_final.stac-item
2022-06-07 10:57:55	ga_ls9c_ard_3-2-1_106082_2022-06-07_final.stac-item
2022-06-30 11:05:14	ga_ls9c_ard_3-2-1_107084_2022-06-30_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-11 09:06:09	ga_ls9c_ard_3-2-1_088080_2022-07-10_final.stac-item
2022-07-12 09:52:12	ga_ls9c_ard_3-2-1_095087_2022-07-12_final.stac-item
2022-07-19 09:58:03	ga_ls9c_ard_3-2-1_096086_2022-07-19_final.stac-item
2022-07-23 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-07-22_final.stac-item
2022-08-08 11:11:41	ga_ls9c_ard_3-2-1_108084_2022-08-08_final.stac-item
2022-08-17 09:27:29	ga_ls9c_ard_3-2-1_091086_2022-08-16_final.stac-item
2022-08-20 09:57:59	ga_ls9c_ard_3-2-1_096085_2022-08-20_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-09-02 09:25:54	ga_ls9c_ard_3-2-1_091082_2022-09-01_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-10 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-09-10_final.stac-item
2022-09-15 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-09-15_final.stac-item
2022-09-19 10:03:40	ga_ls9c_ard_3-2-1_098068_2022-09-19_final.stac-item
2022-09-21 11:32:36	ga_ls9c_ard_3-2-1_112074_2022-09-21_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-04 11:00:07	ga_ls9c_ard_3-2-1_107070_2022-10-04_final.stac-item
2022-10-09 09:41:00	ga_ls9c_ard_3-2-1_094073_2022-10-09_final.stac-item
2022-10-11 11:07:57	ga_ls9c_ard_3-2-1_108074_2022-10-11_final.stac-item
2022-11-03 09:37:38	ga_ls9c_ard_3-2-1_093080_2022-11-03_final.stac-item
2022-11-10 11:20:22	ga_ls9c_ard_3-2-1_110074_2022-11-10_final.stac-item
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-11-23 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-11-23_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-12-03 09:47:13	ga_ls9c_ard_3-2-1_095073_2022-12-03_final.stac-item
2022-12-07 09:23:19	ga_ls9c_ard_3-2-1_091075_2022-12-06_final.stac-item
2022-12-16 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-15_final.stac-item
2022-12-25 09:14:31	ga_ls9c_ard_3-2-1_089084_2022-12-24_final.stac-item
2022-12-28 11:20:20	ga_ls9c_ard_3-2-1_110074_2022-12-28_final.stac-item
2022-12-29 10:28:18	ga_ls9c_ard_3-2-1_101083_2022-12-29_final.stac-item
2022-12-31 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-31_final.stac-item
2023-01-06 11:12:35	ga_ls9c_ard_3-2-1_109070_2023-01-06_final.stac-item
2023-01-13 11:19:55	ga_ls9c_ard_3-2-1_110073_2023-01-13_final.stac-item
2023-01-19 10:42:44	ga_ls9c_ard_3-2-1_104073_2023-01-19_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-23 10:18:26	ga_ls9c_ard_3-2-1_100074_2023-01-23_final.stac-item
2023-01-24 09:24:02	ga_ls9c_ard_3-2-1_091077_2023-01-23_final.stac-item
2023-01-26 09:10:54	ga_ls9c_ard_3-2-1_089075_2023-01-25_final.stac-item
2023-02-02 09:22:46	ga_ls9c_ard_3-2-1_090089_2023-02-01_final.stac-item
2023-02-03 11:42:31	ga_ls9c_ard_3-2-1_113083_2023-02-03_final.stac-item
2023-02-11 10:52:42	ga_ls9c_ard_3-2-1_105082_2023-02-11_final.stac-item
2023-02-25 11:02:02	ga_ls9c_ard_3-2-1_107075_2023-02-25_final.stac-item
2023-02-27 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-02-26_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final.stac-item
2023-03-07 11:38:38	ga_ls9c_ard_3-2-1_113074_2023-03-07_final.stac-item
2023-03-13 09:23:26	ga_ls9c_ard_3-2-1_091076_2023-03-12_final.stac-item
2023-03-17 10:35:59	ga_ls9c_ard_3-2-1_103072_2023-03-17_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-04-24 11:41:52	ga_ls9c_ard_3-2-1_113083_2023-04-24_final.stac-item
2023-04-26 09:51:48	ga_ls9c_ard_3-2-1_095086_2023-04-26_final.stac-item
2023-05-02 09:11:49	ga_ls9c_ard_3-2-1_089079_2023-05-01_final.stac-item
2023-05-31 10:16:23	ga_ls9c_ard_3-2-1_100071_2023-05-31_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-21 10:38:46	ga_ls9c_ard_3-2-1_103081_2023-06-21_final.stac-item
2023-06-22 11:23:13	ga_ls9c_ard_3-2-1_110084_2023-06-22_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_2023-06-25_final.stac-item
2023-06-29 11:24:42	ga_ls9c_ard_3-2-1_111072_2023-06-29_final.stac-item
2023-07-01 09:39:54	ga_ls9c_ard_3-2-1_093088_2023-07-01_final.stac-item
2023-07-03 09:27:10	ga_ls9c_ard_3-2-1_091087_2023-07-02_final.stac-item
2023-07-16 10:28:28	ga_ls9c_ard_3-2-1_102070_2023-07-16_final.stac-item
2023-07-27 10:09:33	ga_ls9c_ard_3-2-1_099069_2023-07-27_final.stac-item
2023-07-28 09:21:31	ga_ls9c_ard_3-2-1_090088_2023-07-27_final.stac-item
2023-08-04 09:27:00	ga_ls9c_ard_3-2-1_091086_2023-08-03_final.stac-item
2023-08-06 10:51:33	ga_ls9c_ard_3-2-1_105081_2023-08-06_final.stac-item
2023-08-13 09:21:16	ga_ls9c_ard_3-2-1_090087_2023-08-12_final.stac-item
2023-08-15 09:06:54	ga_ls9c_ard_3-2-1_088082_2023-08-14_final.stac-item
2023-08-16 11:25:27	ga_ls9c_ard_3-2-1_111073_2023-08-16_final.stac-item
2023-10-16 09:17:20	ga_ls9c_ard_3-2-1_090076_2023-10-15_final.stac-item
2023-10-25 09:11:33	ga_ls9c_ard_3-2-1_089077_2023-10-24_final.stac-item
2023-10-26 11:32:29	ga_ls9c_ard_3-2-1_112074_2023-10-26_final.stac-item
2023-10-30 09:28:50	ga_ls9c_ard_3-2-1_092074_2023-10-29_final.stac-item
2023-11-04 11:24:13	ga_ls9c_ard_3-2-1_111069_2023-11-04_final.stac-item
2023-11-15 09:29:38	ga_ls9c_ard_3-2-1_092076_2023-11-14_final.stac-item
2023-11-15 11:06:07	ga_ls9c_ard_3-2-1_108070_2023-11-15_final.stac-item
2023-11-18 10:03:46	ga_ls9c_ard_3-2-1_097084_2023-11-18_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2023-11-24 09:22:46	ga_ls9c_ard_3-2-1_091074_2023-11-23_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_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