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 10:55:45	ga_ls9c_ard_3-2-1_106074_2021-11-07_final.stac-item
2021-11-08 09:54:15	ga_ls9c_ard_3-2-1_097067_2021-11-08_final.stac-item
2021-11-20 09:42:49	ga_ls9c_ard_3-2-1_094073_2021-11-20_final.stac-item
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2021-12-14 09:57:52	ga_ls9c_ard_3-2-1_097069_2021-12-14_final.stac-item
2021-12-20 09:23:34	ga_ls9c_ard_3-2-1_091076_2021-12-19_final.stac-item
2021-12-22 10:49:41	ga_ls9c_ard_3-2-1_105075_2021-12-22_final.stac-item
2021-12-26 10:27:46	ga_ls9c_ard_3-2-1_101082_2021-12-26_final.stac-item
2022-01-04 10:22:22	ga_ls9c_ard_3-2-1_100084_2022-01-04_final.stac-item
2022-01-30 09:17:46	ga_ls9c_ard_3-2-1_090077_2022-01-29_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-02 09:52:40	ga_ls9c_ard_3-2-1_095087_2022-02-02_final.stac-item
2022-02-02 11:23:58	ga_ls9c_ard_3-2-1_111068_2022-02-02_final.stac-item
2022-02-09 11:31:43	ga_ls9c_ard_3-2-1_112072_2022-02-09_final.stac-item
2022-02-11 11:20:08	ga_ls9c_ard_3-2-1_110074_2022-02-11_final.stac-item
2022-02-14 11:51:49	ga_ls9c_ard_3-2-1_115076_2022-02-14_final.stac-item
2022-02-16 09:58:09	ga_ls9c_ard_3-2-1_097070_2022-02-16_final.stac-item
2022-03-06 09:50:49	ga_ls9c_ard_3-2-1_095083_2022-03-06_final.stac-item
2022-04-03 10:13:04	ga_ls9c_ard_3-2-1_099077_2022-04-03_final.stac-item
2022-04-24 10:28:13	ga_ls9c_ard_3-2-1_102069_2022-04-24_final.stac-item
2022-04-27 11:02:43	ga_ls9c_ard_3-2-1_107078_2022-04-27_final.stac-item
2022-04-29 10:46:22	ga_ls9c_ard_3-2-1_105068_2022-04-29_final.stac-item
2022-05-06 10:58:05	ga_ls9c_ard_3-2-1_106082_2022-05-06_final.stac-item
2022-05-19 10:22:13	ga_ls9c_ard_3-2-1_101070_2022-05-19_final.stac-item
2022-07-06 10:27:20	ga_ls9c_ard_3-2-1_101082_2022-07-06_final.stac-item
2022-07-15 10:16:42	ga_ls9c_ard_3-2-1_100071_2022-07-15_final.stac-item
2022-07-15 10:19:30	ga_ls9c_ard_3-2-1_100078_2022-07-15_final.stac-item
2022-07-21 11:19:49	ga_ls9c_ard_3-2-1_110074_2022-07-21_final.stac-item
2022-07-23 09:33:47	ga_ls9c_ard_3-2-1_092087_2022-07-23_final.stac-item
2022-08-01 09:28:08	ga_ls9c_ard_3-2-1_091088_2022-07-31_final.stac-item
2022-08-11 11:38:37	ga_ls9c_ard_3-2-1_113074_2022-08-11_final.stac-item
2022-08-16 10:19:54	ga_ls9c_ard_3-2-1_100078_2022-08-16_final.stac-item
2022-08-17 09:23:05	ga_ls9c_ard_3-2-1_091075_2022-08-16_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-15 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-09-15_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-29 09:06:42	ga_ls9c_ard_3-2-1_088080_2022-09-28_final.stac-item
2022-10-21 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-10-21_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-10-30 09:57:12	ga_ls9c_ard_3-2-1_097067_2022-10-30_final.stac-item
2022-11-01 09:52:01	ga_ls9c_ard_3-2-1_095085_2022-11-01_final.stac-item
2022-11-04 10:20:06	ga_ls9c_ard_3-2-1_100078_2022-11-04_final.stac-item
2022-11-05 09:28:05	ga_ls9c_ard_3-2-1_091087_2022-11-04_final.stac-item
2022-11-08 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-11-08_final.stac-item
2022-11-11 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-11-11_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-22 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-11-22_final.stac-item
2022-11-26 11:18:45	ga_ls9c_ard_3-2-1_110070_2022-11-26_final.stac-item
2022-12-03 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-12-03_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-09 10:47:03	ga_ls9c_ard_3-2-1_105068_2022-12-09_final.stac-item
2022-12-16 10:59:13	ga_ls9c_ard_3-2-1_106083_2022-12-16_final.stac-item
2022-12-17 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-12-17_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-18 10:44:27	ga_ls9c_ard_3-2-1_104077_2022-12-18_final.stac-item
2022-12-24 10:04:08	ga_ls9c_ard_3-2-1_098069_2022-12-24_final.stac-item
2022-12-24 10:09:43	ga_ls9c_ard_3-2-1_098083_2022-12-24_final.stac-item
2022-12-26 11:36:16	ga_ls9c_ard_3-2-1_112083_2022-12-26_final.stac-item
2022-12-29 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-12-29_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-09 10:03:24	ga_ls9c_ard_3-2-1_098067_2023-01-09_final.stac-item
2023-01-12 10:39:51	ga_ls9c_ard_3-2-1_103081_2023-01-12_final.stac-item
2023-01-15 11:07:56	ga_ls9c_ard_3-2-1_108074_2023-01-15_final.stac-item
2023-01-17 09:21:27	ga_ls9c_ard_3-2-1_090086_2023-01-16_final.stac-item
2023-01-20 11:23:59	ga_ls9c_ard_3-2-1_111068_2023-01-20_final.stac-item
2023-01-23 10:17:38	ga_ls9c_ard_3-2-1_100072_2023-01-23_final.stac-item
2023-01-27 09:52:11	ga_ls9c_ard_3-2-1_096070_2023-01-27_final.stac-item
2023-02-01 11:52:04	ga_ls9c_ard_3-2-1_115076_2023-02-01_final.stac-item
2023-03-13 09:23:26	ga_ls9c_ard_3-2-1_091076_2023-03-12_final.stac-item
2023-03-14 10:09:29	ga_ls9c_ard_3-2-1_098083_2023-03-14_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-29 11:04:55	ga_ls9c_ard_3-2-1_107083_2023-03-29_final.stac-item
2023-04-26 11:25:29	ga_ls9c_ard_3-2-1_111073_2023-04-26_final.stac-item
2023-04-27 10:27:52	ga_ls9c_ard_3-2-1_102068_2023-04-27_final.stac-item
2023-04-27 10:28:39	ga_ls9c_ard_3-2-1_102070_2023-04-27_final.stac-item
2023-05-03 11:31:09	ga_ls9c_ard_3-2-1_112072_2023-05-03_final.stac-item
2023-05-08 10:13:34	ga_ls9c_ard_3-2-1_099079_2023-05-08_final.stac-item
2023-05-11 10:42:04	ga_ls9c_ard_3-2-1_104073_2023-05-11_final.stac-item
2023-05-12 11:24:08	ga_ls9c_ard_3-2-1_111070_2023-05-12_final.stac-item
2023-05-22 10:22:12	ga_ls9c_ard_3-2-1_101070_2023-05-22_final.stac-item
2023-06-19 09:10:39	ga_ls9c_ard_3-2-1_089077_2023-06-18_final.stac-item
2023-06-22 09:44:44	ga_ls9c_ard_3-2-1_094085_2023-06-22_final.stac-item
2023-06-22 11:19:38	ga_ls9c_ard_3-2-1_110075_2023-06-22_final.stac-item
2023-06-27 11:41:24	ga_ls9c_ard_3-2-1_113083_2023-06-27_final.stac-item
2023-07-15 09:45:36	ga_ls9c_ard_3-2-1_095071_2023-07-15_final.stac-item
2023-07-20 10:06:56	ga_ls9c_ard_3-2-1_098078_2023-07-20_final.stac-item
2023-07-31 09:46:05	ga_ls9c_ard_3-2-1_095072_2023-07-31_final.stac-item
2023-08-11 11:07:19	ga_ls9c_ard_3-2-1_108074_2023-08-11_final.stac-item
2023-08-12 10:13:41	ga_ls9c_ard_3-2-1_099079_2023-08-12_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-22 10:17:09	ga_ls9c_ard_3-2-1_100071_2023-10-22_final.stac-item
2023-11-01 09:17:39	ga_ls9c_ard_3-2-1_090077_2023-10-31_final.stac-item
2023-11-15 11:07:19	ga_ls9c_ard_3-2-1_108073_2023-11-15_final.stac-item
2023-11-17 10:58:58	ga_ls9c_ard_3-2-1_106083_2023-11-17_final.stac-item
2023-11-21 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-11-21_final.stac-item
2023-11-23 11:58:04	ga_ls9c_ard_3-2-1_116076_2023-11-23_final.stac-item
2023-11-24 11:02:27	ga_ls9c_ard_3-2-1_107076_2023-11-24_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