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
2021-11-08 09:56:15	ga_ls9c_ard_3-2-1_097072_2021-11-08_final.stac-item
2021-12-05 10:04:57	ga_ls9c_ard_3-2-1_098071_2021-12-05_final.stac-item
2021-12-07 11:36:14	ga_ls9c_ard_3-2-1_112083_2021-12-07_final.stac-item
2021-12-23 11:36:09	ga_ls9c_ard_3-2-1_112083_2021-12-23_final.stac-item
2021-12-29 09:21:47	ga_ls9c_ard_3-2-1_090087_2021-12-28_final.stac-item
2022-01-03 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-01-03_final.stac-item
2022-02-22 10:59:53	ga_ls9c_ard_3-2-1_107070_2022-02-22_final.stac-item
2022-03-03 09:22:42	ga_ls9c_ard_3-2-1_090090_2022-03-02_final.stac-item
2022-03-31 11:17:51	ga_ls9c_ard_3-2-1_110069_2022-03-31_final.stac-item
2022-04-18 11:09:45	ga_ls9c_ard_3-2-1_108080_2022-04-18_final.stac-item
2022-04-26 10:20:39	ga_ls9c_ard_3-2-1_100081_2022-04-26_final.stac-item
2022-04-26 11:57:32	ga_ls9c_ard_3-2-1_116076_2022-04-26_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-05-31 10:52:07	ga_ls9c_ard_3-2-1_105083_2022-05-31_final.stac-item
2022-06-25 10:45:54	ga_ls9c_ard_3-2-1_104082_2022-06-25_final.stac-item
2022-07-15 10:16:42	ga_ls9c_ard_3-2-1_100071_2022-07-15_final.stac-item
2022-07-18 10:50:27	ga_ls9c_ard_3-2-1_105078_2022-07-18_final.stac-item
2022-07-24 11:51:10	ga_ls9c_ard_3-2-1_115075_2022-07-24_final.stac-item
2022-08-05 10:37:57	ga_ls9c_ard_3-2-1_103077_2022-08-05_final.stac-item
2022-08-09 10:13:40	ga_ls9c_ard_3-2-1_099078_2022-08-09_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-08-28 09:06:34	ga_ls9c_ard_3-2-1_088080_2022-08-27_final.stac-item
2022-09-07 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-09-07_final.stac-item
2022-10-09 11:20:17	ga_ls9c_ard_3-2-1_110074_2022-10-09_final.stac-item
2022-10-19 10:19:45	ga_ls9c_ard_3-2-1_100077_2022-10-19_final.stac-item
2022-10-20 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-10-19_final.stac-item
2022-10-25 09:40:41	ga_ls9c_ard_3-2-1_094072_2022-10-25_final.stac-item
2022-10-25 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-10-25_final.stac-item
2022-11-23 10:49:52	ga_ls9c_ard_3-2-1_105075_2022-11-23_final.stac-item
2022-11-30 09:21:06	ga_ls9c_ard_3-2-1_090085_2022-11-29_final.stac-item
2022-12-14 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-12-13_final.stac-item
2022-12-25 09:16:30	ga_ls9c_ard_3-2-1_089089_2022-12-24_final.stac-item
2022-12-28 11:21:08	ga_ls9c_ard_3-2-1_110076_2022-12-28_final.stac-item
2022-12-30 09:33:29	ga_ls9c_ard_3-2-1_092085_2022-12-30_final.stac-item
2022-12-31 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-31_final.stac-item
2023-01-04 09:50:51	ga_ls9c_ard_3-2-1_095082_2023-01-04_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-01-12 10:35:04	ga_ls9c_ard_3-2-1_103069_2023-01-12_final.stac-item
2023-01-20 09:47:05	ga_ls9c_ard_3-2-1_095073_2023-01-20_final.stac-item
2023-01-29 09:41:27	ga_ls9c_ard_3-2-1_094074_2023-01-29_final.stac-item
2023-02-07 09:36:57	ga_ls9c_ard_3-2-1_093078_2023-02-07_final.stac-item
2023-02-09 09:26:11	ga_ls9c_ard_3-2-1_091082_2023-02-08_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-02-13 10:39:55	ga_ls9c_ard_3-2-1_103081_2023-02-13_final.stac-item
2023-03-06 09:21:42	ga_ls9c_ard_3-2-1_090087_2023-03-05_final.stac-item
2023-03-09 09:46:33	ga_ls9c_ard_3-2-1_095072_2023-03-09_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-03-13 10:59:55	ga_ls9c_ard_3-2-1_107070_2023-03-13_final.stac-item
2023-04-01 11:36:13	ga_ls9c_ard_3-2-1_112084_2023-04-01_final.stac-item
2023-04-04 10:22:39	ga_ls9c_ard_3-2-1_101070_2023-04-04_final.stac-item
2023-04-07 10:55:55	ga_ls9c_ard_3-2-1_106076_2023-04-07_final.stac-item
2023-04-19 09:44:04	ga_ls9c_ard_3-2-1_094082_2023-04-19_final.stac-item
2023-04-19 11:18:10	ga_ls9c_ard_3-2-1_110070_2023-04-19_final.stac-item
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-05-04 10:33:54	ga_ls9c_ard_3-2-1_103068_2023-05-04_final.stac-item
2023-05-05 09:40:16	ga_ls9c_ard_3-2-1_094073_2023-05-05_final.stac-item
2023-05-05 11:17:57	ga_ls9c_ard_3-2-1_110070_2023-05-05_final.stac-item
2023-05-10 10:01:12	ga_ls9c_ard_3-2-1_097079_2023-05-10_final.stac-item
2023-05-10 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-05-10_final.stac-item
2023-05-10 11:37:18	ga_ls9c_ard_3-2-1_113072_2023-05-10_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-05-18 10:48:59	ga_ls9c_ard_3-2-1_105075_2023-05-18_final.stac-item
2023-05-24 11:51:53	ga_ls9c_ard_3-2-1_115078_2023-05-24_final.stac-item
2023-06-02 11:46:53	ga_ls9c_ard_3-2-1_114081_2023-06-02_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-06-18 10:06:40	ga_ls9c_ard_3-2-1_098078_2023-06-18_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-07-04 10:09:39	ga_ls9c_ard_3-2-1_098085_2023-07-04_final.stac-item
2023-07-11 10:13:30	ga_ls9c_ard_3-2-1_099079_2023-07-11_final.stac-item
2023-07-28 09:21:55	ga_ls9c_ard_3-2-1_090089_2023-07-27_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-08-12 11:50:59	ga_ls9c_ard_3-2-1_115075_2023-08-12_final.stac-item
2023-08-16 11:28:39	ga_ls9c_ard_3-2-1_111081_2023-08-16_final.stac-item
2023-08-23 11:35:43	ga_ls9c_ard_3-2-1_112083_2023-08-23_final.stac-item
2023-08-25 09:40:30	ga_ls9c_ard_3-2-1_094073_2023-08-25_final.stac-item
2023-08-28 11:52:43	ga_ls9c_ard_3-2-1_115079_2023-08-28_final.stac-item
2023-09-15 09:57:39	ga_ls9c_ard_3-2-1_097069_2023-09-15_final.stac-item
2023-09-18 10:28:09	ga_ls9c_ard_3-2-1_102068_2023-09-18_final.stac-item
2023-09-21 09:26:56	ga_ls9c_ard_3-2-1_091085_2023-09-20_final.stac-item
2023-10-12 11:18:30	ga_ls9c_ard_3-2-1_110070_2023-10-12_final.stac-item
2023-10-15 11:51:26	ga_ls9c_ard_3-2-1_115075_2023-10-15_final.stac-item
2023-10-18 10:41:04	ga_ls9c_ard_3-2-1_104069_2023-10-18_final.stac-item
2023-10-24 10:04:47	ga_ls9c_ard_3-2-1_098071_2023-10-24_final.stac-item
2023-11-01 09:20:50	ga_ls9c_ard_3-2-1_090085_2023-10-31_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-20 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-11-20_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_2023-11-23_final.stac-item
2023-11-25 11:47:43	ga_ls9c_ard_3-2-1_114081_2023-11-25_final.stac-item
2023-12-04 09:58:38	ga_ls9c_ard_3-2-1_097071_2023-12-04_final.stac-item
2023-12-16 10:23:00	ga_ls9c_ard_3-2-1_101070_2023-12-16_final.stac-item
2024-01-03 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-03_final.stac-item
2024-01-04 10:55:50	ga_ls9c_ard_3-2-1_106075_2024-01-04_final.stac-item
2024-01-21 11:40:41	ga_ls9c_ard_3-2-1_113079_2024-01-21_final.stac-item
2024-01-22 09:07:46	ga_ls9c_ard_3-2-1_088083_2024-01-21_final.stac-item
2024-02-03 11:06:15	ga_ls9c_ard_3-2-1_108070_2024-02-03_final.stac-item
2024-02-06 10:01:52	ga_ls9c_ard_3-2-1_097079_2024-02-06_final.stac-item
2024-02-14 10:48:04	ga_ls9c_ard_3-2-1_105071_2024-02-14_final.stac-item
2024-02-21 09:21:36	ga_ls9c_ard_3-2-1_090087_2024-02-20_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