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

74 results

Time (local)	Label
2021-10-31 11:11:36	ga_ls9c_ard_3-2-1_109073_2021-10-31_final.stac-item
2021-11-06 10:19:46	ga_ls9c_ard_3-2-1_100084_2021-11-06_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2021-12-24 10:38:32	ga_ls9c_ard_3-2-1_103078_2021-12-24_final.stac-item
2022-01-01 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-01-01_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-22 11:45:17	ga_ls9c_ard_3-2-1_114075_2022-01-22_final.stac-item
2022-02-15 09:22:29	ga_ls9c_ard_3-2-1_090089_2022-02-14_final.stac-item
2022-03-26 11:05:18	ga_ls9c_ard_3-2-1_107084_2022-03-26_final.stac-item
2022-03-31 09:40:58	ga_ls9c_ard_3-2-1_094074_2022-03-31_final.stac-item
2022-04-20 10:54:10	ga_ls9c_ard_3-2-1_106072_2022-04-20_final.stac-item
2022-04-27 10:59:55	ga_ls9c_ard_3-2-1_107071_2022-04-27_final.stac-item
2022-04-29 09:16:15	ga_ls9c_ard_3-2-1_089090_2022-04-28_final.stac-item
2022-05-18 11:20:39	ga_ls9c_ard_3-2-1_110077_2022-05-18_final.stac-item
2022-05-27 09:36:20	ga_ls9c_ard_3-2-1_093079_2022-05-27_final.stac-item
2022-06-14 11:01:46	ga_ls9c_ard_3-2-1_107076_2022-06-14_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-07-13 10:29:28	ga_ls9c_ard_3-2-1_102072_2022-07-13_final.stac-item
2022-07-16 09:26:41	ga_ls9c_ard_3-2-1_091085_2022-07-15_final.stac-item
2022-07-27 09:06:44	ga_ls9c_ard_3-2-1_088081_2022-07-26_final.stac-item
2022-08-09 11:52:57	ga_ls9c_ard_3-2-1_115079_2022-08-09_final.stac-item
2022-08-20 11:35:17	ga_ls9c_ard_3-2-1_112081_2022-08-20_final.stac-item
2022-09-04 10:48:50	ga_ls9c_ard_3-2-1_105073_2022-09-04_final.stac-item
2022-09-15 10:30:45	ga_ls9c_ard_3-2-1_102074_2022-09-15_final.stac-item
2022-09-19 10:08:27	ga_ls9c_ard_3-2-1_098080_2022-09-19_final.stac-item
2022-09-27 10:55:09	ga_ls9c_ard_3-2-1_106073_2022-09-27_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_2022-09-27_final.stac-item
2022-10-09 09:44:35	ga_ls9c_ard_3-2-1_094082_2022-10-09_final.stac-item
2022-10-16 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-10-16_final.stac-item
2022-10-17 10:31:18	ga_ls9c_ard_3-2-1_102075_2022-10-17_final.stac-item
2022-10-26 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-10-26_final.stac-item
2022-12-09 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-12-09_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2022-12-30 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-12-29_final.stac-item
2023-01-11 09:58:12	ga_ls9c_ard_3-2-1_096085_2023-01-11_final.stac-item
2023-01-31 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-01-31_final.stac-item
2023-01-31 11:10:24	ga_ls9c_ard_3-2-1_108080_2023-01-31_final.stac-item
2023-02-05 11:29:47	ga_ls9c_ard_3-2-1_111082_2023-02-05_final.stac-item
2023-03-11 09:39:46	ga_ls9c_ard_3-2-1_093086_2023-03-11_final.stac-item
2023-03-14 10:10:17	ga_ls9c_ard_3-2-1_098085_2023-03-14_final.stac-item
2023-03-30 10:10:05	ga_ls9c_ard_3-2-1_098085_2023-03-30_final.stac-item
2023-04-08 11:41:10	ga_ls9c_ard_3-2-1_113081_2023-04-08_final.stac-item
2023-04-14 09:23:08	ga_ls9c_ard_3-2-1_091076_2023-04-13_final.stac-item
2023-04-14 09:25:08	ga_ls9c_ard_3-2-1_091081_2023-04-13_final.stac-item
2023-04-28 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-04-28_final.stac-item
2023-04-29 10:17:28	ga_ls9c_ard_3-2-1_100073_2023-04-29_final.stac-item
2023-06-08 11:05:22	ga_ls9c_ard_3-2-1_108070_2023-06-08_final.stac-item
2023-06-11 10:00:56	ga_ls9c_ard_3-2-1_097079_2023-06-11_final.stac-item
2023-06-17 10:59:05	ga_ls9c_ard_3-2-1_107070_2023-06-17_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-07-20 10:04:33	ga_ls9c_ard_3-2-1_098072_2023-07-20_final.stac-item
2023-07-21 09:13:43	ga_ls9c_ard_3-2-1_089084_2023-07-20_final.stac-item
2023-08-05 10:03:53	ga_ls9c_ard_3-2-1_098070_2023-08-05_final.stac-item
2023-08-07 11:36:01	ga_ls9c_ard_3-2-1_112084_2023-08-07_final.stac-item
2023-08-09 09:40:23	ga_ls9c_ard_3-2-1_094073_2023-08-09_final.stac-item
2023-08-10 10:24:03	ga_ls9c_ard_3-2-1_101074_2023-08-10_final.stac-item
2023-08-15 10:42:36	ga_ls9c_ard_3-2-1_104074_2023-08-15_final.stac-item
2023-08-20 09:22:41	ga_ls9c_ard_3-2-1_091075_2023-08-19_final.stac-item
2023-08-29 10:53:31	ga_ls9c_ard_3-2-1_106070_2023-08-29_final.stac-item
2023-08-30 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-08-30_final.stac-item
2023-09-05 09:28:51	ga_ls9c_ard_3-2-1_091090_2023-09-04_final.stac-item
2023-09-13 11:52:04	ga_ls9c_ard_3-2-1_115077_2023-09-13_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-11-06 09:38:59	ga_ls9c_ard_3-2-1_093084_2023-11-06_final.stac-item
2023-11-08 09:26:39	ga_ls9c_ard_3-2-1_091084_2023-11-07_final.stac-item
2023-11-11 09:51:58	ga_ls9c_ard_3-2-1_096070_2023-11-11_final.stac-item
2023-11-12 10:38:01	ga_ls9c_ard_3-2-1_103077_2023-11-12_final.stac-item
2023-11-14 10:23:39	ga_ls9c_ard_3-2-1_101072_2023-11-14_final.stac-item
2023-11-26 09:14:25	ga_ls9c_ard_3-2-1_089084_2023-11-25_final.stac-item
2023-12-30 10:35:22	ga_ls9c_ard_3-2-1_103070_2023-12-30_final.stac-item
2024-02-10 11:13:14	ga_ls9c_ard_3-2-1_109072_2024-02-10_final.stac-item
2024-03-06 09:28:03	ga_ls9c_ard_3-2-1_092072_2024-03-05_final.stac-item
2024-04-14 11:12:26	ga_ls9c_ard_3-2-1_109071_2024-04-14_final.stac-item
2024-04-16 09:25:09	ga_ls9c_ard_3-2-1_091081_2024-04-15_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