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
2021-11-15 11:19:25	ga_ls9c_ard_3-2-1_110074_2021-11-15_final.stac-item
2021-12-06 09:12:06	ga_ls9c_ard_3-2-1_089078_2021-12-05_final.stac-item
2021-12-18 09:39:30	ga_ls9c_ard_3-2-1_093085_2021-12-18_final.stac-item
2021-12-27 09:31:21	ga_ls9c_ard_3-2-1_092080_2021-12-27_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-01-01_final.stac-item
2022-01-13 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-01-13_final.stac-item
2022-02-08 10:46:52	ga_ls9c_ard_3-2-1_105068_2022-02-08_final.stac-item
2022-02-09 11:36:30	ga_ls9c_ard_3-2-1_112084_2022-02-09_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-11 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-02-11_final.stac-item
2022-02-11 11:24:32	ga_ls9c_ard_3-2-1_110085_2022-02-11_final.stac-item
2022-03-03 09:21:30	ga_ls9c_ard_3-2-1_090087_2022-03-02_final.stac-item
2022-03-11 10:03:23	ga_ls9c_ard_3-2-1_098068_2022-03-11_final.stac-item
2022-03-21 09:06:43	ga_ls9c_ard_3-2-1_088081_2022-03-20_final.stac-item
2022-03-22 11:25:40	ga_ls9c_ard_3-2-1_111073_2022-03-22_final.stac-item
2022-03-29 11:33:48	ga_ls9c_ard_3-2-1_112078_2022-03-29_final.stac-item
2022-05-04 09:32:22	ga_ls9c_ard_3-2-1_092084_2022-05-04_final.stac-item
2022-05-09 09:52:04	ga_ls9c_ard_3-2-1_095087_2022-05-09_final.stac-item
2022-05-20 11:07:03	ga_ls9c_ard_3-2-1_108074_2022-05-20_final.stac-item
2022-05-21 10:13:02	ga_ls9c_ard_3-2-1_099078_2022-05-21_final.stac-item
2022-05-29 11:04:52	ga_ls9c_ard_3-2-1_107084_2022-05-29_final.stac-item
2022-05-31 10:52:07	ga_ls9c_ard_3-2-1_105083_2022-05-31_final.stac-item
2022-06-11 10:33:13	ga_ls9c_ard_3-2-1_102082_2022-06-11_final.stac-item
2022-06-17 09:57:49	ga_ls9c_ard_3-2-1_096086_2022-06-17_final.stac-item
2022-07-01 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-07-01_final.stac-item
2022-07-07 09:33:42	ga_ls9c_ard_3-2-1_092087_2022-07-07_final.stac-item
2022-07-25 09:21:28	ga_ls9c_ard_3-2-1_090087_2022-07-24_final.stac-item
2022-08-08 09:33:59	ga_ls9c_ard_3-2-1_092087_2022-08-08_final.stac-item
2022-08-14 10:28:39	ga_ls9c_ard_3-2-1_102069_2022-08-14_final.stac-item
2022-08-22 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-08-22_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-08-30 10:28:42	ga_ls9c_ard_3-2-1_102069_2022-08-30_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-10-09 09:41:24	ga_ls9c_ard_3-2-1_094074_2022-10-09_final.stac-item
2022-10-11 09:34:15	ga_ls9c_ard_3-2-1_092087_2022-10-11_final.stac-item
2022-10-12 11:52:49	ga_ls9c_ard_3-2-1_115078_2022-10-12_final.stac-item
2022-10-30 10:02:24	ga_ls9c_ard_3-2-1_097080_2022-10-30_final.stac-item
2022-11-02 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-11-02_final.stac-item
2022-11-03 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-11-03_final.stac-item
2022-11-05 09:22:30	ga_ls9c_ard_3-2-1_091073_2022-11-04_final.stac-item
2022-11-05 11:02:11	ga_ls9c_ard_3-2-1_107075_2022-11-05_final.stac-item
2022-11-09 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-09_final.stac-item
2022-11-10 09:41:05	ga_ls9c_ard_3-2-1_094073_2022-11-10_final.stac-item
2022-11-10 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-11-10_final.stac-item
2022-11-12 09:33:55	ga_ls9c_ard_3-2-1_092086_2022-11-12_final.stac-item
2022-11-14 10:56:27	ga_ls9c_ard_3-2-1_106076_2022-11-14_final.stac-item
2022-11-23 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-11-22_final.stac-item
2022-11-25 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-11-25_final.stac-item
2022-11-27 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-11-27_final.stac-item
2022-11-28 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-11-27_final.stac-item
2022-11-28 09:29:53	ga_ls9c_ard_3-2-1_092076_2022-11-27_final.stac-item
2022-11-29 11:53:14	ga_ls9c_ard_3-2-1_115079_2022-11-29_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-01 09:58:22	ga_ls9c_ard_3-2-1_097070_2022-12-01_final.stac-item
2022-12-04 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-04_final.stac-item
2022-12-06 10:17:20	ga_ls9c_ard_3-2-1_100071_2022-12-06_final.stac-item
2022-12-15 10:10:22	ga_ls9c_ard_3-2-1_099069_2022-12-15_final.stac-item
2022-12-17 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-12-17_final.stac-item
2022-12-23 11:02:33	ga_ls9c_ard_3-2-1_107076_2022-12-23_final.stac-item
2022-12-25 09:13:19	ga_ls9c_ard_3-2-1_089081_2022-12-24_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-01-16 10:13:53	ga_ls9c_ard_3-2-1_099078_2023-01-16_final.stac-item
2023-01-21 10:31:57	ga_ls9c_ard_3-2-1_102077_2023-01-21_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-01-31 09:29:55	ga_ls9c_ard_3-2-1_092076_2023-01-30_final.stac-item
2023-02-02 09:17:58	ga_ls9c_ard_3-2-1_090077_2023-02-01_final.stac-item
2023-02-05 11:26:11	ga_ls9c_ard_3-2-1_111073_2023-02-05_final.stac-item
2023-02-07 11:18:13	ga_ls9c_ard_3-2-1_109084_2023-02-07_final.stac-item
2023-02-11 10:52:18	ga_ls9c_ard_3-2-1_105081_2023-02-11_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-25 11:24:33	ga_ls9c_ard_3-2-1_111070_2023-03-25_final.stac-item
2023-03-30 10:09:17	ga_ls9c_ard_3-2-1_098083_2023-03-30_final.stac-item
2023-03-30 11:44:34	ga_ls9c_ard_3-2-1_114074_2023-03-30_final.stac-item
2023-04-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2023-04-23_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-05-08 10:09:59	ga_ls9c_ard_3-2-1_099070_2023-05-08_final.stac-item
2023-05-10 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-05-10_final.stac-item
2023-05-16 09:28:28	ga_ls9c_ard_3-2-1_091090_2023-05-15_final.stac-item
2023-05-18 10:48:35	ga_ls9c_ard_3-2-1_105074_2023-05-18_final.stac-item
2023-05-28 11:25:34	ga_ls9c_ard_3-2-1_111074_2023-05-28_final.stac-item
2023-05-31 10:19:10	ga_ls9c_ard_3-2-1_100078_2023-05-31_final.stac-item
2023-06-01 09:27:32	ga_ls9c_ard_3-2-1_091088_2023-05-31_final.stac-item
2023-06-18 10:08:39	ga_ls9c_ard_3-2-1_098083_2023-06-18_final.stac-item
2023-06-22 11:23:13	ga_ls9c_ard_3-2-1_110084_2023-06-22_final.stac-item
2023-06-25 10:14:50	ga_ls9c_ard_3-2-1_099083_2023-06-25_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-07-05 10:48:32	ga_ls9c_ard_3-2-1_105074_2023-07-05_final.stac-item
2023-07-31 09:52:04	ga_ls9c_ard_3-2-1_095087_2023-07-31_final.stac-item
2023-08-04 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-08-04_final.stac-item
2023-08-06 10:51:33	ga_ls9c_ard_3-2-1_105081_2023-08-06_final.stac-item
2023-08-12 11:52:11	ga_ls9c_ard_3-2-1_115078_2023-08-12_final.stac-item
2023-08-18 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-08-18_final.stac-item
2023-10-15 10:13:21	ga_ls9c_ard_3-2-1_099077_2023-10-15_final.stac-item
2023-10-18 10:42:40	ga_ls9c_ard_3-2-1_104073_2023-10-18_final.stac-item
2023-10-22 10:19:57	ga_ls9c_ard_3-2-1_100078_2023-10-22_final.stac-item
2023-10-24 10:03:35	ga_ls9c_ard_3-2-1_098068_2023-10-24_final.stac-item
2023-10-27 10:39:39	ga_ls9c_ard_3-2-1_103081_2023-10-27_final.stac-item
2023-10-31 10:11:17	ga_ls9c_ard_3-2-1_099072_2023-10-31_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