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
2022-11-03 09:37:14	ga_ls9c_ard_3-2-1_093079_2022-11-03_final.stac-item
2022-11-03 11:16:55	ga_ls9c_ard_3-2-1_109081_2022-11-03_final.stac-item
2022-11-15 09:58:26	ga_ls9c_ard_3-2-1_097070_2022-11-15_final.stac-item
2022-11-25 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-11-25_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-07 11:02:12	ga_ls9c_ard_3-2-1_107075_2022-12-07_final.stac-item
2022-12-08 10:08:35	ga_ls9c_ard_3-2-1_098080_2022-12-08_final.stac-item
2022-12-08 11:45:04	ga_ls9c_ard_3-2-1_114074_2022-12-08_final.stac-item
2022-12-14 11:11:35	ga_ls9c_ard_3-2-1_108083_2022-12-14_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-21 11:17:44	ga_ls9c_ard_3-2-1_109083_2022-12-21_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-24 10:04:32	ga_ls9c_ard_3-2-1_098070_2022-12-24_final.stac-item
2022-12-24 10:05:44	ga_ls9c_ard_3-2-1_098073_2022-12-24_final.stac-item
2022-12-24 10:09:19	ga_ls9c_ard_3-2-1_098082_2022-12-24_final.stac-item
2022-12-25 09:10:31	ga_ls9c_ard_3-2-1_089074_2022-12-24_final.stac-item
2022-12-25 09:14:31	ga_ls9c_ard_3-2-1_089084_2022-12-24_final.stac-item
2022-12-25 10:49:00	ga_ls9c_ard_3-2-1_105073_2022-12-25_final.stac-item
2022-12-26 09:56:11	ga_ls9c_ard_3-2-1_096080_2022-12-26_final.stac-item
2022-12-26 11:35:52	ga_ls9c_ard_3-2-1_112082_2022-12-26_final.stac-item
2022-12-26 11:36:40	ga_ls9c_ard_3-2-1_112084_2022-12-26_final.stac-item
2022-12-27 10:38:39	ga_ls9c_ard_3-2-1_103078_2022-12-27_final.stac-item
2022-12-27 10:39:51	ga_ls9c_ard_3-2-1_103081_2022-12-27_final.stac-item
2022-12-28 09:41:03	ga_ls9c_ard_3-2-1_094073_2022-12-28_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_final.stac-item
2022-12-30 09:30:42	ga_ls9c_ard_3-2-1_092078_2022-12-30_final.stac-item
2022-12-30 11:10:47	ga_ls9c_ard_3-2-1_108081_2022-12-30_final.stac-item
2022-12-30 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-30_final.stac-item
2022-12-31 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-12-31_final.stac-item
2023-01-01 09:19:33	ga_ls9c_ard_3-2-1_090081_2022-12-31_final.stac-item
2023-01-02 10:02:01	ga_ls9c_ard_3-2-1_097079_2023-01-02_final.stac-item
2023-01-02 10:03:36	ga_ls9c_ard_3-2-1_097083_2023-01-02_final.stac-item
2023-01-03 10:44:05	ga_ls9c_ard_3-2-1_104076_2023-01-03_final.stac-item
2023-01-04 09:46:52	ga_ls9c_ard_3-2-1_095072_2023-01-04_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-05 10:30:55	ga_ls9c_ard_3-2-1_102074_2023-01-05_final.stac-item
2023-01-06 09:34:54	ga_ls9c_ard_3-2-1_093073_2023-01-06_final.stac-item
2023-01-06 09:38:53	ga_ls9c_ard_3-2-1_093083_2023-01-06_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-08 09:28:55	ga_ls9c_ard_3-2-1_091089_2023-01-07_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-09 10:04:35	ga_ls9c_ard_3-2-1_098070_2023-01-09_final.stac-item
2023-01-09 10:09:23	ga_ls9c_ard_3-2-1_098082_2023-01-09_final.stac-item
2023-01-10 09:10:33	ga_ls9c_ard_3-2-1_089074_2023-01-09_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-10 09:14:09	ga_ls9c_ard_3-2-1_089083_2023-01-09_final.stac-item
2023-01-10 09:14:33	ga_ls9c_ard_3-2-1_089084_2023-01-09_final.stac-item
2023-01-10 09:16:33	ga_ls9c_ard_3-2-1_089089_2023-01-09_final.stac-item
2023-01-10 10:53:02	ga_ls9c_ard_3-2-1_105083_2023-01-10_final.stac-item
2023-01-11 11:35:53	ga_ls9c_ard_3-2-1_112082_2023-01-11_final.stac-item
2023-01-11 11:36:17	ga_ls9c_ard_3-2-1_112083_2023-01-11_final.stac-item
2023-01-11 11:36:41	ga_ls9c_ard_3-2-1_112084_2023-01-11_final.stac-item
2023-01-12 10:38:40	ga_ls9c_ard_3-2-1_103078_2023-01-12_final.stac-item
2023-01-13 09:40:38	ga_ls9c_ard_3-2-1_094072_2023-01-13_final.stac-item
2023-01-13 09:42:38	ga_ls9c_ard_3-2-1_094077_2023-01-13_final.stac-item
2023-01-14 10:23:53	ga_ls9c_ard_3-2-1_101072_2023-01-14_final.stac-item
2023-01-15 09:30:15	ga_ls9c_ard_3-2-1_092077_2023-01-15_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-15 11:11:31	ga_ls9c_ard_3-2-1_108083_2023-01-15_final.stac-item
2023-01-16 10:15:29	ga_ls9c_ard_3-2-1_099082_2023-01-16_final.stac-item
2023-01-17 09:19:03	ga_ls9c_ard_3-2-1_090080_2023-01-16_final.stac-item
2023-01-17 10:53:08	ga_ls9c_ard_3-2-1_106068_2023-01-17_final.stac-item
2023-01-17 10:57:32	ga_ls9c_ard_3-2-1_106079_2023-01-17_final.stac-item
2023-01-18 10:01:29	ga_ls9c_ard_3-2-1_097078_2023-01-18_final.stac-item
2023-01-19 10:43:32	ga_ls9c_ard_3-2-1_104075_2023-01-19_final.stac-item
2023-01-19 10:45:32	ga_ls9c_ard_3-2-1_104080_2023-01-19_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-20 09:48:41	ga_ls9c_ard_3-2-1_095077_2023-01-20_final.stac-item
2023-01-20 09:49:05	ga_ls9c_ard_3-2-1_095078_2023-01-20_final.stac-item
2023-01-20 09:49:29	ga_ls9c_ard_3-2-1_095079_2023-01-20_final.stac-item
2023-01-20 09:52:41	ga_ls9c_ard_3-2-1_095087_2023-01-20_final.stac-item
2023-01-20 11:29:10	ga_ls9c_ard_3-2-1_111081_2023-01-20_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-20 11:29:58	ga_ls9c_ard_3-2-1_111083_2023-01-20_final.stac-item
2023-01-22 09:33:57	ga_ls9c_ard_3-2-1_093071_2023-01-22_final.stac-item
2023-01-22 09:34:45	ga_ls9c_ard_3-2-1_093073_2023-01-22_final.stac-item
2023-01-22 09:38:44	ga_ls9c_ard_3-2-1_093083_2023-01-22_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_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
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-24 09:26:25	ga_ls9c_ard_3-2-1_091083_2023-01-23_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-01-25 10:08:54	ga_ls9c_ard_3-2-1_098081_2023-01-25_final.stac-item
2023-01-26 09:14:06	ga_ls9c_ard_3-2-1_089083_2023-01-25_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-01-26 10:48:36	ga_ls9c_ard_3-2-1_105072_2023-01-26_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-01-26 10:52:59	ga_ls9c_ard_3-2-1_105083_2023-01-26_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-05-30 09:37:31	ga_ls9c_ard_3-2-1_093082_2023-05-30_final.stac-item
2023-05-30 09:37:54	ga_ls9c_ard_3-2-1_093083_2023-05-30_final.stac-item
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years