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 10:59:20	ga_ls9c_ard_3-2-1_106083_2021-11-07_final.stac-item
2021-11-23 11:43:53	ga_ls9c_ard_3-2-1_114076_2021-11-23_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2021-12-22 09:12:24	ga_ls9c_ard_3-2-1_089079_2021-12-21_final.stac-item
2021-12-22 09:12:48	ga_ls9c_ard_3-2-1_089080_2021-12-21_final.stac-item
2022-01-02 10:31:33	ga_ls9c_ard_3-2-1_102076_2022-01-02_final.stac-item
2022-01-04 10:19:34	ga_ls9c_ard_3-2-1_100077_2022-01-04_final.stac-item
2022-01-14 09:18:55	ga_ls9c_ard_3-2-1_090080_2022-01-13_final.stac-item
2022-02-09 11:34:06	ga_ls9c_ard_3-2-1_112078_2022-02-09_final.stac-item
2022-03-02 11:52:25	ga_ls9c_ard_3-2-1_115078_2022-03-02_final.stac-item
2022-03-08 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-03-08_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-23 10:31:14	ga_ls9c_ard_3-2-1_102076_2022-03-23_final.stac-item
2022-03-24 11:16:53	ga_ls9c_ard_3-2-1_109082_2022-03-24_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_final.stac-item
2022-03-26 11:03:42	ga_ls9c_ard_3-2-1_107080_2022-03-26_final.stac-item
2022-04-30 11:33:36	ga_ls9c_ard_3-2-1_112078_2022-04-30_final.stac-item
2022-05-03 10:26:48	ga_ls9c_ard_3-2-1_101081_2022-05-03_final.stac-item
2022-06-02 10:36:34	ga_ls9c_ard_3-2-1_103075_2022-06-02_final.stac-item
2022-06-12 11:14:30	ga_ls9c_ard_3-2-1_109077_2022-06-12_final.stac-item
2022-06-21 09:30:01	ga_ls9c_ard_3-2-1_092078_2022-06-21_final.stac-item
2022-07-18 09:12:22	ga_ls9c_ard_3-2-1_089080_2022-07-17_final.stac-item
2022-07-27 09:06:44	ga_ls9c_ard_3-2-1_088081_2022-07-26_final.stac-item
2022-08-03 10:46:18	ga_ls9c_ard_3-2-1_105067_2022-08-03_final.stac-item
2022-08-05 10:37:09	ga_ls9c_ard_3-2-1_103075_2022-08-05_final.stac-item
2022-08-11 11:40:37	ga_ls9c_ard_3-2-1_113079_2022-08-11_final.stac-item
2022-08-14 10:31:27	ga_ls9c_ard_3-2-1_102076_2022-08-14_final.stac-item
2022-08-20 09:57:59	ga_ls9c_ard_3-2-1_096085_2022-08-20_final.stac-item
2022-08-20 11:34:05	ga_ls9c_ard_3-2-1_112078_2022-08-20_final.stac-item
2022-08-26 10:59:01	ga_ls9c_ard_3-2-1_106083_2022-08-26_final.stac-item
2022-09-16 11:15:13	ga_ls9c_ard_3-2-1_109077_2022-09-16_final.stac-item
2022-09-18 11:04:04	ga_ls9c_ard_3-2-1_107080_2022-09-18_final.stac-item
2022-09-28 10:02:19	ga_ls9c_ard_3-2-1_097080_2022-09-28_final.stac-item
2022-10-02 09:40:47	ga_ls9c_ard_3-2-1_093088_2022-10-02_final.stac-item
2022-10-11 11:11:56	ga_ls9c_ard_3-2-1_108084_2022-10-11_final.stac-item
2022-10-23 11:33:07	ga_ls9c_ard_3-2-1_112075_2022-10-23_final.stac-item
2023-02-12 11:35:09	ga_ls9c_ard_3-2-1_112080_2023-02-12_final.stac-item
2023-02-13 10:37:32	ga_ls9c_ard_3-2-1_103075_2023-02-13_final.stac-item
2023-02-20 10:45:59	ga_ls9c_ard_3-2-1_104081_2023-02-20_final.stac-item
2023-02-21 09:47:56	ga_ls9c_ard_3-2-1_095075_2023-02-21_final.stac-item
2023-03-09 11:25:26	ga_ls9c_ard_3-2-1_111072_2023-03-09_final.stac-item
2023-03-10 10:32:11	ga_ls9c_ard_3-2-1_102078_2023-03-10_final.stac-item
2023-03-10 10:32:35	ga_ls9c_ard_3-2-1_102079_2023-03-10_final.stac-item
2023-05-01 10:07:03	ga_ls9c_ard_3-2-1_098078_2023-05-01_final.stac-item
2023-05-01 10:08:15	ga_ls9c_ard_3-2-1_098081_2023-05-01_final.stac-item
2023-05-02 09:12:13	ga_ls9c_ard_3-2-1_089080_2023-05-01_final.stac-item
2023-05-02 09:13:25	ga_ls9c_ard_3-2-1_089083_2023-05-01_final.stac-item
2023-05-02 10:47:06	ga_ls9c_ard_3-2-1_105070_2023-05-02_final.stac-item
2023-05-03 11:33:32	ga_ls9c_ard_3-2-1_112078_2023-05-03_final.stac-item
2023-05-03 11:34:20	ga_ls9c_ard_3-2-1_112080_2023-05-03_final.stac-item
2023-05-06 10:25:32	ga_ls9c_ard_3-2-1_101078_2023-05-06_final.stac-item
2023-05-07 11:06:48	ga_ls9c_ard_3-2-1_108073_2023-05-07_final.stac-item
2023-05-08 11:51:39	ga_ls9c_ard_3-2-1_115077_2023-05-08_final.stac-item
2023-05-10 11:40:29	ga_ls9c_ard_3-2-1_113080_2023-05-10_final.stac-item
2023-05-12 11:27:19	ga_ls9c_ard_3-2-1_111078_2023-05-12_final.stac-item
2023-05-13 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-14 11:14:57	ga_ls9c_ard_3-2-1_109078_2023-05-14_final.stac-item
2023-05-15 11:57:48	ga_ls9c_ard_3-2-1_116077_2023-05-15_final.stac-item
2023-05-20 10:38:11	ga_ls9c_ard_3-2-1_103079_2023-05-20_final.stac-item
2023-05-21 09:41:45	ga_ls9c_ard_3-2-1_094077_2023-05-21_final.stac-item
2023-05-21 11:22:14	ga_ls9c_ard_3-2-1_110081_2023-05-21_final.stac-item
2023-05-22 10:25:00	ga_ls9c_ard_3-2-1_101077_2023-05-22_final.stac-item
2023-05-22 10:25:48	ga_ls9c_ard_3-2-1_101079_2023-05-22_final.stac-item
2023-07-08 11:21:04	ga_ls9c_ard_3-2-1_110078_2023-07-08_final.stac-item
2023-07-09 10:25:51	ga_ls9c_ard_3-2-1_101079_2023-07-09_final.stac-item
2023-07-10 11:06:19	ga_ls9c_ard_3-2-1_108072_2023-07-10_final.stac-item
2023-07-11 10:10:19	ga_ls9c_ard_3-2-1_099071_2023-07-11_final.stac-item
2023-07-11 11:50:23	ga_ls9c_ard_3-2-1_115074_2023-07-11_final.stac-item
2023-09-05 11:00:33	ga_ls9c_ard_3-2-1_107072_2023-09-05_final.stac-item
2023-09-05 11:03:45	ga_ls9c_ard_3-2-1_107080_2023-09-05_final.stac-item
2023-09-07 09:12:32	ga_ls9c_ard_3-2-1_089080_2023-09-06_final.stac-item
2023-09-07 09:13:19	ga_ls9c_ard_3-2-1_089082_2023-09-06_final.stac-item
2023-09-08 09:55:48	ga_ls9c_ard_3-2-1_096080_2023-09-08_final.stac-item
2023-09-08 11:33:53	ga_ls9c_ard_3-2-1_112078_2023-09-08_final.stac-item
2023-09-09 10:37:05	ga_ls9c_ard_3-2-1_103075_2023-09-09_final.stac-item
2023-09-09 10:37:53	ga_ls9c_ard_3-2-1_103077_2023-09-09_final.stac-item
2023-09-12 09:29:55	ga_ls9c_ard_3-2-1_092077_2023-09-11_final.stac-item
2023-09-13 11:51:17	ga_ls9c_ard_3-2-1_115075_2023-09-13_final.stac-item
2023-09-14 09:17:58	ga_ls9c_ard_3-2-1_090078_2023-09-13_final.stac-item
2023-09-14 10:58:51	ga_ls9c_ard_3-2-1_106083_2023-09-14_final.stac-item
2023-09-16 10:45:18	ga_ls9c_ard_3-2-1_104080_2023-09-16_final.stac-item
2023-09-17 11:25:46	ga_ls9c_ard_3-2-1_111073_2023-09-17_final.stac-item
2023-09-18 10:31:44	ga_ls9c_ard_3-2-1_102077_2023-09-18_final.stac-item
2023-09-18 10:32:32	ga_ls9c_ard_3-2-1_102079_2023-09-18_final.stac-item
2023-09-19 11:12:12	ga_ls9c_ard_3-2-1_109070_2023-09-19_final.stac-item
2023-09-20 10:18:59	ga_ls9c_ard_3-2-1_100076_2023-09-20_final.stac-item
2023-09-21 09:24:33	ga_ls9c_ard_3-2-1_091079_2023-09-20_final.stac-item
2023-09-22 11:45:29	ga_ls9c_ard_3-2-1_114076_2023-09-22_final.stac-item
2023-09-24 11:34:42	ga_ls9c_ard_3-2-1_112080_2023-09-24_final.stac-item
2023-09-25 10:37:28	ga_ls9c_ard_3-2-1_103076_2023-09-25_final.stac-item
2023-09-26 09:45:26	ga_ls9c_ard_3-2-1_094085_2023-09-26_final.stac-item
2023-09-27 10:24:41	ga_ls9c_ard_3-2-1_101075_2023-09-27_final.stac-item
2023-10-01 10:02:00	ga_ls9c_ard_3-2-1_097080_2023-10-01_final.stac-item
2023-10-03 11:26:34	ga_ls9c_ard_3-2-1_111075_2023-10-03_final.stac-item
2023-10-03 11:28:58	ga_ls9c_ard_3-2-1_111081_2023-10-03_final.stac-item
2023-10-05 11:12:38	ga_ls9c_ard_3-2-1_109071_2023-10-05_final.stac-item
2023-10-05 11:15:50	ga_ls9c_ard_3-2-1_109079_2023-10-05_final.stac-item
2023-10-08 11:46:21	ga_ls9c_ard_3-2-1_114078_2023-10-08_final.stac-item
2023-10-09 10:47:33	ga_ls9c_ard_3-2-1_105070_2023-10-09_final.stac-item
2023-10-12 11:23:17	ga_ls9c_ard_3-2-1_110082_2023-10-12_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