Search ga_ls9c_ard_3 across 2023

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
2023-01-05 10:33:19	ga_ls9c_ard_3-2-1_102080_2023-01-05_final.stac-item
2023-01-06 11:16:34	ga_ls9c_ard_3-2-1_109080_2023-01-06_final.stac-item
2023-01-08 09:24:55	ga_ls9c_ard_3-2-1_091079_2023-01-07_final.stac-item
2023-01-10 09:13:21	ga_ls9c_ard_3-2-1_089081_2023-01-09_final.stac-item
2023-01-13 09:44:14	ga_ls9c_ard_3-2-1_094081_2023-01-13_final.stac-item
2023-01-14 10:26:41	ga_ls9c_ard_3-2-1_101079_2023-01-14_final.stac-item
2023-01-14 10:27:05	ga_ls9c_ard_3-2-1_101080_2023-01-14_final.stac-item
2023-01-15 09:31:03	ga_ls9c_ard_3-2-1_092079_2023-01-15_final.stac-item
2023-01-19 10:45:32	ga_ls9c_ard_3-2-1_104080_2023-01-19_final.stac-item
2023-01-21 10:33:09	ga_ls9c_ard_3-2-1_102080_2023-01-21_final.stac-item
2023-01-24 09:24:50	ga_ls9c_ard_3-2-1_091079_2023-01-23_final.stac-item
2023-01-26 09:13:18	ga_ls9c_ard_3-2-1_089081_2023-01-25_final.stac-item
2023-01-29 09:44:15	ga_ls9c_ard_3-2-1_094081_2023-01-29_final.stac-item
2023-01-30 10:27:07	ga_ls9c_ard_3-2-1_101080_2023-01-30_final.stac-item
2023-01-31 09:31:07	ga_ls9c_ard_3-2-1_092079_2023-01-31_final.stac-item
2023-02-06 10:33:22	ga_ls9c_ard_3-2-1_102080_2023-02-06_final.stac-item
2023-02-07 11:16:38	ga_ls9c_ard_3-2-1_109080_2023-02-07_final.stac-item
2023-02-09 09:24:59	ga_ls9c_ard_3-2-1_091079_2023-02-08_final.stac-item
2023-02-11 09:13:25	ga_ls9c_ard_3-2-1_089081_2023-02-10_final.stac-item
2023-02-14 09:44:17	ga_ls9c_ard_3-2-1_094081_2023-02-14_final.stac-item
2023-02-14 11:22:46	ga_ls9c_ard_3-2-1_110080_2023-02-14_final.stac-item
2023-02-15 10:26:44	ga_ls9c_ard_3-2-1_101079_2023-02-15_final.stac-item
2023-02-20 09:07:06	ga_ls9c_ard_3-2-1_088081_2023-02-19_final.stac-item
2023-02-25 09:24:44	ga_ls9c_ard_3-2-1_091079_2023-02-24_final.stac-item
2023-02-27 09:13:11	ga_ls9c_ard_3-2-1_089081_2023-02-26_final.stac-item
2023-03-03 10:26:31	ga_ls9c_ard_3-2-1_101079_2023-03-03_final.stac-item
2023-03-11 11:16:15	ga_ls9c_ard_3-2-1_109080_2023-03-11_final.stac-item
2023-03-13 09:24:37	ga_ls9c_ard_3-2-1_091079_2023-03-12_final.stac-item
2023-03-13 11:03:54	ga_ls9c_ard_3-2-1_107080_2023-03-13_final.stac-item
2023-03-15 09:13:04	ga_ls9c_ard_3-2-1_089081_2023-03-14_final.stac-item
2023-03-18 09:43:57	ga_ls9c_ard_3-2-1_094081_2023-03-18_final.stac-item
2023-03-18 11:22:26	ga_ls9c_ard_3-2-1_110080_2023-03-18_final.stac-item
2023-03-19 10:26:25	ga_ls9c_ard_3-2-1_101079_2023-03-19_final.stac-item
2023-03-20 09:30:47	ga_ls9c_ard_3-2-1_092079_2023-03-20_final.stac-item
2023-03-20 11:10:04	ga_ls9c_ard_3-2-1_108080_2023-03-20_final.stac-item
2023-03-24 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-03-23_final.stac-item
2023-03-25 11:28:32	ga_ls9c_ard_3-2-1_111080_2023-03-25_final.stac-item
2023-03-26 10:32:53	ga_ls9c_ard_3-2-1_102080_2023-03-26_final.stac-item
2023-03-27 11:16:08	ga_ls9c_ard_3-2-1_109080_2023-03-27_final.stac-item
2023-03-29 09:24:26	ga_ls9c_ard_3-2-1_091079_2023-03-28_final.stac-item
2023-03-31 09:12:52	ga_ls9c_ard_3-2-1_089081_2023-03-30_final.stac-item
2023-04-03 09:43:46	ga_ls9c_ard_3-2-1_094081_2023-04-03_final.stac-item
2023-04-04 10:26:14	ga_ls9c_ard_3-2-1_101079_2023-04-04_final.stac-item
2023-04-09 09:06:39	ga_ls9c_ard_3-2-1_088081_2023-04-08_final.stac-item
2023-04-11 10:32:45	ga_ls9c_ard_3-2-1_102080_2023-04-11_final.stac-item
2023-04-13 10:19:58	ga_ls9c_ard_3-2-1_100079_2023-04-13_final.stac-item
2023-04-14 09:24:20	ga_ls9c_ard_3-2-1_091079_2023-04-13_final.stac-item
2023-04-16 09:12:46	ga_ls9c_ard_3-2-1_089081_2023-04-15_final.stac-item
2023-04-19 09:43:40	ga_ls9c_ard_3-2-1_094081_2023-04-19_final.stac-item
2023-04-20 10:26:08	ga_ls9c_ard_3-2-1_101079_2023-04-20_final.stac-item
2023-04-20 10:26:32	ga_ls9c_ard_3-2-1_101080_2023-04-20_final.stac-item
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-30 09:24:13	ga_ls9c_ard_3-2-1_091079_2023-04-29_final.stac-item
2023-05-02 09:12:37	ga_ls9c_ard_3-2-1_089081_2023-05-01_final.stac-item
2023-05-05 09:43:28	ga_ls9c_ard_3-2-1_094081_2023-05-05_final.stac-item
2023-05-05 11:21:57	ga_ls9c_ard_3-2-1_110080_2023-05-05_final.stac-item
2023-05-06 10:25:56	ga_ls9c_ard_3-2-1_101079_2023-05-06_final.stac-item
2023-05-06 10:26:20	ga_ls9c_ard_3-2-1_101080_2023-05-06_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-14 11:15:45	ga_ls9c_ard_3-2-1_109080_2023-05-14_final.stac-item
2023-05-16 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-05-15_final.stac-item
2023-05-18 09:12:30	ga_ls9c_ard_3-2-1_089081_2023-05-17_final.stac-item
2023-05-21 09:43:21	ga_ls9c_ard_3-2-1_094081_2023-05-21_final.stac-item
2023-05-21 11:21:50	ga_ls9c_ard_3-2-1_110080_2023-05-21_final.stac-item
2023-05-22 10:25:48	ga_ls9c_ard_3-2-1_101079_2023-05-22_final.stac-item
2023-05-27 09:06:13	ga_ls9c_ard_3-2-1_088081_2023-05-26_final.stac-item
2023-05-29 10:32:20	ga_ls9c_ard_3-2-1_102080_2023-05-29_final.stac-item
2023-05-30 11:15:36	ga_ls9c_ard_3-2-1_109080_2023-05-30_final.stac-item
2023-06-01 09:23:57	ga_ls9c_ard_3-2-1_091079_2023-05-31_final.stac-item
2023-06-03 09:12:23	ga_ls9c_ard_3-2-1_089081_2023-06-02_final.stac-item
2023-06-06 11:21:44	ga_ls9c_ard_3-2-1_110080_2023-06-06_final.stac-item
2023-06-07 10:25:43	ga_ls9c_ard_3-2-1_101079_2023-06-07_final.stac-item
2023-06-16 10:19:25	ga_ls9c_ard_3-2-1_100079_2023-06-16_final.stac-item
2023-06-17 09:23:48	ga_ls9c_ard_3-2-1_091079_2023-06-16_final.stac-item
2023-06-19 09:12:14	ga_ls9c_ard_3-2-1_089081_2023-06-18_final.stac-item
2023-06-22 09:43:08	ga_ls9c_ard_3-2-1_094081_2023-06-22_final.stac-item
2023-06-22 11:21:37	ga_ls9c_ard_3-2-1_110080_2023-06-22_final.stac-item
2023-06-23 10:25:36	ga_ls9c_ard_3-2-1_101079_2023-06-23_final.stac-item
2023-06-28 09:06:07	ga_ls9c_ard_3-2-1_088081_2023-06-27_final.stac-item
2023-07-01 11:15:35	ga_ls9c_ard_3-2-1_109080_2023-07-01_final.stac-item
2023-07-02 10:19:35	ga_ls9c_ard_3-2-1_100079_2023-07-02_final.stac-item
2023-07-03 09:23:59	ga_ls9c_ard_3-2-1_091079_2023-07-02_final.stac-item
2023-07-05 09:12:26	ga_ls9c_ard_3-2-1_089081_2023-07-04_final.stac-item
2023-07-08 09:43:22	ga_ls9c_ard_3-2-1_094081_2023-07-08_final.stac-item
2023-07-08 11:21:52	ga_ls9c_ard_3-2-1_110080_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
2023-07-17 11:15:44	ga_ls9c_ard_3-2-1_109080_2023-07-17_final.stac-item
2023-08-02 11:15:50	ga_ls9c_ard_3-2-1_109080_2023-08-02_final.stac-item
2023-08-09 11:22:04	ga_ls9c_ard_3-2-1_110080_2023-08-09_final.stac-item
2023-08-18 11:15:53	ga_ls9c_ard_3-2-1_109080_2023-08-18_final.stac-item
2023-08-25 11:22:11	ga_ls9c_ard_3-2-1_110080_2023-08-25_final.stac-item
2023-10-28 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-10-30 09:30:50	ga_ls9c_ard_3-2-1_092079_2023-10-30_final.stac-item
2023-11-06 11:16:17	ga_ls9c_ard_3-2-1_109080_2023-11-06_final.stac-item
2023-11-08 09:24:39	ga_ls9c_ard_3-2-1_091079_2023-11-07_final.stac-item
2023-12-01 09:30:58	ga_ls9c_ard_3-2-1_092079_2023-12-01_final.stac-item
2023-12-08 11:16:20	ga_ls9c_ard_3-2-1_109080_2023-12-08_final.stac-item
2023-12-10 09:24:43	ga_ls9c_ard_3-2-1_091079_2023-12-09_final.stac-item
2023-12-17 09:30:59	ga_ls9c_ard_3-2-1_092079_2023-12-17_final.stac-item

Return to ga_ls9c_ard_3 across 2023 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

2023

All months