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

58 results

Time (local)	Label
2021-11-12 09:20:21	ga_ls9c_ard_3-2-1_091076_2021-11-11_final.stac-item
2021-11-12 10:56:37	ga_ls9c_ard_3-2-1_106070_2021-11-12_final.stac-item
2021-11-22 09:29:38	ga_ls9c_ard_3-2-1_091087_2021-11-21_final.stac-item
2021-12-06 09:16:54	ga_ls9c_ard_3-2-1_089090_2021-12-05_final.stac-item
2021-12-12 11:53:07	ga_ls9c_ard_3-2-1_115079_2021-12-12_final.stac-item
2021-12-13 10:53:06	ga_ls9c_ard_3-2-1_106068_2021-12-13_final.stac-item
2022-01-14 10:58:36	ga_ls9c_ard_3-2-1_106082_2022-01-14_final.stac-item
2022-03-31 11:23:03	ga_ls9c_ard_3-2-1_110082_2022-03-31_final.stac-item
2022-04-04 09:21:50	ga_ls9c_ard_3-2-1_090088_2022-04-03_final.stac-item
2022-04-23 11:24:14	ga_ls9c_ard_3-2-1_111070_2022-04-23_final.stac-item
2022-04-24 10:27:49	ga_ls9c_ard_3-2-1_102068_2022-04-24_final.stac-item
2022-04-26 10:21:27	ga_ls9c_ard_3-2-1_100083_2022-04-26_final.stac-item
2022-04-28 10:04:18	ga_ls9c_ard_3-2-1_098071_2022-04-28_final.stac-item
2022-05-09 11:24:34	ga_ls9c_ard_3-2-1_111071_2022-05-09_final.stac-item
2022-05-22 09:17:00	ga_ls9c_ard_3-2-1_090077_2022-05-21_final.stac-item
2022-05-31 09:11:14	ga_ls9c_ard_3-2-1_089078_2022-05-30_final.stac-item
2022-06-05 09:30:59	ga_ls9c_ard_3-2-1_092081_2022-06-05_final.stac-item
2022-06-14 09:28:04	ga_ls9c_ard_3-2-1_091089_2022-06-13_final.stac-item
2022-06-21 09:28:25	ga_ls9c_ard_3-2-1_092074_2022-06-20_final.stac-item
2022-07-10 09:57:00	ga_ls9c_ard_3-2-1_097068_2022-07-10_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-08-18 10:09:33	ga_ls9c_ard_3-2-1_098083_2022-08-18_final.stac-item
2022-08-18 10:09:57	ga_ls9c_ard_3-2-1_098084_2022-08-18_final.stac-item
2022-09-05 11:36:05	ga_ls9c_ard_3-2-1_112083_2022-09-05_final.stac-item
2022-10-08 10:36:12	ga_ls9c_ard_3-2-1_103072_2022-10-08_final.stac-item
2022-10-12 10:09:56	ga_ls9c_ard_3-2-1_099068_2022-10-12_final.stac-item
2022-10-29 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-10-29_final.stac-item
2022-10-29 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-10-29_final.stac-item
2022-11-07 09:16:32	ga_ls9c_ard_3-2-1_089089_2022-11-06_final.stac-item
2022-11-14 10:59:15	ga_ls9c_ard_3-2-1_106083_2022-11-14_final.stac-item
2023-01-22 11:14:26	ga_ls9c_ard_3-2-1_109075_2023-01-22_final.stac-item
2023-03-01 10:34:31	ga_ls9c_ard_3-2-1_103068_2023-03-01_final.stac-item
2023-04-22 10:15:21	ga_ls9c_ard_3-2-1_099083_2023-04-22_final.stac-item
2023-05-10 11:38:54	ga_ls9c_ard_3-2-1_113076_2023-05-10_final.stac-item
2023-05-24 11:52:17	ga_ls9c_ard_3-2-1_115079_2023-05-24_final.stac-item
2023-06-05 10:38:53	ga_ls9c_ard_3-2-1_103081_2023-06-05_final.stac-item
2023-06-17 11:03:05	ga_ls9c_ard_3-2-1_107080_2023-06-17_final.stac-item
2023-10-10 11:32:26	ga_ls9c_ard_3-2-1_112074_2023-10-10_final.stac-item
2023-10-31 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-10-31_final.stac-item
2023-11-22 09:34:43	ga_ls9c_ard_3-2-1_093073_2023-11-22_final.stac-item
2023-12-13 11:31:45	ga_ls9c_ard_3-2-1_112072_2023-12-13_final.stac-item
2023-12-16 10:25:48	ga_ls9c_ard_3-2-1_101077_2023-12-16_final.stac-item
2023-12-31 09:40:55	ga_ls9c_ard_3-2-1_094073_2023-12-31_final.stac-item
2024-01-17 10:26:09	ga_ls9c_ard_3-2-1_101078_2024-01-17_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_final.stac-item
2024-01-30 11:32:33	ga_ls9c_ard_3-2-1_112074_2024-01-30_final.stac-item
2024-02-09 10:29:34	ga_ls9c_ard_3-2-1_102071_2024-02-09_final.stac-item
2024-02-28 09:23:49	ga_ls9c_ard_3-2-1_091077_2024-02-27_final.stac-item
2024-03-05 10:28:03	ga_ls9c_ard_3-2-1_101083_2024-03-05_final.stac-item
2024-03-06 09:28:51	ga_ls9c_ard_3-2-1_092074_2024-03-05_final.stac-item
2024-03-23 10:08:51	ga_ls9c_ard_3-2-1_099066_2024-03-23_final.stac-item
2024-04-16 09:22:45	ga_ls9c_ard_3-2-1_091075_2024-04-15_final.stac-item
2024-04-18 09:13:32	ga_ls9c_ard_3-2-1_089083_2024-04-17_final.stac-item
2024-04-27 10:42:03	ga_ls9c_ard_3-2-1_104073_2024-04-27_final.stac-item
2024-04-30 09:34:27	ga_ls9c_ard_3-2-1_093074_2024-04-30_final.stac-item
2024-05-04 09:16:06	ga_ls9c_ard_3-2-1_089090_2024-05-03_final.stac-item
2024-05-19 10:09:36	ga_ls9c_ard_3-2-1_098085_2024-05-19_nrt.stac-item
2024-05-20 09:11:35	ga_ls9c_ard_3-2-1_089079_2024-05-19_nrt.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