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

69 results

Time (local)	Label
2021-11-11 10:19:51	ga_ls9c_ard_3-2-1_100078_2021-11-11_final.stac-item
2021-11-17 09:21:17	ga_ls9c_ard_3-2-1_091072_2021-11-16_final.stac-item
2021-11-24 10:42:47	ga_ls9c_ard_3-2-1_104070_2021-11-24_final.stac-item
2021-12-13 10:53:30	ga_ls9c_ard_3-2-1_106069_2021-12-13_final.stac-item
2021-12-20 09:23:57	ga_ls9c_ard_3-2-1_091077_2021-12-19_final.stac-item
2022-01-04 10:17:11	ga_ls9c_ard_3-2-1_100071_2022-01-04_final.stac-item
2022-01-19 11:11:59	ga_ls9c_ard_3-2-1_109069_2022-01-19_final.stac-item
2022-02-11 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-02-11_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-09 10:16:56	ga_ls9c_ard_3-2-1_100071_2022-03-09_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-04-03 10:09:28	ga_ls9c_ard_3-2-1_099068_2022-04-03_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-05-21 10:13:26	ga_ls9c_ard_3-2-1_099079_2022-05-21_final.stac-item
2022-06-07 10:55:31	ga_ls9c_ard_3-2-1_106076_2022-06-07_final.stac-item
2022-06-16 10:49:02	ga_ls9c_ard_3-2-1_105075_2022-06-16_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-08-25 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-08-25_final.stac-item
2022-09-05 11:34:05	ga_ls9c_ard_3-2-1_112078_2022-09-05_final.stac-item
2022-09-10 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-09-10_final.stac-item
2022-10-04 09:22:50	ga_ls9c_ard_3-2-1_091074_2022-10-03_final.stac-item
2022-10-22 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-10-22_final.stac-item
2022-10-24 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-10-24_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-11-29 10:10:45	ga_ls9c_ard_3-2-1_099070_2022-11-29_final.stac-item
2022-12-22 10:19:42	ga_ls9c_ard_3-2-1_100077_2022-12-22_final.stac-item
2022-12-25 09:14:31	ga_ls9c_ard_3-2-1_089084_2022-12-24_final.stac-item
2023-01-05 10:33:43	ga_ls9c_ard_3-2-1_102081_2023-01-05_final.stac-item
2023-01-08 09:28:07	ga_ls9c_ard_3-2-1_091087_2023-01-07_final.stac-item
2023-01-12 10:36:16	ga_ls9c_ard_3-2-1_103072_2023-01-12_final.stac-item
2023-01-23 10:17:14	ga_ls9c_ard_3-2-1_100071_2023-01-23_final.stac-item
2023-01-26 10:47:00	ga_ls9c_ard_3-2-1_105068_2023-01-26_final.stac-item
2023-02-27 09:11:59	ga_ls9c_ard_3-2-1_089078_2023-02-26_final.stac-item
2023-04-29 10:16:40	ga_ls9c_ard_3-2-1_100071_2023-04-29_final.stac-item
2023-05-08 11:52:27	ga_ls9c_ard_3-2-1_115079_2023-05-08_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-06-12 09:06:30	ga_ls9c_ard_3-2-1_088082_2023-06-11_final.stac-item
2023-06-15 09:38:33	ga_ls9c_ard_3-2-1_093085_2023-06-15_final.stac-item
2023-07-30 09:06:48	ga_ls9c_ard_3-2-1_088082_2023-07-29_final.stac-item
2023-08-05 10:03:05	ga_ls9c_ard_3-2-1_098068_2023-08-05_final.stac-item
2023-08-17 10:29:50	ga_ls9c_ard_3-2-1_102073_2023-08-17_final.stac-item
2023-08-27 11:07:51	ga_ls9c_ard_3-2-1_108075_2023-08-27_final.stac-item
2023-09-03 09:40:23	ga_ls9c_ard_3-2-1_093088_2023-09-03_final.stac-item
2023-09-15 09:57:39	ga_ls9c_ard_3-2-1_097069_2023-09-15_final.stac-item
2023-09-19 09:40:30	ga_ls9c_ard_3-2-1_093088_2023-09-19_final.stac-item
2023-10-21 09:34:42	ga_ls9c_ard_3-2-1_093073_2023-10-21_final.stac-item
2023-10-24 10:10:22	ga_ls9c_ard_3-2-1_098085_2023-10-24_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-11-11 11:31:39	ga_ls9c_ard_3-2-1_112072_2023-11-11_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-18 09:56:59	ga_ls9c_ard_3-2-1_097067_2023-11-18_final.stac-item
2023-11-19 10:46:14	ga_ls9c_ard_3-2-1_104082_2023-11-19_final.stac-item
2023-12-08 09:39:27	ga_ls9c_ard_3-2-1_093085_2023-12-08_final.stac-item
2024-01-04 10:53:02	ga_ls9c_ard_3-2-1_106068_2024-01-04_final.stac-item
2024-01-09 11:13:59	ga_ls9c_ard_3-2-1_109074_2024-01-09_final.stac-item
2024-01-31 10:34:32	ga_ls9c_ard_3-2-1_103068_2024-01-31_final.stac-item
2024-01-31 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-31_final.stac-item
2024-02-21 09:18:01	ga_ls9c_ard_3-2-1_090078_2024-02-20_final.stac-item
2024-02-23 09:07:12	ga_ls9c_ard_3-2-1_088082_2024-02-22_final.stac-item
2024-02-29 10:03:30	ga_ls9c_ard_3-2-1_098068_2024-02-29_final.stac-item
2024-03-08 09:21:16	ga_ls9c_ard_3-2-1_090086_2024-03-07_final.stac-item
2024-04-06 10:27:28	ga_ls9c_ard_3-2-1_101082_2024-04-06_final.stac-item
2024-04-08 10:08:43	ga_ls9c_ard_3-2-1_099066_2024-04-08_final.stac-item
2024-04-11 10:45:58	ga_ls9c_ard_3-2-1_104082_2024-04-11_final.stac-item
2024-04-16 09:22:21	ga_ls9c_ard_3-2-1_091074_2024-04-15_final.stac-item
2024-04-24 10:10:20	ga_ls9c_ard_3-2-1_099071_2024-04-24_final.stac-item
2024-05-25 09:27:17	ga_ls9c_ard_3-2-1_092072_2024-05-24_final.stac-item
2024-06-03 09:22:15	ga_ls9c_ard_3-2-1_091075_2024-06-02_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