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
2021-11-08 09:54:15	ga_ls9c_ard_3-2-1_097067_2021-11-08_final.stac-item
2021-11-13 09:57:07	ga_ls9c_ard_3-2-1_097068_2021-11-13_final.stac-item
2021-11-23 10:02:50	ga_ls9c_ard_3-2-1_098070_2021-11-23_final.stac-item
2021-12-05 10:08:08	ga_ls9c_ard_3-2-1_098079_2021-12-05_final.stac-item
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2022-02-06 09:22:44	ga_ls9c_ard_3-2-1_091074_2022-02-05_final.stac-item
2022-02-27 11:19:10	ga_ls9c_ard_3-2-1_110072_2022-02-27_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-04-10 10:19:36	ga_ls9c_ard_3-2-1_100078_2022-04-10_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-05-14 10:03:45	ga_ls9c_ard_3-2-1_098070_2022-05-14_final.stac-item
2022-05-23 09:57:05	ga_ls9c_ard_3-2-1_097069_2022-05-23_final.stac-item
2022-05-25 11:23:36	ga_ls9c_ard_3-2-1_111069_2022-05-25_final.stac-item
2022-06-08 09:57:30	ga_ls9c_ard_3-2-1_097070_2022-06-08_final.stac-item
2022-06-16 09:11:45	ga_ls9c_ard_3-2-1_089079_2022-06-15_final.stac-item
2022-07-05 11:18:10	ga_ls9c_ard_3-2-1_110070_2022-07-05_final.stac-item
2022-07-06 10:27:44	ga_ls9c_ard_3-2-1_101083_2022-07-06_final.stac-item
2022-07-10 09:57:24	ga_ls9c_ard_3-2-1_097069_2022-07-10_final.stac-item
2022-07-10 11:41:52	ga_ls9c_ard_3-2-1_113083_2022-07-10_final.stac-item
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-08-22 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-08-22_final.stac-item
2022-09-04 10:49:14	ga_ls9c_ard_3-2-1_105074_2022-09-04_final.stac-item
2022-09-26 10:13:28	ga_ls9c_ard_3-2-1_099077_2022-09-26_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_final.stac-item
2022-10-03 10:19:39	ga_ls9c_ard_3-2-1_100077_2022-10-03_final.stac-item
2022-10-15 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-14_final.stac-item
2022-10-28 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-10-28_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-10-31 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-30_final.stac-item
2022-11-06 10:04:10	ga_ls9c_ard_3-2-1_098069_2022-11-06_final.stac-item
2022-11-13 10:10:48	ga_ls9c_ard_3-2-1_099070_2022-11-13_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-10 10:53:02	ga_ls9c_ard_3-2-1_105083_2023-01-10_final.stac-item
2023-02-20 09:07:30	ga_ls9c_ard_3-2-1_088082_2023-02-19_final.stac-item
2023-03-29 09:21:39	ga_ls9c_ard_3-2-1_091072_2023-03-28_final.stac-item
2023-05-26 11:41:55	ga_ls9c_ard_3-2-1_113084_2023-05-26_final.stac-item
2023-06-25 10:09:38	ga_ls9c_ard_3-2-1_099070_2023-06-25_final.stac-item
2023-07-04 10:02:28	ga_ls9c_ard_3-2-1_098067_2023-07-04_final.stac-item
2023-07-06 09:54:31	ga_ls9c_ard_3-2-1_096078_2023-07-06_final.stac-item
2023-08-07 11:33:37	ga_ls9c_ard_3-2-1_112078_2023-08-07_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-15 10:42:12	ga_ls9c_ard_3-2-1_104073_2023-08-15_final.stac-item
2023-08-20 09:27:28	ga_ls9c_ard_3-2-1_091087_2023-08-19_final.stac-item
2023-08-28 10:13:02	ga_ls9c_ard_3-2-1_099077_2023-08-28_final.stac-item
2023-09-03 09:34:00	ga_ls9c_ard_3-2-1_093072_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
2023-09-23 09:16:34	ga_ls9c_ard_3-2-1_089090_2023-09-22_final.stac-item
2023-10-08 10:03:53	ga_ls9c_ard_3-2-1_098069_2023-10-08_final.stac-item
2023-10-21 09:34:42	ga_ls9c_ard_3-2-1_093073_2023-10-21_final.stac-item
2023-11-04 09:46:08	ga_ls9c_ard_3-2-1_095071_2023-11-04_final.stac-item
2023-11-14 10:26:03	ga_ls9c_ard_3-2-1_101078_2023-11-14_final.stac-item
2023-12-03 09:17:23	ga_ls9c_ard_3-2-1_090076_2023-12-02_final.stac-item
2023-12-12 09:11:59	ga_ls9c_ard_3-2-1_089078_2023-12-11_final.stac-item
2023-12-27 11:47:45	ga_ls9c_ard_3-2-1_114081_2023-12-27_final.stac-item
2023-12-28 09:15:14	ga_ls9c_ard_3-2-1_089086_2023-12-27_final.stac-item
2023-12-28 10:50:08	ga_ls9c_ard_3-2-1_105076_2023-12-28_final.stac-item
2024-01-18 09:28:56	ga_ls9c_ard_3-2-1_092074_2024-01-17_final.stac-item
2024-02-05 09:23:00	ga_ls9c_ard_3-2-1_090090_2024-02-04_final.stac-item
2024-02-17 11:18:31	ga_ls9c_ard_3-2-1_110070_2024-02-17_final.stac-item
2024-03-24 09:17:12	ga_ls9c_ard_3-2-1_090076_2024-03-23_final.stac-item
2024-03-24 09:22:48	ga_ls9c_ard_3-2-1_090090_2024-03-23_final.stac-item
2024-04-09 09:22:39	ga_ls9c_ard_3-2-1_090090_2024-04-08_final.stac-item
2024-04-11 09:06:41	ga_ls9c_ard_3-2-1_088081_2024-04-10_final.stac-item
2024-05-03 10:03:20	ga_ls9c_ard_3-2-1_098069_2024-05-03_final.stac-item
2024-05-18 09:21:33	ga_ls9c_ard_3-2-1_091073_2024-05-17_nrt.stac-item
2024-05-19 10:03:37	ga_ls9c_ard_3-2-1_098070_2024-05-19_nrt.stac-item
2024-05-26 10:12:31	ga_ls9c_ard_3-2-1_099077_2024-05-26_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years