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

50 results

Time (local)	Label
2021-11-02 10:54:03	ga_ls9c_ard_3-2-1_106076_2021-11-02_final.stac-item
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final.stac-item
2021-12-17 10:33:31	ga_ls9c_ard_3-2-1_102081_2021-12-17_final.stac-item
2021-12-22 10:46:54	ga_ls9c_ard_3-2-1_105068_2021-12-22_final.stac-item
2022-01-21 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-20_final.stac-item
2022-02-22 09:22:36	ga_ls9c_ard_3-2-1_091074_2022-02-21_final.stac-item
2022-02-28 10:22:44	ga_ls9c_ard_3-2-1_101070_2022-02-28_final.stac-item
2022-03-09 11:57:49	ga_ls9c_ard_3-2-1_116076_2022-03-09_final.stac-item
2022-03-24 11:11:42	ga_ls9c_ard_3-2-1_109069_2022-03-24_final.stac-item
2022-04-20 09:16:29	ga_ls9c_ard_3-2-1_090075_2022-04-19_final.stac-item
2022-05-06 10:57:41	ga_ls9c_ard_3-2-1_106081_2022-05-06_final.stac-item
2022-05-31 09:16:02	ga_ls9c_ard_3-2-1_089090_2022-05-30_final.stac-item
2022-06-18 10:38:42	ga_ls9c_ard_3-2-1_103080_2022-06-18_final.stac-item
2022-09-05 11:35:17	ga_ls9c_ard_3-2-1_112081_2022-09-05_final.stac-item
2022-10-22 10:49:52	ga_ls9c_ard_3-2-1_105075_2022-10-22_final.stac-item
2022-10-25 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-10-25_final.stac-item
2022-10-30 09:57:12	ga_ls9c_ard_3-2-1_097067_2022-10-30_final.stac-item
2022-11-01 09:52:01	ga_ls9c_ard_3-2-1_095085_2022-11-01_final.stac-item
2022-11-26 11:24:20	ga_ls9c_ard_3-2-1_110084_2022-11-26_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-02-17 10:13:33	ga_ls9c_ard_3-2-1_099077_2023-02-17_final.stac-item
2023-03-10 10:33:47	ga_ls9c_ard_3-2-1_102082_2023-03-10_final.stac-item
2023-03-18 09:39:58	ga_ls9c_ard_3-2-1_094071_2023-03-18_final.stac-item
2023-03-27 11:17:19	ga_ls9c_ard_3-2-1_109083_2023-03-27_final.stac-item
2023-04-16 10:51:39	ga_ls9c_ard_3-2-1_105081_2023-04-16_final.stac-item
2023-05-30 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-05-30_final.stac-item
2023-06-08 09:31:16	ga_ls9c_ard_3-2-1_092082_2023-06-08_final.stac-item
2023-06-29 09:51:25	ga_ls9c_ard_3-2-1_095086_2023-06-29_final.stac-item
2023-06-29 09:51:48	ga_ls9c_ard_3-2-1_095087_2023-06-29_final.stac-item
2023-07-12 10:55:10	ga_ls9c_ard_3-2-1_106075_2023-07-12_final.stac-item
2023-07-29 11:41:41	ga_ls9c_ard_3-2-1_113083_2023-07-29_final.stac-item
2023-08-20 09:28:40	ga_ls9c_ard_3-2-1_091090_2023-08-19_final.stac-item
2023-08-22 10:51:38	ga_ls9c_ard_3-2-1_105081_2023-08-22_final.stac-item
2023-08-25 09:39:42	ga_ls9c_ard_3-2-1_094071_2023-08-25_final.stac-item
2023-08-31 10:42:22	ga_ls9c_ard_3-2-1_104073_2023-08-31_final.stac-item
2023-10-28 09:46:25	ga_ls9c_ard_3-2-1_094087_2023-10-28_final.stac-item
2023-11-11 11:36:26	ga_ls9c_ard_3-2-1_112084_2023-11-11_final.stac-item
2023-11-22 09:34:43	ga_ls9c_ard_3-2-1_093073_2023-11-22_final.stac-item
2023-11-23 11:57:40	ga_ls9c_ard_3-2-1_116075_2023-11-23_final.stac-item
2023-11-23 11:58:04	ga_ls9c_ard_3-2-1_116076_2023-11-23_final.stac-item
2023-12-10 11:02:25	ga_ls9c_ard_3-2-1_107076_2023-12-10_final.stac-item
2023-12-31 09:40:55	ga_ls9c_ard_3-2-1_094073_2023-12-31_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-02-29 11:47:34	ga_ls9c_ard_3-2-1_114081_2024-02-29_final.stac-item
2024-03-14 10:22:15	ga_ls9c_ard_3-2-1_100084_2024-03-14_final.stac-item
2024-04-05 11:24:18	ga_ls9c_ard_3-2-1_110085_2024-04-05_final.stac-item
2024-04-09 12:31:15	ga_ls9c_ard_3-2-1_122067_2024-04-09_final.stac-item
2024-04-21 11:18:02	ga_ls9c_ard_3-2-1_110070_2024-04-21_final.stac-item
2024-04-24 10:08:21	ga_ls9c_ard_3-2-1_099066_2024-04-24_final.stac-item
2024-05-18 11:03:38	ga_ls9c_ard_3-2-1_107081_2024-05-18_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