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

54 results

Time (local)	Label
2021-11-07 09:22:39	ga_ls9c_ard_3-2-1_090088_2021-11-06_final.stac-item
2021-12-11 11:08:17	ga_ls9c_ard_3-2-1_108075_2021-12-11_final.stac-item
2022-02-11 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-02-11_final.stac-item
2022-02-14 10:09:20	ga_ls9c_ard_3-2-1_099067_2022-02-14_final.stac-item
2022-02-23 10:02:40	ga_ls9c_ard_3-2-1_098066_2022-02-23_final.stac-item
2022-03-25 10:16:52	ga_ls9c_ard_3-2-1_100071_2022-03-25_final.stac-item
2022-05-03 10:27:12	ga_ls9c_ard_3-2-1_101082_2022-05-03_final.stac-item
2022-05-29 09:27:59	ga_ls9c_ard_3-2-1_091089_2022-05-28_final.stac-item
2022-06-21 09:27:38	ga_ls9c_ard_3-2-1_092072_2022-06-20_final.stac-item
2022-06-26 11:24:22	ga_ls9c_ard_3-2-1_111070_2022-06-26_final.stac-item
2022-07-02 09:14:47	ga_ls9c_ard_3-2-1_089086_2022-07-01_final.stac-item
2022-07-18 10:49:15	ga_ls9c_ard_3-2-1_105075_2022-07-18_final.stac-item
2022-07-18 10:49:39	ga_ls9c_ard_3-2-1_105076_2022-07-18_final.stac-item
2022-08-29 11:24:20	ga_ls9c_ard_3-2-1_111069_2022-08-29_final.stac-item
2022-10-04 09:22:50	ga_ls9c_ard_3-2-1_091074_2022-10-03_final.stac-item
2022-10-10 10:28:16	ga_ls9c_ard_3-2-1_101083_2022-10-10_final.stac-item
2023-01-13 09:40:38	ga_ls9c_ard_3-2-1_094072_2023-01-13_final.stac-item
2023-01-13 11:20:19	ga_ls9c_ard_3-2-1_110074_2023-01-13_final.stac-item
2023-02-01 10:10:00	ga_ls9c_ard_3-2-1_099068_2023-02-01_final.stac-item
2023-02-02 10:54:28	ga_ls9c_ard_3-2-1_106071_2023-02-02_final.stac-item
2023-02-21 11:26:01	ga_ls9c_ard_3-2-1_111073_2023-02-21_final.stac-item
2023-03-07 11:37:50	ga_ls9c_ard_3-2-1_113072_2023-03-07_final.stac-item
2023-03-11 09:34:35	ga_ls9c_ard_3-2-1_093073_2023-03-11_final.stac-item
2023-03-24 09:06:25	ga_ls9c_ard_3-2-1_088080_2023-03-23_final.stac-item
2023-03-24 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-03-23_final.stac-item
2023-04-05 09:27:49	ga_ls9c_ard_3-2-1_092072_2023-04-04_final.stac-item
2023-04-24 11:38:16	ga_ls9c_ard_3-2-1_113074_2023-04-24_final.stac-item
2023-05-10 09:56:25	ga_ls9c_ard_3-2-1_097067_2023-05-10_final.stac-item
2023-05-14 11:13:21	ga_ls9c_ard_3-2-1_109074_2023-05-14_final.stac-item
2023-05-16 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-05-15_final.stac-item
2023-07-01 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-07-01_final.stac-item
2023-07-27 10:08:21	ga_ls9c_ard_3-2-1_099066_2023-07-27_final.stac-item
2023-07-31 09:51:40	ga_ls9c_ard_3-2-1_095086_2023-07-31_final.stac-item
2023-08-20 09:22:17	ga_ls9c_ard_3-2-1_091074_2023-08-19_final.stac-item
2023-09-24 11:31:31	ga_ls9c_ard_3-2-1_112072_2023-09-24_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-10-28 09:40:26	ga_ls9c_ard_3-2-1_094072_2023-10-28_final.stac-item
2023-12-08 09:34:40	ga_ls9c_ard_3-2-1_093073_2023-12-08_final.stac-item
2024-01-07 11:24:19	ga_ls9c_ard_3-2-1_111069_2024-01-07_final.stac-item
2024-01-13 09:10:48	ga_ls9c_ard_3-2-1_089075_2024-01-12_final.stac-item
2024-01-13 10:49:41	ga_ls9c_ard_3-2-1_105075_2024-01-13_final.stac-item
2024-01-27 09:21:56	ga_ls9c_ard_3-2-1_091072_2024-01-26_final.stac-item
2024-01-31 10:36:08	ga_ls9c_ard_3-2-1_103072_2024-01-31_final.stac-item
2024-02-08 11:24:00	ga_ls9c_ard_3-2-1_111068_2024-02-08_final.stac-item
2024-02-08 11:26:24	ga_ls9c_ard_3-2-1_111074_2024-02-08_final.stac-item
2024-02-29 10:09:53	ga_ls9c_ard_3-2-1_098084_2024-02-29_final.stac-item
2024-03-15 09:22:14	ga_ls9c_ard_3-2-1_091073_2024-03-14_final.stac-item
2024-03-24 09:17:36	ga_ls9c_ard_3-2-1_090077_2024-03-23_final.stac-item
2024-04-09 09:20:16	ga_ls9c_ard_3-2-1_090084_2024-04-08_final.stac-item
2024-04-15 10:16:48	ga_ls9c_ard_3-2-1_100071_2024-04-15_final.stac-item
2024-04-18 10:46:26	ga_ls9c_ard_3-2-1_105068_2024-04-18_final.stac-item
2024-05-13 10:41:59	ga_ls9c_ard_3-2-1_104073_2024-05-13_final.stac-item
2024-05-18 09:21:57	ga_ls9c_ard_3-2-1_091074_2024-05-17_nrt.stac-item
2024-05-25 11:06:58	ga_ls9c_ard_3-2-1_108074_2024-05-25_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