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

53 results

Time (local)	Label
2021-12-06 10:50:11	ga_ls9c_ard_3-2-1_105076_2021-12-06_final.stac-item
2021-12-29 10:53:53	ga_ls9c_ard_3-2-1_106070_2021-12-29_final.stac-item
2022-01-19 09:34:42	ga_ls9c_ard_3-2-1_093073_2022-01-19_final.stac-item
2022-01-23 09:16:47	ga_ls9c_ard_3-2-1_089090_2022-01-22_final.stac-item
2022-02-06 09:28:20	ga_ls9c_ard_3-2-1_091088_2022-02-05_final.stac-item
2022-03-22 11:24:04	ga_ls9c_ard_3-2-1_111069_2022-03-22_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-03-29 11:34:12	ga_ls9c_ard_3-2-1_112079_2022-03-29_final.stac-item
2022-05-29 11:04:28	ga_ls9c_ard_3-2-1_107083_2022-05-29_final.stac-item
2022-07-16 09:21:30	ga_ls9c_ard_3-2-1_091072_2022-07-15_final.stac-item
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final.stac-item
2022-08-02 10:07:01	ga_ls9c_ard_3-2-1_098077_2022-08-02_final.stac-item
2022-08-08 09:34:23	ga_ls9c_ard_3-2-1_092088_2022-08-08_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-09-02 09:23:07	ga_ls9c_ard_3-2-1_091075_2022-09-01_final.stac-item
2022-09-20 10:47:20	ga_ls9c_ard_3-2-1_105069_2022-09-20_final.stac-item
2022-09-21 09:53:43	ga_ls9c_ard_3-2-1_096074_2022-09-21_final.stac-item
2022-10-02 11:12:05	ga_ls9c_ard_3-2-1_109069_2022-10-02_final.stac-item
2022-10-02 11:14:29	ga_ls9c_ard_3-2-1_109075_2022-10-02_final.stac-item
2022-10-16 11:26:32	ga_ls9c_ard_3-2-1_111074_2022-10-16_final.stac-item
2022-10-21 10:09:47	ga_ls9c_ard_3-2-1_098083_2022-10-21_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-12-11 10:38:17	ga_ls9c_ard_3-2-1_103077_2022-12-11_final.stac-item
2022-12-16 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-12-15_final.stac-item
2022-12-19 11:24:07	ga_ls9c_ard_3-2-1_111068_2022-12-19_final.stac-item
2022-12-31 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-31_final.stac-item
2023-01-20 11:25:10	ga_ls9c_ard_3-2-1_111071_2023-01-20_final.stac-item
2023-02-24 10:19:58	ga_ls9c_ard_3-2-1_100078_2023-02-24_final.stac-item
2023-02-25 09:22:45	ga_ls9c_ard_3-2-1_091074_2023-02-24_final.stac-item
2023-03-15 09:12:16	ga_ls9c_ard_3-2-1_089079_2023-03-14_final.stac-item
2023-03-25 11:25:20	ga_ls9c_ard_3-2-1_111072_2023-03-25_final.stac-item
2023-05-18 10:49:23	ga_ls9c_ard_3-2-1_105076_2023-05-18_final.stac-item
2023-06-01 09:27:32	ga_ls9c_ard_3-2-1_091088_2023-05-31_final.stac-item
2023-06-11 11:37:50	ga_ls9c_ard_3-2-1_113074_2023-06-11_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-06-28 10:43:48	ga_ls9c_ard_3-2-1_104078_2023-06-28_final.stac-item
2023-07-27 10:09:33	ga_ls9c_ard_3-2-1_099069_2023-07-27_final.stac-item
2023-07-27 10:13:56	ga_ls9c_ard_3-2-1_099080_2023-07-27_final.stac-item
2023-07-28 09:17:08	ga_ls9c_ard_3-2-1_090077_2023-07-27_final.stac-item
2023-07-31 11:25:46	ga_ls9c_ard_3-2-1_111074_2023-07-31_final.stac-item
2023-08-26 10:27:46	ga_ls9c_ard_3-2-1_101083_2023-08-26_final.stac-item
2023-09-10 09:45:03	ga_ls9c_ard_3-2-1_094084_2023-09-10_final.stac-item
2023-09-22 10:07:00	ga_ls9c_ard_3-2-1_098077_2023-09-22_final.stac-item
2023-10-08 10:04:40	ga_ls9c_ard_3-2-1_098071_2023-10-08_final.stac-item
2023-10-14 09:28:53	ga_ls9c_ard_3-2-1_092074_2023-10-13_final.stac-item
2023-11-20 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-11-20_final.stac-item
2023-11-26 09:10:50	ga_ls9c_ard_3-2-1_089075_2023-11-25_final.stac-item
2023-12-25 11:58:08	ga_ls9c_ard_3-2-1_116076_2023-12-25_final.stac-item
2023-12-26 09:22:49	ga_ls9c_ard_3-2-1_091074_2023-12-25_final.stac-item
2024-01-16 11:19:47	ga_ls9c_ard_3-2-1_110073_2024-01-16_final.stac-item
2024-02-24 11:25:22	ga_ls9c_ard_3-2-1_111072_2024-02-24_final.stac-item
2024-02-28 11:01:30	ga_ls9c_ard_3-2-1_107074_2024-02-28_final.stac-item
2024-05-03 10:09:20	ga_ls9c_ard_3-2-1_098084_2024-05-03_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