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

65 results

Time (local)	Label
2021-12-13 10:53:06	ga_ls9c_ard_3-2-1_106068_2021-12-13_final.stac-item
2021-12-28 10:14:12	ga_ls9c_ard_3-2-1_099079_2021-12-28_final.stac-item
2022-01-12 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-01-12_final.stac-item
2022-01-14 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-01-14_final.stac-item
2022-02-22 10:59:53	ga_ls9c_ard_3-2-1_107070_2022-02-22_final.stac-item
2022-02-27 09:39:53	ga_ls9c_ard_3-2-1_094071_2022-02-27_final.stac-item
2022-03-03 09:17:07	ga_ls9c_ard_3-2-1_090076_2022-03-02_final.stac-item
2022-03-09 10:17:20	ga_ls9c_ard_3-2-1_100072_2022-03-09_final.stac-item
2022-04-10 10:16:48	ga_ls9c_ard_3-2-1_100071_2022-04-10_final.stac-item
2022-04-13 09:13:35	ga_ls9c_ard_3-2-1_089083_2022-04-12_final.stac-item
2022-04-16 09:40:03	ga_ls9c_ard_3-2-1_094072_2022-04-16_final.stac-item
2022-04-23 09:46:09	ga_ls9c_ard_3-2-1_095072_2022-04-23_final.stac-item
2022-06-07 10:52:20	ga_ls9c_ard_3-2-1_106068_2022-06-07_final.stac-item
2022-06-15 10:09:21	ga_ls9c_ard_3-2-1_098084_2022-06-15_final.stac-item
2022-06-22 10:13:43	ga_ls9c_ard_3-2-1_099079_2022-06-22_final.stac-item
2022-06-28 09:39:31	ga_ls9c_ard_3-2-1_093086_2022-06-28_final.stac-item
2022-06-30 09:27:57	ga_ls9c_ard_3-2-1_091088_2022-06-29_final.stac-item
2022-07-24 10:09:05	ga_ls9c_ard_3-2-1_099067_2022-07-24_final.stac-item
2022-08-08 09:33:59	ga_ls9c_ard_3-2-1_092087_2022-08-08_final.stac-item
2022-08-09 10:10:05	ga_ls9c_ard_3-2-1_099069_2022-08-09_final.stac-item
2022-08-09 10:10:53	ga_ls9c_ard_3-2-1_099071_2022-08-09_final.stac-item
2022-08-18 10:04:45	ga_ls9c_ard_3-2-1_098071_2022-08-18_final.stac-item
2022-08-27 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-08-27_final.stac-item
2022-09-03 10:07:34	ga_ls9c_ard_3-2-1_098078_2022-09-03_final.stac-item
2022-09-09 09:33:40	ga_ls9c_ard_3-2-1_092086_2022-09-09_final.stac-item
2022-09-28 10:03:55	ga_ls9c_ard_3-2-1_097084_2022-09-28_final.stac-item
2022-10-28 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-10-28_final.stac-item
2022-11-13 10:09:12	ga_ls9c_ard_3-2-1_099066_2022-11-13_final.stac-item
2022-12-23 09:23:16	ga_ls9c_ard_3-2-1_091075_2022-12-22_final.stac-item
2022-12-28 09:41:03	ga_ls9c_ard_3-2-1_094073_2022-12-28_final.stac-item
2023-01-24 09:22:02	ga_ls9c_ard_3-2-1_091072_2023-01-23_final.stac-item
2023-02-04 09:07:14	ga_ls9c_ard_3-2-1_088081_2023-02-03_final.stac-item
2023-02-11 10:47:07	ga_ls9c_ard_3-2-1_105068_2023-02-11_final.stac-item
2023-02-17 11:52:50	ga_ls9c_ard_3-2-1_115078_2023-02-17_final.stac-item
2023-02-27 09:12:23	ga_ls9c_ard_3-2-1_089079_2023-02-26_final.stac-item
2023-03-03 10:23:20	ga_ls9c_ard_3-2-1_101071_2023-03-03_final.stac-item
2023-03-25 11:24:09	ga_ls9c_ard_3-2-1_111069_2023-03-25_final.stac-item
2023-03-27 11:12:32	ga_ls9c_ard_3-2-1_109071_2023-03-27_final.stac-item
2023-04-06 10:09:52	ga_ls9c_ard_3-2-1_099069_2023-04-06_final.stac-item
2023-05-28 09:51:28	ga_ls9c_ard_3-2-1_095086_2023-05-28_final.stac-item
2023-07-05 10:50:55	ga_ls9c_ard_3-2-1_105080_2023-07-05_final.stac-item
2023-07-17 09:33:39	ga_ls9c_ard_3-2-1_093072_2023-07-17_final.stac-item
2023-08-13 10:52:34	ga_ls9c_ard_3-2-1_106068_2023-08-13_final.stac-item
2023-09-06 10:06:56	ga_ls9c_ard_3-2-1_098077_2023-09-06_final.stac-item
2023-10-24 10:07:35	ga_ls9c_ard_3-2-1_098078_2023-10-24_final.stac-item
2023-11-05 10:29:01	ga_ls9c_ard_3-2-1_102070_2023-11-05_final.stac-item
2023-11-10 09:12:18	ga_ls9c_ard_3-2-1_089079_2023-11-09_final.stac-item
2023-11-17 09:22:53	ga_ls9c_ard_3-2-1_090090_2023-11-16_final.stac-item
2023-12-04 09:58:14	ga_ls9c_ard_3-2-1_097070_2023-12-04_final.stac-item
2023-12-11 10:07:36	ga_ls9c_ard_3-2-1_098078_2023-12-11_final.stac-item
2023-12-13 11:32:33	ga_ls9c_ard_3-2-1_112074_2023-12-13_final.stac-item
2024-01-03 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-03_final.stac-item
2024-01-05 09:57:24	ga_ls9c_ard_3-2-1_097068_2024-01-05_final.stac-item
2024-01-07 09:47:02	ga_ls9c_ard_3-2-1_095073_2024-01-07_final.stac-item
2024-01-25 09:40:39	ga_ls9c_ard_3-2-1_093088_2024-01-25_final.stac-item
2024-01-27 09:22:44	ga_ls9c_ard_3-2-1_091074_2024-01-26_final.stac-item
2024-01-29 09:11:59	ga_ls9c_ard_3-2-1_089078_2024-01-28_final.stac-item
2024-02-04 10:09:50	ga_ls9c_ard_3-2-1_099068_2024-02-04_final.stac-item
2024-02-07 10:41:56	ga_ls9c_ard_3-2-1_104071_2024-02-07_final.stac-item
2024-02-13 11:45:18	ga_ls9c_ard_3-2-1_114075_2024-02-13_final.stac-item
2024-02-14 09:10:47	ga_ls9c_ard_3-2-1_089075_2024-02-13_final.stac-item
2024-03-13 11:14:17	ga_ls9c_ard_3-2-1_109075_2024-03-13_final.stac-item
2024-04-05 11:19:54	ga_ls9c_ard_3-2-1_110074_2024-04-05_final.stac-item
2024-04-24 10:10:20	ga_ls9c_ard_3-2-1_099071_2024-04-24_final.stac-item
2024-06-06 11:30:50	ga_ls9c_ard_3-2-1_112072_2024-06-06_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