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
2021-11-02 10:54:03	ga_ls9c_ard_3-2-1_106076_2021-11-02_final.stac-item
2021-11-12 11:01:48	ga_ls9c_ard_3-2-1_106083_2021-11-12_final.stac-item
2021-11-15 09:39:58	ga_ls9c_ard_3-2-1_094072_2021-11-15_final.stac-item
2021-11-17 09:21:17	ga_ls9c_ard_3-2-1_091072_2021-11-16_final.stac-item
2021-12-27 11:08:14	ga_ls9c_ard_3-2-1_108075_2021-12-27_final.stac-item
2022-01-24 09:52:27	ga_ls9c_ard_3-2-1_096071_2022-01-24_final.stac-item
2022-02-06 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-02-05_final.stac-item
2022-02-13 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-02-12_final.stac-item
2022-02-18 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-02-18_final.stac-item
2022-03-02 10:09:33	ga_ls9c_ard_3-2-1_099068_2022-03-02_final.stac-item
2022-03-05 09:07:09	ga_ls9c_ard_3-2-1_088082_2022-03-04_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_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
2022-04-17 10:22:54	ga_ls9c_ard_3-2-1_101071_2022-04-17_final.stac-item
2022-06-26 09:51:53	ga_ls9c_ard_3-2-1_095086_2022-06-26_final.stac-item
2022-07-09 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-07-08_final.stac-item
2022-07-09 09:21:44	ga_ls9c_ard_3-2-1_090088_2022-07-08_final.stac-item
2022-07-17 10:03:35	ga_ls9c_ard_3-2-1_098069_2022-07-17_final.stac-item
2022-08-01 09:21:45	ga_ls9c_ard_3-2-1_091072_2022-07-31_final.stac-item
2022-08-08 09:34:23	ga_ls9c_ard_3-2-1_092088_2022-08-08_final.stac-item
2022-08-18 10:09:33	ga_ls9c_ard_3-2-1_098083_2022-08-18_final.stac-item
2022-09-05 09:58:24	ga_ls9c_ard_3-2-1_096086_2022-09-05_final.stac-item
2022-09-09 09:34:04	ga_ls9c_ard_3-2-1_092087_2022-09-09_final.stac-item
2022-09-13 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-09-13_final.stac-item
2022-10-07 11:32:13	ga_ls9c_ard_3-2-1_112073_2022-10-07_final.stac-item
2022-10-12 10:13:32	ga_ls9c_ard_3-2-1_099077_2022-10-12_final.stac-item
2022-11-03 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-11-03_final.stac-item
2022-11-03 09:39:38	ga_ls9c_ard_3-2-1_093085_2022-11-03_final.stac-item
2022-11-05 09:23:17	ga_ls9c_ard_3-2-1_091075_2022-11-04_final.stac-item
2022-11-22 10:10:36	ga_ls9c_ard_3-2-1_098085_2022-11-22_final.stac-item
2022-12-07 11:05:48	ga_ls9c_ard_3-2-1_107084_2022-12-07_final.stac-item
2022-12-08 10:07:47	ga_ls9c_ard_3-2-1_098078_2022-12-08_final.stac-item
2023-01-13 11:20:19	ga_ls9c_ard_3-2-1_110074_2023-01-13_final.stac-item
2023-01-24 11:00:07	ga_ls9c_ard_3-2-1_107070_2023-01-24_final.stac-item
2023-02-04 09:05:14	ga_ls9c_ard_3-2-1_088076_2023-02-03_interim.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-18 09:21:30	ga_ls9c_ard_3-2-1_090086_2023-02-17_final.stac-item
2023-03-07 09:57:21	ga_ls9c_ard_3-2-1_097068_2023-03-07_final.stac-item
2023-03-21 10:09:15	ga_ls9c_ard_3-2-1_099067_2023-03-21_final.stac-item
2023-05-01 10:02:40	ga_ls9c_ard_3-2-1_098067_2023-05-01_final.stac-item
2023-05-20 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-05-20_final.stac-item
2023-05-23 09:27:22	ga_ls9c_ard_3-2-1_092072_2023-05-22_final.stac-item
2023-06-08 09:32:28	ga_ls9c_ard_3-2-1_092085_2023-06-08_final.stac-item
2023-06-09 10:15:19	ga_ls9c_ard_3-2-1_099084_2023-06-09_final.stac-item
2023-06-15 09:38:33	ga_ls9c_ard_3-2-1_093085_2023-06-15_final.stac-item
2023-06-27 09:56:31	ga_ls9c_ard_3-2-1_097068_2023-06-27_final.stac-item
2023-06-29 11:24:18	ga_ls9c_ard_3-2-1_111071_2023-06-29_final.stac-item
2023-07-03 11:01:40	ga_ls9c_ard_3-2-1_107076_2023-07-03_final.stac-item
2023-08-04 11:03:30	ga_ls9c_ard_3-2-1_107080_2023-08-04_final.stac-item
2023-08-12 10:15:17	ga_ls9c_ard_3-2-1_099083_2023-08-12_final.stac-item
2023-08-12 11:52:58	ga_ls9c_ard_3-2-1_115080_2023-08-12_final.stac-item
2023-08-14 11:38:13	ga_ls9c_ard_3-2-1_113074_2023-08-14_final.stac-item
2023-08-28 10:09:50	ga_ls9c_ard_3-2-1_099069_2023-08-28_final.stac-item
2023-08-29 09:16:37	ga_ls9c_ard_3-2-1_090075_2023-08-28_final.stac-item
2023-09-23 10:49:51	ga_ls9c_ard_3-2-1_105076_2023-09-23_final.stac-item
2023-09-26 09:39:51	ga_ls9c_ard_3-2-1_094071_2023-09-26_final.stac-item
2023-12-07 10:33:29	ga_ls9c_ard_3-2-1_102081_2023-12-07_final.stac-item
2023-12-12 09:12:23	ga_ls9c_ard_3-2-1_089079_2023-12-11_final.stac-item
2023-12-12 10:52:28	ga_ls9c_ard_3-2-1_105082_2023-12-12_final.stac-item
2024-01-09 11:14:23	ga_ls9c_ard_3-2-1_109075_2024-01-09_final.stac-item
2024-01-20 09:20:57	ga_ls9c_ard_3-2-1_090085_2024-01-19_final.stac-item
2024-03-11 09:46:35	ga_ls9c_ard_3-2-1_095072_2024-03-11_final.stac-item
2024-03-12 10:29:02	ga_ls9c_ard_3-2-1_102070_2024-03-12_final.stac-item
2024-03-19 10:34:24	ga_ls9c_ard_3-2-1_103068_2024-03-19_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 09:22:00	ga_ls9c_ard_3-2-1_090088_2024-03-23_final.stac-item
2024-04-28 09:45:38	ga_ls9c_ard_3-2-1_095071_2024-04-28_final.stac-item
2024-05-02 09:22:05	ga_ls9c_ard_3-2-1_091074_2024-05-01_nrt.stac-item
2024-05-09 09:33:51	ga_ls9c_ard_3-2-1_092088_2024-05-09_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