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

First 100 results (query limit)

Time (local)	Label
2021-11-03 09:58:56	ga_ls9c_ard_3-2-1_096085_2021-11-03_final.stac-item
2021-11-05 09:41:24	ga_ls9c_ard_3-2-1_093088_2021-11-05_final.stac-item
2021-11-09 10:40:11	ga_ls9c_ard_3-2-1_103082_2021-11-09_final.stac-item
2021-11-12 09:23:56	ga_ls9c_ard_3-2-1_091085_2021-11-11_final.stac-item
2021-11-18 11:40:14	ga_ls9c_ard_3-2-1_113073_2021-11-18_final.stac-item
2021-11-25 09:44:52	ga_ls9c_ard_3-2-1_095072_2021-11-25_final.stac-item
2021-12-14 11:38:21	ga_ls9c_ard_3-2-1_113073_2021-12-14_final.stac-item
2021-12-30 11:38:20	ga_ls9c_ard_3-2-1_113073_2021-12-30_final.stac-item
2022-01-15 11:38:17	ga_ls9c_ard_3-2-1_113073_2022-01-15_final.stac-item
2022-01-22 10:10:24	ga_ls9c_ard_3-2-1_098085_2022-01-22_final.stac-item
2022-02-04 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-02-04_final.stac-item
2022-03-08 11:17:45	ga_ls9c_ard_3-2-1_109084_2022-03-08_final.stac-item
2022-03-21 09:07:31	ga_ls9c_ard_3-2-1_088083_2022-03-20_final.stac-item
2022-03-26 09:24:02	ga_ls9c_ard_3-2-1_091078_2022-03-25_final.stac-item
2022-03-30 10:38:59	ga_ls9c_ard_3-2-1_103080_2022-03-30_final.stac-item
2022-04-09 09:38:44	ga_ls9c_ard_3-2-1_093084_2022-04-09_final.stac-item
2022-04-22 09:06:29	ga_ls9c_ard_3-2-1_088081_2022-04-21_final.stac-item
2022-05-13 11:02:59	ga_ls9c_ard_3-2-1_107079_2022-05-13_final.stac-item
2022-05-20 09:33:21	ga_ls9c_ard_3-2-1_092087_2022-05-20_final.stac-item
2022-05-24 10:43:32	ga_ls9c_ard_3-2-1_104077_2022-05-24_final.stac-item
2022-05-27 09:38:20	ga_ls9c_ard_3-2-1_093084_2022-05-27_final.stac-item
2022-05-29 11:04:04	ga_ls9c_ard_3-2-1_107082_2022-05-29_final.stac-item
2022-06-02 10:38:34	ga_ls9c_ard_3-2-1_103080_2022-06-02_final.stac-item
2022-06-18 10:39:30	ga_ls9c_ard_3-2-1_103082_2022-06-18_final.stac-item
2022-06-28 11:17:36	ga_ls9c_ard_3-2-1_109084_2022-06-28_final.stac-item
2022-06-30 11:04:26	ga_ls9c_ard_3-2-1_107082_2022-06-30_final.stac-item
2022-07-02 09:10:23	ga_ls9c_ard_3-2-1_089075_2022-07-01_final.stac-item
2022-07-16 09:28:17	ga_ls9c_ard_3-2-1_091089_2022-07-15_final.stac-item
2022-08-01 11:03:25	ga_ls9c_ard_3-2-1_107079_2022-08-01_final.stac-item
2022-08-06 09:45:56	ga_ls9c_ard_3-2-1_094086_2022-08-06_final.stac-item
2022-08-29 09:49:02	ga_ls9c_ard_3-2-1_095078_2022-08-29_final.stac-item
2022-09-28 10:00:19	ga_ls9c_ard_3-2-1_097075_2022-09-28_final.stac-item
2022-10-03 10:20:27	ga_ls9c_ard_3-2-1_100079_2022-10-03_final.stac-item
2022-10-04 11:05:19	ga_ls9c_ard_3-2-1_107083_2022-10-04_final.stac-item
2022-10-06 09:12:52	ga_ls9c_ard_3-2-1_089080_2022-10-05_final.stac-item
2022-10-06 09:13:15	ga_ls9c_ard_3-2-1_089081_2022-10-05_final.stac-item
2022-10-09 09:42:36	ga_ls9c_ard_3-2-1_094077_2022-10-09_final.stac-item
2022-10-11 09:28:40	ga_ls9c_ard_3-2-1_092073_2022-10-10_final.stac-item
2022-10-20 09:26:08	ga_ls9c_ard_3-2-1_091082_2022-10-19_final.stac-item
2022-10-20 09:26:32	ga_ls9c_ard_3-2-1_091083_2022-10-19_final.stac-item
2022-10-22 09:12:10	ga_ls9c_ard_3-2-1_089078_2022-10-21_final.stac-item
2022-10-25 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-10-25_final.stac-item
2022-10-27 09:34:18	ga_ls9c_ard_3-2-1_092087_2022-10-27_final.stac-item
2022-10-30 11:38:29	ga_ls9c_ard_3-2-1_113073_2022-10-30_final.stac-item
2022-11-10 09:45:28	ga_ls9c_ard_3-2-1_094084_2022-11-10_final.stac-item
2022-11-10 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-11-10_final.stac-item
2022-11-19 09:40:30	ga_ls9c_ard_3-2-1_093087_2022-11-19_final.stac-item
2022-11-23 10:50:40	ga_ls9c_ard_3-2-1_105077_2022-11-23_final.stac-item
2023-05-10 11:39:17	ga_ls9c_ard_3-2-1_113077_2023-05-10_final.stac-item
2023-05-10 11:39:41	ga_ls9c_ard_3-2-1_113078_2023-05-10_final.stac-item
2023-05-10 11:41:17	ga_ls9c_ard_3-2-1_113082_2023-05-10_final.stac-item
2023-05-11 09:07:11	ga_ls9c_ard_3-2-1_088083_2023-05-10_final.stac-item
2023-05-14 11:17:20	ga_ls9c_ard_3-2-1_109084_2023-05-14_final.stac-item
2023-05-16 11:04:10	ga_ls9c_ard_3-2-1_107082_2023-05-16_final.stac-item
2023-05-17 10:09:43	ga_ls9c_ard_3-2-1_098085_2023-05-17_final.stac-item
2023-05-18 09:09:42	ga_ls9c_ard_3-2-1_089074_2023-05-17_final.stac-item
2023-05-18 09:10:30	ga_ls9c_ard_3-2-1_089076_2023-05-17_final.stac-item
2023-05-23 09:26:58	ga_ls9c_ard_3-2-1_092071_2023-05-22_final.stac-item
2023-05-23 09:27:46	ga_ls9c_ard_3-2-1_092073_2023-05-22_final.stac-item
2023-09-04 11:58:09	ga_ls9c_ard_3-2-1_116077_2023-09-04_final.stac-item
2023-09-04 11:58:33	ga_ls9c_ard_3-2-1_116078_2023-09-04_final.stac-item
2023-09-07 09:10:08	ga_ls9c_ard_3-2-1_089074_2023-09-06_final.stac-item
2023-09-07 09:10:56	ga_ls9c_ard_3-2-1_089076_2023-09-06_final.stac-item
2023-09-07 10:51:48	ga_ls9c_ard_3-2-1_105081_2023-09-07_final.stac-item
2023-09-08 11:31:53	ga_ls9c_ard_3-2-1_112073_2023-09-08_final.stac-item
2023-09-12 09:27:32	ga_ls9c_ard_3-2-1_092071_2023-09-11_final.stac-item
2023-09-12 09:28:19	ga_ls9c_ard_3-2-1_092073_2023-09-11_final.stac-item
2023-09-12 09:34:43	ga_ls9c_ard_3-2-1_092089_2023-09-12_final.stac-item
2023-09-12 09:35:07	ga_ls9c_ard_3-2-1_092090_2023-09-12_final.stac-item
2023-09-13 11:53:16	ga_ls9c_ard_3-2-1_115080_2023-09-13_final.stac-item
2023-09-14 09:16:22	ga_ls9c_ard_3-2-1_090074_2023-09-13_final.stac-item
2023-09-15 11:38:08	ga_ls9c_ard_3-2-1_113073_2023-09-15_final.stac-item
2023-09-15 11:41:43	ga_ls9c_ard_3-2-1_113082_2023-09-15_final.stac-item
2023-09-15 11:42:07	ga_ls9c_ard_3-2-1_113083_2023-09-15_final.stac-item
2023-09-17 11:24:58	ga_ls9c_ard_3-2-1_111071_2023-09-17_final.stac-item
2023-09-23 09:10:58	ga_ls9c_ard_3-2-1_089076_2023-09-22_final.stac-item
2023-09-28 09:27:27	ga_ls9c_ard_3-2-1_092071_2023-09-27_final.stac-item
2023-09-28 09:28:15	ga_ls9c_ard_3-2-1_092073_2023-09-27_final.stac-item
2023-09-28 09:34:14	ga_ls9c_ard_3-2-1_092088_2023-09-28_final.stac-item
2023-09-28 09:34:38	ga_ls9c_ard_3-2-1_092089_2023-09-28_final.stac-item
2023-09-28 09:35:02	ga_ls9c_ard_3-2-1_092090_2023-09-28_final.stac-item
2023-09-30 09:16:20	ga_ls9c_ard_3-2-1_090074_2023-09-29_final.stac-item
2023-09-30 10:58:01	ga_ls9c_ard_3-2-1_106081_2023-09-30_final.stac-item
2023-09-30 10:58:25	ga_ls9c_ard_3-2-1_106082_2023-09-30_final.stac-item
2023-10-01 11:38:06	ga_ls9c_ard_3-2-1_113073_2023-10-01_final.stac-item
2023-10-01 11:42:05	ga_ls9c_ard_3-2-1_113083_2023-10-01_final.stac-item
2023-10-03 09:50:05	ga_ls9c_ard_3-2-1_095081_2023-10-03_final.stac-item
2023-10-03 09:50:53	ga_ls9c_ard_3-2-1_095083_2023-10-03_final.stac-item
2023-10-03 09:51:40	ga_ls9c_ard_3-2-1_095085_2023-10-03_final.stac-item
2023-10-03 11:30:10	ga_ls9c_ard_3-2-1_111084_2023-10-03_final.stac-item
2023-10-05 09:39:44	ga_ls9c_ard_3-2-1_093086_2023-10-05_final.stac-item
2023-10-05 09:40:32	ga_ls9c_ard_3-2-1_093088_2023-10-05_final.stac-item
2023-10-09 09:11:03	ga_ls9c_ard_3-2-1_089076_2023-10-08_final.stac-item
2023-10-10 11:32:02	ga_ls9c_ard_3-2-1_112073_2023-10-10_final.stac-item
2023-10-12 11:24:29	ga_ls9c_ard_3-2-1_110085_2023-10-12_final.stac-item
2023-10-14 09:27:41	ga_ls9c_ard_3-2-1_092071_2023-10-13_final.stac-item
2023-10-14 09:28:29	ga_ls9c_ard_3-2-1_092073_2023-10-13_final.stac-item
2023-10-14 09:35:16	ga_ls9c_ard_3-2-1_092090_2023-10-14_final.stac-item
2023-10-15 10:16:32	ga_ls9c_ard_3-2-1_099085_2023-10-15_final.stac-item
2023-10-16 09:21:20	ga_ls9c_ard_3-2-1_090086_2023-10-15_final.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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years