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

70 results

Time (local)	Label
2021-11-02 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-05 09:40:12	ga_ls9c_ard_3-2-1_093085_2021-11-05_final.stac-item
2021-11-13 10:02:18	ga_ls9c_ard_3-2-1_097081_2021-11-13_final.stac-item
2021-11-18 09:59:11	ga_ls9c_ard_3-2-1_097067_2021-11-18_final.stac-item
2021-12-05 10:03:21	ga_ls9c_ard_3-2-1_098067_2021-12-05_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2021-12-30 09:59:51	ga_ls9c_ard_3-2-1_097074_2021-12-30_final.stac-item
2022-01-12 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-01-12_final.stac-item
2022-02-24 10:49:30	ga_ls9c_ard_3-2-1_105075_2022-02-24_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-03-08 11:13:45	ga_ls9c_ard_3-2-1_109074_2022-03-08_final.stac-item
2022-03-25 10:17:16	ga_ls9c_ard_3-2-1_100072_2022-03-25_final.stac-item
2022-03-26 11:00:07	ga_ls9c_ard_3-2-1_107071_2022-03-26_final.stac-item
2022-04-04 10:55:55	ga_ls9c_ard_3-2-1_106076_2022-04-04_final.stac-item
2022-04-05 10:03:29	ga_ls9c_ard_3-2-1_097084_2022-04-05_final.stac-item
2022-04-23 11:24:38	ga_ls9c_ard_3-2-1_111071_2022-04-23_final.stac-item
2022-04-29 09:16:15	ga_ls9c_ard_3-2-1_089090_2022-04-28_final.stac-item
2022-05-11 11:14:34	ga_ls9c_ard_3-2-1_109077_2022-05-11_final.stac-item
2022-05-28 10:18:25	ga_ls9c_ard_3-2-1_100076_2022-05-28_final.stac-item
2022-05-29 09:22:00	ga_ls9c_ard_3-2-1_091074_2022-05-28_final.stac-item
2022-06-19 11:23:11	ga_ls9c_ard_3-2-1_110083_2022-06-19_final.stac-item
2022-07-31 10:21:45	ga_ls9c_ard_3-2-1_100083_2022-07-31_final.stac-item
2022-08-04 11:34:46	ga_ls9c_ard_3-2-1_112080_2022-08-04_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-25 11:08:18	ga_ls9c_ard_3-2-1_108075_2022-09-25_final.stac-item
2022-11-07 09:14:09	ga_ls9c_ard_3-2-1_089083_2022-11-06_final.stac-item
2022-11-22 10:03:25	ga_ls9c_ard_3-2-1_098067_2022-11-22_final.stac-item
2022-12-01 09:59:34	ga_ls9c_ard_3-2-1_097073_2022-12-01_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_nrt.stac-item
2022-12-12 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-12-12_final.stac-item
2022-12-24 11:47:01	ga_ls9c_ard_3-2-1_114079_2022-12-24_final.stac-item
2022-12-26 09:54:59	ga_ls9c_ard_3-2-1_096077_2022-12-26_final.stac-item
2023-01-08 11:00:37	ga_ls9c_ard_3-2-1_107071_2023-01-08_final.stac-item
2023-01-17 09:21:03	ga_ls9c_ard_3-2-1_090085_2023-01-16_final.stac-item
2023-01-22 09:39:56	ga_ls9c_ard_3-2-1_093086_2023-01-22_final.stac-item
2023-01-29 11:18:21	ga_ls9c_ard_3-2-1_110069_2023-01-29_final.stac-item
2023-02-17 10:16:20	ga_ls9c_ard_3-2-1_099084_2023-02-17_final.stac-item
2023-02-21 09:51:32	ga_ls9c_ard_3-2-1_095084_2023-02-21_final.stac-item
2023-03-13 09:28:37	ga_ls9c_ard_3-2-1_091089_2023-03-12_final.stac-item
2023-03-25 11:25:44	ga_ls9c_ard_3-2-1_111073_2023-03-25_final.stac-item
2023-04-16 09:12:22	ga_ls9c_ard_3-2-1_089080_2023-04-15_final.stac-item
2023-04-16 10:47:15	ga_ls9c_ard_3-2-1_105070_2023-04-16_final.stac-item
2023-04-30 09:27:24	ga_ls9c_ard_3-2-1_091087_2023-04-29_final.stac-item
2023-05-05 09:45:03	ga_ls9c_ard_3-2-1_094085_2023-05-05_final.stac-item
2023-05-09 10:53:14	ga_ls9c_ard_3-2-1_106070_2023-05-09_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-10 09:17:18	ga_ls9c_ard_3-2-1_090078_2023-06-09_final.stac-item
2023-07-08 09:39:23	ga_ls9c_ard_3-2-1_094071_2023-07-08_final.stac-item
2023-07-19 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-07-18_final.stac-item
2023-07-27 10:09:09	ga_ls9c_ard_3-2-1_099068_2023-07-27_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-07 09:57:32	ga_ls9c_ard_3-2-1_096085_2023-08-07_final.stac-item
2023-08-25 11:19:47	ga_ls9c_ard_3-2-1_110074_2023-08-25_final.stac-item
2023-09-01 11:24:26	ga_ls9c_ard_3-2-1_111070_2023-09-01_final.stac-item
2023-09-22 10:07:24	ga_ls9c_ard_3-2-1_098078_2023-09-22_final.stac-item
2023-10-19 11:29:56	ga_ls9c_ard_3-2-1_111083_2023-10-19_final.stac-item
2023-11-02 09:57:42	ga_ls9c_ard_3-2-1_097069_2023-11-02_final.stac-item
2023-11-03 10:42:32	ga_ls9c_ard_3-2-1_104073_2023-11-03_final.stac-item
2023-11-06 09:39:47	ga_ls9c_ard_3-2-1_093086_2023-11-06_final.stac-item
2023-11-29 11:20:13	ga_ls9c_ard_3-2-1_110074_2023-11-29_final.stac-item
2023-12-06 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-12-06_final.stac-item
2024-01-09 11:13:59	ga_ls9c_ard_3-2-1_109074_2024-01-09_final.stac-item
2024-01-11 09:25:09	ga_ls9c_ard_3-2-1_091080_2024-01-10_final.stac-item
2024-01-30 09:52:04	ga_ls9c_ard_3-2-1_096070_2024-01-30_final.stac-item
2024-02-19 11:05:43	ga_ls9c_ard_3-2-1_108069_2024-02-19_final.stac-item
2024-02-20 10:15:39	ga_ls9c_ard_3-2-1_099083_2024-02-20_final.stac-item
2024-03-11 11:29:27	ga_ls9c_ard_3-2-1_111082_2024-03-11_final.stac-item
2024-03-14 10:21:27	ga_ls9c_ard_3-2-1_100082_2024-03-14_final.stac-item
2024-04-02 09:13:43	ga_ls9c_ard_3-2-1_089083_2024-04-01_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