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

77 results

Time (local)	Label
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-12-05 10:04:57	ga_ls9c_ard_3-2-1_098071_2021-12-05_final.stac-item
2021-12-08 10:36:13	ga_ls9c_ard_3-2-1_103072_2021-12-08_final.stac-item
2021-12-28 10:14:12	ga_ls9c_ard_3-2-1_099079_2021-12-28_final.stac-item
2021-12-29 09:19:23	ga_ls9c_ard_3-2-1_090081_2021-12-28_final.stac-item
2022-01-17 11:26:20	ga_ls9c_ard_3-2-1_111074_2022-01-17_final.stac-item
2022-02-13 09:28:05	ga_ls9c_ard_3-2-1_092072_2022-02-12_final.stac-item
2022-03-12 10:49:02	ga_ls9c_ard_3-2-1_105074_2022-03-12_final.stac-item
2022-03-24 09:35:12	ga_ls9c_ard_3-2-1_093075_2022-03-24_final.stac-item
2022-04-03 10:13:52	ga_ls9c_ard_3-2-1_099079_2022-04-03_final.stac-item
2022-04-09 11:14:02	ga_ls9c_ard_3-2-1_109075_2022-04-09_final.stac-item
2022-04-13 10:49:16	ga_ls9c_ard_3-2-1_105075_2022-04-13_final.stac-item
2022-04-15 10:35:42	ga_ls9c_ard_3-2-1_103072_2022-04-15_final.stac-item
2022-05-05 10:12:50	ga_ls9c_ard_3-2-1_099077_2022-05-05_final.stac-item
2022-05-09 11:28:33	ga_ls9c_ard_3-2-1_111081_2022-05-09_final.stac-item
2022-05-12 10:16:32	ga_ls9c_ard_3-2-1_100071_2022-05-12_final.stac-item
2022-06-05 09:29:24	ga_ls9c_ard_3-2-1_092077_2022-06-04_final.stac-item
2022-06-06 10:08:16	ga_ls9c_ard_3-2-1_099066_2022-06-06_final.stac-item
2022-06-30 09:25:33	ga_ls9c_ard_3-2-1_091082_2022-06-29_final.stac-item
2022-06-30 09:27:33	ga_ls9c_ard_3-2-1_091087_2022-06-29_final.stac-item
2022-08-09 11:51:21	ga_ls9c_ard_3-2-1_115075_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
2022-09-26 10:11:05	ga_ls9c_ard_3-2-1_099071_2022-09-26_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-14_final.stac-item
2022-11-05 09:28:05	ga_ls9c_ard_3-2-1_091087_2022-11-04_final.stac-item
2022-11-09 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-09_final.stac-item
2022-11-13 10:10:00	ga_ls9c_ard_3-2-1_099068_2022-11-13_final.stac-item
2022-12-03 11:24:54	ga_ls9c_ard_3-2-1_111070_2022-12-03_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-24 10:04:32	ga_ls9c_ard_3-2-1_098070_2022-12-24_final.stac-item
2023-01-03 10:42:29	ga_ls9c_ard_3-2-1_104072_2023-01-03_final.stac-item
2023-01-08 09:22:56	ga_ls9c_ard_3-2-1_091074_2023-01-07_final.stac-item
2023-01-26 10:47:00	ga_ls9c_ard_3-2-1_105068_2023-01-26_final.stac-item
2023-01-28 10:36:16	ga_ls9c_ard_3-2-1_103072_2023-01-28_final.stac-item
2023-02-09 11:00:41	ga_ls9c_ard_3-2-1_107071_2023-02-09_final.stac-item
2023-02-11 09:12:37	ga_ls9c_ard_3-2-1_089079_2023-02-10_final.stac-item
2023-03-02 11:20:33	ga_ls9c_ard_3-2-1_110075_2023-03-02_final.stac-item
2023-03-18 09:41:10	ga_ls9c_ard_3-2-1_094074_2023-03-18_final.stac-item
2023-03-23 09:59:15	ga_ls9c_ard_3-2-1_097073_2023-03-23_final.stac-item
2023-03-25 09:52:03	ga_ls9c_ard_3-2-1_095086_2023-03-25_final.stac-item
2023-04-26 09:45:48	ga_ls9c_ard_3-2-1_095071_2023-04-26_final.stac-item
2023-04-26 09:46:12	ga_ls9c_ard_3-2-1_095072_2023-04-26_final.stac-item
2023-05-02 09:11:25	ga_ls9c_ard_3-2-1_089078_2023-05-01_final.stac-item
2023-05-09 09:21:56	ga_ls9c_ard_3-2-1_090089_2023-05-08_final.stac-item
2023-06-20 11:30:48	ga_ls9c_ard_3-2-1_112072_2023-06-20_final.stac-item
2023-06-26 09:21:37	ga_ls9c_ard_3-2-1_090089_2023-06-25_final.stac-item
2023-07-08 09:39:23	ga_ls9c_ard_3-2-1_094071_2023-07-08_final.stac-item
2023-07-20 10:03:45	ga_ls9c_ard_3-2-1_098070_2023-07-20_final.stac-item
2023-08-12 10:10:30	ga_ls9c_ard_3-2-1_099071_2023-08-12_final.stac-item
2023-08-19 10:21:29	ga_ls9c_ard_3-2-1_100083_2023-08-19_final.stac-item
2023-08-28 10:15:50	ga_ls9c_ard_3-2-1_099084_2023-08-28_final.stac-item
2023-09-09 10:35:53	ga_ls9c_ard_3-2-1_103072_2023-09-09_final.stac-item
2023-09-21 09:21:45	ga_ls9c_ard_3-2-1_091072_2023-09-20_final.stac-item
2023-09-23 09:12:58	ga_ls9c_ard_3-2-1_089081_2023-09-22_final.stac-item
2023-09-30 09:17:32	ga_ls9c_ard_3-2-1_090077_2023-09-29_final.stac-item
2023-10-03 11:24:10	ga_ls9c_ard_3-2-1_111069_2023-10-03_final.stac-item
2023-11-16 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-11-16_final.stac-item
2023-11-20 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-11-20_final.stac-item
2023-11-29 11:19:25	ga_ls9c_ard_3-2-1_110072_2023-11-29_final.stac-item
2023-12-04 09:57:26	ga_ls9c_ard_3-2-1_097068_2023-12-04_final.stac-item
2023-12-31 09:41:19	ga_ls9c_ard_3-2-1_094074_2023-12-31_final.stac-item
2024-01-25 11:17:56	ga_ls9c_ard_3-2-1_109084_2024-01-25_final.stac-item
2024-02-11 10:19:12	ga_ls9c_ard_3-2-1_100076_2024-02-11_final.stac-item
2024-02-12 09:27:57	ga_ls9c_ard_3-2-1_091087_2024-02-11_final.stac-item
2024-02-22 11:41:44	ga_ls9c_ard_3-2-1_113082_2024-02-22_final.stac-item
2024-03-17 10:47:10	ga_ls9c_ard_3-2-1_105069_2024-03-17_final.stac-item
2024-03-27 11:25:44	ga_ls9c_ard_3-2-1_111073_2024-03-27_final.stac-item
2024-03-31 11:04:58	ga_ls9c_ard_3-2-1_107083_2024-03-31_final.stac-item
2024-04-09 09:17:04	ga_ls9c_ard_3-2-1_090076_2024-04-08_final.stac-item
2024-04-09 09:17:28	ga_ls9c_ard_3-2-1_090077_2024-04-08_final.stac-item
2024-04-12 09:52:20	ga_ls9c_ard_3-2-1_095087_2024-04-12_final.stac-item
2024-04-23 09:33:54	ga_ls9c_ard_3-2-1_092088_2024-04-23_final.stac-item
2024-05-03 10:03:44	ga_ls9c_ard_3-2-1_098070_2024-05-03_final.stac-item
2024-05-09 09:33:27	ga_ls9c_ard_3-2-1_092087_2024-05-09_final.stac-item
2024-05-19 10:04:01	ga_ls9c_ard_3-2-1_098071_2024-05-19_nrt.stac-item
2024-05-21 09:51:15	ga_ls9c_ard_3-2-1_096070_2024-05-21_final.stac-item
2024-05-25 09:28:05	ga_ls9c_ard_3-2-1_092074_2024-05-24_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years