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

80 results

Time (local)	Label
2021-11-06 10:14:59	ga_ls9c_ard_3-2-1_100072_2021-11-06_final.stac-item
2021-11-18 11:43:25	ga_ls9c_ard_3-2-1_113081_2021-11-18_final.stac-item
2022-01-21 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-01-20_final.stac-item
2022-02-15 09:18:30	ga_ls9c_ard_3-2-1_090079_2022-02-14_final.stac-item
2022-02-17 09:06:31	ga_ls9c_ard_3-2-1_088080_2022-02-16_final.stac-item
2022-02-22 09:22:36	ga_ls9c_ard_3-2-1_091074_2022-02-21_final.stac-item
2022-02-23 11:47:32	ga_ls9c_ard_3-2-1_114081_2022-02-23_final.stac-item
2022-03-02 10:13:08	ga_ls9c_ard_3-2-1_099077_2022-03-02_final.stac-item
2022-04-05 09:57:06	ga_ls9c_ard_3-2-1_097068_2022-04-05_final.stac-item
2022-04-13 09:11:35	ga_ls9c_ard_3-2-1_089078_2022-04-12_final.stac-item
2022-04-16 11:17:45	ga_ls9c_ard_3-2-1_110069_2022-04-16_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-05-15 09:11:19	ga_ls9c_ard_3-2-1_089078_2022-05-14_final.stac-item
2022-06-21 09:32:01	ga_ls9c_ard_3-2-1_092083_2022-06-21_final.stac-item
2022-06-30 09:23:33	ga_ls9c_ard_3-2-1_091077_2022-06-29_final.stac-item
2022-07-17 10:06:46	ga_ls9c_ard_3-2-1_098077_2022-07-17_final.stac-item
2022-08-13 09:52:10	ga_ls9c_ard_3-2-1_095086_2022-08-13_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-08-25 11:52:14	ga_ls9c_ard_3-2-1_115077_2022-08-25_final.stac-item
2022-09-09 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-09-08_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-23 09:44:10	ga_ls9c_ard_3-2-1_094081_2022-09-23_final.stac-item
2022-09-25 09:32:12	ga_ls9c_ard_3-2-1_092082_2022-09-25_final.stac-item
2022-09-25 11:06:18	ga_ls9c_ard_3-2-1_108070_2022-09-25_final.stac-item
2022-10-16 09:52:02	ga_ls9c_ard_3-2-1_095085_2022-10-16_final.stac-item
2022-10-25 09:40:41	ga_ls9c_ard_3-2-1_094072_2022-10-25_final.stac-item
2022-10-26 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-10-26_final.stac-item
2022-11-14 09:22:22	ga_ls9c_ard_3-2-1_090088_2022-11-13_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-11-17 11:26:57	ga_ls9c_ard_3-2-1_111075_2022-11-17_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-12 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-12-12_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-16 10:13:05	ga_ls9c_ard_3-2-1_099076_2023-01-16_final.stac-item
2023-01-16 11:51:58	ga_ls9c_ard_3-2-1_115076_2023-01-16_final.stac-item
2023-02-18 09:21:54	ga_ls9c_ard_3-2-1_090087_2023-02-17_final.stac-item
2023-02-18 09:22:42	ga_ls9c_ard_3-2-1_090089_2023-02-17_final.stac-item
2023-02-27 10:47:41	ga_ls9c_ard_3-2-1_105070_2023-02-27_final.stac-item
2023-03-04 09:28:54	ga_ls9c_ard_3-2-1_092074_2023-03-03_final.stac-item
2023-03-23 11:42:31	ga_ls9c_ard_3-2-1_113084_2023-03-23_final.stac-item
2023-03-27 11:12:56	ga_ls9c_ard_3-2-1_109072_2023-03-27_final.stac-item
2023-04-09 10:44:20	ga_ls9c_ard_3-2-1_104078_2023-04-09_final.stac-item
2023-04-11 10:33:33	ga_ls9c_ard_3-2-1_102082_2023-04-11_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-05-17 10:03:44	ga_ls9c_ard_3-2-1_098070_2023-05-17_final.stac-item
2023-05-27 09:06:36	ga_ls9c_ard_3-2-1_088082_2023-05-26_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-02 11:46:53	ga_ls9c_ard_3-2-1_114081_2023-06-02_final.stac-item
2023-06-13 09:45:22	ga_ls9c_ard_3-2-1_095071_2023-06-13_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-07-03 09:27:34	ga_ls9c_ard_3-2-1_091088_2023-07-02_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-07-31 11:25:46	ga_ls9c_ard_3-2-1_111074_2023-07-31_final.stac-item
2023-08-03 10:16:38	ga_ls9c_ard_3-2-1_100071_2023-08-03_final.stac-item
2023-08-14 09:57:44	ga_ls9c_ard_3-2-1_097070_2023-08-14_final.stac-item
2023-08-18 09:34:12	ga_ls9c_ard_3-2-1_093073_2023-08-18_final.stac-item
2023-10-12 11:18:06	ga_ls9c_ard_3-2-1_110069_2023-10-12_final.stac-item
2023-10-21 09:34:42	ga_ls9c_ard_3-2-1_093073_2023-10-21_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-31 10:13:17	ga_ls9c_ard_3-2-1_099077_2023-10-31_final.stac-item
2023-11-07 11:57:33	ga_ls9c_ard_3-2-1_116075_2023-11-07_final.stac-item
2023-11-18 09:56:59	ga_ls9c_ard_3-2-1_097067_2023-11-18_final.stac-item
2023-11-18 09:57:22	ga_ls9c_ard_3-2-1_097068_2023-11-18_final.stac-item
2023-12-03 09:22:58	ga_ls9c_ard_3-2-1_090090_2023-12-02_final.stac-item
2023-12-08 09:34:40	ga_ls9c_ard_3-2-1_093073_2023-12-08_final.stac-item
2023-12-11 10:04:01	ga_ls9c_ard_3-2-1_098069_2023-12-11_final.stac-item
2023-12-15 11:19:25	ga_ls9c_ard_3-2-1_110072_2023-12-15_final.stac-item
2023-12-22 11:24:50	ga_ls9c_ard_3-2-1_111070_2023-12-22_final.stac-item
2023-12-31 11:23:00	ga_ls9c_ard_3-2-1_110081_2023-12-31_final.stac-item
2024-02-04 11:53:07	ga_ls9c_ard_3-2-1_115079_2024-02-04_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-02-19 09:34:01	ga_ls9c_ard_3-2-1_092087_2024-02-19_final.stac-item
2024-02-27 10:19:02	ga_ls9c_ard_3-2-1_100076_2024-02-27_final.stac-item
2024-02-29 10:07:53	ga_ls9c_ard_3-2-1_098079_2024-02-29_final.stac-item
2024-03-13 09:39:24	ga_ls9c_ard_3-2-1_093085_2024-03-13_final.stac-item
2024-03-23 11:52:31	ga_ls9c_ard_3-2-1_115078_2024-03-23_final.stac-item
2024-04-08 10:08:43	ga_ls9c_ard_3-2-1_099066_2024-04-08_final.stac-item
2024-04-22 10:25:34	ga_ls9c_ard_3-2-1_101078_2024-04-22_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