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

59 results

Time (local)	Label
2021-12-04 09:28:53	ga_ls9c_ard_3-2-1_091089_2021-12-03_final.stac-item
2021-12-16 11:26:45	ga_ls9c_ard_3-2-1_111075_2021-12-16_final.stac-item
2021-12-29 10:55:04	ga_ls9c_ard_3-2-1_106073_2021-12-29_final.stac-item
2022-01-14 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-01-13_final.stac-item
2022-01-21 09:26:20	ga_ls9c_ard_3-2-1_091083_2022-01-20_final.stac-item
2022-02-15 10:53:23	ga_ls9c_ard_3-2-1_106069_2022-02-15_final.stac-item
2022-02-17 10:40:37	ga_ls9c_ard_3-2-1_104068_2022-02-17_final.stac-item
2022-03-03 09:21:06	ga_ls9c_ard_3-2-1_090086_2022-03-02_final.stac-item
2022-03-05 10:40:27	ga_ls9c_ard_3-2-1_104068_2022-03-05_final.stac-item
2022-03-31 09:40:34	ga_ls9c_ard_3-2-1_094073_2022-03-31_final.stac-item
2022-04-02 09:34:12	ga_ls9c_ard_3-2-1_092088_2022-04-02_final.stac-item
2022-04-05 11:38:23	ga_ls9c_ard_3-2-1_113074_2022-04-05_final.stac-item
2022-04-30 09:57:31	ga_ls9c_ard_3-2-1_096085_2022-04-30_final.stac-item
2022-06-21 09:34:01	ga_ls9c_ard_3-2-1_092088_2022-06-21_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-07-18 09:16:22	ga_ls9c_ard_3-2-1_089090_2022-07-17_final.stac-item
2022-08-01 09:28:32	ga_ls9c_ard_3-2-1_091089_2022-07-31_final.stac-item
2022-09-09 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-09-08_final.stac-item
2022-10-11 11:06:45	ga_ls9c_ard_3-2-1_108071_2022-10-11_final.stac-item
2022-10-20 11:05:25	ga_ls9c_ard_3-2-1_107083_2022-10-20_final.stac-item
2022-10-28 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-10-28_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-17 11:25:46	ga_ls9c_ard_3-2-1_111072_2022-11-17_final.stac-item
2023-01-21 10:30:21	ga_ls9c_ard_3-2-1_102073_2023-01-21_final.stac-item
2023-01-27 09:57:47	ga_ls9c_ard_3-2-1_096084_2023-01-27_final.stac-item
2023-02-16 11:06:24	ga_ls9c_ard_3-2-1_108070_2023-02-16_final.stac-item
2023-02-20 09:07:06	ga_ls9c_ard_3-2-1_088081_2023-02-19_final.stac-item
2023-02-23 09:39:31	ga_ls9c_ard_3-2-1_093085_2023-02-23_final.stac-item
2023-04-06 10:11:04	ga_ls9c_ard_3-2-1_099072_2023-04-06_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-05-01 10:06:40	ga_ls9c_ard_3-2-1_098077_2023-05-01_final.stac-item
2023-05-12 11:25:43	ga_ls9c_ard_3-2-1_111074_2023-05-12_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-05-18 09:13:41	ga_ls9c_ard_3-2-1_089084_2023-05-17_final.stac-item
2023-05-21 11:19:26	ga_ls9c_ard_3-2-1_110074_2023-05-21_final.stac-item
2023-06-25 11:52:07	ga_ls9c_ard_3-2-1_115079_2023-06-25_final.stac-item
2023-07-06 11:31:00	ga_ls9c_ard_3-2-1_112072_2023-07-06_final.stac-item
2023-07-29 09:58:25	ga_ls9c_ard_3-2-1_097072_2023-07-29_final.stac-item
2023-08-03 10:17:26	ga_ls9c_ard_3-2-1_100073_2023-08-03_final.stac-item
2023-08-13 10:53:22	ga_ls9c_ard_3-2-1_106070_2023-08-13_final.stac-item
2023-09-01 09:46:45	ga_ls9c_ard_3-2-1_095073_2023-09-01_final.stac-item
2023-09-14 09:17:34	ga_ls9c_ard_3-2-1_090077_2023-09-13_final.stac-item
2023-10-09 09:13:03	ga_ls9c_ard_3-2-1_089081_2023-10-08_final.stac-item
2023-10-28 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-28_final.stac-item
2023-10-29 10:23:17	ga_ls9c_ard_3-2-1_101071_2023-10-29_final.stac-item
2023-11-06 09:35:48	ga_ls9c_ard_3-2-1_093076_2023-11-06_final.stac-item
2023-11-10 10:49:35	ga_ls9c_ard_3-2-1_105075_2023-11-10_final.stac-item
2023-11-17 09:16:53	ga_ls9c_ard_3-2-1_090075_2023-11-16_final.stac-item
2023-12-18 10:11:27	ga_ls9c_ard_3-2-1_099072_2023-12-18_final.stac-item
2023-12-24 09:40:46	ga_ls9c_ard_3-2-1_093088_2023-12-24_final.stac-item
2023-12-26 11:00:30	ga_ls9c_ard_3-2-1_107071_2023-12-26_final.stac-item
2024-01-05 10:01:23	ga_ls9c_ard_3-2-1_097078_2024-01-05_final.stac-item
2024-01-11 09:26:21	ga_ls9c_ard_3-2-1_091083_2024-01-10_final.stac-item
2024-02-13 11:45:42	ga_ls9c_ard_3-2-1_114076_2024-02-13_final.stac-item
2024-03-15 09:22:14	ga_ls9c_ard_3-2-1_091073_2024-03-14_final.stac-item
2024-04-16 09:22:21	ga_ls9c_ard_3-2-1_091074_2024-04-15_final.stac-item
2024-04-30 11:13:20	ga_ls9c_ard_3-2-1_109074_2024-04-30_final.stac-item
2024-05-11 10:53:11	ga_ls9c_ard_3-2-1_106070_2024-05-11_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