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
2021-11-12 09:23:08	ga_ls9c_ard_3-2-1_091083_2021-11-11_final.stac-item
2021-11-13 10:01:30	ga_ls9c_ard_3-2-1_097079_2021-11-13_final.stac-item
2021-12-05 10:05:21	ga_ls9c_ard_3-2-1_098072_2021-12-05_final.stac-item
2021-12-10 10:26:37	ga_ls9c_ard_3-2-1_101079_2021-12-10_final.stac-item
2021-12-27 11:05:50	ga_ls9c_ard_3-2-1_108069_2021-12-27_final.stac-item
2022-01-03 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-01-03_final.stac-item
2022-01-04 10:18:23	ga_ls9c_ard_3-2-1_100074_2022-01-04_final.stac-item
2022-02-14 10:09:20	ga_ls9c_ard_3-2-1_099067_2022-02-14_final.stac-item
2022-02-18 11:25:27	ga_ls9c_ard_3-2-1_111072_2022-02-18_final.stac-item
2022-02-20 11:11:53	ga_ls9c_ard_3-2-1_109069_2022-02-20_final.stac-item
2022-03-03 10:55:36	ga_ls9c_ard_3-2-1_106075_2022-03-03_final.stac-item
2022-04-02 09:27:49	ga_ls9c_ard_3-2-1_092072_2022-04-01_final.stac-item
2022-04-28 11:46:22	ga_ls9c_ard_3-2-1_114079_2022-04-28_final.stac-item
2022-05-06 10:58:29	ga_ls9c_ard_3-2-1_106083_2022-05-06_final.stac-item
2022-05-11 09:38:29	ga_ls9c_ard_3-2-1_093084_2022-05-11_final.stac-item
2022-05-14 10:07:45	ga_ls9c_ard_3-2-1_098080_2022-05-14_final.stac-item
2022-05-18 11:18:39	ga_ls9c_ard_3-2-1_110072_2022-05-18_final.stac-item
2022-06-16 09:13:21	ga_ls9c_ard_3-2-1_089083_2022-06-15_final.stac-item
2022-06-22 10:14:07	ga_ls9c_ard_3-2-1_099080_2022-06-22_final.stac-item
2022-07-05 11:18:58	ga_ls9c_ard_3-2-1_110072_2022-07-05_final.stac-item
2022-08-26 09:17:20	ga_ls9c_ard_3-2-1_090076_2022-08-25_final.stac-item
2022-08-31 09:40:40	ga_ls9c_ard_3-2-1_093088_2022-08-31_final.stac-item
2022-09-15 10:30:45	ga_ls9c_ard_3-2-1_102074_2022-09-15_final.stac-item
2022-09-18 09:23:12	ga_ls9c_ard_3-2-1_091075_2022-09-17_final.stac-item
2022-09-25 11:08:42	ga_ls9c_ard_3-2-1_108076_2022-09-25_final.stac-item
2022-09-30 11:24:03	ga_ls9c_ard_3-2-1_111068_2022-09-30_final.stac-item
2022-11-11 10:23:57	ga_ls9c_ard_3-2-1_101072_2022-11-11_final.stac-item
2022-11-13 11:52:28	ga_ls9c_ard_3-2-1_115077_2022-11-13_final.stac-item
2022-11-17 11:25:22	ga_ls9c_ard_3-2-1_111071_2022-11-17_final.stac-item
2022-12-23 09:27:16	ga_ls9c_ard_3-2-1_091085_2022-12-22_final.stac-item
2022-12-24 10:08:32	ga_ls9c_ard_3-2-1_098080_2022-12-24_final.stac-item
2023-01-08 09:24:08	ga_ls9c_ard_3-2-1_091077_2023-01-07_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-02-06 10:28:34	ga_ls9c_ard_3-2-1_102068_2023-02-06_final.stac-item
2023-02-25 11:02:26	ga_ls9c_ard_3-2-1_107076_2023-02-25_final.stac-item
2023-03-12 10:20:38	ga_ls9c_ard_3-2-1_100080_2023-03-12_final.stac-item
2023-03-31 09:11:16	ga_ls9c_ard_3-2-1_089077_2023-03-30_final.stac-item
2023-04-16 10:46:51	ga_ls9c_ard_3-2-1_105069_2023-04-16_final.stac-item
2023-04-28 09:33:49	ga_ls9c_ard_3-2-1_093072_2023-04-28_final.stac-item
2023-04-30 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-04-29_final.stac-item
2023-05-07 09:34:18	ga_ls9c_ard_3-2-1_092089_2023-05-07_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-25 10:52:40	ga_ls9c_ard_3-2-1_106069_2023-05-25_final.stac-item
2023-07-26 09:33:27	ga_ls9c_ard_3-2-1_092087_2023-07-26_final.stac-item
2023-08-16 11:29:27	ga_ls9c_ard_3-2-1_111083_2023-08-16_final.stac-item
2023-08-20 10:59:34	ga_ls9c_ard_3-2-1_107070_2023-08-20_final.stac-item
2023-09-05 10:59:45	ga_ls9c_ard_3-2-1_107070_2023-09-05_final.stac-item
2023-09-23 09:12:34	ga_ls9c_ard_3-2-1_089080_2023-09-22_final.stac-item
2023-09-30 09:17:08	ga_ls9c_ard_3-2-1_090076_2023-09-29_final.stac-item
2023-10-06 10:21:49	ga_ls9c_ard_3-2-1_100083_2023-10-06_final.stac-item
2023-10-12 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-12_final.stac-item
2023-10-24 10:05:11	ga_ls9c_ard_3-2-1_098072_2023-10-24_final.stac-item
2023-10-29 10:26:28	ga_ls9c_ard_3-2-1_101079_2023-10-29_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_final.stac-item
2023-12-06 11:29:07	ga_ls9c_ard_3-2-1_111081_2023-12-06_final.stac-item
2023-12-09 10:19:56	ga_ls9c_ard_3-2-1_100078_2023-12-09_final.stac-item
2023-12-15 09:40:08	ga_ls9c_ard_3-2-1_094071_2023-12-15_final.stac-item
2023-12-18 11:52:20	ga_ls9c_ard_3-2-1_115077_2023-12-18_final.stac-item
2024-01-02 09:29:20	ga_ls9c_ard_3-2-1_092075_2024-01-01_final.stac-item
2024-01-02 09:32:08	ga_ls9c_ard_3-2-1_092082_2024-01-02_final.stac-item
2024-01-15 10:36:56	ga_ls9c_ard_3-2-1_103074_2024-01-15_final.stac-item
2024-01-15 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-15_final.stac-item
2024-02-12 09:21:58	ga_ls9c_ard_3-2-1_091072_2024-02-11_final.stac-item
2024-02-29 11:45:34	ga_ls9c_ard_3-2-1_114076_2024-02-29_final.stac-item
2024-03-02 11:36:25	ga_ls9c_ard_3-2-1_112084_2024-03-02_final.stac-item
2024-03-08 09:20:53	ga_ls9c_ard_3-2-1_090085_2024-03-07_final.stac-item
2024-03-09 11:38:38	ga_ls9c_ard_3-2-1_113074_2024-03-09_final.stac-item
2024-03-11 09:47:47	ga_ls9c_ard_3-2-1_095075_2024-03-11_final.stac-item
2024-03-25 11:38:32	ga_ls9c_ard_3-2-1_113074_2024-03-25_final.stac-item
2024-03-31 09:23:17	ga_ls9c_ard_3-2-1_091076_2024-03-30_final.stac-item
2024-04-07 09:28:39	ga_ls9c_ard_3-2-1_092074_2024-04-06_final.stac-item
2024-04-07 09:33:02	ga_ls9c_ard_3-2-1_092085_2024-04-07_final.stac-item
2024-04-26 09:56:48	ga_ls9c_ard_3-2-1_097068_2024-04-26_final.stac-item
2024-04-28 11:29:42	ga_ls9c_ard_3-2-1_111084_2024-04-28_final.stac-item
2024-05-21 11:30:56	ga_ls9c_ard_3-2-1_112072_2024-05-21_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