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

First 100 results (query limit)

Time (local)	Label
2021-11-05 11:13:17	ga_ls9c_ard_3-2-1_109071_2021-11-05_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2022-01-01 09:50:17	ga_ls9c_ard_3-2-1_095081_2022-01-01_final.stac-item
2022-01-17 11:25:08	ga_ls9c_ard_3-2-1_111071_2022-01-17_final.stac-item
2022-01-29 11:53:05	ga_ls9c_ard_3-2-1_115079_2022-01-29_final.stac-item
2022-01-30 09:19:46	ga_ls9c_ard_3-2-1_090082_2022-01-29_final.stac-item
2022-02-01 10:41:54	ga_ls9c_ard_3-2-1_104071_2022-02-01_final.stac-item
2022-03-02 10:13:56	ga_ls9c_ard_3-2-1_099079_2022-03-02_final.stac-item
2022-03-22 09:47:35	ga_ls9c_ard_3-2-1_095075_2022-03-22_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-04-01 10:27:01	ga_ls9c_ard_3-2-1_101081_2022-04-01_final.stac-item
2022-04-22 10:40:11	ga_ls9c_ard_3-2-1_104068_2022-04-22_final.stac-item
2022-05-10 10:32:31	ga_ls9c_ard_3-2-1_102080_2022-05-10_final.stac-item
2022-05-11 11:16:58	ga_ls9c_ard_3-2-1_109083_2022-05-11_final.stac-item
2022-05-23 10:01:52	ga_ls9c_ard_3-2-1_097081_2022-05-23_final.stac-item
2022-05-27 11:11:14	ga_ls9c_ard_3-2-1_109069_2022-05-27_final.stac-item
2022-05-29 09:21:12	ga_ls9c_ard_3-2-1_091072_2022-05-28_final.stac-item
2022-05-30 10:07:39	ga_ls9c_ard_3-2-1_098080_2022-05-30_final.stac-item
2022-06-07 09:21:49	ga_ls9c_ard_3-2-1_090089_2022-06-06_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-07-07 11:10:59	ga_ls9c_ard_3-2-1_108083_2022-07-07_final.stac-item
2022-07-28 11:25:18	ga_ls9c_ard_3-2-1_111072_2022-07-28_final.stac-item
2022-07-29 10:30:29	ga_ls9c_ard_3-2-1_102074_2022-07-29_final.stac-item
2022-08-22 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-08-22_final.stac-item
2022-08-26 10:54:13	ga_ls9c_ard_3-2-1_106071_2022-08-26_final.stac-item
2022-09-02 09:28:42	ga_ls9c_ard_3-2-1_091089_2022-09-01_final.stac-item
2022-09-02 11:02:48	ga_ls9c_ard_3-2-1_107077_2022-09-02_final.stac-item
2022-09-12 11:41:30	ga_ls9c_ard_3-2-1_113081_2022-09-12_final.stac-item
2022-09-13 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-09-12_final.stac-item
2022-09-15 10:31:09	ga_ls9c_ard_3-2-1_102075_2022-09-15_final.stac-item
2022-09-27 10:55:09	ga_ls9c_ard_3-2-1_106073_2022-09-27_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-09 11:23:28	ga_ls9c_ard_3-2-1_110082_2022-10-09_final.stac-item
2022-10-20 09:29:19	ga_ls9c_ard_3-2-1_091090_2022-10-19_final.stac-item
2022-10-26 10:27:32	ga_ls9c_ard_3-2-1_101081_2022-10-26_final.stac-item
2022-10-27 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-10-27_final.stac-item
2022-12-01 10:01:34	ga_ls9c_ard_3-2-1_097078_2022-12-01_final.stac-item
2022-12-08 10:03:48	ga_ls9c_ard_3-2-1_098068_2022-12-08_final.stac-item
2022-12-14 11:07:12	ga_ls9c_ard_3-2-1_108072_2022-12-14_final.stac-item
2022-12-15 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-15_final.stac-item
2022-12-17 11:42:29	ga_ls9c_ard_3-2-1_113083_2022-12-17_final.stac-item
2022-12-19 09:52:01	ga_ls9c_ard_3-2-1_095085_2022-12-19_final.stac-item
2023-01-04 11:26:56	ga_ls9c_ard_3-2-1_111075_2023-01-04_final.stac-item
2023-01-14 10:28:16	ga_ls9c_ard_3-2-1_101083_2023-01-14_final.stac-item
2023-01-18 11:41:10	ga_ls9c_ard_3-2-1_113080_2023-01-18_final.stac-item
2023-01-27 11:35:04	ga_ls9c_ard_3-2-1_112080_2023-01-27_final.stac-item
2023-02-02 10:56:04	ga_ls9c_ard_3-2-1_106075_2023-02-02_final.stac-item
2023-02-25 09:26:44	ga_ls9c_ard_3-2-1_091084_2023-02-24_final.stac-item
2023-02-27 10:52:04	ga_ls9c_ard_3-2-1_105081_2023-02-27_final.stac-item
2023-03-18 09:40:22	ga_ls9c_ard_3-2-1_094072_2023-03-18_final.stac-item
2023-03-31 10:50:09	ga_ls9c_ard_3-2-1_105077_2023-03-31_final.stac-item
2023-04-16 10:46:04	ga_ls9c_ard_3-2-1_105067_2023-04-16_final.stac-item
2023-04-17 11:34:31	ga_ls9c_ard_3-2-1_112080_2023-04-17_final.stac-item
2023-04-18 10:34:30	ga_ls9c_ard_3-2-1_103069_2023-04-18_final.stac-item
2023-04-21 09:32:06	ga_ls9c_ard_3-2-1_092083_2023-04-21_final.stac-item
2023-04-22 10:14:10	ga_ls9c_ard_3-2-1_099080_2023-04-22_final.stac-item
2023-04-30 11:04:42	ga_ls9c_ard_3-2-1_107083_2023-04-30_final.stac-item
2023-05-08 11:50:27	ga_ls9c_ard_3-2-1_115074_2023-05-08_final.stac-item
2023-05-18 10:45:47	ga_ls9c_ard_3-2-1_105067_2023-05-18_final.stac-item
2023-05-26 11:41:31	ga_ls9c_ard_3-2-1_113083_2023-05-26_final.stac-item
2023-06-04 11:33:43	ga_ls9c_ard_3-2-1_112079_2023-06-04_final.stac-item
2023-06-04 11:35:19	ga_ls9c_ard_3-2-1_112083_2023-06-04_final.stac-item
2023-06-15 09:38:09	ga_ls9c_ard_3-2-1_093084_2023-06-15_final.stac-item
2023-06-16 10:17:01	ga_ls9c_ard_3-2-1_100073_2023-06-16_final.stac-item
2023-06-17 09:22:36	ga_ls9c_ard_3-2-1_091076_2023-06-16_final.stac-item
2023-06-18 10:04:16	ga_ls9c_ard_3-2-1_098072_2023-06-18_final.stac-item
2023-06-19 10:45:32	ga_ls9c_ard_3-2-1_105067_2023-06-19_final.stac-item
2023-06-25 11:50:07	ga_ls9c_ard_3-2-1_115074_2023-06-25_final.stac-item
2023-07-08 09:44:34	ga_ls9c_ard_3-2-1_094084_2023-07-08_final.stac-item
2023-07-12 10:53:35	ga_ls9c_ard_3-2-1_106071_2023-07-12_final.stac-item
2023-07-19 11:00:10	ga_ls9c_ard_3-2-1_107072_2023-07-19_final.stac-item
2023-07-21 09:13:43	ga_ls9c_ard_3-2-1_089084_2023-07-20_final.stac-item
2023-07-26 11:05:09	ga_ls9c_ard_3-2-1_108069_2023-07-26_final.stac-item
2023-08-03 10:18:37	ga_ls9c_ard_3-2-1_100076_2023-08-03_final.stac-item
2023-08-04 11:04:41	ga_ls9c_ard_3-2-1_107083_2023-08-04_final.stac-item
2023-08-07 11:35:37	ga_ls9c_ard_3-2-1_112083_2023-08-07_final.stac-item
2023-08-08 10:36:00	ga_ls9c_ard_3-2-1_103073_2023-08-08_final.stac-item
2023-08-16 09:50:10	ga_ls9c_ard_3-2-1_095082_2023-08-16_final.stac-item
2023-08-20 11:03:10	ga_ls9c_ard_3-2-1_107079_2023-08-20_final.stac-item
2023-08-20 11:05:09	ga_ls9c_ard_3-2-1_107084_2023-08-20_final.stac-item
2023-09-05 09:28:51	ga_ls9c_ard_3-2-1_091090_2023-09-04_final.stac-item
2023-09-06 10:04:56	ga_ls9c_ard_3-2-1_098072_2023-09-06_final.stac-item
2023-09-08 11:36:17	ga_ls9c_ard_3-2-1_112084_2023-09-08_final.stac-item
2023-10-03 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-10-03_final.stac-item
2023-10-09 09:13:27	ga_ls9c_ard_3-2-1_089082_2023-10-08_final.stac-item
2023-10-09 10:48:45	ga_ls9c_ard_3-2-1_105073_2023-10-09_final.stac-item
2023-10-12 09:45:12	ga_ls9c_ard_3-2-1_094084_2023-10-12_final.stac-item
2023-10-12 11:18:06	ga_ls9c_ard_3-2-1_110069_2023-10-12_final.stac-item
2023-11-01 10:57:43	ga_ls9c_ard_3-2-1_106080_2023-11-01_final.stac-item
2023-11-04 11:29:01	ga_ls9c_ard_3-2-1_111081_2023-11-04_final.stac-item
2023-11-06 11:12:17	ga_ls9c_ard_3-2-1_109070_2023-11-06_final.stac-item
2023-11-09 11:47:12	ga_ls9c_ard_3-2-1_114080_2023-11-09_final.stac-item
2023-11-13 11:18:53	ga_ls9c_ard_3-2-1_110071_2023-11-13_final.stac-item
2023-11-20 09:46:15	ga_ls9c_ard_3-2-1_095071_2023-11-20_final.stac-item
2023-11-28 10:37:45	ga_ls9c_ard_3-2-1_103076_2023-11-28_final.stac-item
2023-12-14 10:36:33	ga_ls9c_ard_3-2-1_103073_2023-12-14_final.stac-item
2023-12-15 09:45:19	ga_ls9c_ard_3-2-1_094084_2023-12-15_final.stac-item
2023-12-20 10:02:42	ga_ls9c_ard_3-2-1_097081_2023-12-20_final.stac-item
2023-12-24 09:40:23	ga_ls9c_ard_3-2-1_093087_2023-12-24_final.stac-item
2024-01-03 10:12:59	ga_ls9c_ard_3-2-1_099076_2024-01-03_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