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
2021-11-15 11:19:25	ga_ls9c_ard_3-2-1_110074_2021-11-15_final.stac-item
2021-12-05 10:05:21	ga_ls9c_ard_3-2-1_098072_2021-12-05_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2021-12-18 11:12:48	ga_ls9c_ard_3-2-1_109071_2021-12-18_final.stac-item
2021-12-29 10:54:17	ga_ls9c_ard_3-2-1_106071_2021-12-29_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-02-02 09:52:40	ga_ls9c_ard_3-2-1_095087_2022-02-02_final.stac-item
2022-02-15 09:19:42	ga_ls9c_ard_3-2-1_090082_2022-02-14_final.stac-item
2022-03-07 10:33:41	ga_ls9c_ard_3-2-1_102082_2022-03-07_final.stac-item
2022-03-22 11:23:40	ga_ls9c_ard_3-2-1_111068_2022-03-22_final.stac-item
2022-03-27 10:10:04	ga_ls9c_ard_3-2-1_098085_2022-03-27_final.stac-item
2022-04-12 10:03:14	ga_ls9c_ard_3-2-1_098068_2022-04-12_final.stac-item
2022-05-05 10:12:50	ga_ls9c_ard_3-2-1_099077_2022-05-05_final.stac-item
2022-05-06 09:17:36	ga_ls9c_ard_3-2-1_090078_2022-05-05_final.stac-item
2022-05-13 09:26:06	ga_ls9c_ard_3-2-1_091084_2022-05-12_final.stac-item
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final.stac-item
2022-05-27 09:39:56	ga_ls9c_ard_3-2-1_093088_2022-05-27_final.stac-item
2022-06-06 10:10:40	ga_ls9c_ard_3-2-1_099072_2022-06-06_final.stac-item
2022-06-11 10:33:13	ga_ls9c_ard_3-2-1_102082_2022-06-11_final.stac-item
2022-06-19 09:44:18	ga_ls9c_ard_3-2-1_094083_2022-06-19_final.stac-item
2022-06-24 11:41:06	ga_ls9c_ard_3-2-1_113081_2022-06-24_final.stac-item
2022-07-07 11:05:48	ga_ls9c_ard_3-2-1_108070_2022-07-07_final.stac-item
2022-07-12 09:52:12	ga_ls9c_ard_3-2-1_095087_2022-07-12_final.stac-item
2022-07-23 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-07-23_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-20 10:52:55	ga_ls9c_ard_3-2-1_105083_2022-09-20_final.stac-item
2022-09-25 09:34:12	ga_ls9c_ard_3-2-1_092087_2022-09-25_final.stac-item
2022-10-05 10:04:30	ga_ls9c_ard_3-2-1_098070_2022-10-05_final.stac-item
2022-10-08 10:39:48	ga_ls9c_ard_3-2-1_103081_2022-10-08_final.stac-item
2022-10-24 10:39:54	ga_ls9c_ard_3-2-1_103081_2022-10-24_final.stac-item
2022-10-29 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-10-28_final.stac-item
2022-10-29 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-10-29_final.stac-item
2022-11-01 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-11-01_final.stac-item
2022-11-01 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-11-01_final.stac-item
2022-11-03 09:37:38	ga_ls9c_ard_3-2-1_093080_2022-11-03_final.stac-item
2022-11-05 09:27:41	ga_ls9c_ard_3-2-1_091086_2022-11-04_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-14 10:56:27	ga_ls9c_ard_3-2-1_106076_2022-11-14_final.stac-item
2022-11-15 10:04:01	ga_ls9c_ard_3-2-1_097084_2022-11-15_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-11-17 11:30:33	ga_ls9c_ard_3-2-1_111084_2022-11-17_final.stac-item
2022-11-24 09:57:50	ga_ls9c_ard_3-2-1_096084_2022-11-24_final.stac-item
2022-11-28 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-11-28_final.stac-item
2022-11-29 11:51:38	ga_ls9c_ard_3-2-1_115075_2022-11-29_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-12-01 11:41:15	ga_ls9c_ard_3-2-1_113080_2022-12-01_final.stac-item
2022-12-03 11:30:29	ga_ls9c_ard_3-2-1_111084_2022-12-03_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-04_final.stac-item
2022-12-06 10:18:08	ga_ls9c_ard_3-2-1_100073_2022-12-06_final.stac-item
2022-12-06 10:22:08	ga_ls9c_ard_3-2-1_100083_2022-12-06_final.stac-item
2022-12-07 09:27:43	ga_ls9c_ard_3-2-1_091086_2022-12-06_final.stac-item
2022-12-09 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-12-09_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2022-12-23 09:24:04	ga_ls9c_ard_3-2-1_091077_2022-12-22_final.stac-item
2022-12-25 09:12:55	ga_ls9c_ard_3-2-1_089080_2022-12-24_final.stac-item
2022-12-31 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-31_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-17 09:20:39	ga_ls9c_ard_3-2-1_090084_2023-01-16_final.stac-item
2023-01-26 09:13:42	ga_ls9c_ard_3-2-1_089082_2023-01-25_final.stac-item
2023-01-31 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-01-31_final.stac-item
2023-02-01 10:12:47	ga_ls9c_ard_3-2-1_099075_2023-02-01_final.stac-item
2023-02-05 11:25:47	ga_ls9c_ard_3-2-1_111072_2023-02-05_final.stac-item
2023-02-17 10:14:45	ga_ls9c_ard_3-2-1_099080_2023-02-17_final.stac-item
2023-03-02 09:40:05	ga_ls9c_ard_3-2-1_094071_2023-03-02_final.stac-item
2023-03-31 10:46:58	ga_ls9c_ard_3-2-1_105069_2023-03-31_final.stac-item
2023-04-07 10:58:19	ga_ls9c_ard_3-2-1_106082_2023-04-07_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_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
2023-05-01 11:44:21	ga_ls9c_ard_3-2-1_114074_2023-05-01_final.stac-item
2023-05-03 09:57:03	ga_ls9c_ard_3-2-1_096084_2023-05-03_final.stac-item
2023-05-07 11:05:36	ga_ls9c_ard_3-2-1_108070_2023-05-07_final.stac-item
2023-05-08 10:10:47	ga_ls9c_ard_3-2-1_099072_2023-05-08_final.stac-item
2023-05-08 10:15:10	ga_ls9c_ard_3-2-1_099083_2023-05-08_final.stac-item
2023-05-11 10:42:04	ga_ls9c_ard_3-2-1_104073_2023-05-11_final.stac-item
2023-05-13 10:28:06	ga_ls9c_ard_3-2-1_102069_2023-05-13_final.stac-item
2023-05-16 09:26:05	ga_ls9c_ard_3-2-1_091084_2023-05-15_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-05-22 10:27:00	ga_ls9c_ard_3-2-1_101082_2023-05-22_final.stac-item
2023-06-01 09:25:57	ga_ls9c_ard_3-2-1_091084_2023-05-31_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-06-23 10:27:12	ga_ls9c_ard_3-2-1_101083_2023-06-23_final.stac-item
2023-06-25 11:51:19	ga_ls9c_ard_3-2-1_115077_2023-06-25_final.stac-item
2023-07-24 11:18:41	ga_ls9c_ard_3-2-1_110072_2023-07-24_final.stac-item
2023-07-26 09:33:27	ga_ls9c_ard_3-2-1_092087_2023-07-26_final.stac-item
2023-07-28 10:52:49	ga_ls9c_ard_3-2-1_106069_2023-07-28_final.stac-item
2023-08-14 09:56:33	ga_ls9c_ard_3-2-1_097067_2023-08-14_final.stac-item
2023-10-15 10:10:33	ga_ls9c_ard_3-2-1_099070_2023-10-15_final.stac-item
2023-10-17 09:57:01	ga_ls9c_ard_3-2-1_097067_2023-10-17_final.stac-item
2023-10-23 09:23:31	ga_ls9c_ard_3-2-1_091076_2023-10-22_final.stac-item
2023-10-23 11:00:25	ga_ls9c_ard_3-2-1_107071_2023-10-23_final.stac-item
2023-10-25 09:14:45	ga_ls9c_ard_3-2-1_089085_2023-10-24_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-11-01 10:56:08	ga_ls9c_ard_3-2-1_106076_2023-11-01_final.stac-item
2023-11-04 11:26:13	ga_ls9c_ard_3-2-1_111074_2023-11-04_final.stac-item
2023-11-16 10:11:18	ga_ls9c_ard_3-2-1_099072_2023-11-16_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_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