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
2021-12-10 10:25:26	ga_ls9c_ard_3-2-1_101076_2021-12-10_final.stac-item
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_final.stac-item
2021-12-16 09:46:41	ga_ls9c_ard_3-2-1_095072_2021-12-16_final.stac-item
2021-12-21 11:46:54	ga_ls9c_ard_3-2-1_114079_2021-12-21_final.stac-item
2021-12-24 10:39:20	ga_ls9c_ard_3-2-1_103080_2021-12-24_final.stac-item
2021-12-25 09:41:43	ga_ls9c_ard_3-2-1_094075_2021-12-25_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-30 09:18:34	ga_ls9c_ard_3-2-1_090079_2022-01-29_final.stac-item
2022-02-07 10:10:23	ga_ls9c_ard_3-2-1_098085_2022-02-07_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-06-21 09:29:13	ga_ls9c_ard_3-2-1_092076_2022-06-20_final.stac-item
2022-07-09 09:17:20	ga_ls9c_ard_3-2-1_090077_2022-07-08_final.stac-item
2022-07-25 10:53:10	ga_ls9c_ard_3-2-1_106069_2022-07-25_final.stac-item
2022-08-19 10:48:25	ga_ls9c_ard_3-2-1_105072_2022-08-19_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-08-31 11:17:09	ga_ls9c_ard_3-2-1_109082_2022-08-31_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-10-01 10:31:37	ga_ls9c_ard_3-2-1_102076_2022-10-01_final.stac-item
2022-10-08 10:35:25	ga_ls9c_ard_3-2-1_103070_2022-10-08_final.stac-item
2022-10-13 10:54:24	ga_ls9c_ard_3-2-1_106071_2022-10-13_final.stac-item
2022-10-14 10:01:59	ga_ls9c_ard_3-2-1_097079_2022-10-14_final.stac-item
2022-10-16 11:29:43	ga_ls9c_ard_3-2-1_111082_2022-10-16_final.stac-item
2022-10-18 11:17:22	ga_ls9c_ard_3-2-1_109082_2022-10-18_final.stac-item
2022-10-20 11:01:49	ga_ls9c_ard_3-2-1_107074_2022-10-20_final.stac-item
2022-11-05 11:05:46	ga_ls9c_ard_3-2-1_107084_2022-11-05_final.stac-item
2023-05-12 09:47:14	ga_ls9c_ard_3-2-1_095075_2023-05-12_final.stac-item
2023-05-13 10:29:42	ga_ls9c_ard_3-2-1_102073_2023-05-13_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-05-14 11:13:45	ga_ls9c_ard_3-2-1_109075_2023-05-14_final.stac-item
2023-05-15 10:17:19	ga_ls9c_ard_3-2-1_100073_2023-05-15_final.stac-item
2023-05-15 10:17:43	ga_ls9c_ard_3-2-1_100074_2023-05-15_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-15 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-05-15_final.stac-item
2023-05-16 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-05-15_final.stac-item
2023-05-16 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-05-15_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-05-17 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-05-17_final.stac-item
2023-05-18 10:47:23	ga_ls9c_ard_3-2-1_105071_2023-05-18_final.stac-item
2023-05-20 10:35:00	ga_ls9c_ard_3-2-1_103071_2023-05-20_final.stac-item
2023-05-20 10:35:24	ga_ls9c_ard_3-2-1_103072_2023-05-20_final.stac-item
2023-09-04 10:17:40	ga_ls9c_ard_3-2-1_100073_2023-09-04_final.stac-item
2023-09-04 10:18:04	ga_ls9c_ard_3-2-1_100074_2023-09-04_final.stac-item
2023-09-05 09:24:28	ga_ls9c_ard_3-2-1_091079_2023-09-04_final.stac-item
2023-09-05 09:25:15	ga_ls9c_ard_3-2-1_091081_2023-09-04_final.stac-item
2023-09-05 09:27:15	ga_ls9c_ard_3-2-1_091086_2023-09-04_final.stac-item
2023-09-06 10:08:32	ga_ls9c_ard_3-2-1_098081_2023-09-06_final.stac-item
2023-09-07 10:47:25	ga_ls9c_ard_3-2-1_105070_2023-09-07_final.stac-item
2023-09-08 09:56:36	ga_ls9c_ard_3-2-1_096082_2023-09-08_final.stac-item
2023-09-09 10:35:05	ga_ls9c_ard_3-2-1_103070_2023-09-09_final.stac-item
2023-09-09 10:35:29	ga_ls9c_ard_3-2-1_103071_2023-09-09_final.stac-item
2023-09-10 09:41:28	ga_ls9c_ard_3-2-1_094075_2023-09-10_final.stac-item
2023-09-10 09:44:16	ga_ls9c_ard_3-2-1_094082_2023-09-10_final.stac-item
2023-09-10 11:22:21	ga_ls9c_ard_3-2-1_110080_2023-09-10_final.stac-item
2023-09-10 11:23:33	ga_ls9c_ard_3-2-1_110083_2023-09-10_final.stac-item
2023-09-12 09:29:31	ga_ls9c_ard_3-2-1_092076_2023-09-11_final.stac-item
2023-09-15 10:00:26	ga_ls9c_ard_3-2-1_097076_2023-09-15_final.stac-item
2023-09-15 10:01:38	ga_ls9c_ard_3-2-1_097079_2023-09-15_final.stac-item
2023-09-15 11:40:31	ga_ls9c_ard_3-2-1_113079_2023-09-15_final.stac-item
2023-09-17 09:52:04	ga_ls9c_ard_3-2-1_095086_2023-09-17_final.stac-item
2023-09-18 10:28:57	ga_ls9c_ard_3-2-1_102070_2023-09-18_final.stac-item
2023-09-18 10:29:21	ga_ls9c_ard_3-2-1_102071_2023-09-18_final.stac-item
2023-09-18 10:32:08	ga_ls9c_ard_3-2-1_102078_2023-09-18_final.stac-item
2023-09-20 10:17:47	ga_ls9c_ard_3-2-1_100073_2023-09-20_final.stac-item
2023-09-23 10:47:28	ga_ls9c_ard_3-2-1_105070_2023-09-23_final.stac-item
2023-09-24 09:56:37	ga_ls9c_ard_3-2-1_096082_2023-09-24_final.stac-item
2023-09-25 10:34:17	ga_ls9c_ard_3-2-1_103068_2023-09-25_final.stac-item
2023-09-25 10:38:40	ga_ls9c_ard_3-2-1_103079_2023-09-25_final.stac-item
2023-09-26 09:41:26	ga_ls9c_ard_3-2-1_094075_2023-09-26_final.stac-item
2023-09-26 09:44:14	ga_ls9c_ard_3-2-1_094082_2023-09-26_final.stac-item
2023-09-26 09:45:26	ga_ls9c_ard_3-2-1_094085_2023-09-26_final.stac-item
2023-09-26 09:45:50	ga_ls9c_ard_3-2-1_094086_2023-09-26_final.stac-item
2023-09-26 11:18:43	ga_ls9c_ard_3-2-1_110071_2023-09-26_final.stac-item
2023-09-27 10:23:05	ga_ls9c_ard_3-2-1_101071_2023-09-27_final.stac-item
2023-09-27 10:25:53	ga_ls9c_ard_3-2-1_101078_2023-09-27_final.stac-item
2023-09-27 10:27:05	ga_ls9c_ard_3-2-1_101081_2023-09-27_final.stac-item
2023-09-28 09:32:15	ga_ls9c_ard_3-2-1_092083_2023-09-28_final.stac-item
2023-09-28 09:32:38	ga_ls9c_ard_3-2-1_092084_2023-09-28_final.stac-item
2023-09-30 09:19:31	ga_ls9c_ard_3-2-1_090082_2023-09-29_final.stac-item
2023-09-30 09:19:55	ga_ls9c_ard_3-2-1_090083_2023-09-29_final.stac-item
2023-09-30 10:57:13	ga_ls9c_ard_3-2-1_106079_2023-09-30_final.stac-item
2023-10-01 10:02:48	ga_ls9c_ard_3-2-1_097082_2023-10-01_final.stac-item
2023-10-01 10:03:12	ga_ls9c_ard_3-2-1_097083_2023-10-01_final.stac-item
2023-10-01 11:39:42	ga_ls9c_ard_3-2-1_113077_2023-10-01_final.stac-item
2023-10-01 11:40:54	ga_ls9c_ard_3-2-1_113080_2023-10-01_final.stac-item
2023-10-03 11:28:58	ga_ls9c_ard_3-2-1_111081_2023-10-03_final.stac-item
2023-10-04 10:28:58	ga_ls9c_ard_3-2-1_102070_2023-10-04_final.stac-item
2023-10-04 10:31:45	ga_ls9c_ard_3-2-1_102077_2023-10-04_final.stac-item
2023-10-06 10:21:25	ga_ls9c_ard_3-2-1_100082_2023-10-06_final.stac-item
2023-10-07 09:24:36	ga_ls9c_ard_3-2-1_091079_2023-10-06_final.stac-item
2023-10-07 09:25:24	ga_ls9c_ard_3-2-1_091081_2023-10-06_final.stac-item
2023-10-07 10:59:53	ga_ls9c_ard_3-2-1_107070_2023-10-07_final.stac-item
2023-10-07 11:03:29	ga_ls9c_ard_3-2-1_107079_2023-10-07_final.stac-item
2023-10-08 10:10:16	ga_ls9c_ard_3-2-1_098085_2023-10-08_final.stac-item
2023-10-09 09:11:51	ga_ls9c_ard_3-2-1_089078_2023-10-08_final.stac-item
2023-10-09 10:47:57	ga_ls9c_ard_3-2-1_105071_2023-10-09_final.stac-item
2023-10-11 10:34:50	ga_ls9c_ard_3-2-1_103069_2023-10-11_final.stac-item
2023-10-12 09:44:24	ga_ls9c_ard_3-2-1_094082_2023-10-12_final.stac-item
2023-10-12 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-12_final.stac-item
2023-10-14 09:29:41	ga_ls9c_ard_3-2-1_092076_2023-10-13_final.stac-item
2023-10-16 09:20:08	ga_ls9c_ard_3-2-1_090083_2023-10-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years