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
2021-11-13 09:56:43	ga_ls9c_ard_3-2-1_097067_2021-11-13_final.stac-item
2021-11-22 09:26:27	ga_ls9c_ard_3-2-1_091079_2021-11-21_final.stac-item
2021-12-10 10:26:13	ga_ls9c_ard_3-2-1_101078_2021-12-10_final.stac-item
2021-12-23 09:52:28	ga_ls9c_ard_3-2-1_096071_2021-12-23_final.stac-item
2021-12-25 11:21:00	ga_ls9c_ard_3-2-1_110076_2021-12-25_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-14 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-01-13_final.stac-item
2022-01-19 09:35:06	ga_ls9c_ard_3-2-1_093074_2022-01-19_final.stac-item
2022-01-20 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-01-20_final.stac-item
2022-01-21 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-01-21_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-01-26 09:43:41	ga_ls9c_ard_3-2-1_094080_2022-01-26_final.stac-item
2022-02-04 11:13:12	ga_ls9c_ard_3-2-1_109072_2022-02-04_final.stac-item
2022-02-10 10:36:05	ga_ls9c_ard_3-2-1_103072_2022-02-10_final.stac-item
2022-02-14 11:52:13	ga_ls9c_ard_3-2-1_115077_2022-02-14_final.stac-item
2022-02-16 09:58:33	ga_ls9c_ard_3-2-1_097071_2022-02-16_final.stac-item
2022-03-04 09:57:35	ga_ls9c_ard_3-2-1_097069_2022-03-04_final.stac-item
2022-03-10 09:23:18	ga_ls9c_ard_3-2-1_091076_2022-03-09_final.stac-item
2022-03-11 10:02:59	ga_ls9c_ard_3-2-1_098067_2022-03-11_final.stac-item
2022-03-28 10:46:57	ga_ls9c_ard_3-2-1_105069_2022-03-28_final.stac-item
2022-04-05 09:57:30	ga_ls9c_ard_3-2-1_097069_2022-04-05_final.stac-item
2022-05-03 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-05-03_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-05-13 09:28:29	ga_ls9c_ard_3-2-1_091090_2022-05-12_final.stac-item
2022-05-27 09:39:56	ga_ls9c_ard_3-2-1_093088_2022-05-27_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-05 11:07:29	ga_ls9c_ard_3-2-1_108075_2022-06-05_final.stac-item
2022-07-01 10:02:49	ga_ls9c_ard_3-2-1_098067_2022-07-01_final.stac-item
2022-07-02 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-07-02_final.stac-item
2022-07-05 11:18:58	ga_ls9c_ard_3-2-1_110072_2022-07-05_final.stac-item
2022-07-16 09:25:05	ga_ls9c_ard_3-2-1_091081_2022-07-15_final.stac-item
2022-08-17 09:27:29	ga_ls9c_ard_3-2-1_091086_2022-08-16_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-08-25 11:53:02	ga_ls9c_ard_3-2-1_115079_2022-08-25_final.stac-item
2022-08-31 11:13:34	ga_ls9c_ard_3-2-1_109073_2022-08-31_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-16 09:40:20	ga_ls9c_ard_3-2-1_093087_2022-09-16_final.stac-item
2022-09-27 09:23:03	ga_ls9c_ard_3-2-1_090090_2022-09-26_final.stac-item
2022-10-02 11:17:17	ga_ls9c_ard_3-2-1_109082_2022-10-02_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_2022-10-03_final.stac-item
2022-10-05 10:04:06	ga_ls9c_ard_3-2-1_098069_2022-10-05_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-23 09:52:39	ga_ls9c_ard_3-2-1_096071_2022-10-23_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-10-29 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-10-29_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-06 10:09:45	ga_ls9c_ard_3-2-1_098083_2022-11-06_final.stac-item
2022-11-12 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-11-11_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-15 11:38:07	ga_ls9c_ard_3-2-1_113072_2022-11-15_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-21 09:27:44	ga_ls9c_ard_3-2-1_091086_2022-11-20_final.stac-item
2022-11-23 09:13:22	ga_ls9c_ard_3-2-1_089081_2022-11-22_final.stac-item
2022-11-25 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-25_final.stac-item
2022-12-07 09:23:43	ga_ls9c_ard_3-2-1_091076_2022-12-06_final.stac-item
2022-12-14 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-14_final.stac-item
2022-12-17 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-12-17_final.stac-item
2022-12-29 10:27:55	ga_ls9c_ard_3-2-1_101082_2022-12-29_final.stac-item
2023-01-06 11:14:59	ga_ls9c_ard_3-2-1_109076_2023-01-06_final.stac-item
2023-01-07 10:18:33	ga_ls9c_ard_3-2-1_100074_2023-01-07_final.stac-item
2023-01-08 09:27:19	ga_ls9c_ard_3-2-1_091085_2023-01-07_final.stac-item
2023-01-15 11:08:20	ga_ls9c_ard_3-2-1_108075_2023-01-15_final.stac-item
2023-01-17 09:23:02	ga_ls9c_ard_3-2-1_090090_2023-01-16_final.stac-item
2023-01-28 10:35:28	ga_ls9c_ard_3-2-1_103070_2023-01-28_final.stac-item
2023-01-29 11:20:44	ga_ls9c_ard_3-2-1_110075_2023-01-29_final.stac-item
2023-02-08 10:18:37	ga_ls9c_ard_3-2-1_100074_2023-02-08_final.stac-item
2023-02-16 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-02-16_final.stac-item
2023-02-23 11:14:24	ga_ls9c_ard_3-2-1_109075_2023-02-23_final.stac-item
2023-02-26 10:08:24	ga_ls9c_ard_3-2-1_098080_2023-02-26_final.stac-item
2023-02-27 10:52:52	ga_ls9c_ard_3-2-1_105083_2023-02-27_final.stac-item
2023-03-26 10:30:06	ga_ls9c_ard_3-2-1_102073_2023-03-26_final.stac-item
2023-03-27 11:14:08	ga_ls9c_ard_3-2-1_109075_2023-03-27_final.stac-item
2023-03-28 10:18:05	ga_ls9c_ard_3-2-1_100074_2023-03-28_final.stac-item
2023-03-29 09:21:39	ga_ls9c_ard_3-2-1_091072_2023-03-28_final.stac-item
2023-04-04 10:25:50	ga_ls9c_ard_3-2-1_101078_2023-04-04_final.stac-item
2023-04-10 09:52:18	ga_ls9c_ard_3-2-1_095087_2023-04-10_final.stac-item
2023-04-15 10:06:23	ga_ls9c_ard_3-2-1_098076_2023-04-15_final.stac-item
2023-04-23 10:53:25	ga_ls9c_ard_3-2-1_106070_2023-04-23_final.stac-item
2023-04-28 11:17:29	ga_ls9c_ard_3-2-1_109084_2023-04-28_final.stac-item
2023-05-08 10:15:10	ga_ls9c_ard_3-2-1_099083_2023-05-08_final.stac-item
2023-05-15 11:57:24	ga_ls9c_ard_3-2-1_116076_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 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-05-15_final.stac-item
2023-05-29 10:29:32	ga_ls9c_ard_3-2-1_102073_2023-05-29_final.stac-item
2023-06-22 09:45:32	ga_ls9c_ard_3-2-1_094087_2023-06-22_final.stac-item
2023-07-23 10:33:50	ga_ls9c_ard_3-2-1_103068_2023-07-23_final.stac-item
2023-07-25 10:25:27	ga_ls9c_ard_3-2-1_101078_2023-07-25_final.stac-item
2023-08-05 10:03:53	ga_ls9c_ard_3-2-1_098070_2023-08-05_final.stac-item
2023-08-13 09:16:28	ga_ls9c_ard_3-2-1_090075_2023-08-12_final.stac-item
2023-08-14 10:00:56	ga_ls9c_ard_3-2-1_097078_2023-08-14_final.stac-item
2023-10-24 10:03:35	ga_ls9c_ard_3-2-1_098068_2023-10-24_final.stac-item
2023-10-25 10:48:50	ga_ls9c_ard_3-2-1_105073_2023-10-25_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-30 09:32:26	ga_ls9c_ard_3-2-1_092083_2023-10-30_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-11-04 11:26:13	ga_ls9c_ard_3-2-1_111074_2023-11-04_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-21 10:28:43	ga_ls9c_ard_3-2-1_102069_2023-11-21_final.stac-item
2023-11-21 10:33:31	ga_ls9c_ard_3-2-1_102081_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