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
2021-11-10 09:40:41	ga_ls9c_ard_3-2-1_094080_2021-11-10_final.stac-item
2021-11-10 09:43:28	ga_ls9c_ard_3-2-1_094087_2021-11-10_final.stac-item
2021-11-18 11:40:38	ga_ls9c_ard_3-2-1_113074_2021-11-18_final.stac-item
2021-11-22 11:01:32	ga_ls9c_ard_3-2-1_107070_2021-11-22_final.stac-item
2021-12-09 11:20:16	ga_ls9c_ard_3-2-1_110074_2021-12-09_final.stac-item
2021-12-14 09:58:16	ga_ls9c_ard_3-2-1_097070_2021-12-14_final.stac-item
2021-12-18 11:17:59	ga_ls9c_ard_3-2-1_109084_2021-12-18_final.stac-item
2021-12-20 09:27:57	ga_ls9c_ard_3-2-1_091087_2021-12-19_final.stac-item
2022-01-21 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-01-20_final.stac-item
2022-01-29 10:13:00	ga_ls9c_ard_3-2-1_099076_2022-01-29_final.stac-item
2022-01-31 11:38:43	ga_ls9c_ard_3-2-1_113074_2022-01-31_final.stac-item
2022-02-11 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-02-11_final.stac-item
2022-02-12 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-02-12_final.stac-item
2022-02-14 10:15:19	ga_ls9c_ard_3-2-1_099082_2022-02-14_final.stac-item
2022-02-22 09:26:12	ga_ls9c_ard_3-2-1_091083_2022-02-21_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-03-12 09:12:09	ga_ls9c_ard_3-2-1_089079_2022-03-11_final.stac-item
2022-03-20 09:57:58	ga_ls9c_ard_3-2-1_097070_2022-03-20_final.stac-item
2022-04-02 09:31:00	ga_ls9c_ard_3-2-1_092080_2022-04-02_final.stac-item
2022-04-26 10:20:39	ga_ls9c_ard_3-2-1_100081_2022-04-26_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-20 09:32:09	ga_ls9c_ard_3-2-1_092084_2022-05-20_final.stac-item
2022-05-21 11:52:43	ga_ls9c_ard_3-2-1_115080_2022-05-21_final.stac-item
2022-05-22 09:21:00	ga_ls9c_ard_3-2-1_090087_2022-05-21_final.stac-item
2022-06-05 11:10:16	ga_ls9c_ard_3-2-1_108082_2022-06-05_final.stac-item
2022-06-07 09:20:38	ga_ls9c_ard_3-2-1_090086_2022-06-06_final.stac-item
2022-06-27 10:29:09	ga_ls9c_ard_3-2-1_102071_2022-06-27_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_2022-07-08_final.stac-item
2022-07-15 11:58:23	ga_ls9c_ard_3-2-1_116078_2022-07-15_final.stac-item
2022-07-30 09:35:17	ga_ls9c_ard_3-2-1_093075_2022-07-30_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-08-25 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-08-25_final.stac-item
2022-08-26 09:22:07	ga_ls9c_ard_3-2-1_090088_2022-08-25_final.stac-item
2022-08-28 09:07:22	ga_ls9c_ard_3-2-1_088082_2022-08-27_final.stac-item
2022-08-31 09:39:04	ga_ls9c_ard_3-2-1_093084_2022-08-31_final.stac-item
2022-09-01 10:17:08	ga_ls9c_ard_3-2-1_100071_2022-09-01_final.stac-item
2022-09-07 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-09-07_final.stac-item
2022-09-07 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-09-07_final.stac-item
2022-10-06 10:48:09	ga_ls9c_ard_3-2-1_105071_2022-10-06_final.stac-item
2022-10-09 09:46:35	ga_ls9c_ard_3-2-1_094087_2022-10-09_final.stac-item
2022-10-18 11:14:58	ga_ls9c_ard_3-2-1_109076_2022-10-18_final.stac-item
2022-10-25 09:46:16	ga_ls9c_ard_3-2-1_094086_2022-10-25_final.stac-item
2022-10-27 11:07:36	ga_ls9c_ard_3-2-1_108073_2022-10-27_final.stac-item
2022-10-29 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-10-29_final.stac-item
2022-11-06 10:05:22	ga_ls9c_ard_3-2-1_098072_2022-11-06_final.stac-item
2022-11-08 11:35:06	ga_ls9c_ard_3-2-1_112080_2022-11-08_final.stac-item
2022-11-12 09:33:07	ga_ls9c_ard_3-2-1_092084_2022-11-12_final.stac-item
2022-11-17 09:46:29	ga_ls9c_ard_3-2-1_095071_2022-11-17_final.stac-item
2022-11-19 11:15:00	ga_ls9c_ard_3-2-1_109076_2022-11-19_final.stac-item
2022-11-22 10:08:36	ga_ls9c_ard_3-2-1_098080_2022-11-22_final.stac-item
2022-11-23 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-11-22_final.stac-item
2022-11-26 09:44:40	ga_ls9c_ard_3-2-1_094082_2022-11-26_final.stac-item
2022-11-29 10:13:57	ga_ls9c_ard_3-2-1_099078_2022-11-29_final.stac-item
2022-12-05 11:15:21	ga_ls9c_ard_3-2-1_109077_2022-12-05_final.stac-item
2022-12-12 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-12-12_final.stac-item
2022-12-24 10:04:08	ga_ls9c_ard_3-2-1_098069_2022-12-24_final.stac-item
2022-12-24 10:10:31	ga_ls9c_ard_3-2-1_098085_2022-12-24_final.stac-item
2022-12-29 10:25:07	ga_ls9c_ard_3-2-1_101075_2022-12-29_final.stac-item
2022-12-29 10:28:18	ga_ls9c_ard_3-2-1_101083_2022-12-29_final.stac-item
2023-01-02 11:38:54	ga_ls9c_ard_3-2-1_113074_2023-01-02_final.stac-item
2023-01-11 09:57:48	ga_ls9c_ard_3-2-1_096084_2023-01-11_final.stac-item
2023-01-11 09:58:36	ga_ls9c_ard_3-2-1_096086_2023-01-11_final.stac-item
2023-01-17 09:20:39	ga_ls9c_ard_3-2-1_090084_2023-01-16_final.stac-item
2023-01-17 10:55:08	ga_ls9c_ard_3-2-1_106073_2023-01-17_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-21 10:28:45	ga_ls9c_ard_3-2-1_102069_2023-01-21_final.stac-item
2023-01-24 11:01:43	ga_ls9c_ard_3-2-1_107074_2023-01-24_final.stac-item
2023-02-05 09:52:05	ga_ls9c_ard_3-2-1_095085_2023-02-05_final.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-23 11:16:48	ga_ls9c_ard_3-2-1_109081_2023-02-23_final.stac-item
2023-02-25 09:29:08	ga_ls9c_ard_3-2-1_091090_2023-02-24_final.stac-item
2023-03-02 11:23:45	ga_ls9c_ard_3-2-1_110083_2023-03-02_final.stac-item
2023-03-09 09:46:33	ga_ls9c_ard_3-2-1_095072_2023-03-09_final.stac-item
2023-03-12 10:18:15	ga_ls9c_ard_3-2-1_100074_2023-03-12_final.stac-item
2023-03-25 11:25:20	ga_ls9c_ard_3-2-1_111072_2023-03-25_final.stac-item
2023-03-31 09:12:04	ga_ls9c_ard_3-2-1_089079_2023-03-30_final.stac-item
2023-04-14 09:28:19	ga_ls9c_ard_3-2-1_091089_2023-04-13_final.stac-item
2023-04-14 11:00:01	ga_ls9c_ard_3-2-1_107071_2023-04-14_final.stac-item
2023-04-15 10:02:47	ga_ls9c_ard_3-2-1_098067_2023-04-15_final.stac-item
2023-04-30 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-04-29_final.stac-item
2023-04-30 11:01:30	ga_ls9c_ard_3-2-1_107075_2023-04-30_final.stac-item
2023-05-09 09:21:32	ga_ls9c_ard_3-2-1_090088_2023-05-08_final.stac-item
2023-05-21 09:45:45	ga_ls9c_ard_3-2-1_094087_2023-05-21_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-25 11:50:31	ga_ls9c_ard_3-2-1_115075_2023-06-25_final.stac-item
2023-07-16 10:28:28	ga_ls9c_ard_3-2-1_102070_2023-07-16_final.stac-item
2023-07-18 11:58:11	ga_ls9c_ard_3-2-1_116078_2023-07-18_final.stac-item
2023-07-20 10:02:57	ga_ls9c_ard_3-2-1_098068_2023-07-20_final.stac-item
2023-07-21 10:51:24	ga_ls9c_ard_3-2-1_105081_2023-07-21_final.stac-item
2023-08-03 11:57:55	ga_ls9c_ard_3-2-1_116077_2023-08-03_final.stac-item
2023-08-06 09:16:15	ga_ls9c_ard_3-2-1_089090_2023-08-05_final.stac-item
2023-08-14 11:41:49	ga_ls9c_ard_3-2-1_113083_2023-08-14_final.stac-item
2023-08-16 11:25:03	ga_ls9c_ard_3-2-1_111072_2023-08-16_final.stac-item
2023-10-23 09:27:31	ga_ls9c_ard_3-2-1_091086_2023-10-22_final.stac-item
2023-10-25 09:13:33	ga_ls9c_ard_3-2-1_089082_2023-10-24_final.stac-item
2023-10-26 09:58:00	ga_ls9c_ard_3-2-1_096085_2023-10-26_final.stac-item
2023-11-04 11:28:37	ga_ls9c_ard_3-2-1_111080_2023-11-04_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_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