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
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final.stac-item
2021-12-11 09:30:59	ga_ls9c_ard_3-2-1_092079_2021-12-11_final.stac-item
2021-12-22 09:14:48	ga_ls9c_ard_3-2-1_089085_2021-12-21_final.stac-item
2021-12-24 10:38:08	ga_ls9c_ard_3-2-1_103077_2021-12-24_final.stac-item
2022-01-15 11:41:53	ga_ls9c_ard_3-2-1_113082_2022-01-15_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-01-31 11:41:55	ga_ls9c_ard_3-2-1_113082_2022-01-31_final.stac-item
2022-02-12 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-02-12_final.stac-item
2022-02-20 11:17:04	ga_ls9c_ard_3-2-1_109082_2022-02-20_final.stac-item
2022-02-25 09:55:28	ga_ls9c_ard_3-2-1_096079_2022-02-25_final.stac-item
2022-02-27 09:45:28	ga_ls9c_ard_3-2-1_094085_2022-02-27_final.stac-item
2022-03-20 11:40:26	ga_ls9c_ard_3-2-1_113079_2022-03-20_final.stac-item
2022-04-12 11:44:54	ga_ls9c_ard_3-2-1_114075_2022-04-12_final.stac-item
2022-04-16 09:45:15	ga_ls9c_ard_3-2-1_094085_2022-04-16_final.stac-item
2022-05-06 10:54:05	ga_ls9c_ard_3-2-1_106072_2022-05-06_final.stac-item
2022-05-11 11:15:46	ga_ls9c_ard_3-2-1_109080_2022-05-11_final.stac-item
2022-05-16 09:52:58	ga_ls9c_ard_3-2-1_096074_2022-05-16_final.stac-item
2022-05-23 09:59:52	ga_ls9c_ard_3-2-1_097076_2022-05-23_final.stac-item
2022-06-14 09:24:05	ga_ls9c_ard_3-2-1_091079_2022-06-13_final.stac-item
2022-06-27 10:28:21	ga_ls9c_ard_3-2-1_102069_2022-06-27_final.stac-item
2022-06-30 11:00:51	ga_ls9c_ard_3-2-1_107073_2022-06-30_final.stac-item
2022-08-04 09:53:05	ga_ls9c_ard_3-2-1_096073_2022-08-04_final.stac-item
2022-08-24 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-08-24_final.stac-item
2022-08-24 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-08-24_final.stac-item
2022-09-08 10:24:06	ga_ls9c_ard_3-2-1_101073_2022-09-08_final.stac-item
2022-09-09 11:10:10	ga_ls9c_ard_3-2-1_108080_2022-09-09_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-09-16 09:40:44	ga_ls9c_ard_3-2-1_093088_2022-09-16_final.stac-item
2022-09-20 09:12:51	ga_ls9c_ard_3-2-1_089080_2022-09-19_final.stac-item
2022-09-20 09:13:14	ga_ls9c_ard_3-2-1_089081_2022-09-19_final.stac-item
2022-09-24 10:23:50	ga_ls9c_ard_3-2-1_101072_2022-09-24_final.stac-item
2022-09-25 11:07:06	ga_ls9c_ard_3-2-1_108072_2022-09-25_final.stac-item
2022-09-28 11:41:36	ga_ls9c_ard_3-2-1_113081_2022-09-28_final.stac-item
2022-10-08 10:37:00	ga_ls9c_ard_3-2-1_103074_2022-10-08_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-11-02 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-11-02_final.stac-item
2022-11-08 09:55:49	ga_ls9c_ard_3-2-1_096079_2022-11-08_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-17 09:46:29	ga_ls9c_ard_3-2-1_095071_2022-11-17_final.stac-item
2022-11-20 10:20:58	ga_ls9c_ard_3-2-1_100080_2022-11-20_final.stac-item
2022-11-28 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-11-28_final.stac-item
2022-12-02 10:43:14	ga_ls9c_ard_3-2-1_104074_2022-12-02_final.stac-item
2022-12-06 10:18:56	ga_ls9c_ard_3-2-1_100075_2022-12-06_final.stac-item
2022-12-07 11:04:12	ga_ls9c_ard_3-2-1_107080_2022-12-07_final.stac-item
2022-12-08 11:46:16	ga_ls9c_ard_3-2-1_114077_2022-12-08_final.stac-item
2022-12-12 11:19:57	ga_ls9c_ard_3-2-1_110073_2022-12-12_final.stac-item
2022-12-15 10:12:22	ga_ls9c_ard_3-2-1_099074_2022-12-15_final.stac-item
2022-12-18 10:42:28	ga_ls9c_ard_3-2-1_104072_2022-12-18_final.stac-item
2022-12-19 09:52:49	ga_ls9c_ard_3-2-1_095087_2022-12-19_final.stac-item
2022-12-21 09:39:15	ga_ls9c_ard_3-2-1_093084_2022-12-21_final.stac-item
2022-12-31 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-12-31_final.stac-item
2023-01-01 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-12-31_final.stac-item
2023-01-04 09:48:27	ga_ls9c_ard_3-2-1_095076_2023-01-04_final.stac-item
2023-01-18 11:41:58	ga_ls9c_ard_3-2-1_113082_2023-01-18_final.stac-item
2023-01-19 10:43:32	ga_ls9c_ard_3-2-1_104075_2023-01-19_final.stac-item
2023-01-24 11:04:31	ga_ls9c_ard_3-2-1_107081_2023-01-24_final.stac-item
2023-01-27 09:55:47	ga_ls9c_ard_3-2-1_096079_2023-01-27_final.stac-item
2023-01-27 11:34:16	ga_ls9c_ard_3-2-1_112078_2023-01-27_final.stac-item
2023-01-29 09:42:15	ga_ls9c_ard_3-2-1_094076_2023-01-29_final.stac-item
2023-01-31 09:30:19	ga_ls9c_ard_3-2-1_092077_2023-01-31_final.stac-item
2023-01-31 09:32:18	ga_ls9c_ard_3-2-1_092082_2023-01-31_final.stac-item
2023-02-03 11:42:07	ga_ls9c_ard_3-2-1_113082_2023-02-03_final.stac-item
2023-02-26 10:06:48	ga_ls9c_ard_3-2-1_098076_2023-02-26_final.stac-item
2023-03-01 10:38:30	ga_ls9c_ard_3-2-1_103078_2023-03-01_final.stac-item
2023-03-07 10:00:57	ga_ls9c_ard_3-2-1_097077_2023-03-07_final.stac-item
2023-03-07 11:39:50	ga_ls9c_ard_3-2-1_113077_2023-03-07_final.stac-item
2023-03-11 09:36:11	ga_ls9c_ard_3-2-1_093077_2023-03-11_final.stac-item
2023-03-14 11:47:10	ga_ls9c_ard_3-2-1_114080_2023-03-14_final.stac-item
2023-04-01 09:52:32	ga_ls9c_ard_3-2-1_096072_2023-04-01_final.stac-item
2023-04-04 10:24:38	ga_ls9c_ard_3-2-1_101075_2023-04-04_final.stac-item
2023-04-12 11:17:12	ga_ls9c_ard_3-2-1_109083_2023-04-12_final.stac-item
2023-04-14 09:26:19	ga_ls9c_ard_3-2-1_091084_2023-04-13_final.stac-item
2023-05-05 09:45:27	ga_ls9c_ard_3-2-1_094086_2023-05-05_final.stac-item
2023-05-05 11:20:21	ga_ls9c_ard_3-2-1_110076_2023-05-05_final.stac-item
2023-05-05 11:21:33	ga_ls9c_ard_3-2-1_110079_2023-05-05_final.stac-item
2023-05-07 11:06:24	ga_ls9c_ard_3-2-1_108072_2023-05-07_final.stac-item
2023-05-11 10:44:52	ga_ls9c_ard_3-2-1_104080_2023-05-11_final.stac-item
2023-05-14 09:35:16	ga_ls9c_ard_3-2-1_093076_2023-05-14_final.stac-item
2023-05-21 09:45:45	ga_ls9c_ard_3-2-1_094087_2023-05-21_final.stac-item
2023-05-21 11:20:38	ga_ls9c_ard_3-2-1_110077_2023-05-21_final.stac-item
2023-06-24 09:28:47	ga_ls9c_ard_3-2-1_092076_2023-06-23_final.stac-item
2023-06-27 09:58:31	ga_ls9c_ard_3-2-1_097073_2023-06-27_final.stac-item
2023-07-05 10:48:08	ga_ls9c_ard_3-2-1_105073_2023-07-05_final.stac-item
2023-07-15 11:28:53	ga_ls9c_ard_3-2-1_111082_2023-07-15_final.stac-item
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-07-18_final.stac-item
2023-07-25 10:23:28	ga_ls9c_ard_3-2-1_101073_2023-07-25_final.stac-item
2023-07-27 10:09:09	ga_ls9c_ard_3-2-1_099068_2023-07-27_final.stac-item
2023-07-28 09:18:44	ga_ls9c_ard_3-2-1_090081_2023-07-27_final.stac-item
2023-07-29 10:00:01	ga_ls9c_ard_3-2-1_097076_2023-07-29_final.stac-item
2023-08-02 09:38:57	ga_ls9c_ard_3-2-1_093085_2023-08-02_final.stac-item
2023-08-03 10:21:01	ga_ls9c_ard_3-2-1_100082_2023-08-03_final.stac-item
2023-08-12 11:52:58	ga_ls9c_ard_3-2-1_115080_2023-08-12_final.stac-item
2023-10-14 11:08:34	ga_ls9c_ard_3-2-1_108076_2023-10-14_final.stac-item
2023-10-15 11:53:02	ga_ls9c_ard_3-2-1_115079_2023-10-15_final.stac-item
2023-10-16 10:57:49	ga_ls9c_ard_3-2-1_106080_2023-10-16_final.stac-item
2023-10-21 11:12:23	ga_ls9c_ard_3-2-1_109070_2023-10-21_final.stac-item
2023-11-03 10:41:44	ga_ls9c_ard_3-2-1_104071_2023-11-03_final.stac-item
2023-11-15 09:30:49	ga_ls9c_ard_3-2-1_092079_2023-11-15_final.stac-item
2023-11-17 09:18:53	ga_ls9c_ard_3-2-1_090080_2023-11-16_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_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