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
2021-11-05 11:14:05	ga_ls9c_ard_3-2-1_109073_2021-11-05_final.stac-item
2021-11-10 11:18:33	ga_ls9c_ard_3-2-1_110078_2021-11-10_final.stac-item
2021-12-09 11:20:16	ga_ls9c_ard_3-2-1_110074_2021-12-09_final.stac-item
2021-12-11 11:07:05	ga_ls9c_ard_3-2-1_108072_2021-12-11_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-14 11:41:08	ga_ls9c_ard_3-2-1_113080_2021-12-14_final.stac-item
2021-12-20 09:24:21	ga_ls9c_ard_3-2-1_091078_2021-12-19_final.stac-item
2022-01-01 11:26:46	ga_ls9c_ard_3-2-1_111075_2022-01-01_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-15 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-01-15_final.stac-item
2022-01-16 10:41:04	ga_ls9c_ard_3-2-1_104069_2022-01-16_final.stac-item
2022-01-21 09:21:57	ga_ls9c_ard_3-2-1_091072_2022-01-20_final.stac-item
2022-02-04 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-02-04_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-17 10:41:01	ga_ls9c_ard_3-2-1_104069_2022-02-17_final.stac-item
2022-02-21 10:18:14	ga_ls9c_ard_3-2-1_100074_2022-02-21_final.stac-item
2022-02-25 11:36:20	ga_ls9c_ard_3-2-1_112084_2022-02-25_final.stac-item
2022-02-26 10:35:31	ga_ls9c_ard_3-2-1_103071_2022-02-26_final.stac-item
2022-03-02 10:12:44	ga_ls9c_ard_3-2-1_099076_2022-03-02_final.stac-item
2022-03-04 09:58:23	ga_ls9c_ard_3-2-1_097071_2022-03-04_final.stac-item
2022-03-07 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-03-07_final.stac-item
2022-03-11 10:10:10	ga_ls9c_ard_3-2-1_098085_2022-03-11_final.stac-item
2022-03-11 11:45:03	ga_ls9c_ard_3-2-1_114075_2022-03-11_final.stac-item
2022-03-20 10:01:33	ga_ls9c_ard_3-2-1_097079_2022-03-20_final.stac-item
2022-03-24 09:34:01	ga_ls9c_ard_3-2-1_093072_2022-03-24_final.stac-item
2022-04-05 11:38:47	ga_ls9c_ard_3-2-1_113075_2022-04-05_final.stac-item
2022-04-05 11:40:47	ga_ls9c_ard_3-2-1_113080_2022-04-05_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-11 11:02:51	ga_ls9c_ard_3-2-1_107078_2022-04-11_final.stac-item
2022-04-16 09:46:03	ga_ls9c_ard_3-2-1_094087_2022-04-16_final.stac-item
2022-05-14 11:45:26	ga_ls9c_ard_3-2-1_114077_2022-05-14_final.stac-item
2022-06-09 10:40:22	ga_ls9c_ard_3-2-1_104069_2022-06-09_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-11 10:28:50	ga_ls9c_ard_3-2-1_102071_2022-06-11_final.stac-item
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final.stac-item
2022-06-26 11:29:34	ga_ls9c_ard_3-2-1_111083_2022-06-26_final.stac-item
2022-07-05 09:42:05	ga_ls9c_ard_3-2-1_094077_2022-07-05_final.stac-item
2022-07-18 09:13:58	ga_ls9c_ard_3-2-1_089084_2022-07-17_final.stac-item
2022-07-19 11:35:44	ga_ls9c_ard_3-2-1_112083_2022-07-19_final.stac-item
2022-07-20 10:38:08	ga_ls9c_ard_3-2-1_103078_2022-07-20_final.stac-item
2022-07-25 09:19:04	ga_ls9c_ard_3-2-1_090081_2022-07-24_final.stac-item
2022-08-09 10:16:04	ga_ls9c_ard_3-2-1_099084_2022-08-09_final.stac-item
2022-08-18 10:08:45	ga_ls9c_ard_3-2-1_098081_2022-08-18_final.stac-item
2022-08-27 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-08-27_final.stac-item
2022-09-10 10:12:57	ga_ls9c_ard_3-2-1_099076_2022-09-10_final.stac-item
2022-09-12 11:41:54	ga_ls9c_ard_3-2-1_113082_2022-09-12_final.stac-item
2022-09-26 10:12:17	ga_ls9c_ard_3-2-1_099074_2022-09-26_final.stac-item
2022-10-02 09:40:47	ga_ls9c_ard_3-2-1_093088_2022-10-02_final.stac-item
2022-10-04 11:02:31	ga_ls9c_ard_3-2-1_107076_2022-10-04_final.stac-item
2022-10-16 09:51:38	ga_ls9c_ard_3-2-1_095084_2022-10-16_final.stac-item
2022-10-18 11:16:58	ga_ls9c_ard_3-2-1_109081_2022-10-18_final.stac-item
2022-10-20 09:28:31	ga_ls9c_ard_3-2-1_091088_2022-10-19_final.stac-item
2022-10-20 11:02:13	ga_ls9c_ard_3-2-1_107075_2022-10-20_final.stac-item
2022-10-22 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-10-21_final.stac-item
2022-11-03 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-11-03_final.stac-item
2022-11-12 11:06:01	ga_ls9c_ard_3-2-1_108069_2022-11-12_final.stac-item
2022-12-03 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-12-03_final.stac-item
2022-12-05 09:34:04	ga_ls9c_ard_3-2-1_093071_2022-12-05_final.stac-item
2022-12-05 11:12:57	ga_ls9c_ard_3-2-1_109071_2022-12-05_final.stac-item
2022-12-06 10:20:56	ga_ls9c_ard_3-2-1_100080_2022-12-06_final.stac-item
2022-12-11 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-12-11_final.stac-item
2022-12-14 11:09:11	ga_ls9c_ard_3-2-1_108077_2022-12-14_final.stac-item
2022-12-19 11:30:30	ga_ls9c_ard_3-2-1_111084_2022-12-19_final.stac-item
2022-12-27 10:38:39	ga_ls9c_ard_3-2-1_103078_2022-12-27_final.stac-item
2022-12-28 11:21:32	ga_ls9c_ard_3-2-1_110077_2022-12-28_final.stac-item
2023-01-04 11:27:44	ga_ls9c_ard_3-2-1_111077_2023-01-04_final.stac-item
2023-01-07 10:20:33	ga_ls9c_ard_3-2-1_100079_2023-01-07_final.stac-item
2023-01-12 10:38:16	ga_ls9c_ard_3-2-1_103077_2023-01-12_final.stac-item
2023-01-16 10:16:41	ga_ls9c_ard_3-2-1_099085_2023-01-16_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-25 10:08:06	ga_ls9c_ard_3-2-1_098079_2023-01-25_final.stac-item
2023-01-26 10:50:35	ga_ls9c_ard_3-2-1_105077_2023-01-26_final.stac-item
2023-01-27 11:35:28	ga_ls9c_ard_3-2-1_112081_2023-01-27_final.stac-item
2023-01-31 11:11:12	ga_ls9c_ard_3-2-1_108082_2023-01-31_final.stac-item
2023-02-01 11:51:16	ga_ls9c_ard_3-2-1_115074_2023-02-01_final.stac-item
2023-02-02 09:19:10	ga_ls9c_ard_3-2-1_090080_2023-02-01_final.stac-item
2023-02-05 11:28:59	ga_ls9c_ard_3-2-1_111080_2023-02-05_final.stac-item
2023-02-09 11:03:04	ga_ls9c_ard_3-2-1_107077_2023-02-09_final.stac-item
2023-02-11 10:50:42	ga_ls9c_ard_3-2-1_105077_2023-02-11_final.stac-item
2023-02-14 09:46:17	ga_ls9c_ard_3-2-1_094086_2023-02-14_final.stac-item
2023-03-07 10:03:20	ga_ls9c_ard_3-2-1_097083_2023-03-07_final.stac-item
2023-03-09 11:25:02	ga_ls9c_ard_3-2-1_111071_2023-03-09_final.stac-item
2023-03-13 11:00:19	ga_ls9c_ard_3-2-1_107071_2023-03-13_final.stac-item
2023-03-27 11:12:08	ga_ls9c_ard_3-2-1_109070_2023-03-27_final.stac-item
2023-04-12 11:16:24	ga_ls9c_ard_3-2-1_109081_2023-04-12_final.stac-item
2023-04-28 09:34:37	ga_ls9c_ard_3-2-1_093074_2023-04-28_final.stac-item
2023-04-29 10:17:52	ga_ls9c_ard_3-2-1_100074_2023-04-29_final.stac-item
2023-05-02 09:13:49	ga_ls9c_ard_3-2-1_089084_2023-05-01_final.stac-item
2023-05-28 09:46:41	ga_ls9c_ard_3-2-1_095074_2023-05-28_final.stac-item
2023-05-30 09:37:07	ga_ls9c_ard_3-2-1_093081_2023-05-30_final.stac-item
2023-06-26 10:53:19	ga_ls9c_ard_3-2-1_106071_2023-06-26_final.stac-item
2023-07-01 09:34:19	ga_ls9c_ard_3-2-1_093074_2023-07-01_final.stac-item
2023-07-18 10:21:18	ga_ls9c_ard_3-2-1_100083_2023-07-18_final.stac-item
2023-07-30 10:40:54	ga_ls9c_ard_3-2-1_104070_2023-07-30_final.stac-item
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final.stac-item
2023-08-06 10:45:58	ga_ls9c_ard_3-2-1_105067_2023-08-06_final.stac-item
2023-08-09 11:18:29	ga_ls9c_ard_3-2-1_110071_2023-08-09_final.stac-item
2023-10-17 11:41:29	ga_ls9c_ard_3-2-1_113081_2023-10-17_final.stac-item
2023-11-14 10:25:15	ga_ls9c_ard_3-2-1_101076_2023-11-14_final.stac-item
2023-11-21 10:31:31	ga_ls9c_ard_3-2-1_102076_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