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
2021-10-31 11:15:11	ga_ls9c_ard_3-2-1_109082_2021-10-31_final.stac-item
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-07 09:19:28	ga_ls9c_ard_3-2-1_090080_2021-11-06_final.stac-item
2021-11-15 11:18:14	ga_ls9c_ard_3-2-1_110071_2021-11-15_final.stac-item
2021-11-22 11:07:07	ga_ls9c_ard_3-2-1_107084_2021-11-22_final.stac-item
2021-12-06 10:48:36	ga_ls9c_ard_3-2-1_105072_2021-12-06_final.stac-item
2021-12-07 11:35:26	ga_ls9c_ard_3-2-1_112081_2021-12-07_final.stac-item
2021-12-18 11:12:24	ga_ls9c_ard_3-2-1_109070_2021-12-18_final.stac-item
2022-01-09 10:36:54	ga_ls9c_ard_3-2-1_103074_2022-01-09_final.stac-item
2022-01-22 11:46:53	ga_ls9c_ard_3-2-1_114079_2022-01-22_final.stac-item
2022-02-08 10:52:03	ga_ls9c_ard_3-2-1_105081_2022-02-08_final.stac-item
2022-02-21 10:19:02	ga_ls9c_ard_3-2-1_100076_2022-02-21_final.stac-item
2022-02-21 10:20:38	ga_ls9c_ard_3-2-1_100080_2022-02-21_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-03-12 09:14:56	ga_ls9c_ard_3-2-1_089086_2022-03-11_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-03-24 09:39:36	ga_ls9c_ard_3-2-1_093086_2022-03-24_final.stac-item
2022-03-27 11:46:10	ga_ls9c_ard_3-2-1_114078_2022-03-27_final.stac-item
2022-04-21 10:00:07	ga_ls9c_ard_3-2-1_097076_2022-04-21_final.stac-item
2022-05-11 11:12:10	ga_ls9c_ard_3-2-1_109071_2022-05-11_final.stac-item
2022-05-11 11:16:10	ga_ls9c_ard_3-2-1_109081_2022-05-11_final.stac-item
2022-05-17 10:34:36	ga_ls9c_ard_3-2-1_103070_2022-05-17_final.stac-item
2022-05-18 11:22:14	ga_ls9c_ard_3-2-1_110081_2022-05-18_final.stac-item
2022-05-19 10:23:24	ga_ls9c_ard_3-2-1_101073_2022-05-19_final.stac-item
2022-05-23 10:00:40	ga_ls9c_ard_3-2-1_097078_2022-05-23_final.stac-item
2022-05-23 10:02:40	ga_ls9c_ard_3-2-1_097083_2022-05-23_final.stac-item
2022-05-25 09:47:30	ga_ls9c_ard_3-2-1_095076_2022-05-25_final.stac-item
2022-05-28 10:16:49	ga_ls9c_ard_3-2-1_100072_2022-05-28_final.stac-item
2022-06-26 11:29:58	ga_ls9c_ard_3-2-1_111084_2022-06-26_final.stac-item
2022-07-05 11:18:34	ga_ls9c_ard_3-2-1_110071_2022-07-05_final.stac-item
2022-07-07 11:10:35	ga_ls9c_ard_3-2-1_108082_2022-07-07_final.stac-item
2022-07-12 11:25:06	ga_ls9c_ard_3-2-1_111072_2022-07-12_final.stac-item
2022-07-21 11:17:49	ga_ls9c_ard_3-2-1_110069_2022-07-21_final.stac-item
2022-07-21 11:21:25	ga_ls9c_ard_3-2-1_110078_2022-07-21_final.stac-item
2022-07-21 11:22:13	ga_ls9c_ard_3-2-1_110080_2022-07-21_final.stac-item
2022-07-25 10:56:45	ga_ls9c_ard_3-2-1_106078_2022-07-25_final.stac-item
2022-08-03 09:16:12	ga_ls9c_ard_3-2-1_089089_2022-08-02_final.stac-item
2022-08-04 09:57:52	ga_ls9c_ard_3-2-1_096085_2022-08-04_final.stac-item
2022-08-11 09:58:08	ga_ls9c_ard_3-2-1_097070_2022-08-11_final.stac-item
2022-08-15 11:13:07	ga_ls9c_ard_3-2-1_109072_2022-08-15_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-08-24 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-08-24_final.stac-item
2022-08-27 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-08-27_final.stac-item
2022-08-31 11:12:46	ga_ls9c_ard_3-2-1_109071_2022-08-31_final.stac-item
2022-09-13 10:41:54	ga_ls9c_ard_3-2-1_104071_2022-09-13_final.stac-item
2022-09-16 11:13:13	ga_ls9c_ard_3-2-1_109072_2022-09-16_final.stac-item
2022-09-18 09:25:11	ga_ls9c_ard_3-2-1_091080_2022-09-17_final.stac-item
2022-09-18 11:01:17	ga_ls9c_ard_3-2-1_107073_2022-09-18_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-09-30 09:51:57	ga_ls9c_ard_3-2-1_095085_2022-09-30_final.stac-item
2022-10-06 10:50:57	ga_ls9c_ard_3-2-1_105078_2022-10-06_final.stac-item
2022-10-11 11:10:44	ga_ls9c_ard_3-2-1_108081_2022-10-11_final.stac-item
2022-10-26 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-10-26_final.stac-item
2022-10-27 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-10-26_final.stac-item
2022-11-04 10:22:30	ga_ls9c_ard_3-2-1_100084_2022-11-04_final.stac-item
2022-11-06 10:03:46	ga_ls9c_ard_3-2-1_098068_2022-11-06_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 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-11-23_final.stac-item
2022-11-25 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-11-25_final.stac-item
2022-12-02 10:42:50	ga_ls9c_ard_3-2-1_104073_2022-12-02_final.stac-item
2022-12-10 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-12-10_final.stac-item
2022-12-12 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-12-12_final.stac-item
2022-12-13 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-12-13_final.stac-item
2022-12-16 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-12-16_final.stac-item
2022-12-23 11:01:21	ga_ls9c_ard_3-2-1_107073_2022-12-23_final.stac-item
2022-12-24 10:08:32	ga_ls9c_ard_3-2-1_098080_2022-12-24_final.stac-item
2022-12-25 10:50:36	ga_ls9c_ard_3-2-1_105077_2022-12-25_final.stac-item
2022-12-29 10:25:31	ga_ls9c_ard_3-2-1_101076_2022-12-29_final.stac-item
2022-12-29 10:26:43	ga_ls9c_ard_3-2-1_101079_2022-12-29_final.stac-item
2022-12-30 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-30_final.stac-item
2023-01-02 10:01:37	ga_ls9c_ard_3-2-1_097078_2023-01-02_final.stac-item
2023-01-04 09:51:15	ga_ls9c_ard_3-2-1_095083_2023-01-04_final.stac-item
2023-01-04 11:30:08	ga_ls9c_ard_3-2-1_111083_2023-01-04_final.stac-item
2023-01-06 09:40:53	ga_ls9c_ard_3-2-1_093088_2023-01-06_final.stac-item
2023-01-06 11:16:58	ga_ls9c_ard_3-2-1_109081_2023-01-06_final.stac-item
2023-01-08 11:04:12	ga_ls9c_ard_3-2-1_107080_2023-01-08_final.stac-item
2023-01-29 09:44:15	ga_ls9c_ard_3-2-1_094081_2023-01-29_final.stac-item
2023-02-23 11:17:12	ga_ls9c_ard_3-2-1_109082_2023-02-23_final.stac-item
2023-03-07 10:01:21	ga_ls9c_ard_3-2-1_097078_2023-03-07_final.stac-item
2023-04-02 10:39:48	ga_ls9c_ard_3-2-1_103082_2023-04-02_final.stac-item
2023-04-15 10:02:47	ga_ls9c_ard_3-2-1_098067_2023-04-15_final.stac-item
2023-04-21 09:30:30	ga_ls9c_ard_3-2-1_092079_2023-04-21_final.stac-item
2023-05-02 10:47:54	ga_ls9c_ard_3-2-1_105072_2023-05-02_final.stac-item
2023-05-05 11:19:09	ga_ls9c_ard_3-2-1_110073_2023-05-05_final.stac-item
2023-05-18 09:13:41	ga_ls9c_ard_3-2-1_089084_2023-05-17_final.stac-item
2023-05-19 11:34:14	ga_ls9c_ard_3-2-1_112080_2023-05-19_final.stac-item
2023-05-21 09:44:09	ga_ls9c_ard_3-2-1_094083_2023-05-21_final.stac-item
2023-05-23 11:05:27	ga_ls9c_ard_3-2-1_108070_2023-05-23_final.stac-item
2023-05-24 10:13:48	ga_ls9c_ard_3-2-1_099080_2023-05-24_final.stac-item
2023-06-01 10:59:14	ga_ls9c_ard_3-2-1_107070_2023-06-01_final.stac-item
2023-06-02 11:44:06	ga_ls9c_ard_3-2-1_114074_2023-06-02_final.stac-item
2023-06-07 10:23:43	ga_ls9c_ard_3-2-1_101074_2023-06-07_final.stac-item
2023-06-13 11:29:26	ga_ls9c_ard_3-2-1_111084_2023-06-13_final.stac-item
2023-06-15 11:12:15	ga_ls9c_ard_3-2-1_109072_2023-06-15_final.stac-item
2023-06-19 09:11:02	ga_ls9c_ard_3-2-1_089078_2023-06-18_final.stac-item
2023-07-21 10:46:36	ga_ls9c_ard_3-2-1_105069_2023-07-21_final.stac-item
2023-08-16 11:27:27	ga_ls9c_ard_3-2-1_111078_2023-08-16_final.stac-item
2023-08-17 10:28:14	ga_ls9c_ard_3-2-1_102069_2023-08-17_final.stac-item
2023-10-27 10:37:39	ga_ls9c_ard_3-2-1_103076_2023-10-27_final.stac-item
2023-11-04 09:50:55	ga_ls9c_ard_3-2-1_095083_2023-11-04_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