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
2021-11-16 10:22:19	ga_ls9c_ard_3-2-1_100078_2021-11-16_final.stac-item
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2021-12-19 10:19:11	ga_ls9c_ard_3-2-1_100076_2021-12-19_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2021-12-31 10:44:18	ga_ls9c_ard_3-2-1_104077_2021-12-31_final.stac-item
2022-01-03 09:34:43	ga_ls9c_ard_3-2-1_093073_2022-01-03_final.stac-item
2022-01-05 09:25:09	ga_ls9c_ard_3-2-1_091080_2022-01-04_final.stac-item
2022-01-21 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-01-20_final.stac-item
2022-02-10 10:35:41	ga_ls9c_ard_3-2-1_103071_2022-02-10_final.stac-item
2022-03-03 09:17:31	ga_ls9c_ard_3-2-1_090077_2022-03-02_final.stac-item
2022-04-03 11:52:21	ga_ls9c_ard_3-2-1_115078_2022-04-03_final.stac-item
2022-04-16 11:18:56	ga_ls9c_ard_3-2-1_110072_2022-04-16_final.stac-item
2022-04-29 10:46:22	ga_ls9c_ard_3-2-1_105068_2022-04-29_final.stac-item
2022-05-06 09:17:36	ga_ls9c_ard_3-2-1_090078_2022-05-05_final.stac-item
2022-05-14 10:09:20	ga_ls9c_ard_3-2-1_098084_2022-05-14_final.stac-item
2022-05-30 10:04:04	ga_ls9c_ard_3-2-1_098071_2022-05-30_final.stac-item
2022-06-12 09:33:13	ga_ls9c_ard_3-2-1_093071_2022-06-12_final.stac-item
2022-06-14 09:24:29	ga_ls9c_ard_3-2-1_091080_2022-06-13_final.stac-item
2022-06-17 11:31:07	ga_ls9c_ard_3-2-1_112072_2022-06-17_final.stac-item
2022-06-22 10:10:07	ga_ls9c_ard_3-2-1_099070_2022-06-22_final.stac-item
2022-06-27 10:29:57	ga_ls9c_ard_3-2-1_102073_2022-06-27_final.stac-item
2022-07-13 10:29:52	ga_ls9c_ard_3-2-1_102073_2022-07-13_final.stac-item
2022-07-25 09:22:39	ga_ls9c_ard_3-2-1_090090_2022-07-24_final.stac-item
2022-08-28 09:06:58	ga_ls9c_ard_3-2-1_088081_2022-08-27_final.stac-item
2022-09-07 11:23:43	ga_ls9c_ard_3-2-1_110083_2022-09-07_final.stac-item
2022-09-20 09:13:14	ga_ls9c_ard_3-2-1_089081_2022-09-19_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-09-23 11:23:27	ga_ls9c_ard_3-2-1_110082_2022-09-23_final.stac-item
2022-09-25 11:06:42	ga_ls9c_ard_3-2-1_108071_2022-09-25_final.stac-item
2022-09-26 10:09:53	ga_ls9c_ard_3-2-1_099068_2022-09-26_final.stac-item
2022-09-26 11:53:33	ga_ls9c_ard_3-2-1_115080_2022-09-26_final.stac-item
2022-10-02 09:35:12	ga_ls9c_ard_3-2-1_093074_2022-10-02_final.stac-item
2022-10-05 11:46:58	ga_ls9c_ard_3-2-1_114079_2022-10-05_final.stac-item
2022-10-06 10:52:32	ga_ls9c_ard_3-2-1_105082_2022-10-06_final.stac-item
2022-10-10 10:28:16	ga_ls9c_ard_3-2-1_101083_2022-10-10_final.stac-item
2022-10-12 11:52:49	ga_ls9c_ard_3-2-1_115078_2022-10-12_final.stac-item
2022-10-18 09:34:53	ga_ls9c_ard_3-2-1_093073_2022-10-18_final.stac-item
2022-10-21 10:07:48	ga_ls9c_ard_3-2-1_098078_2022-10-21_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-26 10:23:56	ga_ls9c_ard_3-2-1_101072_2022-10-26_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 11:11:36	ga_ls9c_ard_3-2-1_108083_2022-11-12_final.stac-item
2022-11-13 11:53:40	ga_ls9c_ard_3-2-1_115080_2022-11-13_final.stac-item
2022-11-15 10:03:38	ga_ls9c_ard_3-2-1_097083_2022-11-15_final.stac-item
2022-11-15 11:42:31	ga_ls9c_ard_3-2-1_113083_2022-11-15_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-22 11:45:53	ga_ls9c_ard_3-2-1_114076_2022-11-22_final.stac-item
2022-12-02 10:42:50	ga_ls9c_ard_3-2-1_104073_2022-12-02_final.stac-item
2022-12-07 09:28:54	ga_ls9c_ard_3-2-1_091089_2022-12-06_final.stac-item
2022-12-08 11:45:52	ga_ls9c_ard_3-2-1_114076_2022-12-08_final.stac-item
2022-12-09 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-12-08_final.stac-item
2022-12-12 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-12-12_final.stac-item
2022-12-15 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-15_final.stac-item
2022-12-15 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-15_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2022-12-24 10:03:44	ga_ls9c_ard_3-2-1_098068_2022-12-24_final.stac-item
2022-12-25 10:52:36	ga_ls9c_ard_3-2-1_105082_2022-12-25_final.stac-item
2023-01-01 10:53:14	ga_ls9c_ard_3-2-1_106068_2023-01-01_final.stac-item
2023-01-09 11:46:16	ga_ls9c_ard_3-2-1_114077_2023-01-09_final.stac-item
2023-01-09 11:46:40	ga_ls9c_ard_3-2-1_114078_2023-01-09_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-16 10:10:42	ga_ls9c_ard_3-2-1_099070_2023-01-16_final.stac-item
2023-01-16 10:12:41	ga_ls9c_ard_3-2-1_099075_2023-01-16_final.stac-item
2023-01-17 09:20:15	ga_ls9c_ard_3-2-1_090083_2023-01-16_final.stac-item
2023-01-17 09:22:14	ga_ls9c_ard_3-2-1_090088_2023-01-16_final.stac-item
2023-01-21 10:29:33	ga_ls9c_ard_3-2-1_102071_2023-01-21_final.stac-item
2023-01-30 10:27:55	ga_ls9c_ard_3-2-1_101082_2023-01-30_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-01 11:52:28	ga_ls9c_ard_3-2-1_115077_2023-02-01_final.stac-item
2023-02-05 11:30:11	ga_ls9c_ard_3-2-1_111083_2023-02-05_final.stac-item
2023-02-10 10:07:03	ga_ls9c_ard_3-2-1_098076_2023-02-10_final.stac-item
2023-04-21 11:05:48	ga_ls9c_ard_3-2-1_108070_2023-04-21_final.stac-item
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final.stac-item
2023-04-28 11:11:54	ga_ls9c_ard_3-2-1_109070_2023-04-28_final.stac-item
2023-04-30 09:24:37	ga_ls9c_ard_3-2-1_091080_2023-04-29_final.stac-item
2023-05-01 11:45:09	ga_ls9c_ard_3-2-1_114076_2023-05-01_final.stac-item
2023-05-09 09:21:56	ga_ls9c_ard_3-2-1_090089_2023-05-08_final.stac-item
2023-05-14 11:16:08	ga_ls9c_ard_3-2-1_109081_2023-05-14_final.stac-item
2023-05-18 09:12:30	ga_ls9c_ard_3-2-1_089081_2023-05-17_final.stac-item
2023-05-19 09:51:21	ga_ls9c_ard_3-2-1_096070_2023-05-19_final.stac-item
2023-05-19 11:35:49	ga_ls9c_ard_3-2-1_112084_2023-05-19_final.stac-item
2023-06-01 09:24:45	ga_ls9c_ard_3-2-1_091081_2023-05-31_final.stac-item
2023-06-04 09:51:15	ga_ls9c_ard_3-2-1_096070_2023-06-04_final.stac-item
2023-06-18 10:07:04	ga_ls9c_ard_3-2-1_098079_2023-06-18_final.stac-item
2023-06-19 09:12:14	ga_ls9c_ard_3-2-1_089081_2023-06-18_final.stac-item
2023-06-19 09:15:26	ga_ls9c_ard_3-2-1_089089_2023-06-18_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-07-19 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-07-19_final.stac-item
2023-07-21 09:15:42	ga_ls9c_ard_3-2-1_089089_2023-07-20_final.stac-item
2023-08-03 10:16:38	ga_ls9c_ard_3-2-1_100071_2023-08-03_final.stac-item
2023-08-05 10:03:05	ga_ls9c_ard_3-2-1_098068_2023-08-05_final.stac-item
2023-08-06 09:12:40	ga_ls9c_ard_3-2-1_089081_2023-08-05_final.stac-item
2023-08-10 10:27:39	ga_ls9c_ard_3-2-1_101083_2023-08-10_final.stac-item
2023-08-13 09:21:40	ga_ls9c_ard_3-2-1_090088_2023-08-12_final.stac-item
2023-10-14 09:34:28	ga_ls9c_ard_3-2-1_092088_2023-10-14_final.stac-item
2023-10-26 11:31:42	ga_ls9c_ard_3-2-1_112072_2023-10-26_final.stac-item
2023-11-02 11:42:10	ga_ls9c_ard_3-2-1_113083_2023-11-02_final.stac-item
2023-11-17 09:18:05	ga_ls9c_ard_3-2-1_090078_2023-11-16_final.stac-item
2023-11-19 10:43:03	ga_ls9c_ard_3-2-1_104074_2023-11-19_final.stac-item
2023-11-23 11:58:28	ga_ls9c_ard_3-2-1_116077_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