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
2021-11-02 10:54:03	ga_ls9c_ard_3-2-1_106076_2021-11-02_final.stac-item
2021-11-24 10:41:59	ga_ls9c_ard_3-2-1_104068_2021-11-24_final.stac-item
2021-12-05 10:10:08	ga_ls9c_ard_3-2-1_098084_2021-12-05_final.stac-item
2021-12-09 11:24:39	ga_ls9c_ard_3-2-1_110085_2021-12-09_final.stac-item
2021-12-13 10:53:30	ga_ls9c_ard_3-2-1_106069_2021-12-13_final.stac-item
2021-12-13 10:54:42	ga_ls9c_ard_3-2-1_106072_2021-12-13_final.stac-item
2021-12-18 11:14:48	ga_ls9c_ard_3-2-1_109076_2021-12-18_final.stac-item
2021-12-25 09:40:07	ga_ls9c_ard_3-2-1_094071_2021-12-25_final.stac-item
2021-12-31 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-31_final.stac-item
2022-01-04 10:17:11	ga_ls9c_ard_3-2-1_100071_2022-01-04_final.stac-item
2022-01-19 09:34:42	ga_ls9c_ard_3-2-1_093073_2022-01-19_final.stac-item
2022-01-21 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-01-20_final.stac-item
2022-01-21 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-21_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-01-24 11:32:32	ga_ls9c_ard_3-2-1_112074_2022-01-24_final.stac-item
2022-01-29 10:14:36	ga_ls9c_ard_3-2-1_099080_2022-01-29_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-14 10:09:44	ga_ls9c_ard_3-2-1_099068_2022-02-14_final.stac-item
2022-02-17 09:07:19	ga_ls9c_ard_3-2-1_088082_2022-02-16_final.stac-item
2022-02-21 10:17:02	ga_ls9c_ard_3-2-1_100071_2022-02-21_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-24 09:40:00	ga_ls9c_ard_3-2-1_093087_2022-03-24_final.stac-item
2022-04-03 11:51:57	ga_ls9c_ard_3-2-1_115077_2022-04-03_final.stac-item
2022-04-04 10:52:44	ga_ls9c_ard_3-2-1_106068_2022-04-04_final.stac-item
2022-04-12 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-04-12_final.stac-item
2022-04-27 11:03:55	ga_ls9c_ard_3-2-1_107081_2022-04-27_final.stac-item
2022-05-05 10:09:14	ga_ls9c_ard_3-2-1_099068_2022-05-05_final.stac-item
2022-05-22 09:21:24	ga_ls9c_ard_3-2-1_090088_2022-05-21_final.stac-item
2022-05-29 09:27:11	ga_ls9c_ard_3-2-1_091087_2022-05-28_final.stac-item
2022-06-05 11:06:41	ga_ls9c_ard_3-2-1_108073_2022-06-05_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-10 09:51:08	ga_ls9c_ard_3-2-1_095085_2022-06-10_final.stac-item
2022-06-30 09:28:21	ga_ls9c_ard_3-2-1_091089_2022-06-29_final.stac-item
2022-07-04 10:35:43	ga_ls9c_ard_3-2-1_103072_2022-07-04_final.stac-item
2022-07-12 11:24:18	ga_ls9c_ard_3-2-1_111070_2022-07-12_final.stac-item
2022-07-18 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-18_final.stac-item
2022-07-25 09:16:40	ga_ls9c_ard_3-2-1_090075_2022-07-24_final.stac-item
2022-08-13 09:50:59	ga_ls9c_ard_3-2-1_095083_2022-08-13_final.stac-item
2022-08-25 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-08-25_final.stac-item
2022-10-02 11:16:29	ga_ls9c_ard_3-2-1_109080_2022-10-02_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-05 09:22:54	ga_ls9c_ard_3-2-1_091074_2022-11-04_final.stac-item
2022-11-22 10:10:36	ga_ls9c_ard_3-2-1_098085_2022-11-22_final.stac-item
2022-11-24 11:36:43	ga_ls9c_ard_3-2-1_112084_2022-11-24_final.stac-item
2022-12-11 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-12-11_final.stac-item
2022-12-15 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-12-15_final.stac-item
2022-12-17 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-12-17_final.stac-item
2022-12-24 10:06:32	ga_ls9c_ard_3-2-1_098075_2022-12-24_final.stac-item
2022-12-29 10:23:55	ga_ls9c_ard_3-2-1_101072_2022-12-29_final.stac-item
2023-01-16 11:51:34	ga_ls9c_ard_3-2-1_115075_2023-01-16_final.stac-item
2023-01-26 09:10:54	ga_ls9c_ard_3-2-1_089075_2023-01-25_final.stac-item
2023-01-27 09:52:59	ga_ls9c_ard_3-2-1_096072_2023-01-27_final.stac-item
2023-01-28 10:36:16	ga_ls9c_ard_3-2-1_103072_2023-01-28_final.stac-item
2023-02-01 10:09:36	ga_ls9c_ard_3-2-1_099067_2023-02-01_final.stac-item
2023-02-03 09:58:27	ga_ls9c_ard_3-2-1_097070_2023-02-03_final.stac-item
2023-02-08 10:20:13	ga_ls9c_ard_3-2-1_100078_2023-02-08_final.stac-item
2023-02-21 09:46:44	ga_ls9c_ard_3-2-1_095072_2023-02-21_final.stac-item
2023-04-28 09:33:49	ga_ls9c_ard_3-2-1_093072_2023-04-28_final.stac-item
2023-05-05 09:39:52	ga_ls9c_ard_3-2-1_094072_2023-05-05_final.stac-item
2023-05-09 09:20:44	ga_ls9c_ard_3-2-1_090086_2023-05-08_final.stac-item
2023-06-01 09:27:32	ga_ls9c_ard_3-2-1_091088_2023-05-31_final.stac-item
2023-06-03 10:49:16	ga_ls9c_ard_3-2-1_105076_2023-06-03_final.stac-item
2023-06-06 11:23:20	ga_ls9c_ard_3-2-1_110084_2023-06-06_final.stac-item
2023-06-08 09:32:28	ga_ls9c_ard_3-2-1_092085_2023-06-08_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-19 10:51:31	ga_ls9c_ard_3-2-1_105082_2023-06-19_final.stac-item
2023-07-19 09:22:29	ga_ls9c_ard_3-2-1_091075_2023-07-18_final.stac-item
2023-07-19 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-07-18_final.stac-item
2023-08-22 10:48:50	ga_ls9c_ard_3-2-1_105074_2023-08-22_final.stac-item
2023-09-03 11:14:05	ga_ls9c_ard_3-2-1_109075_2023-09-03_final.stac-item
2023-09-23 10:49:27	ga_ls9c_ard_3-2-1_105075_2023-09-23_final.stac-item
2023-09-27 10:25:29	ga_ls9c_ard_3-2-1_101077_2023-09-27_final.stac-item
2023-09-30 09:16:44	ga_ls9c_ard_3-2-1_090075_2023-09-29_final.stac-item
2023-10-07 09:22:36	ga_ls9c_ard_3-2-1_091074_2023-10-06_final.stac-item
2023-10-24 10:04:47	ga_ls9c_ard_3-2-1_098071_2023-10-24_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final.stac-item
2023-11-11 11:32:27	ga_ls9c_ard_3-2-1_112074_2023-11-11_final.stac-item
2023-11-15 09:28:02	ga_ls9c_ard_3-2-1_092072_2023-11-14_final.stac-item
2023-11-17 10:52:59	ga_ls9c_ard_3-2-1_106068_2023-11-17_final.stac-item
2023-11-27 11:31:47	ga_ls9c_ard_3-2-1_112072_2023-11-27_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-08 09:34:16	ga_ls9c_ard_3-2-1_093072_2023-12-08_final.stac-item
2023-12-17 09:28:11	ga_ls9c_ard_3-2-1_092072_2023-12-16_final.stac-item
2024-01-01 10:28:10	ga_ls9c_ard_3-2-1_101083_2024-01-01_final.stac-item
2024-01-02 09:28:56	ga_ls9c_ard_3-2-1_092074_2024-01-01_final.stac-item
2024-01-04 10:54:38	ga_ls9c_ard_3-2-1_106072_2024-01-04_final.stac-item
2024-01-20 09:17:45	ga_ls9c_ard_3-2-1_090077_2024-01-19_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_final.stac-item
2024-02-04 10:09:26	ga_ls9c_ard_3-2-1_099067_2024-02-04_final.stac-item
2024-02-07 09:07:03	ga_ls9c_ard_3-2-1_088081_2024-02-06_final.stac-item
2024-02-20 11:51:21	ga_ls9c_ard_3-2-1_115075_2024-02-20_final.stac-item
2024-02-21 09:18:01	ga_ls9c_ard_3-2-1_090078_2024-02-20_final.stac-item
2024-02-23 09:07:12	ga_ls9c_ard_3-2-1_088082_2024-02-22_final.stac-item
2024-03-01 10:49:34	ga_ls9c_ard_3-2-1_105075_2024-03-01_final.stac-item
2024-03-08 09:17:17	ga_ls9c_ard_3-2-1_090076_2024-03-07_final.stac-item
2024-03-08 09:17:41	ga_ls9c_ard_3-2-1_090077_2024-03-07_final.stac-item
2024-03-12 10:33:26	ga_ls9c_ard_3-2-1_102081_2024-03-12_final.stac-item
2024-03-15 09:23:02	ga_ls9c_ard_3-2-1_091075_2024-03-14_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