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
2021-11-12 09:21:56	ga_ls9c_ard_3-2-1_091080_2021-11-11_final.stac-item
2021-11-13 11:41:21	ga_ls9c_ard_3-2-1_113082_2021-11-13_final.stac-item
2021-11-20 11:21:05	ga_ls9c_ard_3-2-1_110072_2021-11-20_final.stac-item
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-15 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-01-15_final.stac-item
2022-01-15 09:58:12	ga_ls9c_ard_3-2-1_097070_2022-01-15_final.stac-item
2022-01-29 10:13:24	ga_ls9c_ard_3-2-1_099077_2022-01-29_final.stac-item
2022-01-30 09:22:58	ga_ls9c_ard_3-2-1_090090_2022-01-29_final.stac-item
2022-02-04 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-02-04_final.stac-item
2022-02-15 10:53:47	ga_ls9c_ard_3-2-1_106070_2022-02-15_final.stac-item
2022-02-16 10:01:21	ga_ls9c_ard_3-2-1_097078_2022-02-16_final.stac-item
2022-02-16 10:02:09	ga_ls9c_ard_3-2-1_097080_2022-02-16_final.stac-item
2022-02-17 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-02-17_final.stac-item
2022-02-20 09:34:59	ga_ls9c_ard_3-2-1_093074_2022-02-20_final.stac-item
2022-02-21 10:19:02	ga_ls9c_ard_3-2-1_100076_2022-02-21_final.stac-item
2022-03-19 10:54:47	ga_ls9c_ard_3-2-1_106073_2022-03-19_final.stac-item
2022-05-15 09:12:54	ga_ls9c_ard_3-2-1_089082_2022-05-14_final.stac-item
2022-05-21 10:09:26	ga_ls9c_ard_3-2-1_099069_2022-05-21_final.stac-item
2022-05-30 10:03:16	ga_ls9c_ard_3-2-1_098069_2022-05-30_final.stac-item
2022-05-31 10:51:43	ga_ls9c_ard_3-2-1_105082_2022-05-31_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-06-03_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-16 09:22:18	ga_ls9c_ard_3-2-1_091074_2022-07-15_final.stac-item
2022-07-25 09:20:40	ga_ls9c_ard_3-2-1_090085_2022-07-24_final.stac-item
2022-07-30 11:16:09	ga_ls9c_ard_3-2-1_109080_2022-07-30_final.stac-item
2022-08-08 09:28:48	ga_ls9c_ard_3-2-1_092074_2022-08-07_final.stac-item
2022-08-20 11:31:41	ga_ls9c_ard_3-2-1_112072_2022-08-20_final.stac-item
2022-08-23 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-08-23_final.stac-item
2022-09-03 10:06:22	ga_ls9c_ard_3-2-1_098075_2022-09-03_final.stac-item
2022-09-04 09:11:57	ga_ls9c_ard_3-2-1_089078_2022-09-03_final.stac-item
2022-09-14 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-09-14_final.stac-item
2022-09-14 11:29:33	ga_ls9c_ard_3-2-1_111082_2022-09-14_final.stac-item
2022-09-17 10:19:12	ga_ls9c_ard_3-2-1_100076_2022-09-17_final.stac-item
2022-09-18 09:28:47	ga_ls9c_ard_3-2-1_091089_2022-09-17_final.stac-item
2022-09-29 10:42:47	ga_ls9c_ard_3-2-1_104073_2022-09-29_final.stac-item
2022-10-01 10:28:26	ga_ls9c_ard_3-2-1_102068_2022-10-01_final.stac-item
2022-10-14 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-10-14_final.stac-item
2022-10-25 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-10-25_final.stac-item
2022-11-05 09:25:41	ga_ls9c_ard_3-2-1_091081_2022-11-04_final.stac-item
2022-11-05 09:28:05	ga_ls9c_ard_3-2-1_091087_2022-11-04_final.stac-item
2022-11-07 09:13:45	ga_ls9c_ard_3-2-1_089082_2022-11-06_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-11-29 11:52:26	ga_ls9c_ard_3-2-1_115077_2022-11-29_final.stac-item
2022-12-24 10:08:32	ga_ls9c_ard_3-2-1_098080_2022-12-24_final.stac-item
2023-01-22 11:12:02	ga_ls9c_ard_3-2-1_109069_2023-01-22_final.stac-item
2023-01-26 09:12:06	ga_ls9c_ard_3-2-1_089078_2023-01-25_final.stac-item
2023-02-13 10:39:08	ga_ls9c_ard_3-2-1_103079_2023-02-13_final.stac-item
2023-02-17 11:52:02	ga_ls9c_ard_3-2-1_115076_2023-02-17_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-02-24 10:19:10	ga_ls9c_ard_3-2-1_100076_2023-02-24_final.stac-item
2023-02-25 09:22:21	ga_ls9c_ard_3-2-1_091073_2023-02-24_final.stac-item
2023-03-07 11:37:50	ga_ls9c_ard_3-2-1_113072_2023-03-07_final.stac-item
2023-03-15 10:52:45	ga_ls9c_ard_3-2-1_105083_2023-03-15_final.stac-item
2023-03-27 11:16:56	ga_ls9c_ard_3-2-1_109082_2023-03-27_final.stac-item
2023-04-08 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-04-08_final.stac-item
2023-04-24 11:39:52	ga_ls9c_ard_3-2-1_113078_2023-04-24_final.stac-item
2023-05-28 09:50:40	ga_ls9c_ard_3-2-1_095084_2023-05-28_final.stac-item
2023-06-03 09:11:35	ga_ls9c_ard_3-2-1_089079_2023-06-02_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-15 11:17:02	ga_ls9c_ard_3-2-1_109084_2023-06-15_final.stac-item
2023-06-18 10:03:28	ga_ls9c_ard_3-2-1_098070_2023-06-18_final.stac-item
2023-06-18 10:07:04	ga_ls9c_ard_3-2-1_098079_2023-06-18_final.stac-item
2023-07-11 11:52:23	ga_ls9c_ard_3-2-1_115079_2023-07-11_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-08-12 10:12:30	ga_ls9c_ard_3-2-1_099076_2023-08-12_final.stac-item
2023-08-22 09:11:57	ga_ls9c_ard_3-2-1_089079_2023-08-21_final.stac-item
2023-08-22 10:48:50	ga_ls9c_ard_3-2-1_105074_2023-08-22_final.stac-item
2023-08-30 10:03:05	ga_ls9c_ard_3-2-1_097083_2023-08-30_final.stac-item
2023-09-03 09:34:00	ga_ls9c_ard_3-2-1_093072_2023-09-03_final.stac-item
2023-09-08 09:51:49	ga_ls9c_ard_3-2-1_096070_2023-09-08_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-09-20 10:16:59	ga_ls9c_ard_3-2-1_100071_2023-09-20_final.stac-item
2023-10-02 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-10-01_final.stac-item
2023-10-07 09:25:00	ga_ls9c_ard_3-2-1_091080_2023-10-06_final.stac-item
2023-10-07 11:01:29	ga_ls9c_ard_3-2-1_107074_2023-10-07_final.stac-item
2023-10-16 09:22:07	ga_ls9c_ard_3-2-1_090088_2023-10-15_final.stac-item
2023-11-05 10:30:13	ga_ls9c_ard_3-2-1_102073_2023-11-05_final.stac-item
2023-11-08 09:29:02	ga_ls9c_ard_3-2-1_091090_2023-11-07_final.stac-item
2023-11-09 11:46:24	ga_ls9c_ard_3-2-1_114078_2023-11-09_final.stac-item
2023-11-26 09:13:13	ga_ls9c_ard_3-2-1_089081_2023-11-25_final.stac-item
2023-11-27 09:52:06	ga_ls9c_ard_3-2-1_096070_2023-11-27_final.stac-item
2023-12-01 11:06:39	ga_ls9c_ard_3-2-1_108071_2023-12-01_final.stac-item
2023-12-10 09:23:56	ga_ls9c_ard_3-2-1_091077_2023-12-09_final.stac-item
2023-12-11 11:46:29	ga_ls9c_ard_3-2-1_114078_2023-12-11_final.stac-item
2023-12-13 09:53:40	ga_ls9c_ard_3-2-1_096074_2023-12-13_final.stac-item
2023-12-15 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-12-15_final.stac-item
2023-12-17 09:28:11	ga_ls9c_ard_3-2-1_092072_2023-12-16_final.stac-item
2023-12-18 11:51:56	ga_ls9c_ard_3-2-1_115076_2023-12-18_final.stac-item
2023-12-24 09:33:59	ga_ls9c_ard_3-2-1_093071_2023-12-24_final.stac-item
2024-01-06 10:42:39	ga_ls9c_ard_3-2-1_104073_2024-01-06_final.stac-item
2024-01-07 09:46:14	ga_ls9c_ard_3-2-1_095071_2024-01-07_final.stac-item
2024-01-10 10:17:34	ga_ls9c_ard_3-2-1_100072_2024-01-10_final.stac-item
2024-01-12 11:46:30	ga_ls9c_ard_3-2-1_114078_2024-01-12_final.stac-item
2024-01-19 11:51:52	ga_ls9c_ard_3-2-1_115076_2024-01-19_final.stac-item
2024-01-28 11:46:29	ga_ls9c_ard_3-2-1_114078_2024-01-28_final.stac-item
2024-01-29 09:16:47	ga_ls9c_ard_3-2-1_089090_2024-01-28_final.stac-item
2024-02-14 10:48:52	ga_ls9c_ard_3-2-1_105073_2024-02-14_final.stac-item
2024-02-19 11:11:42	ga_ls9c_ard_3-2-1_108084_2024-02-19_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