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
2021-11-19 10:39:32	ga_ls9c_ard_3-2-1_104068_2021-11-19_final.stac-item
2021-11-23 11:43:05	ga_ls9c_ard_3-2-1_114074_2021-11-23_final.stac-item
2021-12-12 11:51:32	ga_ls9c_ard_3-2-1_115075_2021-12-12_final.stac-item
2022-01-12 09:29:18	ga_ls9c_ard_3-2-1_092075_2022-01-11_final.stac-item
2022-01-12 09:34:05	ga_ls9c_ard_3-2-1_092087_2022-01-12_final.stac-item
2022-01-22 10:03:13	ga_ls9c_ard_3-2-1_098067_2022-01-22_final.stac-item
2022-02-08 10:52:27	ga_ls9c_ard_3-2-1_105082_2022-02-08_final.stac-item
2022-02-18 09:46:10	ga_ls9c_ard_3-2-1_095071_2022-02-18_final.stac-item
2022-02-20 11:12:17	ga_ls9c_ard_3-2-1_109070_2022-02-20_final.stac-item
2022-02-21 10:17:26	ga_ls9c_ard_3-2-1_100072_2022-02-21_final.stac-item
2022-02-28 10:25:31	ga_ls9c_ard_3-2-1_101077_2022-02-28_final.stac-item
2022-03-12 10:47:02	ga_ls9c_ard_3-2-1_105069_2022-03-12_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-04-03 11:51:57	ga_ls9c_ard_3-2-1_115077_2022-04-03_final.stac-item
2022-04-09 11:17:37	ga_ls9c_ard_3-2-1_109084_2022-04-09_final.stac-item
2022-04-27 11:01:31	ga_ls9c_ard_3-2-1_107075_2022-04-27_final.stac-item
2022-05-07 11:38:08	ga_ls9c_ard_3-2-1_113074_2022-05-07_final.stac-item
2022-05-17 10:39:00	ga_ls9c_ard_3-2-1_103081_2022-05-17_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-05-26 10:28:22	ga_ls9c_ard_3-2-1_102070_2022-05-26_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-05-30 11:44:33	ga_ls9c_ard_3-2-1_114075_2022-05-30_final.stac-item
2022-06-15 10:02:34	ga_ls9c_ard_3-2-1_098067_2022-06-15_final.stac-item
2022-06-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-06-23_final.stac-item
2022-06-30 09:28:21	ga_ls9c_ard_3-2-1_091089_2022-06-29_final.stac-item
2022-07-11 09:06:09	ga_ls9c_ard_3-2-1_088080_2022-07-10_final.stac-item
2022-07-19 09:58:03	ga_ls9c_ard_3-2-1_096086_2022-07-19_final.stac-item
2022-07-26 11:38:26	ga_ls9c_ard_3-2-1_113074_2022-07-26_final.stac-item
2022-08-17 11:01:58	ga_ls9c_ard_3-2-1_107075_2022-08-17_final.stac-item
2022-08-22 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-08-22_final.stac-item
2022-09-14 11:30:21	ga_ls9c_ard_3-2-1_111084_2022-09-14_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-29 09:07:06	ga_ls9c_ard_3-2-1_088081_2022-09-28_final.stac-item
2022-10-23 09:56:38	ga_ls9c_ard_3-2-1_096081_2022-10-23_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-10-27 11:06:24	ga_ls9c_ard_3-2-1_108070_2022-10-27_final.stac-item
2022-10-29 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-10-29_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-03 11:14:56	ga_ls9c_ard_3-2-1_109076_2022-11-03_final.stac-item
2022-11-05 11:00:11	ga_ls9c_ard_3-2-1_107070_2022-11-05_final.stac-item
2022-11-09 10:39:53	ga_ls9c_ard_3-2-1_103081_2022-11-09_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-21 09:26:56	ga_ls9c_ard_3-2-1_091084_2022-11-20_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-26 09:52:36	ga_ls9c_ard_3-2-1_096071_2022-12-26_final.stac-item
2022-12-29 10:23:55	ga_ls9c_ard_3-2-1_101072_2022-12-29_final.stac-item
2023-01-02 10:04:24	ga_ls9c_ard_3-2-1_097085_2023-01-02_final.stac-item
2023-01-06 11:12:11	ga_ls9c_ard_3-2-1_109069_2023-01-06_final.stac-item
2023-01-17 10:55:08	ga_ls9c_ard_3-2-1_106073_2023-01-17_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-12 09:53:29	ga_ls9c_ard_3-2-1_096073_2023-02-12_final.stac-item
2023-02-18 09:21:54	ga_ls9c_ard_3-2-1_090087_2023-02-17_final.stac-item
2023-02-21 09:46:20	ga_ls9c_ard_3-2-1_095071_2023-02-21_final.stac-item
2023-02-25 11:01:38	ga_ls9c_ard_3-2-1_107074_2023-02-25_final.stac-item
2023-03-04 09:34:05	ga_ls9c_ard_3-2-1_092087_2023-03-04_final.stac-item
2023-03-18 09:41:10	ga_ls9c_ard_3-2-1_094074_2023-03-18_final.stac-item
2023-03-19 10:23:13	ga_ls9c_ard_3-2-1_101071_2023-03-19_final.stac-item
2023-04-24 11:41:52	ga_ls9c_ard_3-2-1_113083_2023-04-24_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-05-16 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-05-15_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-17 10:06:56	ga_ls9c_ard_3-2-1_098078_2023-05-17_final.stac-item
2023-05-24 10:08:37	ga_ls9c_ard_3-2-1_099067_2023-05-24_final.stac-item
2023-06-24 11:10:27	ga_ls9c_ard_3-2-1_108083_2023-06-24_final.stac-item
2023-08-18 09:38:12	ga_ls9c_ard_3-2-1_093083_2023-08-18_final.stac-item
2023-08-28 10:10:38	ga_ls9c_ard_3-2-1_099071_2023-08-28_final.stac-item
2023-08-31 09:07:04	ga_ls9c_ard_3-2-1_088082_2023-08-30_final.stac-item
2023-09-05 09:28:03	ga_ls9c_ard_3-2-1_091088_2023-09-04_final.stac-item
2023-09-07 10:46:37	ga_ls9c_ard_3-2-1_105068_2023-09-07_final.stac-item
2023-09-16 09:07:13	ga_ls9c_ard_3-2-1_088082_2023-09-15_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 09:23:24	ga_ls9c_ard_3-2-1_091076_2023-10-06_final.stac-item
2023-10-15 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-10-15_final.stac-item
2023-10-19 11:25:56	ga_ls9c_ard_3-2-1_111073_2023-10-19_final.stac-item
2023-10-30 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-10-29_final.stac-item
2023-10-31 10:10:29	ga_ls9c_ard_3-2-1_099070_2023-10-31_final.stac-item
2023-11-02 11:38:34	ga_ls9c_ard_3-2-1_113074_2023-11-02_final.stac-item
2023-11-05 10:29:01	ga_ls9c_ard_3-2-1_102070_2023-11-05_final.stac-item
2023-11-09 10:05:07	ga_ls9c_ard_3-2-1_098072_2023-11-09_final.stac-item
2023-11-10 09:11:30	ga_ls9c_ard_3-2-1_089077_2023-11-09_final.stac-item
2023-11-12 10:35:14	ga_ls9c_ard_3-2-1_103070_2023-11-12_final.stac-item
2023-11-17 10:55:46	ga_ls9c_ard_3-2-1_106075_2023-11-17_final.stac-item
2023-11-19 09:06:33	ga_ls9c_ard_3-2-1_088080_2023-11-18_final.stac-item
2023-11-27 11:36:34	ga_ls9c_ard_3-2-1_112084_2023-11-27_final.stac-item
2023-12-03 10:54:40	ga_ls9c_ard_3-2-1_106072_2023-12-03_final.stac-item
2023-12-23 10:30:25	ga_ls9c_ard_3-2-1_102073_2023-12-23_final.stac-item
2024-01-05 09:58:12	ga_ls9c_ard_3-2-1_097070_2024-01-05_final.stac-item
2024-01-09 11:17:58	ga_ls9c_ard_3-2-1_109084_2024-01-09_final.stac-item
2024-01-11 11:05:38	ga_ls9c_ard_3-2-1_107084_2024-01-11_final.stac-item
2024-01-13 09:13:36	ga_ls9c_ard_3-2-1_089082_2024-01-12_final.stac-item
2024-01-26 10:17:32	ga_ls9c_ard_3-2-1_100072_2024-01-26_final.stac-item
2024-02-03 11:07:51	ga_ls9c_ard_3-2-1_108074_2024-02-03_final.stac-item
2024-02-17 11:19:19	ga_ls9c_ard_3-2-1_110072_2024-02-17_final.stac-item
2024-02-21 10:53:42	ga_ls9c_ard_3-2-1_106070_2024-02-21_final.stac-item
2024-02-26 09:35:21	ga_ls9c_ard_3-2-1_093075_2024-02-26_final.stac-item
2024-03-12 10:30:14	ga_ls9c_ard_3-2-1_102073_2024-03-12_final.stac-item
2024-03-21 10:24:25	ga_ls9c_ard_3-2-1_101074_2024-03-21_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