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 10:54:51	ga_ls9c_ard_3-2-1_106078_2021-11-02_final.stac-item
2021-11-03 09:52:58	ga_ls9c_ard_3-2-1_096070_2021-11-03_final.stac-item
2021-11-11 10:20:39	ga_ls9c_ard_3-2-1_100080_2021-11-11_final.stac-item
2021-11-13 10:03:29	ga_ls9c_ard_3-2-1_097084_2021-11-13_final.stac-item
2021-12-05 10:10:32	ga_ls9c_ard_3-2-1_098085_2021-12-05_final.stac-item
2021-12-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2021-12-08_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2021-12-18 09:40:42	ga_ls9c_ard_3-2-1_093088_2021-12-18_final.stac-item
2021-12-28 10:14:12	ga_ls9c_ard_3-2-1_099079_2021-12-28_final.stac-item
2021-12-31 09:07:01	ga_ls9c_ard_3-2-1_088081_2021-12-30_final.stac-item
2022-01-07 09:13:59	ga_ls9c_ard_3-2-1_089083_2022-01-06_final.stac-item
2022-01-09 10:34:30	ga_ls9c_ard_3-2-1_103068_2022-01-09_final.stac-item
2022-01-13 10:11:21	ga_ls9c_ard_3-2-1_099072_2022-01-13_final.stac-item
2022-01-13 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-01-13_final.stac-item
2022-01-15 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-01-15_final.stac-item
2022-01-23 09:13:35	ga_ls9c_ard_3-2-1_089082_2022-01-22_final.stac-item
2022-01-28 11:08:13	ga_ls9c_ard_3-2-1_108075_2022-01-28_final.stac-item
2022-02-02 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-02-02_final.stac-item
2022-02-02 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-02-02_final.stac-item
2022-02-04 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-02-04_final.stac-item
2022-02-17 09:06:31	ga_ls9c_ard_3-2-1_088080_2022-02-16_final.stac-item
2022-03-09 10:16:56	ga_ls9c_ard_3-2-1_100071_2022-03-09_final.stac-item
2022-03-11 10:09:46	ga_ls9c_ard_3-2-1_098084_2022-03-11_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-29 11:32:13	ga_ls9c_ard_3-2-1_112074_2022-03-29_final.stac-item
2022-04-29 10:49:09	ga_ls9c_ard_3-2-1_105075_2022-04-29_final.stac-item
2022-05-04 11:10:27	ga_ls9c_ard_3-2-1_108082_2022-05-04_final.stac-item
2022-05-06 10:55:41	ga_ls9c_ard_3-2-1_106076_2022-05-06_final.stac-item
2022-05-13 11:04:11	ga_ls9c_ard_3-2-1_107082_2022-05-13_final.stac-item
2022-05-21 10:13:26	ga_ls9c_ard_3-2-1_099079_2022-05-21_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-05-29 09:26:47	ga_ls9c_ard_3-2-1_091086_2022-05-28_final.stac-item
2022-05-30 10:09:39	ga_ls9c_ard_3-2-1_098085_2022-05-30_final.stac-item
2022-06-03 11:17:50	ga_ls9c_ard_3-2-1_110070_2022-06-03_final.stac-item
2022-06-08 09:56:42	ga_ls9c_ard_3-2-1_097068_2022-06-08_final.stac-item
2022-06-15 10:07:21	ga_ls9c_ard_3-2-1_098079_2022-06-15_final.stac-item
2022-06-16 10:48:38	ga_ls9c_ard_3-2-1_105074_2022-06-16_final.stac-item
2022-06-19 11:23:35	ga_ls9c_ard_3-2-1_110084_2022-06-19_final.stac-item
2022-06-30 09:26:45	ga_ls9c_ard_3-2-1_091085_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
2022-07-15 10:16:42	ga_ls9c_ard_3-2-1_100071_2022-07-15_final.stac-item
2022-08-01 09:23:44	ga_ls9c_ard_3-2-1_091077_2022-07-31_final.stac-item
2022-08-08 09:34:47	ga_ls9c_ard_3-2-1_092089_2022-08-08_final.stac-item
2022-08-08 11:11:17	ga_ls9c_ard_3-2-1_108083_2022-08-08_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-08-27 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-08-27_final.stac-item
2022-09-03 10:03:59	ga_ls9c_ard_3-2-1_098069_2022-09-03_final.stac-item
2022-09-18 09:23:12	ga_ls9c_ard_3-2-1_091075_2022-09-17_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-25 09:29:25	ga_ls9c_ard_3-2-1_092075_2022-09-24_final.stac-item
2022-09-27 09:21:03	ga_ls9c_ard_3-2-1_090085_2022-09-26_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-15 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-14_final.stac-item
2022-10-15 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-15_final.stac-item
2022-10-16 11:24:32	ga_ls9c_ard_3-2-1_111069_2022-10-16_final.stac-item
2022-10-18 11:12:11	ga_ls9c_ard_3-2-1_109069_2022-10-18_final.stac-item
2022-10-24 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-10-24_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-11-01 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-11-01_final.stac-item
2022-11-21 11:01:02	ga_ls9c_ard_3-2-1_107072_2022-11-21_final.stac-item
2022-11-24 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-24_final.stac-item
2022-11-24 11:36:19	ga_ls9c_ard_3-2-1_112083_2022-11-24_final.stac-item
2022-11-30 10:56:00	ga_ls9c_ard_3-2-1_106075_2022-11-30_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-24 10:04:56	ga_ls9c_ard_3-2-1_098071_2022-12-24_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 10:24:43	ga_ls9c_ard_3-2-1_101074_2022-12-29_final.stac-item
2023-01-01 09:17:57	ga_ls9c_ard_3-2-1_090077_2022-12-31_final.stac-item
2023-01-06 11:12:11	ga_ls9c_ard_3-2-1_109069_2023-01-06_final.stac-item
2023-02-17 11:51:38	ga_ls9c_ard_3-2-1_115075_2023-02-17_final.stac-item
2023-02-19 09:57:33	ga_ls9c_ard_3-2-1_097068_2023-02-19_final.stac-item
2023-02-27 10:52:52	ga_ls9c_ard_3-2-1_105083_2023-02-27_final.stac-item
2023-03-06 10:55:47	ga_ls9c_ard_3-2-1_106075_2023-03-06_final.stac-item
2023-03-14 10:09:53	ga_ls9c_ard_3-2-1_098084_2023-03-14_final.stac-item
2023-03-16 11:32:01	ga_ls9c_ard_3-2-1_112073_2023-03-16_final.stac-item
2023-03-19 10:27:36	ga_ls9c_ard_3-2-1_101082_2023-03-19_final.stac-item
2023-03-30 10:04:06	ga_ls9c_ard_3-2-1_098070_2023-03-30_final.stac-item
2023-04-05 09:33:48	ga_ls9c_ard_3-2-1_092087_2023-04-05_final.stac-item
2023-04-09 09:07:03	ga_ls9c_ard_3-2-1_088082_2023-04-08_final.stac-item
2023-05-01 10:09:51	ga_ls9c_ard_3-2-1_098085_2023-05-01_final.stac-item
2023-05-15 10:16:31	ga_ls9c_ard_3-2-1_100071_2023-05-15_final.stac-item
2023-06-01 09:22:21	ga_ls9c_ard_3-2-1_091075_2023-05-31_final.stac-item
2023-06-01 09:26:44	ga_ls9c_ard_3-2-1_091086_2023-05-31_final.stac-item
2023-06-09 10:09:44	ga_ls9c_ard_3-2-1_099070_2023-06-09_final.stac-item
2023-06-12 10:41:48	ga_ls9c_ard_3-2-1_104073_2023-06-12_final.stac-item
2023-06-17 09:21:48	ga_ls9c_ard_3-2-1_091074_2023-06-16_final.stac-item
2023-06-19 10:48:20	ga_ls9c_ard_3-2-1_105074_2023-06-19_final.stac-item
2023-06-22 11:23:13	ga_ls9c_ard_3-2-1_110084_2023-06-22_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-07-04 10:08:51	ga_ls9c_ard_3-2-1_098083_2023-07-04_final.stac-item
2023-07-11 11:52:47	ga_ls9c_ard_3-2-1_115080_2023-07-11_final.stac-item
2023-09-05 10:59:45	ga_ls9c_ard_3-2-1_107070_2023-09-05_final.stac-item
2023-09-09 10:35:53	ga_ls9c_ard_3-2-1_103072_2023-09-09_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-09-16 09:07:13	ga_ls9c_ard_3-2-1_088082_2023-09-15_final.stac-item
2023-10-09 10:46:45	ga_ls9c_ard_3-2-1_105068_2023-10-09_final.stac-item
2023-10-11 10:39:37	ga_ls9c_ard_3-2-1_103081_2023-10-11_final.stac-item
2023-10-23 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-10-23_final.stac-item
2023-10-29 10:27:40	ga_ls9c_ard_3-2-1_101082_2023-10-29_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years