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
2021-12-16 11:25:58	ga_ls9c_ard_3-2-1_111073_2021-12-16_final.stac-item
2021-12-18 09:39:30	ga_ls9c_ard_3-2-1_093085_2021-12-18_final.stac-item
2021-12-25 11:24:35	ga_ls9c_ard_3-2-1_110085_2021-12-25_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2022-01-05 09:23:57	ga_ls9c_ard_3-2-1_091077_2022-01-04_final.stac-item
2022-01-12 09:29:18	ga_ls9c_ard_3-2-1_092075_2022-01-11_final.stac-item
2022-01-14 10:55:01	ga_ls9c_ard_3-2-1_106073_2022-01-14_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_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 09:07:43	ga_ls9c_ard_3-2-1_088083_2022-02-16_final.stac-item
2022-02-27 11:19:34	ga_ls9c_ard_3-2-1_110073_2022-02-27_final.stac-item
2022-02-27 11:19:58	ga_ls9c_ard_3-2-1_110074_2022-02-27_final.stac-item
2022-03-04 11:42:04	ga_ls9c_ard_3-2-1_113083_2022-03-04_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-19 10:55:11	ga_ls9c_ard_3-2-1_106074_2022-03-19_final.stac-item
2022-03-23 10:28:03	ga_ls9c_ard_3-2-1_102068_2022-03-23_final.stac-item
2022-04-04 09:22:38	ga_ls9c_ard_3-2-1_090090_2022-04-03_final.stac-item
2022-04-28 10:03:30	ga_ls9c_ard_3-2-1_098069_2022-04-28_final.stac-item
2022-05-06 09:20:24	ga_ls9c_ard_3-2-1_090085_2022-05-05_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-06-27 10:27:57	ga_ls9c_ard_3-2-1_102068_2022-06-27_final.stac-item
2022-07-16 09:21:30	ga_ls9c_ard_3-2-1_091072_2022-07-15_final.stac-item
2022-07-16 11:01:35	ga_ls9c_ard_3-2-1_107075_2022-07-16_final.stac-item
2022-07-18 10:50:27	ga_ls9c_ard_3-2-1_105078_2022-07-18_final.stac-item
2022-07-30 11:16:09	ga_ls9c_ard_3-2-1_109080_2022-07-30_final.stac-item
2022-08-09 10:13:16	ga_ls9c_ard_3-2-1_099077_2022-08-09_final.stac-item
2022-08-26 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-08-25_final.stac-item
2022-08-28 10:42:40	ga_ls9c_ard_3-2-1_104073_2022-08-28_final.stac-item
2022-08-30 10:30:18	ga_ls9c_ard_3-2-1_102073_2022-08-30_final.stac-item
2022-09-07 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-09-07_final.stac-item
2022-09-19 10:04:28	ga_ls9c_ard_3-2-1_098070_2022-09-19_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-30 09:57:12	ga_ls9c_ard_3-2-1_097067_2022-10-30_final.stac-item
2022-10-31 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-31_final.stac-item
2022-11-05 09:23:41	ga_ls9c_ard_3-2-1_091076_2022-11-04_final.stac-item
2022-11-05 09:24:05	ga_ls9c_ard_3-2-1_091077_2022-11-04_final.stac-item
2022-11-17 11:30:33	ga_ls9c_ard_3-2-1_111084_2022-11-17_final.stac-item
2022-11-26 11:18:45	ga_ls9c_ard_3-2-1_110070_2022-11-26_final.stac-item
2022-11-27 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-11-27_final.stac-item
2022-11-29 10:13:33	ga_ls9c_ard_3-2-1_099077_2022-11-29_final.stac-item
2022-12-08 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-12-08_final.stac-item
2022-12-08 10:10:35	ga_ls9c_ard_3-2-1_098085_2022-12-08_final.stac-item
2022-12-09 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-12-08_final.stac-item
2022-12-14 09:33:06	ga_ls9c_ard_3-2-1_092084_2022-12-14_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-29 10:23:55	ga_ls9c_ard_3-2-1_101072_2022-12-29_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-17 10:53:32	ga_ls9c_ard_3-2-1_106069_2023-01-17_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-02-06 10:29:22	ga_ls9c_ard_3-2-1_102070_2023-02-06_final.stac-item
2023-02-16 09:29:30	ga_ls9c_ard_3-2-1_092075_2023-02-15_final.stac-item
2023-02-20 09:07:30	ga_ls9c_ard_3-2-1_088082_2023-02-19_final.stac-item
2023-02-27 09:10:47	ga_ls9c_ard_3-2-1_089075_2023-02-26_final.stac-item
2023-03-06 09:22:30	ga_ls9c_ard_3-2-1_090089_2023-03-05_final.stac-item
2023-03-11 09:39:22	ga_ls9c_ard_3-2-1_093085_2023-03-11_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-17 10:35:12	ga_ls9c_ard_3-2-1_103070_2023-03-17_final.stac-item
2023-03-18 09:41:10	ga_ls9c_ard_3-2-1_094074_2023-03-18_final.stac-item
2023-03-27 11:17:19	ga_ls9c_ard_3-2-1_109083_2023-03-27_final.stac-item
2023-03-30 10:04:30	ga_ls9c_ard_3-2-1_098071_2023-03-30_final.stac-item
2023-03-31 10:46:10	ga_ls9c_ard_3-2-1_105067_2023-03-31_final.stac-item
2023-04-10 09:52:18	ga_ls9c_ard_3-2-1_095087_2023-04-10_final.stac-item
2023-04-13 11:58:27	ga_ls9c_ard_3-2-1_116078_2023-04-13_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-05-11 10:42:04	ga_ls9c_ard_3-2-1_104073_2023-05-11_final.stac-item
2023-07-03 10:59:16	ga_ls9c_ard_3-2-1_107070_2023-07-03_final.stac-item
2023-07-04 10:04:04	ga_ls9c_ard_3-2-1_098071_2023-07-04_final.stac-item
2023-07-21 09:11:43	ga_ls9c_ard_3-2-1_089079_2023-07-20_final.stac-item
2023-08-01 10:27:46	ga_ls9c_ard_3-2-1_102068_2023-08-01_final.stac-item
2023-08-05 10:09:29	ga_ls9c_ard_3-2-1_098084_2023-08-05_final.stac-item
2023-08-12 10:08:54	ga_ls9c_ard_3-2-1_099067_2023-08-12_final.stac-item
2023-08-13 09:19:40	ga_ls9c_ard_3-2-1_090083_2023-08-12_final.stac-item
2023-08-20 09:21:29	ga_ls9c_ard_3-2-1_091072_2023-08-19_final.stac-item
2023-08-21 10:03:10	ga_ls9c_ard_3-2-1_098068_2023-08-21_final.stac-item
2023-08-27 11:07:27	ga_ls9c_ard_3-2-1_108074_2023-08-27_final.stac-item
2023-08-29 09:17:25	ga_ls9c_ard_3-2-1_090077_2023-08-28_final.stac-item
2023-08-29 09:20:37	ga_ls9c_ard_3-2-1_090085_2023-08-28_final.stac-item
2023-08-30 10:03:29	ga_ls9c_ard_3-2-1_097084_2023-08-30_final.stac-item
2023-09-17 09:52:28	ga_ls9c_ard_3-2-1_095087_2023-09-17_final.stac-item
2023-09-18 10:30:09	ga_ls9c_ard_3-2-1_102073_2023-09-18_final.stac-item
2023-09-26 09:41:02	ga_ls9c_ard_3-2-1_094074_2023-09-26_final.stac-item
2023-10-21 09:40:41	ga_ls9c_ard_3-2-1_093088_2023-10-21_final.stac-item
2023-10-30 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-10-29_final.stac-item
2023-11-06 11:14:41	ga_ls9c_ard_3-2-1_109076_2023-11-06_final.stac-item
2023-11-08 09:27:50	ga_ls9c_ard_3-2-1_091087_2023-11-07_final.stac-item
2023-11-17 09:20:53	ga_ls9c_ard_3-2-1_090085_2023-11-16_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2023-11-22 11:17:59	ga_ls9c_ard_3-2-1_109084_2023-11-22_final.stac-item
2023-11-24 09:23:58	ga_ls9c_ard_3-2-1_091077_2023-11-23_final.stac-item
2023-11-24 11:00:28	ga_ls9c_ard_3-2-1_107071_2023-11-24_final.stac-item
2023-11-26 10:50:07	ga_ls9c_ard_3-2-1_105076_2023-11-26_final.stac-item
2023-12-01 09:29:22	ga_ls9c_ard_3-2-1_092075_2023-11-30_final.stac-item
2023-12-02 10:11:25	ga_ls9c_ard_3-2-1_099072_2023-12-02_final.stac-item
2023-12-02 10:13:49	ga_ls9c_ard_3-2-1_099078_2023-12-02_final.stac-item
2023-12-09 11:58:01	ga_ls9c_ard_3-2-1_116076_2023-12-09_final.stac-item
2023-12-18 10:14:15	ga_ls9c_ard_3-2-1_099079_2023-12-18_final.stac-item
2023-12-19 09:22:37	ga_ls9c_ard_3-2-1_090089_2023-12-18_final.stac-item
2023-12-24 09:39:35	ga_ls9c_ard_3-2-1_093085_2023-12-24_final.stac-item
2023-12-30 10:34:34	ga_ls9c_ard_3-2-1_103068_2023-12-30_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