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 09:23:08	ga_ls9c_ard_3-2-1_091083_2021-11-11_final.stac-item
2021-11-13 10:01:54	ga_ls9c_ard_3-2-1_097080_2021-11-13_final.stac-item
2021-11-20 11:21:29	ga_ls9c_ard_3-2-1_110073_2021-11-20_final.stac-item
2021-12-04 11:00:11	ga_ls9c_ard_3-2-1_107070_2021-12-04_final.stac-item
2021-12-13 10:54:18	ga_ls9c_ard_3-2-1_106071_2021-12-13_final.stac-item
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-14 11:42:20	ga_ls9c_ard_3-2-1_113083_2021-12-14_final.stac-item
2021-12-20 09:26:21	ga_ls9c_ard_3-2-1_091083_2021-12-19_final.stac-item
2022-01-22 10:03:13	ga_ls9c_ard_3-2-1_098067_2022-01-22_final.stac-item
2022-01-24 11:32:08	ga_ls9c_ard_3-2-1_112073_2022-01-24_final.stac-item
2022-01-30 09:20:10	ga_ls9c_ard_3-2-1_090083_2022-01-29_final.stac-item
2022-02-01 10:41:06	ga_ls9c_ard_3-2-1_104069_2022-02-01_final.stac-item
2022-02-06 09:25:56	ga_ls9c_ard_3-2-1_091082_2022-02-05_final.stac-item
2022-02-07 10:08:24	ga_ls9c_ard_3-2-1_098080_2022-02-07_final.stac-item
2022-02-10 10:36:05	ga_ls9c_ard_3-2-1_103072_2022-02-10_final.stac-item
2022-02-18 09:47:22	ga_ls9c_ard_3-2-1_095074_2022-02-18_final.stac-item
2022-02-25 09:52:16	ga_ls9c_ard_3-2-1_096071_2022-02-25_final.stac-item
2022-03-29 11:36:12	ga_ls9c_ard_3-2-1_112084_2022-03-29_final.stac-item
2022-04-30 09:51:56	ga_ls9c_ard_3-2-1_096071_2022-04-30_final.stac-item
2022-05-09 09:50:52	ga_ls9c_ard_3-2-1_095084_2022-05-09_final.stac-item
2022-06-04 10:27:24	ga_ls9c_ard_3-2-1_101083_2022-06-04_final.stac-item
2022-06-11 10:29:37	ga_ls9c_ard_3-2-1_102073_2022-06-11_final.stac-item
2022-06-18 10:33:54	ga_ls9c_ard_3-2-1_103068_2022-06-18_final.stac-item
2022-06-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-06-23_final.stac-item
2022-07-02 10:46:29	ga_ls9c_ard_3-2-1_105068_2022-07-02_final.stac-item
2022-07-09 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-07-09_final.stac-item
2022-07-21 11:19:01	ga_ls9c_ard_3-2-1_110072_2022-07-21_final.stac-item
2022-08-02 10:04:37	ga_ls9c_ard_3-2-1_098071_2022-08-02_final.stac-item
2022-08-08 11:06:05	ga_ls9c_ard_3-2-1_108070_2022-08-08_final.stac-item
2022-08-10 09:21:15	ga_ls9c_ard_3-2-1_090086_2022-08-09_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-31 09:35:29	ga_ls9c_ard_3-2-1_093075_2022-08-31_final.stac-item
2022-08-31 11:13:34	ga_ls9c_ard_3-2-1_109073_2022-08-31_final.stac-item
2022-09-02 09:28:18	ga_ls9c_ard_3-2-1_091088_2022-09-01_final.stac-item
2022-09-16 11:14:49	ga_ls9c_ard_3-2-1_109076_2022-09-16_final.stac-item
2022-09-27 09:18:15	ga_ls9c_ard_3-2-1_090078_2022-09-26_final.stac-item
2022-10-04 09:29:13	ga_ls9c_ard_3-2-1_091090_2022-10-03_final.stac-item
2022-10-11 11:06:21	ga_ls9c_ard_3-2-1_108070_2022-10-11_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-20 11:00:37	ga_ls9c_ard_3-2-1_107071_2022-10-20_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-11-10 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-11-10_final.stac-item
2022-11-21 09:28:56	ga_ls9c_ard_3-2-1_091089_2022-11-20_final.stac-item
2022-11-26 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-11-26_final.stac-item
2022-11-28 11:05:59	ga_ls9c_ard_3-2-1_108069_2022-11-28_final.stac-item
2022-11-30 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-11-30_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-08 10:05:23	ga_ls9c_ard_3-2-1_098072_2022-12-08_final.stac-item
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-26 09:54:59	ga_ls9c_ard_3-2-1_096077_2022-12-26_final.stac-item
2022-12-27 10:37:28	ga_ls9c_ard_3-2-1_103075_2022-12-27_final.stac-item
2023-01-22 11:12:26	ga_ls9c_ard_3-2-1_109070_2023-01-22_final.stac-item
2023-01-28 10:35:28	ga_ls9c_ard_3-2-1_103070_2023-01-28_final.stac-item
2023-01-31 11:11:59	ga_ls9c_ard_3-2-1_108084_2023-01-31_final.stac-item
2023-02-12 09:52:41	ga_ls9c_ard_3-2-1_096071_2023-02-12_final.stac-item
2023-02-16 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-02-16_final.stac-item
2023-02-18 10:55:11	ga_ls9c_ard_3-2-1_106073_2023-02-18_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-09 11:25:02	ga_ls9c_ard_3-2-1_111071_2023-03-09_final.stac-item
2023-03-11 11:14:40	ga_ls9c_ard_3-2-1_109076_2023-03-11_final.stac-item
2023-03-11 11:17:51	ga_ls9c_ard_3-2-1_109084_2023-03-11_final.stac-item
2023-03-12 10:18:15	ga_ls9c_ard_3-2-1_100074_2023-03-12_final.stac-item
2023-03-17 10:39:59	ga_ls9c_ard_3-2-1_103082_2023-03-17_final.stac-item
2023-04-06 11:51:09	ga_ls9c_ard_3-2-1_115075_2023-04-06_final.stac-item
2023-04-08 09:57:30	ga_ls9c_ard_3-2-1_097069_2023-04-08_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-05-12 09:52:02	ga_ls9c_ard_3-2-1_095087_2023-05-12_final.stac-item
2023-05-21 11:23:26	ga_ls9c_ard_3-2-1_110084_2023-05-21_final.stac-item
2023-05-23 09:32:57	ga_ls9c_ard_3-2-1_092086_2023-05-23_final.stac-item
2023-06-01 11:01:14	ga_ls9c_ard_3-2-1_107075_2023-06-01_final.stac-item
2023-06-13 09:50:57	ga_ls9c_ard_3-2-1_095085_2023-06-13_final.stac-item
2023-06-15 09:34:10	ga_ls9c_ard_3-2-1_093074_2023-06-15_final.stac-item
2023-06-17 11:04:17	ga_ls9c_ard_3-2-1_107083_2023-06-17_final.stac-item
2023-06-30 10:27:55	ga_ls9c_ard_3-2-1_102069_2023-06-30_final.stac-item
2023-07-06 11:35:48	ga_ls9c_ard_3-2-1_112084_2023-07-06_final.stac-item
2023-07-08 11:19:04	ga_ls9c_ard_3-2-1_110073_2023-07-08_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-07-16 10:28:28	ga_ls9c_ard_3-2-1_102070_2023-07-16_final.stac-item
2023-07-26 11:05:33	ga_ls9c_ard_3-2-1_108070_2023-07-26_final.stac-item
2023-07-27 10:09:09	ga_ls9c_ard_3-2-1_099068_2023-07-27_final.stac-item
2023-07-31 09:52:04	ga_ls9c_ard_3-2-1_095087_2023-07-31_final.stac-item
2023-08-14 11:41:49	ga_ls9c_ard_3-2-1_113083_2023-08-14_final.stac-item
2023-08-18 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-08-18_final.stac-item
2023-08-22 09:11:33	ga_ls9c_ard_3-2-1_089078_2023-08-21_final.stac-item
2023-08-25 09:45:17	ga_ls9c_ard_3-2-1_094085_2023-08-25_final.stac-item
2023-08-27 11:07:27	ga_ls9c_ard_3-2-1_108074_2023-08-27_final.stac-item
2023-08-31 10:42:22	ga_ls9c_ard_3-2-1_104073_2023-08-31_final.stac-item
2023-09-03 09:39:59	ga_ls9c_ard_3-2-1_093087_2023-09-03_final.stac-item
2023-09-13 10:11:12	ga_ls9c_ard_3-2-1_099072_2023-09-13_final.stac-item
2023-09-29 10:15:32	ga_ls9c_ard_3-2-1_099083_2023-09-29_final.stac-item
2023-10-02 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-10-02_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-24 10:05:11	ga_ls9c_ard_3-2-1_098072_2023-10-24_final.stac-item
2023-11-26 10:50:07	ga_ls9c_ard_3-2-1_105076_2023-11-26_final.stac-item
2023-12-03 09:18:11	ga_ls9c_ard_3-2-1_090078_2023-12-02_final.stac-item
2023-12-06 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-12-06_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