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
2021-11-04 10:36:55	ga_ls9c_ard_3-2-1_103080_2021-11-04_final.stac-item
2021-11-07 10:58:32	ga_ls9c_ard_3-2-1_106081_2021-11-07_final.stac-item
2021-11-08 09:56:38	ga_ls9c_ard_3-2-1_097073_2021-11-08_final.stac-item
2021-11-08 09:57:02	ga_ls9c_ard_3-2-1_097074_2021-11-08_final.stac-item
2021-11-14 10:37:05	ga_ls9c_ard_3-2-1_103068_2021-11-14_final.stac-item
2021-11-18 10:03:10	ga_ls9c_ard_3-2-1_097077_2021-11-18_final.stac-item
2021-11-20 11:20:41	ga_ls9c_ard_3-2-1_110071_2021-11-20_final.stac-item
2021-11-23 11:43:29	ga_ls9c_ard_3-2-1_114075_2021-11-23_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-30 11:39:32	ga_ls9c_ard_3-2-1_113076_2021-12-30_final.stac-item
2022-01-07 10:52:04	ga_ls9c_ard_3-2-1_105081_2022-01-07_final.stac-item
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-15 10:01:48	ga_ls9c_ard_3-2-1_097079_2022-01-15_final.stac-item
2022-01-17 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-01-17_final.stac-item
2022-01-27 10:25:21	ga_ls9c_ard_3-2-1_101076_2022-01-27_final.stac-item
2022-02-07 11:46:53	ga_ls9c_ard_3-2-1_114079_2022-02-07_final.stac-item
2022-02-15 09:20:29	ga_ls9c_ard_3-2-1_090084_2022-02-14_final.stac-item
2022-02-21 10:20:38	ga_ls9c_ard_3-2-1_100080_2022-02-21_final.stac-item
2022-02-26 10:39:06	ga_ls9c_ard_3-2-1_103080_2022-02-26_final.stac-item
2022-03-11 11:45:27	ga_ls9c_ard_3-2-1_114076_2022-03-11_final.stac-item
2022-03-22 09:47:35	ga_ls9c_ard_3-2-1_095075_2022-03-22_final.stac-item
2022-04-03 10:15:27	ga_ls9c_ard_3-2-1_099083_2022-04-03_final.stac-item
2022-04-08 10:30:23	ga_ls9c_ard_3-2-1_102074_2022-04-08_final.stac-item
2022-05-19 10:23:24	ga_ls9c_ard_3-2-1_101073_2022-05-19_final.stac-item
2022-05-25 11:29:11	ga_ls9c_ard_3-2-1_111083_2022-05-25_final.stac-item
2022-05-25 11:29:35	ga_ls9c_ard_3-2-1_111084_2022-05-25_final.stac-item
2022-05-27 11:16:25	ga_ls9c_ard_3-2-1_109082_2022-05-27_final.stac-item
2022-06-08 09:57:06	ga_ls9c_ard_3-2-1_097069_2022-06-08_final.stac-item
2022-06-21 09:31:37	ga_ls9c_ard_3-2-1_092082_2022-06-21_final.stac-item
2022-07-01 11:46:30	ga_ls9c_ard_3-2-1_114079_2022-07-01_final.stac-item
2022-07-12 09:51:24	ga_ls9c_ard_3-2-1_095085_2022-07-12_final.stac-item
2022-08-31 09:35:53	ga_ls9c_ard_3-2-1_093076_2022-08-31_final.stac-item
2022-09-24 10:25:26	ga_ls9c_ard_3-2-1_101076_2022-09-24_final.stac-item
2022-09-28 10:01:31	ga_ls9c_ard_3-2-1_097078_2022-09-28_final.stac-item
2022-10-05 11:45:46	ga_ls9c_ard_3-2-1_114076_2022-10-05_final.stac-item
2022-10-25 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-10-25_final.stac-item
2022-11-19 11:12:36	ga_ls9c_ard_3-2-1_109070_2022-11-19_final.stac-item
2022-11-21 09:25:44	ga_ls9c_ard_3-2-1_091081_2022-11-20_final.stac-item
2023-01-31 09:34:42	ga_ls9c_ard_3-2-1_092088_2023-01-31_final.stac-item
2023-02-11 10:49:07	ga_ls9c_ard_3-2-1_105073_2023-02-11_final.stac-item
2023-02-12 09:53:05	ga_ls9c_ard_3-2-1_096072_2023-02-12_final.stac-item
2023-02-14 09:45:53	ga_ls9c_ard_3-2-1_094085_2023-02-14_final.stac-item
2023-02-15 10:25:09	ga_ls9c_ard_3-2-1_101075_2023-02-15_final.stac-item
2023-02-16 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-02-16_final.stac-item
2023-02-16 11:11:11	ga_ls9c_ard_3-2-1_108082_2023-02-16_final.stac-item
2023-02-17 10:15:33	ga_ls9c_ard_3-2-1_099082_2023-02-17_final.stac-item
2023-02-18 09:18:18	ga_ls9c_ard_3-2-1_090078_2023-02-17_final.stac-item
2023-02-18 10:57:59	ga_ls9c_ard_3-2-1_106080_2023-02-18_final.stac-item
2023-02-20 10:43:59	ga_ls9c_ard_3-2-1_104076_2023-02-20_final.stac-item
2023-03-14 11:45:11	ga_ls9c_ard_3-2-1_114075_2023-03-14_final.stac-item
2023-03-16 11:35:13	ga_ls9c_ard_3-2-1_112081_2023-03-16_final.stac-item
2023-03-19 10:23:37	ga_ls9c_ard_3-2-1_101072_2023-03-19_final.stac-item
2023-03-23 09:59:39	ga_ls9c_ard_3-2-1_097074_2023-03-23_final.stac-item
2023-04-14 09:25:55	ga_ls9c_ard_3-2-1_091083_2023-04-13_final.stac-item
2023-04-20 10:23:44	ga_ls9c_ard_3-2-1_101073_2023-04-20_final.stac-item
2023-04-20 10:24:08	ga_ls9c_ard_3-2-1_101074_2023-04-20_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-04-29 10:18:15	ga_ls9c_ard_3-2-1_100075_2023-04-29_final.stac-item
2023-05-05 11:22:21	ga_ls9c_ard_3-2-1_110081_2023-05-05_final.stac-item
2023-05-06 10:23:32	ga_ls9c_ard_3-2-1_101073_2023-05-06_final.stac-item
2023-05-07 09:32:18	ga_ls9c_ard_3-2-1_092084_2023-05-07_final.stac-item
2023-05-07 11:09:35	ga_ls9c_ard_3-2-1_108080_2023-05-07_final.stac-item
2023-05-08 11:50:27	ga_ls9c_ard_3-2-1_115074_2023-05-08_final.stac-item
2023-05-10 11:40:05	ga_ls9c_ard_3-2-1_113079_2023-05-10_final.stac-item
2023-05-14 11:12:33	ga_ls9c_ard_3-2-1_109072_2023-05-14_final.stac-item
2023-05-15 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-05-15_final.stac-item
2023-05-16 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-05-15_final.stac-item
2023-05-18 09:14:05	ga_ls9c_ard_3-2-1_089085_2023-05-17_final.stac-item
2023-05-19 09:51:45	ga_ls9c_ard_3-2-1_096071_2023-05-19_final.stac-item
2023-05-23 09:32:09	ga_ls9c_ard_3-2-1_092084_2023-05-23_final.stac-item
2023-05-25 09:17:22	ga_ls9c_ard_3-2-1_090078_2023-05-24_final.stac-item
2023-05-26 10:00:38	ga_ls9c_ard_3-2-1_097078_2023-05-26_final.stac-item
2023-05-28 11:28:45	ga_ls9c_ard_3-2-1_111082_2023-05-28_final.stac-item
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_final.stac-item
2023-06-23 10:26:24	ga_ls9c_ard_3-2-1_101081_2023-06-23_final.stac-item
2023-06-24 09:28:47	ga_ls9c_ard_3-2-1_092076_2023-06-23_final.stac-item
2023-07-03 09:25:34	ga_ls9c_ard_3-2-1_091083_2023-07-02_final.stac-item
2023-07-06 09:54:55	ga_ls9c_ard_3-2-1_096079_2023-07-06_final.stac-item
2023-07-08 11:22:15	ga_ls9c_ard_3-2-1_110081_2023-07-08_final.stac-item
2023-07-10 09:30:38	ga_ls9c_ard_3-2-1_092080_2023-07-10_final.stac-item
2023-07-11 10:11:06	ga_ls9c_ard_3-2-1_099073_2023-07-11_final.stac-item
2023-07-12 09:17:29	ga_ls9c_ard_3-2-1_090078_2023-07-11_final.stac-item
2023-09-11 10:24:20	ga_ls9c_ard_3-2-1_101074_2023-09-11_final.stac-item
2023-09-12 09:31:55	ga_ls9c_ard_3-2-1_092082_2023-09-12_final.stac-item
2023-09-15 10:04:02	ga_ls9c_ard_3-2-1_097085_2023-09-15_final.stac-item
2023-09-17 09:47:41	ga_ls9c_ard_3-2-1_095075_2023-09-17_final.stac-item
2023-09-17 09:50:52	ga_ls9c_ard_3-2-1_095083_2023-09-17_final.stac-item
2023-09-23 10:48:15	ga_ls9c_ard_3-2-1_105072_2023-09-23_final.stac-item
2023-09-25 10:36:17	ga_ls9c_ard_3-2-1_103073_2023-09-25_final.stac-item
2023-09-26 11:23:07	ga_ls9c_ard_3-2-1_110082_2023-09-26_final.stac-item
2023-09-26 11:24:19	ga_ls9c_ard_3-2-1_110085_2023-09-26_final.stac-item
2023-09-27 10:25:53	ga_ls9c_ard_3-2-1_101078_2023-09-27_final.stac-item
2023-09-28 09:31:03	ga_ls9c_ard_3-2-1_092080_2023-09-28_final.stac-item
2023-09-29 10:12:44	ga_ls9c_ard_3-2-1_099076_2023-09-29_final.stac-item
2023-10-01 10:01:36	ga_ls9c_ard_3-2-1_097079_2023-10-01_final.stac-item
2023-10-01 10:03:12	ga_ls9c_ard_3-2-1_097083_2023-10-01_final.stac-item
2023-10-05 09:38:32	ga_ls9c_ard_3-2-1_093083_2023-10-05_final.stac-item
2023-10-08 11:45:33	ga_ls9c_ard_3-2-1_114076_2023-10-08_final.stac-item
2023-10-08 11:46:45	ga_ls9c_ard_3-2-1_114079_2023-10-08_final.stac-item
2023-10-13 10:24:29	ga_ls9c_ard_3-2-1_101074_2023-10-13_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