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
2021-11-09 10:37:48	ga_ls9c_ard_3-2-1_103076_2021-11-09_final.stac-item
2021-12-07 11:33:03	ga_ls9c_ard_3-2-1_112075_2021-12-07_final.stac-item
2021-12-14 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-14_final.stac-item
2021-12-17 10:31:32	ga_ls9c_ard_3-2-1_102076_2021-12-17_final.stac-item
2021-12-18 11:13:36	ga_ls9c_ard_3-2-1_109073_2021-12-18_final.stac-item
2021-12-23 11:36:09	ga_ls9c_ard_3-2-1_112083_2021-12-23_final.stac-item
2021-12-30 11:37:56	ga_ls9c_ard_3-2-1_113072_2021-12-30_final.stac-item
2022-01-01 11:29:58	ga_ls9c_ard_3-2-1_111083_2022-01-01_final.stac-item
2022-01-08 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-08_final.stac-item
2022-01-17 11:26:44	ga_ls9c_ard_3-2-1_111075_2022-01-17_final.stac-item
2022-01-20 10:20:45	ga_ls9c_ard_3-2-1_100080_2022-01-20_final.stac-item
2022-02-04 11:13:12	ga_ls9c_ard_3-2-1_109072_2022-02-04_final.stac-item
2022-02-16 10:01:45	ga_ls9c_ard_3-2-1_097079_2022-02-16_final.stac-item
2022-02-16 11:41:26	ga_ls9c_ard_3-2-1_113081_2022-02-16_final.stac-item
2022-02-19 10:28:38	ga_ls9c_ard_3-2-1_102069_2022-02-19_final.stac-item
2022-02-23 11:45:32	ga_ls9c_ard_3-2-1_114076_2022-02-23_final.stac-item
2022-03-03 10:58:48	ga_ls9c_ard_3-2-1_106083_2022-03-03_final.stac-item
2022-03-09 10:20:32	ga_ls9c_ard_3-2-1_100080_2022-03-09_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-04-08 10:29:35	ga_ls9c_ard_3-2-1_102072_2022-04-08_final.stac-item
2022-04-21 11:41:48	ga_ls9c_ard_3-2-1_113083_2022-04-21_final.stac-item
2022-05-07 11:41:44	ga_ls9c_ard_3-2-1_113083_2022-05-07_final.stac-item
2022-05-10 10:30:31	ga_ls9c_ard_3-2-1_102075_2022-05-10_final.stac-item
2022-05-13 09:21:18	ga_ls9c_ard_3-2-1_091072_2022-05-12_final.stac-item
2022-05-20 11:05:03	ga_ls9c_ard_3-2-1_108069_2022-05-20_final.stac-item
2022-05-22 09:21:00	ga_ls9c_ard_3-2-1_090087_2022-05-21_final.stac-item
2022-05-23 09:58:40	ga_ls9c_ard_3-2-1_097073_2022-05-23_final.stac-item
2022-05-23 09:59:52	ga_ls9c_ard_3-2-1_097076_2022-05-23_final.stac-item
2022-06-28 11:12:49	ga_ls9c_ard_3-2-1_109072_2022-06-28_final.stac-item
2022-07-09 09:17:44	ga_ls9c_ard_3-2-1_090078_2022-07-08_final.stac-item
2022-07-12 11:25:06	ga_ls9c_ard_3-2-1_111072_2022-07-12_final.stac-item
2022-07-19 09:52:03	ga_ls9c_ard_3-2-1_096071_2022-07-19_final.stac-item
2022-07-26 11:41:14	ga_ls9c_ard_3-2-1_113081_2022-07-26_final.stac-item
2022-08-02 10:05:01	ga_ls9c_ard_3-2-1_098072_2022-08-02_final.stac-item
2022-08-06 11:20:49	ga_ls9c_ard_3-2-1_110076_2022-08-06_final.stac-item
2022-08-08 11:09:41	ga_ls9c_ard_3-2-1_108079_2022-08-08_final.stac-item
2022-08-17 09:25:29	ga_ls9c_ard_3-2-1_091081_2022-08-16_final.stac-item
2022-08-20 09:52:00	ga_ls9c_ard_3-2-1_096070_2022-08-20_final.stac-item
2022-09-03 10:04:23	ga_ls9c_ard_3-2-1_098070_2022-09-03_final.stac-item
2022-09-07 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-09-07_final.stac-item
2022-09-07 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-09-07_final.stac-item
2022-09-12 10:01:01	ga_ls9c_ard_3-2-1_097077_2022-09-12_final.stac-item
2022-09-19 10:07:16	ga_ls9c_ard_3-2-1_098077_2022-09-19_final.stac-item
2022-09-29 10:43:35	ga_ls9c_ard_3-2-1_104075_2022-09-29_final.stac-item
2022-10-04 09:27:13	ga_ls9c_ard_3-2-1_091085_2022-10-03_final.stac-item
2022-10-06 10:50:57	ga_ls9c_ard_3-2-1_105078_2022-10-06_final.stac-item
2022-10-09 09:43:47	ga_ls9c_ard_3-2-1_094080_2022-10-09_final.stac-item
2022-10-14 11:41:40	ga_ls9c_ard_3-2-1_113081_2022-10-14_final.stac-item
2022-10-19 10:18:33	ga_ls9c_ard_3-2-1_100074_2022-10-19_final.stac-item
2022-10-21 11:47:05	ga_ls9c_ard_3-2-1_114079_2022-10-21_final.stac-item
2022-10-31 10:41:39	ga_ls9c_ard_3-2-1_104070_2022-10-31_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-04 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-11-04_final.stac-item
2022-11-07 09:13:45	ga_ls9c_ard_3-2-1_089082_2022-11-06_final.stac-item
2022-12-02 10:44:25	ga_ls9c_ard_3-2-1_104077_2022-12-02_final.stac-item
2022-12-04 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-04_final.stac-item
2022-12-05 11:15:45	ga_ls9c_ard_3-2-1_109078_2022-12-05_final.stac-item
2022-12-16 10:58:25	ga_ls9c_ard_3-2-1_106081_2022-12-16_final.stac-item
2022-12-22 10:22:06	ga_ls9c_ard_3-2-1_100083_2022-12-22_final.stac-item
2022-12-31 11:51:15	ga_ls9c_ard_3-2-1_115074_2022-12-31_final.stac-item
2023-01-04 11:30:32	ga_ls9c_ard_3-2-1_111084_2023-01-04_final.stac-item
2023-01-06 11:16:58	ga_ls9c_ard_3-2-1_109081_2023-01-06_final.stac-item
2023-01-26 09:12:54	ga_ls9c_ard_3-2-1_089080_2023-01-25_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-09 11:04:16	ga_ls9c_ard_3-2-1_107080_2023-02-09_final.stac-item
2023-02-10 10:08:15	ga_ls9c_ard_3-2-1_098079_2023-02-10_final.stac-item
2023-02-24 11:58:51	ga_ls9c_ard_3-2-1_116078_2023-02-24_final.stac-item
2023-03-02 09:40:53	ga_ls9c_ard_3-2-1_094073_2023-03-02_final.stac-item
2023-03-13 11:02:43	ga_ls9c_ard_3-2-1_107077_2023-03-13_final.stac-item
2023-03-15 09:15:04	ga_ls9c_ard_3-2-1_089086_2023-03-14_final.stac-item
2023-04-09 10:43:09	ga_ls9c_ard_3-2-1_104075_2023-04-09_final.stac-item
2023-04-15 11:46:28	ga_ls9c_ard_3-2-1_114079_2023-04-15_final.stac-item
2023-04-24 11:40:16	ga_ls9c_ard_3-2-1_113079_2023-04-24_final.stac-item
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-04-30 09:23:25	ga_ls9c_ard_3-2-1_091077_2023-04-29_final.stac-item
2023-05-09 10:54:02	ga_ls9c_ard_3-2-1_106072_2023-05-09_final.stac-item
2023-05-09 10:54:26	ga_ls9c_ard_3-2-1_106073_2023-05-09_final.stac-item
2023-05-13 10:28:30	ga_ls9c_ard_3-2-1_102070_2023-05-13_final.stac-item
2023-05-18 09:14:05	ga_ls9c_ard_3-2-1_089085_2023-05-17_final.stac-item
2023-05-18 10:48:11	ga_ls9c_ard_3-2-1_105073_2023-05-18_final.stac-item
2023-05-19 09:51:21	ga_ls9c_ard_3-2-1_096070_2023-05-19_final.stac-item
2023-05-28 09:49:52	ga_ls9c_ard_3-2-1_095082_2023-05-28_final.stac-item
2023-06-01 09:24:21	ga_ls9c_ard_3-2-1_091080_2023-05-31_final.stac-item
2023-06-23 10:23:12	ga_ls9c_ard_3-2-1_101073_2023-06-23_final.stac-item
2023-06-24 09:28:23	ga_ls9c_ard_3-2-1_092075_2023-06-23_final.stac-item
2023-06-24 11:05:40	ga_ls9c_ard_3-2-1_108071_2023-06-24_final.stac-item
2023-06-26 09:20:25	ga_ls9c_ard_3-2-1_090086_2023-06-25_final.stac-item
2023-07-01 11:15:35	ga_ls9c_ard_3-2-1_109080_2023-07-01_final.stac-item
2023-07-12 10:55:34	ga_ls9c_ard_3-2-1_106076_2023-07-12_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-08-03 10:18:13	ga_ls9c_ard_3-2-1_100075_2023-08-03_final.stac-item
2023-08-09 09:45:59	ga_ls9c_ard_3-2-1_094087_2023-08-09_final.stac-item
2023-08-11 11:07:19	ga_ls9c_ard_3-2-1_108074_2023-08-11_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-10-30 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-10-30_final.stac-item
2023-10-30 11:07:43	ga_ls9c_ard_3-2-1_108074_2023-10-30_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-18 10:01:22	ga_ls9c_ard_3-2-1_097078_2023-11-18_final.stac-item
2023-11-23 10:20:47	ga_ls9c_ard_3-2-1_100080_2023-11-23_final.stac-item
2023-11-25 10:03:15	ga_ls9c_ard_3-2-1_098067_2023-11-25_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