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 10:36:31	ga_ls9c_ard_3-2-1_103079_2021-11-04_final.stac-item
2021-11-04 10:36:55	ga_ls9c_ard_3-2-1_103080_2021-11-04_final.stac-item
2021-11-08 11:36:06	ga_ls9c_ard_3-2-1_113075_2021-11-08_final.stac-item
2021-11-09 10:38:12	ga_ls9c_ard_3-2-1_103077_2021-11-09_final.stac-item
2021-12-06 10:48:12	ga_ls9c_ard_3-2-1_105071_2021-12-06_final.stac-item
2021-12-09 09:45:46	ga_ls9c_ard_3-2-1_094085_2021-12-09_final.stac-item
2021-12-11 11:05:53	ga_ls9c_ard_3-2-1_108069_2021-12-11_final.stac-item
2021-12-18 11:15:36	ga_ls9c_ard_3-2-1_109078_2021-12-18_final.stac-item
2021-12-27 11:10:38	ga_ls9c_ard_3-2-1_108081_2021-12-27_final.stac-item
2021-12-28 10:11:49	ga_ls9c_ard_3-2-1_099073_2021-12-28_final.stac-item
2022-01-01 09:48:17	ga_ls9c_ard_3-2-1_095076_2022-01-01_final.stac-item
2022-01-01 11:29:34	ga_ls9c_ard_3-2-1_111082_2022-01-01_final.stac-item
2022-01-08 09:56:02	ga_ls9c_ard_3-2-1_096080_2022-01-08_final.stac-item
2022-01-08 11:32:55	ga_ls9c_ard_3-2-1_112075_2022-01-08_final.stac-item
2022-01-12 11:10:58	ga_ls9c_ard_3-2-1_108082_2022-01-12_final.stac-item
2022-01-15 11:39:05	ga_ls9c_ard_3-2-1_113075_2022-01-15_final.stac-item
2022-01-31 10:03:02	ga_ls9c_ard_3-2-1_097082_2022-01-31_final.stac-item
2022-02-18 11:27:27	ga_ls9c_ard_3-2-1_111077_2022-02-18_final.stac-item
2022-02-21 10:21:02	ga_ls9c_ard_3-2-1_100081_2022-02-21_final.stac-item
2022-02-26 10:34:43	ga_ls9c_ard_3-2-1_103069_2022-02-26_final.stac-item
2022-03-08 11:15:45	ga_ls9c_ard_3-2-1_109079_2022-03-08_final.stac-item
2022-04-09 09:39:32	ga_ls9c_ard_3-2-1_093086_2022-04-09_final.stac-item
2022-04-21 11:41:24	ga_ls9c_ard_3-2-1_113082_2022-04-21_final.stac-item
2022-04-23 11:26:14	ga_ls9c_ard_3-2-1_111075_2022-04-23_final.stac-item
2022-05-06 10:56:05	ga_ls9c_ard_3-2-1_106077_2022-05-06_final.stac-item
2022-05-06 10:56:29	ga_ls9c_ard_3-2-1_106078_2022-05-06_final.stac-item
2022-05-09 09:51:16	ga_ls9c_ard_3-2-1_095085_2022-05-09_final.stac-item
2022-05-14 11:45:02	ga_ls9c_ard_3-2-1_114076_2022-05-14_final.stac-item
2022-05-14 11:45:50	ga_ls9c_ard_3-2-1_114078_2022-05-14_final.stac-item
2022-05-16 09:52:58	ga_ls9c_ard_3-2-1_096074_2022-05-16_final.stac-item
2022-05-20 11:06:15	ga_ls9c_ard_3-2-1_108072_2022-05-20_final.stac-item
2022-05-20 11:09:27	ga_ls9c_ard_3-2-1_108080_2022-05-20_final.stac-item
2022-05-21 10:11:50	ga_ls9c_ard_3-2-1_099075_2022-05-21_final.stac-item
2022-05-25 09:47:06	ga_ls9c_ard_3-2-1_095075_2022-05-25_final.stac-item
2022-06-01 11:34:59	ga_ls9c_ard_3-2-1_112082_2022-06-01_final.stac-item
2022-06-14 09:26:29	ga_ls9c_ard_3-2-1_091085_2022-06-13_final.stac-item
2022-06-17 09:55:01	ga_ls9c_ard_3-2-1_096079_2022-06-17_final.stac-item
2022-07-01 11:46:54	ga_ls9c_ard_3-2-1_114080_2022-07-01_final.stac-item
2022-07-04 10:38:06	ga_ls9c_ard_3-2-1_103078_2022-07-04_final.stac-item
2022-07-07 09:31:42	ga_ls9c_ard_3-2-1_092082_2022-07-07_final.stac-item
2022-07-09 10:56:37	ga_ls9c_ard_3-2-1_106078_2022-07-09_final.stac-item
2022-08-08 09:35:11	ga_ls9c_ard_3-2-1_092090_2022-08-08_final.stac-item
2022-08-11 11:41:48	ga_ls9c_ard_3-2-1_113082_2022-08-11_final.stac-item
2022-08-22 11:21:20	ga_ls9c_ard_3-2-1_110077_2022-08-22_final.stac-item
2022-08-24 11:05:47	ga_ls9c_ard_3-2-1_108069_2022-08-24_final.stac-item
2022-08-26 10:57:01	ga_ls9c_ard_3-2-1_106078_2022-08-26_final.stac-item
2022-09-04 09:13:09	ga_ls9c_ard_3-2-1_089081_2022-09-03_final.stac-item
2022-09-16 11:16:49	ga_ls9c_ard_3-2-1_109081_2022-09-16_final.stac-item
2022-09-25 09:32:36	ga_ls9c_ard_3-2-1_092083_2022-09-25_final.stac-item
2022-10-02 09:40:47	ga_ls9c_ard_3-2-1_093088_2022-10-02_final.stac-item
2022-10-06 09:10:28	ga_ls9c_ard_3-2-1_089074_2022-10-05_final.stac-item
2022-10-12 11:51:13	ga_ls9c_ard_3-2-1_115074_2022-10-12_final.stac-item
2022-10-18 11:16:58	ga_ls9c_ard_3-2-1_109081_2022-10-18_final.stac-item
2022-11-03 11:15:19	ga_ls9c_ard_3-2-1_109077_2022-11-03_final.stac-item
2022-11-12 11:10:00	ga_ls9c_ard_3-2-1_108079_2022-11-12_final.stac-item
2022-11-14 09:19:58	ga_ls9c_ard_3-2-1_090082_2022-11-13_final.stac-item
2022-11-17 11:28:57	ga_ls9c_ard_3-2-1_111080_2022-11-17_final.stac-item
2022-11-21 09:26:08	ga_ls9c_ard_3-2-1_091082_2022-11-20_final.stac-item
2022-11-24 11:35:55	ga_ls9c_ard_3-2-1_112082_2022-11-24_final.stac-item
2022-11-29 10:15:08	ga_ls9c_ard_3-2-1_099081_2022-11-29_final.stac-item
2022-12-03 09:50:24	ga_ls9c_ard_3-2-1_095081_2022-12-03_final.stac-item
2022-12-05 11:16:33	ga_ls9c_ard_3-2-1_109080_2022-12-05_final.stac-item
2022-12-12 11:23:57	ga_ls9c_ard_3-2-1_110083_2022-12-12_final.stac-item
2022-12-17 10:00:00	ga_ls9c_ard_3-2-1_097074_2022-12-17_final.stac-item
2022-12-19 09:50:01	ga_ls9c_ard_3-2-1_095080_2022-12-19_final.stac-item
2022-12-23 09:26:28	ga_ls9c_ard_3-2-1_091083_2022-12-22_final.stac-item
2022-12-26 09:56:35	ga_ls9c_ard_3-2-1_096081_2022-12-26_final.stac-item
2022-12-27 10:39:27	ga_ls9c_ard_3-2-1_103080_2022-12-27_final.stac-item
2022-12-28 09:44:14	ga_ls9c_ard_3-2-1_094081_2022-12-28_final.stac-item
2023-01-07 10:21:45	ga_ls9c_ard_3-2-1_100082_2023-01-07_final.stac-item
2023-01-14 10:27:29	ga_ls9c_ard_3-2-1_101081_2023-01-14_final.stac-item
2023-01-24 11:04:31	ga_ls9c_ard_3-2-1_107081_2023-01-24_final.stac-item
2023-03-06 09:19:42	ga_ls9c_ard_3-2-1_090082_2023-03-05_final.stac-item
2023-03-08 10:41:48	ga_ls9c_ard_3-2-1_104071_2023-03-08_final.stac-item
2023-03-23 09:59:39	ga_ls9c_ard_3-2-1_097074_2023-03-23_final.stac-item
2023-04-01 09:53:20	ga_ls9c_ard_3-2-1_096074_2023-04-01_final.stac-item
2023-04-12 09:36:19	ga_ls9c_ard_3-2-1_093078_2023-04-12_final.stac-item
2023-04-14 11:04:24	ga_ls9c_ard_3-2-1_107082_2023-04-14_final.stac-item
2023-05-01 10:08:15	ga_ls9c_ard_3-2-1_098081_2023-05-01_final.stac-item
2023-05-02 10:52:18	ga_ls9c_ard_3-2-1_105083_2023-05-02_final.stac-item
2023-05-03 09:56:39	ga_ls9c_ard_3-2-1_096083_2023-05-03_final.stac-item
2023-05-03 11:31:33	ga_ls9c_ard_3-2-1_112073_2023-05-03_final.stac-item
2023-05-12 09:51:14	ga_ls9c_ard_3-2-1_095085_2023-05-12_final.stac-item
2023-05-21 09:45:45	ga_ls9c_ard_3-2-1_094087_2023-05-21_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-06-24 09:31:58	ga_ls9c_ard_3-2-1_092084_2023-06-24_final.stac-item
2023-06-24 11:10:03	ga_ls9c_ard_3-2-1_108082_2023-06-24_final.stac-item
2023-07-11 11:52:23	ga_ls9c_ard_3-2-1_115079_2023-07-11_final.stac-item
2023-07-12 09:19:29	ga_ls9c_ard_3-2-1_090083_2023-07-11_final.stac-item
2023-09-06 11:45:01	ga_ls9c_ard_3-2-1_114075_2023-09-06_final.stac-item
2023-09-14 09:20:22	ga_ls9c_ard_3-2-1_090084_2023-09-13_final.stac-item
2023-09-20 10:20:34	ga_ls9c_ard_3-2-1_100080_2023-09-20_final.stac-item
2023-09-21 11:03:02	ga_ls9c_ard_3-2-1_107078_2023-09-21_final.stac-item
2023-09-22 10:06:12	ga_ls9c_ard_3-2-1_098075_2023-09-22_final.stac-item
2023-09-23 10:51:27	ga_ls9c_ard_3-2-1_105080_2023-09-23_final.stac-item
2023-09-25 10:37:52	ga_ls9c_ard_3-2-1_103077_2023-09-25_final.stac-item
2023-09-28 11:08:20	ga_ls9c_ard_3-2-1_108076_2023-09-28_final.stac-item
2023-09-30 09:20:19	ga_ls9c_ard_3-2-1_090084_2023-09-29_final.stac-item
2023-10-02 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-10-01_final.stac-item
2023-10-04 10:32:57	ga_ls9c_ard_3-2-1_102080_2023-10-04_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