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
2021-11-13 09:58:43	ga_ls9c_ard_3-2-1_097072_2021-11-13_final.stac-item
2021-11-16 10:21:31	ga_ls9c_ard_3-2-1_100076_2021-11-16_final.stac-item
2021-12-04 09:25:41	ga_ls9c_ard_3-2-1_091081_2021-12-03_final.stac-item
2021-12-11 09:30:36	ga_ls9c_ard_3-2-1_092078_2021-12-11_final.stac-item
2021-12-18 09:35:55	ga_ls9c_ard_3-2-1_093076_2021-12-18_final.stac-item
2021-12-22 09:14:24	ga_ls9c_ard_3-2-1_089084_2021-12-21_final.stac-item
2022-01-06 11:46:53	ga_ls9c_ard_3-2-1_114079_2022-01-06_final.stac-item
2022-01-12 11:07:47	ga_ls9c_ard_3-2-1_108074_2022-01-12_final.stac-item
2022-01-14 09:18:55	ga_ls9c_ard_3-2-1_090080_2022-01-13_final.stac-item
2022-01-17 11:29:55	ga_ls9c_ard_3-2-1_111083_2022-01-17_final.stac-item
2022-01-30 09:22:58	ga_ls9c_ard_3-2-1_090090_2022-01-29_final.stac-item
2022-02-06 09:28:44	ga_ls9c_ard_3-2-1_091089_2022-02-05_final.stac-item
2022-02-07 10:10:23	ga_ls9c_ard_3-2-1_098085_2022-02-07_final.stac-item
2022-02-25 09:51:52	ga_ls9c_ard_3-2-1_096070_2022-02-25_final.stac-item
2022-03-04 11:40:52	ga_ls9c_ard_3-2-1_113080_2022-03-04_final.stac-item
2022-03-24 11:17:41	ga_ls9c_ard_3-2-1_109084_2022-03-24_final.stac-item
2022-04-04 10:55:07	ga_ls9c_ard_3-2-1_106074_2022-04-04_final.stac-item
2022-04-16 11:20:56	ga_ls9c_ard_3-2-1_110077_2022-04-16_final.stac-item
2022-04-18 09:33:15	ga_ls9c_ard_3-2-1_092086_2022-04-18_final.stac-item
2022-04-20 09:18:52	ga_ls9c_ard_3-2-1_090081_2022-04-19_final.stac-item
2022-04-27 11:00:19	ga_ls9c_ard_3-2-1_107072_2022-04-27_final.stac-item
2022-05-28 10:20:48	ga_ls9c_ard_3-2-1_100082_2022-05-28_final.stac-item
2022-05-30 10:07:15	ga_ls9c_ard_3-2-1_098079_2022-05-30_final.stac-item
2022-06-12 11:12:06	ga_ls9c_ard_3-2-1_109071_2022-06-12_final.stac-item
2022-06-14 11:01:22	ga_ls9c_ard_3-2-1_107075_2022-06-14_final.stac-item
2022-06-28 11:12:01	ga_ls9c_ard_3-2-1_109070_2022-06-28_final.stac-item
2022-06-28 11:16:00	ga_ls9c_ard_3-2-1_109080_2022-06-28_final.stac-item
2022-07-08 11:52:39	ga_ls9c_ard_3-2-1_115079_2022-07-08_final.stac-item
2022-07-14 11:12:19	ga_ls9c_ard_3-2-1_109071_2022-07-14_final.stac-item
2022-07-14 11:16:19	ga_ls9c_ard_3-2-1_109081_2022-07-14_final.stac-item
2022-07-16 11:01:59	ga_ls9c_ard_3-2-1_107076_2022-07-16_final.stac-item
2022-07-17 10:07:58	ga_ls9c_ard_3-2-1_098080_2022-07-17_final.stac-item
2022-07-23 11:06:17	ga_ls9c_ard_3-2-1_108071_2022-07-23_final.stac-item
2022-07-31 10:21:21	ga_ls9c_ard_3-2-1_100082_2022-07-31_final.stac-item
2022-08-25 10:12:09	ga_ls9c_ard_3-2-1_099074_2022-08-25_final.stac-item
2022-08-28 10:44:39	ga_ls9c_ard_3-2-1_104078_2022-08-28_final.stac-item
2022-09-09 11:11:21	ga_ls9c_ard_3-2-1_108083_2022-09-09_final.stac-item
2022-09-13 10:44:41	ga_ls9c_ard_3-2-1_104078_2022-09-13_final.stac-item
2022-09-16 11:12:50	ga_ls9c_ard_3-2-1_109071_2022-09-16_final.stac-item
2022-09-20 10:48:08	ga_ls9c_ard_3-2-1_105071_2022-09-20_final.stac-item
2022-10-04 11:02:55	ga_ls9c_ard_3-2-1_107077_2022-10-04_final.stac-item
2022-10-10 10:24:16	ga_ls9c_ard_3-2-1_101073_2022-10-10_final.stac-item
2022-10-12 10:12:20	ga_ls9c_ard_3-2-1_099074_2022-10-12_final.stac-item
2022-10-23 09:53:02	ga_ls9c_ard_3-2-1_096072_2022-10-23_final.stac-item
2022-10-23 11:35:07	ga_ls9c_ard_3-2-1_112080_2022-10-23_final.stac-item
2022-11-03 11:16:55	ga_ls9c_ard_3-2-1_109081_2022-11-03_final.stac-item
2022-11-13 10:16:47	ga_ls9c_ard_3-2-1_099085_2022-11-13_final.stac-item
2022-11-19 09:38:06	ga_ls9c_ard_3-2-1_093081_2022-11-19_final.stac-item
2022-11-19 11:17:23	ga_ls9c_ard_3-2-1_109082_2022-11-19_final.stac-item
2022-12-08 10:07:23	ga_ls9c_ard_3-2-1_098077_2022-12-08_final.stac-item
2022-12-08 11:46:16	ga_ls9c_ard_3-2-1_114077_2022-12-08_final.stac-item
2022-12-11 10:37:54	ga_ls9c_ard_3-2-1_103076_2022-12-11_final.stac-item
2022-12-12 11:22:21	ga_ls9c_ard_3-2-1_110079_2022-12-12_final.stac-item
2022-12-14 11:08:24	ga_ls9c_ard_3-2-1_108075_2022-12-14_final.stac-item
2022-12-22 11:58:11	ga_ls9c_ard_3-2-1_116076_2022-12-22_final.stac-item
2022-12-24 11:45:49	ga_ls9c_ard_3-2-1_114076_2022-12-24_final.stac-item
2022-12-24 11:46:13	ga_ls9c_ard_3-2-1_114077_2022-12-24_final.stac-item
2022-12-24 11:47:25	ga_ls9c_ard_3-2-1_114080_2022-12-24_final.stac-item
2022-12-30 11:07:11	ga_ls9c_ard_3-2-1_108072_2022-12-30_final.stac-item
2022-12-30 11:11:35	ga_ls9c_ard_3-2-1_108083_2022-12-30_final.stac-item
2022-12-31 10:16:45	ga_ls9c_ard_3-2-1_099085_2022-12-31_final.stac-item
2023-01-05 10:34:07	ga_ls9c_ard_3-2-1_102082_2023-01-05_final.stac-item
2023-01-09 11:46:16	ga_ls9c_ard_3-2-1_114077_2023-01-09_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-20 09:51:29	ga_ls9c_ard_3-2-1_095084_2023-01-20_final.stac-item
2023-01-20 11:30:22	ga_ls9c_ard_3-2-1_111084_2023-01-20_final.stac-item
2023-01-23 11:58:07	ga_ls9c_ard_3-2-1_116076_2023-01-23_final.stac-item
2023-02-02 09:19:58	ga_ls9c_ard_3-2-1_090082_2023-02-01_final.stac-item
2023-02-07 11:13:26	ga_ls9c_ard_3-2-1_109072_2023-02-07_final.stac-item
2023-02-12 11:36:21	ga_ls9c_ard_3-2-1_112083_2023-02-12_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 11:11:35	ga_ls9c_ard_3-2-1_108083_2023-02-16_final.stac-item
2023-02-19 10:02:20	ga_ls9c_ard_3-2-1_097080_2023-02-19_final.stac-item
2023-02-21 11:29:37	ga_ls9c_ard_3-2-1_111082_2023-02-21_final.stac-item
2023-03-13 11:01:55	ga_ls9c_ard_3-2-1_107075_2023-03-13_final.stac-item
2023-03-14 11:47:10	ga_ls9c_ard_3-2-1_114080_2023-03-14_final.stac-item
2023-04-02 10:38:36	ga_ls9c_ard_3-2-1_103079_2023-04-02_final.stac-item
2023-04-04 10:27:50	ga_ls9c_ard_3-2-1_101083_2023-04-04_final.stac-item
2023-04-06 10:15:51	ga_ls9c_ard_3-2-1_099084_2023-04-06_final.stac-item
2023-05-02 09:13:25	ga_ls9c_ard_3-2-1_089083_2023-05-01_final.stac-item
2023-05-14 09:35:16	ga_ls9c_ard_3-2-1_093076_2023-05-14_final.stac-item
2023-05-31 10:19:58	ga_ls9c_ard_3-2-1_100080_2023-05-31_final.stac-item
2023-06-20 11:33:59	ga_ls9c_ard_3-2-1_112080_2023-06-20_final.stac-item
2023-06-24 11:07:40	ga_ls9c_ard_3-2-1_108076_2023-06-24_final.stac-item
2023-06-24 11:09:39	ga_ls9c_ard_3-2-1_108081_2023-06-24_final.stac-item
2023-06-30 10:31:30	ga_ls9c_ard_3-2-1_102078_2023-06-30_final.stac-item
2023-07-18 11:58:11	ga_ls9c_ard_3-2-1_116078_2023-07-18_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-07-31 11:27:22	ga_ls9c_ard_3-2-1_111078_2023-07-31_final.stac-item
2023-08-04 11:01:54	ga_ls9c_ard_3-2-1_107076_2023-08-04_final.stac-item
2023-08-06 10:48:21	ga_ls9c_ard_3-2-1_105073_2023-08-06_final.stac-item
2023-08-12 11:52:35	ga_ls9c_ard_3-2-1_115079_2023-08-12_final.stac-item
2023-08-14 11:41:01	ga_ls9c_ard_3-2-1_113081_2023-08-14_final.stac-item
2023-10-24 10:03:11	ga_ls9c_ard_3-2-1_098067_2023-10-24_final.stac-item
2023-10-25 10:50:26	ga_ls9c_ard_3-2-1_105077_2023-10-25_final.stac-item
2023-10-26 09:52:25	ga_ls9c_ard_3-2-1_096071_2023-10-26_final.stac-item
2023-11-02 11:40:58	ga_ls9c_ard_3-2-1_113080_2023-11-02_final.stac-item
2023-11-04 11:29:48	ga_ls9c_ard_3-2-1_111083_2023-11-04_final.stac-item
2023-11-18 11:41:27	ga_ls9c_ard_3-2-1_113081_2023-11-18_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_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