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 11:40:57	ga_ls9c_ard_3-2-1_113081_2021-11-13_final.stac-item
2021-11-22 11:03:32	ga_ls9c_ard_3-2-1_107075_2021-11-22_final.stac-item
2022-01-01 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-01-01_final.stac-item
2022-01-24 11:34:56	ga_ls9c_ard_3-2-1_112080_2022-01-24_final.stac-item
2022-02-08 09:12:46	ga_ls9c_ard_3-2-1_089080_2022-02-07_final.stac-item
2022-02-08 10:50:51	ga_ls9c_ard_3-2-1_105078_2022-02-08_final.stac-item
2022-02-22 09:27:00	ga_ls9c_ard_3-2-1_091085_2022-02-21_final.stac-item
2022-02-27 11:21:09	ga_ls9c_ard_3-2-1_110077_2022-02-27_final.stac-item
2022-03-11 10:10:10	ga_ls9c_ard_3-2-1_098085_2022-03-11_final.stac-item
2022-03-31 11:21:51	ga_ls9c_ard_3-2-1_110079_2022-03-31_final.stac-item
2022-04-01 10:27:01	ga_ls9c_ard_3-2-1_101081_2022-04-01_final.stac-item
2022-04-13 10:51:40	ga_ls9c_ard_3-2-1_105081_2022-04-13_final.stac-item
2022-04-14 09:52:51	ga_ls9c_ard_3-2-1_096073_2022-04-14_final.stac-item
2022-04-21 11:40:12	ga_ls9c_ard_3-2-1_113079_2022-04-21_final.stac-item
2022-05-08 10:44:06	ga_ls9c_ard_3-2-1_104078_2022-05-08_final.stac-item
2022-05-17 10:37:24	ga_ls9c_ard_3-2-1_103077_2022-05-17_final.stac-item
2022-06-10 11:28:01	ga_ls9c_ard_3-2-1_111080_2022-06-10_final.stac-item
2022-06-22 11:50:36	ga_ls9c_ard_3-2-1_115074_2022-06-22_final.stac-item
2022-07-02 10:52:28	ga_ls9c_ard_3-2-1_105083_2022-07-02_final.stac-item
2022-07-07 11:05:24	ga_ls9c_ard_3-2-1_108069_2022-07-07_final.stac-item
2022-07-07 11:11:23	ga_ls9c_ard_3-2-1_108084_2022-07-07_final.stac-item
2022-07-09 09:19:44	ga_ls9c_ard_3-2-1_090083_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
2022-07-24 11:51:34	ga_ls9c_ard_3-2-1_115076_2022-07-24_final.stac-item
2022-07-27 10:40:26	ga_ls9c_ard_3-2-1_104068_2022-07-27_final.stac-item
2022-08-08 11:10:29	ga_ls9c_ard_3-2-1_108081_2022-08-08_final.stac-item
2022-08-09 11:51:45	ga_ls9c_ard_3-2-1_115076_2022-08-09_final.stac-item
2022-08-15 11:11:56	ga_ls9c_ard_3-2-1_109069_2022-08-15_final.stac-item
2022-08-24 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-08-24_final.stac-item
2022-09-06 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-09-06_final.stac-item
2022-09-07 09:42:02	ga_ls9c_ard_3-2-1_094076_2022-09-07_final.stac-item
2022-09-16 11:12:50	ga_ls9c_ard_3-2-1_109071_2022-09-16_final.stac-item
2022-09-22 10:34:59	ga_ls9c_ard_3-2-1_103069_2022-09-22_final.stac-item
2022-10-28 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-10-28_final.stac-item
2022-11-05 09:25:41	ga_ls9c_ard_3-2-1_091081_2022-11-04_final.stac-item
2022-11-05 11:01:23	ga_ls9c_ard_3-2-1_107073_2022-11-05_final.stac-item
2022-11-07 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-11-06_final.stac-item
2022-11-07 10:50:38	ga_ls9c_ard_3-2-1_105077_2022-11-07_final.stac-item
2022-11-18 10:34:08	ga_ls9c_ard_3-2-1_102082_2022-11-18_final.stac-item
2022-11-30 09:20:42	ga_ls9c_ard_3-2-1_090084_2022-11-29_final.stac-item
2022-12-06 11:59:01	ga_ls9c_ard_3-2-1_116078_2022-12-06_final.stac-item
2022-12-09 10:47:51	ga_ls9c_ard_3-2-1_105070_2022-12-09_final.stac-item
2022-12-12 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-12-12_final.stac-item
2022-12-31 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-12-31_final.stac-item
2023-01-06 09:36:30	ga_ls9c_ard_3-2-1_093077_2023-01-06_final.stac-item
2023-01-11 11:36:17	ga_ls9c_ard_3-2-1_112083_2023-01-11_final.stac-item
2023-01-13 09:45:49	ga_ls9c_ard_3-2-1_094085_2023-01-13_final.stac-item
2023-01-18 09:57:06	ga_ls9c_ard_3-2-1_097067_2023-01-18_final.stac-item
2023-01-26 09:12:54	ga_ls9c_ard_3-2-1_089080_2023-01-25_final.stac-item
2023-01-29 09:43:51	ga_ls9c_ard_3-2-1_094080_2023-01-29_final.stac-item
2023-02-11 10:50:42	ga_ls9c_ard_3-2-1_105077_2023-02-11_final.stac-item
2023-02-16 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-02-16_final.stac-item
2023-03-04 11:05:47	ga_ls9c_ard_3-2-1_108069_2023-03-04_final.stac-item
2023-03-18 11:23:38	ga_ls9c_ard_3-2-1_110083_2023-03-18_final.stac-item
2023-04-05 11:05:30	ga_ls9c_ard_3-2-1_108069_2023-04-05_final.stac-item
2023-04-08 11:42:22	ga_ls9c_ard_3-2-1_113084_2023-04-08_final.stac-item
2023-04-16 10:51:39	ga_ls9c_ard_3-2-1_105081_2023-04-16_final.stac-item
2023-04-17 11:34:31	ga_ls9c_ard_3-2-1_112080_2023-04-17_final.stac-item
2023-04-18 10:34:30	ga_ls9c_ard_3-2-1_103069_2023-04-18_final.stac-item
2023-05-09 10:54:02	ga_ls9c_ard_3-2-1_106072_2023-05-09_final.stac-item
2023-05-10 11:40:29	ga_ls9c_ard_3-2-1_113080_2023-05-10_final.stac-item
2023-05-16 12:37:04	ga_ls9c_ard_3-2-1_123067_2023-05-16_final.stac-item
2023-06-09 11:50:13	ga_ls9c_ard_3-2-1_115074_2023-06-09_final.stac-item
2023-06-11 10:00:33	ga_ls9c_ard_3-2-1_097078_2023-06-11_final.stac-item
2023-06-15 11:12:15	ga_ls9c_ard_3-2-1_109072_2023-06-15_final.stac-item
2023-06-27 09:58:31	ga_ls9c_ard_3-2-1_097073_2023-06-27_final.stac-item
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final.stac-item
2023-08-20 09:25:04	ga_ls9c_ard_3-2-1_091081_2023-08-19_final.stac-item
2023-09-03 09:34:48	ga_ls9c_ard_3-2-1_093074_2023-09-03_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-06 10:09:20	ga_ls9c_ard_3-2-1_098083_2023-09-06_final.stac-item
2023-09-11 10:25:08	ga_ls9c_ard_3-2-1_101076_2023-09-11_final.stac-item
2023-10-22 11:58:50	ga_ls9c_ard_3-2-1_116078_2023-10-22_final.stac-item
2023-10-26 09:52:01	ga_ls9c_ard_3-2-1_096070_2023-10-26_final.stac-item
2023-10-27 10:38:27	ga_ls9c_ard_3-2-1_103078_2023-10-27_final.stac-item
2023-11-06 11:17:05	ga_ls9c_ard_3-2-1_109082_2023-11-06_final.stac-item
2023-11-13 09:45:35	ga_ls9c_ard_3-2-1_094085_2023-11-13_final.stac-item
2023-11-22 09:39:06	ga_ls9c_ard_3-2-1_093084_2023-11-22_final.stac-item
2023-12-10 09:29:07	ga_ls9c_ard_3-2-1_091090_2023-12-09_final.stac-item
2023-12-13 11:36:09	ga_ls9c_ard_3-2-1_112083_2023-12-13_final.stac-item
2023-12-20 11:41:35	ga_ls9c_ard_3-2-1_113081_2023-12-20_final.stac-item
2023-12-21 10:42:46	ga_ls9c_ard_3-2-1_104073_2023-12-21_final.stac-item
2023-12-25 10:18:27	ga_ls9c_ard_3-2-1_100074_2023-12-25_final.stac-item
2023-12-28 10:52:08	ga_ls9c_ard_3-2-1_105081_2023-12-28_final.stac-item
2024-01-10 08:42:40	ga_ls9c_ard_3-2-1_084082_2024-01-09_final.stac-item
2024-02-14 09:13:58	ga_ls9c_ard_3-2-1_089083_2024-02-13_final.stac-item
2024-02-16 10:36:28	ga_ls9c_ard_3-2-1_103073_2024-02-16_final.stac-item
2024-02-19 09:29:38	ga_ls9c_ard_3-2-1_092076_2024-02-18_final.stac-item
2024-02-23 10:45:17	ga_ls9c_ard_3-2-1_104080_2024-02-23_final.stac-item
2024-03-01 10:50:21	ga_ls9c_ard_3-2-1_105077_2024-03-01_final.stac-item
2024-03-21 10:22:50	ga_ls9c_ard_3-2-1_101070_2024-03-21_final.stac-item
2024-03-22 09:31:11	ga_ls9c_ard_3-2-1_092080_2024-03-22_final.stac-item
2024-03-25 11:41:44	ga_ls9c_ard_3-2-1_113082_2024-03-25_final.stac-item
2024-03-29 09:40:02	ga_ls9c_ard_3-2-1_093087_2024-03-29_final.stac-item
2024-04-09 09:19:28	ga_ls9c_ard_3-2-1_090082_2024-04-08_final.stac-item
2024-04-10 10:00:19	ga_ls9c_ard_3-2-1_097076_2024-04-10_final.stac-item
2024-04-13 10:30:23	ga_ls9c_ard_3-2-1_102074_2024-04-13_final.stac-item
2024-04-23 09:30:42	ga_ls9c_ard_3-2-1_092080_2024-04-23_final.stac-item
2024-04-24 11:50:25	ga_ls9c_ard_3-2-1_115074_2024-04-24_final.stac-item
2024-05-02 09:24:28	ga_ls9c_ard_3-2-1_091080_2024-05-01_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