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
2021-10-31 11:11:36	ga_ls9c_ard_3-2-1_109073_2021-10-31_final.stac-item
2021-11-07 10:55:45	ga_ls9c_ard_3-2-1_106074_2021-11-07_final.stac-item
2021-11-16 10:19:31	ga_ls9c_ard_3-2-1_100071_2021-11-16_final.stac-item
2021-12-04 09:27:17	ga_ls9c_ard_3-2-1_091085_2021-12-03_final.stac-item
2021-12-09 11:20:40	ga_ls9c_ard_3-2-1_110075_2021-12-09_final.stac-item
2021-12-25 11:20:12	ga_ls9c_ard_3-2-1_110074_2021-12-25_final.stac-item
2022-01-04 10:19:11	ga_ls9c_ard_3-2-1_100076_2022-01-04_final.stac-item
2022-01-19 09:35:06	ga_ls9c_ard_3-2-1_093074_2022-01-19_final.stac-item
2022-02-03 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-02-03_final.stac-item
2022-02-14 11:52:37	ga_ls9c_ard_3-2-1_115078_2022-02-14_final.stac-item
2022-02-24 09:15:00	ga_ls9c_ard_3-2-1_089086_2022-02-23_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-06 11:24:55	ga_ls9c_ard_3-2-1_111071_2022-03-06_final.stac-item
2022-03-27 10:10:04	ga_ls9c_ard_3-2-1_098085_2022-03-27_final.stac-item
2022-04-02 09:34:12	ga_ls9c_ard_3-2-1_092088_2022-04-02_final.stac-item
2022-04-19 11:51:24	ga_ls9c_ard_3-2-1_115076_2022-04-19_final.stac-item
2022-04-20 09:17:40	ga_ls9c_ard_3-2-1_090078_2022-04-19_final.stac-item
2022-05-04 11:05:40	ga_ls9c_ard_3-2-1_108070_2022-05-04_final.stac-item
2022-05-10 10:28:08	ga_ls9c_ard_3-2-1_102069_2022-05-10_final.stac-item
2022-05-13 11:04:59	ga_ls9c_ard_3-2-1_107084_2022-05-13_final.stac-item
2022-05-30 10:07:39	ga_ls9c_ard_3-2-1_098080_2022-05-30_final.stac-item
2022-06-03 09:42:09	ga_ls9c_ard_3-2-1_094078_2022-06-03_final.stac-item
2022-06-07 09:21:26	ga_ls9c_ard_3-2-1_090088_2022-06-06_final.stac-item
2022-06-07 10:57:55	ga_ls9c_ard_3-2-1_106082_2022-06-07_final.stac-item
2022-06-21 11:05:43	ga_ls9c_ard_3-2-1_108070_2022-06-21_final.stac-item
2022-06-29 10:17:11	ga_ls9c_ard_3-2-1_100072_2022-06-29_final.stac-item
2022-07-21 09:45:43	ga_ls9c_ard_3-2-1_094086_2022-07-21_final.stac-item
2022-07-24 10:09:29	ga_ls9c_ard_3-2-1_099068_2022-07-24_final.stac-item
2022-07-30 09:40:28	ga_ls9c_ard_3-2-1_093088_2022-07-30_final.stac-item
2022-08-24 11:06:11	ga_ls9c_ard_3-2-1_108070_2022-08-24_final.stac-item
2022-09-11 09:21:20	ga_ls9c_ard_3-2-1_090086_2022-09-10_final.stac-item
2022-10-16 09:50:50	ga_ls9c_ard_3-2-1_095082_2022-10-16_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-29 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-10-28_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-11-22 10:05:24	ga_ls9c_ard_3-2-1_098072_2022-11-22_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-11-28 09:33:29	ga_ls9c_ard_3-2-1_092085_2022-11-28_final.stac-item
2022-11-28 11:06:47	ga_ls9c_ard_3-2-1_108071_2022-11-28_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-06 10:22:08	ga_ls9c_ard_3-2-1_100083_2022-12-06_final.stac-item
2022-12-07 09:24:07	ga_ls9c_ard_3-2-1_091077_2022-12-06_final.stac-item
2022-12-07 11:02:36	ga_ls9c_ard_3-2-1_107076_2022-12-07_final.stac-item
2022-12-10 11:35:54	ga_ls9c_ard_3-2-1_112082_2022-12-10_final.stac-item
2022-12-12 11:20:21	ga_ls9c_ard_3-2-1_110074_2022-12-12_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-14 09:34:42	ga_ls9c_ard_3-2-1_092088_2022-12-14_final.stac-item
2022-12-14 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-14_final.stac-item
2022-12-16 09:17:33	ga_ls9c_ard_3-2-1_090076_2022-12-15_final.stac-item
2022-12-21 09:39:39	ga_ls9c_ard_3-2-1_093085_2022-12-21_final.stac-item
2022-12-31 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-31_final.stac-item
2023-01-01 09:18:21	ga_ls9c_ard_3-2-1_090078_2022-12-31_final.stac-item
2023-01-01 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-31_final.stac-item
2023-01-03 10:44:05	ga_ls9c_ard_3-2-1_104076_2023-01-03_final.stac-item
2023-01-11 11:33:06	ga_ls9c_ard_3-2-1_112075_2023-01-11_final.stac-item
2023-01-25 10:09:42	ga_ls9c_ard_3-2-1_098083_2023-01-25_final.stac-item
2023-01-27 11:35:52	ga_ls9c_ard_3-2-1_112082_2023-01-27_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-03 11:42:31	ga_ls9c_ard_3-2-1_113083_2023-02-03_final.stac-item
2023-02-05 11:25:47	ga_ls9c_ard_3-2-1_111072_2023-02-05_final.stac-item
2023-02-06 10:30:34	ga_ls9c_ard_3-2-1_102073_2023-02-06_final.stac-item
2023-02-09 09:27:23	ga_ls9c_ard_3-2-1_091085_2023-02-08_final.stac-item
2023-02-09 11:00:17	ga_ls9c_ard_3-2-1_107070_2023-02-09_final.stac-item
2023-02-27 10:49:16	ga_ls9c_ard_3-2-1_105074_2023-02-27_final.stac-item
2023-03-01 10:34:55	ga_ls9c_ard_3-2-1_103069_2023-03-01_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-03-11 11:14:40	ga_ls9c_ard_3-2-1_109076_2023-03-11_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-24 09:58:36	ga_ls9c_ard_3-2-1_097072_2023-04-24_final.stac-item
2023-04-26 11:25:05	ga_ls9c_ard_3-2-1_111072_2023-04-26_final.stac-item
2023-04-26 11:25:53	ga_ls9c_ard_3-2-1_111074_2023-04-26_final.stac-item
2023-05-01 10:02:40	ga_ls9c_ard_3-2-1_098067_2023-05-01_final.stac-item
2023-05-07 11:05:36	ga_ls9c_ard_3-2-1_108070_2023-05-07_final.stac-item
2023-05-13 10:28:06	ga_ls9c_ard_3-2-1_102069_2023-05-13_final.stac-item
2023-05-31 10:16:23	ga_ls9c_ard_3-2-1_100071_2023-05-31_final.stac-item
2023-05-31 10:16:47	ga_ls9c_ard_3-2-1_100072_2023-05-31_final.stac-item
2023-05-31 10:21:10	ga_ls9c_ard_3-2-1_100083_2023-05-31_final.stac-item
2023-06-01 09:21:09	ga_ls9c_ard_3-2-1_091072_2023-05-31_final.stac-item
2023-06-02 10:04:01	ga_ls9c_ard_3-2-1_098071_2023-06-02_final.stac-item
2023-06-19 09:12:38	ga_ls9c_ard_3-2-1_089082_2023-06-18_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-06-21 10:38:46	ga_ls9c_ard_3-2-1_103081_2023-06-21_final.stac-item
2023-06-27 11:37:48	ga_ls9c_ard_3-2-1_113074_2023-06-27_final.stac-item
2023-06-30 10:28:19	ga_ls9c_ard_3-2-1_102070_2023-06-30_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-20 10:03:45	ga_ls9c_ard_3-2-1_098070_2023-07-20_final.stac-item
2023-10-16 09:20:56	ga_ls9c_ard_3-2-1_090085_2023-10-15_final.stac-item
2023-10-21 09:35:29	ga_ls9c_ard_3-2-1_093075_2023-10-21_final.stac-item
2023-10-23 09:27:31	ga_ls9c_ard_3-2-1_091086_2023-10-22_final.stac-item
2023-10-26 11:31:42	ga_ls9c_ard_3-2-1_112072_2023-10-26_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-20 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-11-20_final.stac-item
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_final.stac-item
2023-11-22 09:38:42	ga_ls9c_ard_3-2-1_093083_2023-11-22_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_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