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
2021-11-22 09:29:15	ga_ls9c_ard_3-2-1_091086_2021-11-21_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-13 10:53:54	ga_ls9c_ard_3-2-1_106070_2021-12-13_final.stac-item
2021-12-14 11:39:09	ga_ls9c_ard_3-2-1_113075_2021-12-14_final.stac-item
2021-12-29 09:20:11	ga_ls9c_ard_3-2-1_090083_2021-12-28_final.stac-item
2022-01-06 10:08:24	ga_ls9c_ard_3-2-1_098080_2022-01-06_final.stac-item
2022-02-09 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-02-09_final.stac-item
2022-02-15 09:18:30	ga_ls9c_ard_3-2-1_090079_2022-02-14_final.stac-item
2022-03-07 10:28:30	ga_ls9c_ard_3-2-1_102069_2022-03-07_final.stac-item
2022-03-07 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-03-07_final.stac-item
2022-03-10 09:25:18	ga_ls9c_ard_3-2-1_091081_2022-03-09_final.stac-item
2022-03-31 11:21:03	ga_ls9c_ard_3-2-1_110077_2022-03-31_final.stac-item
2022-04-07 11:29:12	ga_ls9c_ard_3-2-1_111082_2022-04-07_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-04-13 09:11:11	ga_ls9c_ard_3-2-1_089077_2022-04-12_final.stac-item
2022-05-02 09:40:45	ga_ls9c_ard_3-2-1_094074_2022-05-02_final.stac-item
2022-05-18 11:19:03	ga_ls9c_ard_3-2-1_110073_2022-05-18_final.stac-item
2022-05-20 09:27:22	ga_ls9c_ard_3-2-1_092072_2022-05-19_final.stac-item
2022-05-25 09:50:18	ga_ls9c_ard_3-2-1_095083_2022-05-25_final.stac-item
2022-06-12 09:36:49	ga_ls9c_ard_3-2-1_093080_2022-06-12_final.stac-item
2022-06-18 10:34:42	ga_ls9c_ard_3-2-1_103070_2022-06-18_final.stac-item
2022-06-19 11:20:24	ga_ls9c_ard_3-2-1_110076_2022-06-19_final.stac-item
2022-06-19 11:23:35	ga_ls9c_ard_3-2-1_110084_2022-06-19_final.stac-item
2022-07-10 10:02:11	ga_ls9c_ard_3-2-1_097081_2022-07-10_final.stac-item
2022-07-16 11:03:58	ga_ls9c_ard_3-2-1_107081_2022-07-16_final.stac-item
2022-07-18 09:11:10	ga_ls9c_ard_3-2-1_089077_2022-07-17_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-07-29 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-07-29_final.stac-item
2022-08-18 11:46:50	ga_ls9c_ard_3-2-1_114079_2022-08-18_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-20 09:52:24	ga_ls9c_ard_3-2-1_096071_2022-08-20_final.stac-item
2022-08-22 11:20:56	ga_ls9c_ard_3-2-1_110076_2022-08-22_final.stac-item
2022-08-26 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-08-26_final.stac-item
2022-08-28 10:40:40	ga_ls9c_ard_3-2-1_104068_2022-08-28_final.stac-item
2022-09-04 10:49:14	ga_ls9c_ard_3-2-1_105074_2022-09-04_final.stac-item
2022-09-19 10:10:27	ga_ls9c_ard_3-2-1_098085_2022-09-19_final.stac-item
2022-10-09 09:46:35	ga_ls9c_ard_3-2-1_094087_2022-10-09_final.stac-item
2022-10-17 10:31:18	ga_ls9c_ard_3-2-1_102075_2022-10-17_final.stac-item
2022-10-20 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-10-19_final.stac-item
2022-10-21 10:10:35	ga_ls9c_ard_3-2-1_098085_2022-10-21_final.stac-item
2022-10-23 11:35:31	ga_ls9c_ard_3-2-1_112081_2022-10-23_final.stac-item
2022-10-30 10:01:12	ga_ls9c_ard_3-2-1_097077_2022-10-30_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-15 09:58:26	ga_ls9c_ard_3-2-1_097070_2022-11-15_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-11-17 09:50:28	ga_ls9c_ard_3-2-1_095081_2022-11-17_final.stac-item
2022-11-17 11:29:45	ga_ls9c_ard_3-2-1_111082_2022-11-17_final.stac-item
2022-11-25 10:38:41	ga_ls9c_ard_3-2-1_103078_2022-11-25_final.stac-item
2022-12-03 09:50:48	ga_ls9c_ard_3-2-1_095082_2022-12-03_final.stac-item
2022-12-03 09:52:00	ga_ls9c_ard_3-2-1_095085_2022-12-03_final.stac-item
2022-12-09 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-12-09_final.stac-item
2022-12-09 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-12-09_final.stac-item
2022-12-17 11:41:41	ga_ls9c_ard_3-2-1_113081_2022-12-17_final.stac-item
2022-12-18 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-12-18_final.stac-item
2022-12-23 09:29:16	ga_ls9c_ard_3-2-1_091090_2022-12-22_final.stac-item
2023-01-06 09:40:05	ga_ls9c_ard_3-2-1_093086_2023-01-06_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-09 10:09:47	ga_ls9c_ard_3-2-1_098083_2023-01-09_final.stac-item
2023-01-11 11:33:06	ga_ls9c_ard_3-2-1_112075_2023-01-11_final.stac-item
2023-01-17 09:19:51	ga_ls9c_ard_3-2-1_090082_2023-01-16_final.stac-item
2023-01-27 11:36:16	ga_ls9c_ard_3-2-1_112083_2023-01-27_final.stac-item
2023-02-05 11:29:47	ga_ls9c_ard_3-2-1_111082_2023-02-05_final.stac-item
2023-02-16 09:29:54	ga_ls9c_ard_3-2-1_092076_2023-02-15_final.stac-item
2023-02-23 09:37:31	ga_ls9c_ard_3-2-1_093080_2023-02-23_final.stac-item
2023-02-24 10:18:46	ga_ls9c_ard_3-2-1_100075_2023-02-24_final.stac-item
2023-03-02 11:22:57	ga_ls9c_ard_3-2-1_110081_2023-03-02_final.stac-item
2023-03-08 10:41:24	ga_ls9c_ard_3-2-1_104070_2023-03-08_final.stac-item
2023-03-20 09:31:59	ga_ls9c_ard_3-2-1_092082_2023-03-20_final.stac-item
2023-03-23 10:02:27	ga_ls9c_ard_3-2-1_097081_2023-03-23_final.stac-item
2023-04-02 10:34:12	ga_ls9c_ard_3-2-1_103068_2023-04-02_final.stac-item
2023-04-19 09:44:04	ga_ls9c_ard_3-2-1_094082_2023-04-19_final.stac-item
2023-04-21 11:11:23	ga_ls9c_ard_3-2-1_108084_2023-04-21_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-05-02 09:15:48	ga_ls9c_ard_3-2-1_089089_2023-05-01_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-17 11:44:13	ga_ls9c_ard_3-2-1_114074_2023-05-17_final.stac-item
2023-05-25 10:53:27	ga_ls9c_ard_3-2-1_106071_2023-05-25_final.stac-item
2023-05-26 09:57:26	ga_ls9c_ard_3-2-1_097070_2023-05-26_final.stac-item
2023-05-28 09:47:05	ga_ls9c_ard_3-2-1_095075_2023-05-28_final.stac-item
2023-06-02 10:05:13	ga_ls9c_ard_3-2-1_098074_2023-06-02_final.stac-item
2023-06-05 10:35:42	ga_ls9c_ard_3-2-1_103073_2023-06-05_final.stac-item
2023-06-08 11:04:58	ga_ls9c_ard_3-2-1_108069_2023-06-08_final.stac-item
2023-06-17 11:02:17	ga_ls9c_ard_3-2-1_107078_2023-06-17_final.stac-item
2023-06-19 09:11:26	ga_ls9c_ard_3-2-1_089079_2023-06-18_final.stac-item
2023-06-29 11:23:07	ga_ls9c_ard_3-2-1_111068_2023-06-29_final.stac-item
2023-07-07 10:39:23	ga_ls9c_ard_3-2-1_103082_2023-07-07_final.stac-item
2023-07-15 09:47:36	ga_ls9c_ard_3-2-1_095076_2023-07-15_final.stac-item
2023-07-16 10:28:04	ga_ls9c_ard_3-2-1_102069_2023-07-16_final.stac-item
2023-08-16 09:45:46	ga_ls9c_ard_3-2-1_095071_2023-08-16_final.stac-item
2023-08-18 11:13:05	ga_ls9c_ard_3-2-1_109073_2023-08-18_final.stac-item
2023-08-18 11:17:29	ga_ls9c_ard_3-2-1_109084_2023-08-18_final.stac-item
2023-08-20 11:01:34	ga_ls9c_ard_3-2-1_107075_2023-08-20_final.stac-item
2023-08-25 11:23:46	ga_ls9c_ard_3-2-1_110084_2023-08-25_final.stac-item
2023-08-28 10:14:14	ga_ls9c_ard_3-2-1_099080_2023-08-28_final.stac-item
2023-08-31 10:40:46	ga_ls9c_ard_3-2-1_104069_2023-08-31_final.stac-item
2023-09-05 09:26:03	ga_ls9c_ard_3-2-1_091083_2023-09-04_final.stac-item
2023-09-05 11:02:09	ga_ls9c_ard_3-2-1_107076_2023-09-05_final.stac-item
2023-11-17 10:53:23	ga_ls9c_ard_3-2-1_106069_2023-11-17_final.stac-item
2023-11-22 09:40:18	ga_ls9c_ard_3-2-1_093087_2023-11-22_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