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 11:10:48	ga_ls9c_ard_3-2-1_109071_2021-10-31_final.stac-item
2021-11-03 09:57:21	ga_ls9c_ard_3-2-1_096081_2021-11-03_final.stac-item
2021-11-07 09:17:29	ga_ls9c_ard_3-2-1_090075_2021-11-06_final.stac-item
2021-11-08 11:38:06	ga_ls9c_ard_3-2-1_113080_2021-11-08_final.stac-item
2021-11-10 11:17:21	ga_ls9c_ard_3-2-1_110075_2021-11-10_final.stac-item
2021-11-14 10:41:27	ga_ls9c_ard_3-2-1_103079_2021-11-14_final.stac-item
2021-11-17 09:22:52	ga_ls9c_ard_3-2-1_091076_2021-11-16_final.stac-item
2021-12-07 09:56:33	ga_ls9c_ard_3-2-1_096081_2021-12-07_final.stac-item
2021-12-09 11:20:40	ga_ls9c_ard_3-2-1_110075_2021-12-09_final.stac-item
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-11 09:34:59	ga_ls9c_ard_3-2-1_092089_2021-12-11_final.stac-item
2021-12-16 09:47:29	ga_ls9c_ard_3-2-1_095074_2021-12-16_final.stac-item
2021-12-22 10:47:18	ga_ls9c_ard_3-2-1_105069_2021-12-22_final.stac-item
2021-12-24 10:38:56	ga_ls9c_ard_3-2-1_103079_2021-12-24_final.stac-item
2021-12-25 11:20:36	ga_ls9c_ard_3-2-1_110075_2021-12-25_final.stac-item
2021-12-26 10:23:47	ga_ls9c_ard_3-2-1_101072_2021-12-26_final.stac-item
2021-12-27 09:35:20	ga_ls9c_ard_3-2-1_092090_2021-12-27_final.stac-item
2021-12-27 11:07:02	ga_ls9c_ard_3-2-1_108072_2021-12-27_final.stac-item
2022-06-26 09:47:05	ga_ls9c_ard_3-2-1_095074_2022-06-26_final.stac-item
2022-06-28 09:37:07	ga_ls9c_ard_3-2-1_093080_2022-06-28_final.stac-item
2022-06-28 11:12:25	ga_ls9c_ard_3-2-1_109071_2022-06-28_final.stac-item
2022-07-02 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-07-02_final.stac-item
2022-07-08 10:14:57	ga_ls9c_ard_3-2-1_099082_2022-07-08_final.stac-item
2022-07-09 09:16:32	ga_ls9c_ard_3-2-1_090075_2022-07-08_final.stac-item
2022-07-11 10:42:15	ga_ls9c_ard_3-2-1_104073_2022-07-11_final.stac-item
2022-07-13 10:28:16	ga_ls9c_ard_3-2-1_102069_2022-07-13_final.stac-item
2022-07-19 09:54:03	ga_ls9c_ard_3-2-1_096076_2022-07-19_final.stac-item
2022-07-21 11:23:00	ga_ls9c_ard_3-2-1_110082_2022-07-21_final.stac-item
2022-07-25 09:16:40	ga_ls9c_ard_3-2-1_090075_2022-07-24_final.stac-item
2022-07-30 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-07-30_final.stac-item
2022-08-02 10:08:37	ga_ls9c_ard_3-2-1_098081_2022-08-02_final.stac-item
2022-08-03 09:15:00	ga_ls9c_ard_3-2-1_089086_2022-08-02_final.stac-item
2022-08-03 10:47:30	ga_ls9c_ard_3-2-1_105070_2022-08-03_final.stac-item
2022-08-06 11:23:13	ga_ls9c_ard_3-2-1_110082_2022-08-06_final.stac-item
2022-08-09 10:15:16	ga_ls9c_ard_3-2-1_099082_2022-08-09_final.stac-item
2022-08-10 09:16:51	ga_ls9c_ard_3-2-1_090075_2022-08-09_final.stac-item
2022-08-11 11:39:49	ga_ls9c_ard_3-2-1_113077_2022-08-11_final.stac-item
2022-08-13 11:29:04	ga_ls9c_ard_3-2-1_111081_2022-08-13_final.stac-item
2022-08-18 10:08:45	ga_ls9c_ard_3-2-1_098081_2022-08-18_final.stac-item
2022-08-19 10:47:37	ga_ls9c_ard_3-2-1_105070_2022-08-19_final.stac-item
2022-08-24 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-08-23_final.stac-item
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final.stac-item
2022-09-01 10:21:08	ga_ls9c_ard_3-2-1_100081_2022-09-01_final.stac-item
2022-09-02 09:23:07	ga_ls9c_ard_3-2-1_091075_2022-09-01_final.stac-item
2022-09-02 09:28:18	ga_ls9c_ard_3-2-1_091088_2022-09-01_final.stac-item
2022-09-03 10:08:46	ga_ls9c_ard_3-2-1_098081_2022-09-03_final.stac-item
2022-09-03 10:09:10	ga_ls9c_ard_3-2-1_098082_2022-09-03_final.stac-item
2022-09-05 09:52:25	ga_ls9c_ard_3-2-1_096071_2022-09-05_final.stac-item
2022-09-05 11:32:30	ga_ls9c_ard_3-2-1_112074_2022-09-05_final.stac-item
2022-09-06 10:38:52	ga_ls9c_ard_3-2-1_103079_2022-09-06_final.stac-item
2022-09-07 09:43:14	ga_ls9c_ard_3-2-1_094079_2022-09-07_final.stac-item
2022-09-07 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-09-07_final.stac-item
2022-09-07 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-09-07_final.stac-item
2022-09-07 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-09-07_final.stac-item
2022-09-07 11:18:08	ga_ls9c_ard_3-2-1_110069_2022-09-07_final.stac-item
2022-09-07 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-09-07_final.stac-item
2022-09-07 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-09-07_final.stac-item
2022-09-07 11:24:07	ga_ls9c_ard_3-2-1_110084_2022-09-07_final.stac-item
2022-09-08 10:24:06	ga_ls9c_ard_3-2-1_101073_2022-09-08_final.stac-item
2022-09-08 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-09-08_final.stac-item
2022-09-08 10:26:54	ga_ls9c_ard_3-2-1_101080_2022-09-08_final.stac-item
2022-09-08 10:27:18	ga_ls9c_ard_3-2-1_101081_2022-09-08_final.stac-item
2022-09-08 10:28:06	ga_ls9c_ard_3-2-1_101083_2022-09-08_final.stac-item
2022-09-09 09:30:29	ga_ls9c_ard_3-2-1_092078_2022-09-09_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-09-09 09:33:40	ga_ls9c_ard_3-2-1_092086_2022-09-09_final.stac-item
2022-09-09 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-09-09_final.stac-item
2022-09-09 11:10:10	ga_ls9c_ard_3-2-1_108080_2022-09-09_final.stac-item
2022-09-09 11:10:57	ga_ls9c_ard_3-2-1_108082_2022-09-09_final.stac-item
2022-09-09 11:11:21	ga_ls9c_ard_3-2-1_108083_2022-09-09_final.stac-item
2022-09-09 11:11:45	ga_ls9c_ard_3-2-1_108084_2022-09-09_final.stac-item
2022-09-10 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-09-10_final.stac-item
2022-09-10 10:09:46	ga_ls9c_ard_3-2-1_099068_2022-09-10_final.stac-item
2022-09-10 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-09-10_final.stac-item
2022-09-10 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-09-10_final.stac-item
2022-09-10 10:14:57	ga_ls9c_ard_3-2-1_099081_2022-09-10_final.stac-item
2022-09-10 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-09-10_final.stac-item
2022-09-11 09:16:33	ga_ls9c_ard_3-2-1_090074_2022-09-10_final.stac-item
2022-09-11 09:20:32	ga_ls9c_ard_3-2-1_090084_2022-09-10_final.stac-item
2022-09-11 09:20:56	ga_ls9c_ard_3-2-1_090085_2022-09-10_final.stac-item
2022-09-11 09:21:20	ga_ls9c_ard_3-2-1_090086_2022-09-10_final.stac-item
2022-09-11 09:21:44	ga_ls9c_ard_3-2-1_090087_2022-09-10_final.stac-item
2022-09-11 09:22:32	ga_ls9c_ard_3-2-1_090089_2022-09-10_final.stac-item
2022-09-11 09:22:56	ga_ls9c_ard_3-2-1_090090_2022-09-10_final.stac-item
2022-09-11 10:53:50	ga_ls9c_ard_3-2-1_106070_2022-09-11_final.stac-item
2022-09-11 10:57:02	ga_ls9c_ard_3-2-1_106078_2022-09-11_final.stac-item
2022-09-11 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-09-11_final.stac-item
2022-09-11 10:57:49	ga_ls9c_ard_3-2-1_106080_2022-09-11_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-12 09:58:37	ga_ls9c_ard_3-2-1_097071_2022-09-12_final.stac-item
2022-09-12 09:59:25	ga_ls9c_ard_3-2-1_097073_2022-09-12_final.stac-item
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final.stac-item
2022-09-14 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-09-14_final.stac-item
2022-09-15 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-09-15_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-15 10:31:09	ga_ls9c_ard_3-2-1_102075_2022-09-15_final.stac-item
2022-09-18 09:23:12	ga_ls9c_ard_3-2-1_091075_2022-09-17_final.stac-item
2022-09-19 10:08:51	ga_ls9c_ard_3-2-1_098081_2022-09-19_final.stac-item
2022-09-19 11:46:09	ga_ls9c_ard_3-2-1_114077_2022-09-19_final.stac-item
2022-09-21 09:54:31	ga_ls9c_ard_3-2-1_096076_2022-09-21_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