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
2021-11-10 11:18:09	ga_ls9c_ard_3-2-1_110077_2021-11-10_final.stac-item
2021-11-20 11:21:05	ga_ls9c_ard_3-2-1_110072_2021-11-20_final.stac-item
2021-11-22 09:30:50	ga_ls9c_ard_3-2-1_091090_2021-11-22_final.stac-item
2021-11-25 09:46:52	ga_ls9c_ard_3-2-1_095077_2021-11-25_final.stac-item
2021-12-05 10:09:20	ga_ls9c_ard_3-2-1_098082_2021-12-05_final.stac-item
2021-12-09 11:20:40	ga_ls9c_ard_3-2-1_110075_2021-12-09_final.stac-item
2021-12-09 11:21:28	ga_ls9c_ard_3-2-1_110077_2021-12-09_final.stac-item
2021-12-11 09:29:48	ga_ls9c_ard_3-2-1_092076_2021-12-10_final.stac-item
2021-12-18 09:35:07	ga_ls9c_ard_3-2-1_093074_2021-12-18_final.stac-item
2022-01-01 09:51:05	ga_ls9c_ard_3-2-1_095083_2022-01-01_final.stac-item
2022-01-17 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-01-17_final.stac-item
2022-01-22 10:03:13	ga_ls9c_ard_3-2-1_098067_2022-01-22_final.stac-item
2022-01-24 09:52:51	ga_ls9c_ard_3-2-1_096072_2022-01-24_final.stac-item
2022-01-24 11:31:44	ga_ls9c_ard_3-2-1_112072_2022-01-24_final.stac-item
2022-02-02 09:47:28	ga_ls9c_ard_3-2-1_095074_2022-02-02_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-03-02 11:51:13	ga_ls9c_ard_3-2-1_115075_2022-03-02_final.stac-item
2022-03-08 11:14:33	ga_ls9c_ard_3-2-1_109076_2022-03-08_final.stac-item
2022-03-12 10:48:14	ga_ls9c_ard_3-2-1_105072_2022-03-12_final.stac-item
2022-03-25 10:22:03	ga_ls9c_ard_3-2-1_100084_2022-03-25_final.stac-item
2022-03-26 11:05:18	ga_ls9c_ard_3-2-1_107084_2022-03-26_final.stac-item
2022-03-28 10:50:08	ga_ls9c_ard_3-2-1_105077_2022-03-28_final.stac-item
2022-05-02 11:20:50	ga_ls9c_ard_3-2-1_110077_2022-05-02_final.stac-item
2022-05-04 11:10:03	ga_ls9c_ard_3-2-1_108081_2022-05-04_final.stac-item
2022-06-14 10:59:46	ga_ls9c_ard_3-2-1_107071_2022-06-14_final.stac-item
2022-06-16 10:50:14	ga_ls9c_ard_3-2-1_105078_2022-06-16_final.stac-item
2022-06-26 11:25:10	ga_ls9c_ard_3-2-1_111072_2022-06-26_final.stac-item
2022-07-16 09:24:17	ga_ls9c_ard_3-2-1_091079_2022-07-15_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-07-26 10:03:56	ga_ls9c_ard_3-2-1_097085_2022-07-26_final.stac-item
2022-07-28 11:27:18	ga_ls9c_ard_3-2-1_111077_2022-07-28_final.stac-item
2022-08-08 09:28:00	ga_ls9c_ard_3-2-1_092072_2022-08-07_final.stac-item
2022-08-09 11:52:57	ga_ls9c_ard_3-2-1_115079_2022-08-09_final.stac-item
2022-08-26 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-08-26_final.stac-item
2022-09-03 10:07:58	ga_ls9c_ard_3-2-1_098079_2022-09-03_final.stac-item
2022-09-07 11:23:43	ga_ls9c_ard_3-2-1_110083_2022-09-07_final.stac-item
2022-09-11 09:16:57	ga_ls9c_ard_3-2-1_090075_2022-09-10_final.stac-item
2022-09-14 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-09-14_final.stac-item
2022-09-14 11:29:33	ga_ls9c_ard_3-2-1_111082_2022-09-14_final.stac-item
2022-09-27 09:17:03	ga_ls9c_ard_3-2-1_090075_2022-09-26_final.stac-item
2022-10-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2022-10-08_final.stac-item
2022-10-09 09:45:23	ga_ls9c_ard_3-2-1_094084_2022-10-09_final.stac-item
2022-10-18 11:14:10	ga_ls9c_ard_3-2-1_109074_2022-10-18_final.stac-item
2022-10-19 10:22:09	ga_ls9c_ard_3-2-1_100083_2022-10-19_final.stac-item
2022-11-20 10:21:46	ga_ls9c_ard_3-2-1_100082_2022-11-20_final.stac-item
2022-11-21 09:26:32	ga_ls9c_ard_3-2-1_091083_2022-11-20_final.stac-item
2022-11-23 09:12:11	ga_ls9c_ard_3-2-1_089078_2022-11-22_final.stac-item
2022-12-06 10:22:08	ga_ls9c_ard_3-2-1_100083_2022-12-06_final.stac-item
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-14 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-14_final.stac-item
2022-12-16 09:20:20	ga_ls9c_ard_3-2-1_090083_2022-12-15_final.stac-item
2022-12-19 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-12-19_final.stac-item
2023-01-25 10:08:30	ga_ls9c_ard_3-2-1_098080_2023-01-25_final.stac-item
2023-01-31 09:28:19	ga_ls9c_ard_3-2-1_092072_2023-01-30_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-11 09:15:25	ga_ls9c_ard_3-2-1_089086_2023-02-10_final.stac-item
2023-02-12 11:36:45	ga_ls9c_ard_3-2-1_112084_2023-02-12_final.stac-item
2023-02-14 11:19:59	ga_ls9c_ard_3-2-1_110073_2023-02-14_final.stac-item
2023-02-19 10:01:57	ga_ls9c_ard_3-2-1_097079_2023-02-19_final.stac-item
2023-02-19 11:38:50	ga_ls9c_ard_3-2-1_113074_2023-02-19_final.stac-item
2023-02-22 10:31:58	ga_ls9c_ard_3-2-1_102077_2023-02-22_final.stac-item
2023-03-08 09:07:18	ga_ls9c_ard_3-2-1_088082_2023-03-07_final.stac-item
2023-03-19 10:28:00	ga_ls9c_ard_3-2-1_101083_2023-03-19_final.stac-item
2023-03-20 11:07:16	ga_ls9c_ard_3-2-1_108073_2023-03-20_final.stac-item
2023-03-21 11:52:55	ga_ls9c_ard_3-2-1_115079_2023-03-21_final.stac-item
2023-03-24 10:40:54	ga_ls9c_ard_3-2-1_104069_2023-03-24_final.stac-item
2023-04-26 09:50:12	ga_ls9c_ard_3-2-1_095082_2023-04-26_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-05-21 09:40:33	ga_ls9c_ard_3-2-1_094074_2023-05-21_final.stac-item
2023-05-23 11:11:02	ga_ls9c_ard_3-2-1_108084_2023-05-23_final.stac-item
2023-06-01 10:59:38	ga_ls9c_ard_3-2-1_107071_2023-06-01_final.stac-item
2023-06-03 09:11:59	ga_ls9c_ard_3-2-1_089080_2023-06-02_final.stac-item
2023-06-06 11:21:44	ga_ls9c_ard_3-2-1_110080_2023-06-06_final.stac-item
2023-06-08 11:06:34	ga_ls9c_ard_3-2-1_108073_2023-06-08_final.stac-item
2023-06-24 11:06:04	ga_ls9c_ard_3-2-1_108072_2023-06-24_final.stac-item
2023-06-28 10:40:13	ga_ls9c_ard_3-2-1_104069_2023-06-28_final.stac-item
2023-07-08 09:43:46	ga_ls9c_ard_3-2-1_094082_2023-07-08_final.stac-item
2023-07-13 09:57:34	ga_ls9c_ard_3-2-1_097070_2023-07-13_final.stac-item
2023-07-29 10:03:36	ga_ls9c_ard_3-2-1_097085_2023-07-29_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-05 10:02:42	ga_ls9c_ard_3-2-1_098067_2023-08-05_final.stac-item
2023-08-13 09:22:04	ga_ls9c_ard_3-2-1_090089_2023-08-12_final.stac-item
2023-08-20 11:01:10	ga_ls9c_ard_3-2-1_107074_2023-08-20_final.stac-item
2023-08-21 10:03:58	ga_ls9c_ard_3-2-1_098070_2023-08-21_final.stac-item
2023-09-10 11:23:57	ga_ls9c_ard_3-2-1_110084_2023-09-10_final.stac-item
2023-09-12 09:33:31	ga_ls9c_ard_3-2-1_092086_2023-09-12_final.stac-item
2023-10-10 11:35:37	ga_ls9c_ard_3-2-1_112082_2023-10-10_final.stac-item
2023-10-31 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-10-31_final.stac-item
2023-11-01 10:54:08	ga_ls9c_ard_3-2-1_106071_2023-11-01_final.stac-item
2023-11-04 09:46:56	ga_ls9c_ard_3-2-1_095073_2023-11-04_final.stac-item
2023-11-12 10:34:26	ga_ls9c_ard_3-2-1_103068_2023-11-12_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-11-17 09:17:17	ga_ls9c_ard_3-2-1_090076_2023-11-16_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_final.stac-item
2023-12-01 11:06:39	ga_ls9c_ard_3-2-1_108071_2023-12-01_final.stac-item
2023-12-02 10:15:49	ga_ls9c_ard_3-2-1_099083_2023-12-02_final.stac-item
2023-12-20 11:42:23	ga_ls9c_ard_3-2-1_113083_2023-12-20_final.stac-item
2023-12-26 11:00:07	ga_ls9c_ard_3-2-1_107070_2023-12-26_final.stac-item
2023-12-28 10:50:08	ga_ls9c_ard_3-2-1_105076_2023-12-28_final.stac-item
2023-12-30 10:35:22	ga_ls9c_ard_3-2-1_103070_2023-12-30_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