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 09:25:16	ga_ls9c_ard_3-2-1_091076_2021-11-21_final.stac-item
2021-12-04 09:29:17	ga_ls9c_ard_3-2-1_091090_2021-12-03_final.stac-item
2021-12-11 11:07:53	ga_ls9c_ard_3-2-1_108074_2021-12-11_final.stac-item
2022-01-03 09:33:55	ga_ls9c_ard_3-2-1_093071_2022-01-03_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-19 11:13:59	ga_ls9c_ard_3-2-1_109074_2022-01-19_final.stac-item
2022-01-20 10:17:34	ga_ls9c_ard_3-2-1_100072_2022-01-20_final.stac-item
2022-01-20 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-01-20_final.stac-item
2022-02-05 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-02-05_final.stac-item
2022-02-06 11:05:13	ga_ls9c_ard_3-2-1_107083_2022-02-06_final.stac-item
2022-02-08 09:13:10	ga_ls9c_ard_3-2-1_089081_2022-02-07_final.stac-item
2022-02-08 09:15:10	ga_ls9c_ard_3-2-1_089086_2022-02-07_final.stac-item
2022-02-22 09:26:12	ga_ls9c_ard_3-2-1_091083_2022-02-21_final.stac-item
2022-03-26 09:23:38	ga_ls9c_ard_3-2-1_091077_2022-03-25_final.stac-item
2022-04-05 09:57:54	ga_ls9c_ard_3-2-1_097070_2022-04-05_final.stac-item
2022-04-24 10:28:13	ga_ls9c_ard_3-2-1_102069_2022-04-24_final.stac-item
2022-05-02 11:19:38	ga_ls9c_ard_3-2-1_110074_2022-05-02_final.stac-item
2022-05-15 09:10:07	ga_ls9c_ard_3-2-1_089075_2022-05-14_final.stac-item
2022-05-19 10:27:00	ga_ls9c_ard_3-2-1_101082_2022-05-19_final.stac-item
2022-05-21 10:09:02	ga_ls9c_ard_3-2-1_099068_2022-05-21_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-05-30 10:02:52	ga_ls9c_ard_3-2-1_098068_2022-05-30_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-06-17 09:57:25	ga_ls9c_ard_3-2-1_096085_2022-06-17_final.stac-item
2022-07-06 10:25:20	ga_ls9c_ard_3-2-1_101077_2022-07-06_final.stac-item
2022-07-28 11:25:42	ga_ls9c_ard_3-2-1_111073_2022-07-28_final.stac-item
2022-08-04 09:57:28	ga_ls9c_ard_3-2-1_096084_2022-08-04_final.stac-item
2022-08-18 10:03:34	ga_ls9c_ard_3-2-1_098068_2022-08-18_final.stac-item
2022-08-19 09:11:56	ga_ls9c_ard_3-2-1_089078_2022-08-18_final.stac-item
2022-08-22 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-08-22_final.stac-item
2022-09-02 09:28:18	ga_ls9c_ard_3-2-1_091088_2022-09-01_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-10 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-09-10_final.stac-item
2022-09-14 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-09-14_final.stac-item
2022-09-15 10:28:21	ga_ls9c_ard_3-2-1_102068_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
2022-09-18 11:05:16	ga_ls9c_ard_3-2-1_107083_2022-09-18_final.stac-item
2022-09-26 10:10:41	ga_ls9c_ard_3-2-1_099070_2022-09-26_final.stac-item
2022-10-06 10:47:21	ga_ls9c_ard_3-2-1_105069_2022-10-06_final.stac-item
2022-10-11 11:10:20	ga_ls9c_ard_3-2-1_108080_2022-10-11_final.stac-item
2022-10-12 10:10:44	ga_ls9c_ard_3-2-1_099070_2022-10-12_final.stac-item
2022-10-15 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-14_final.stac-item
2022-10-23 09:56:38	ga_ls9c_ard_3-2-1_096081_2022-10-23_final.stac-item
2022-10-28 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-10-28_final.stac-item
2022-10-30 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-10-30_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-02 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-11-02_final.stac-item
2022-11-05 09:27:41	ga_ls9c_ard_3-2-1_091086_2022-11-04_final.stac-item
2022-11-05 11:02:34	ga_ls9c_ard_3-2-1_107076_2022-11-05_final.stac-item
2022-11-10 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-11-10_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-11-24 11:36:19	ga_ls9c_ard_3-2-1_112083_2022-11-24_final.stac-item
2022-11-30 10:54:48	ga_ls9c_ard_3-2-1_106072_2022-11-30_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-07 09:27:43	ga_ls9c_ard_3-2-1_091086_2022-12-06_final.stac-item
2022-12-10 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-12-10_final.stac-item
2022-12-17 11:38:05	ga_ls9c_ard_3-2-1_113072_2022-12-17_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2022-12-26 09:52:36	ga_ls9c_ard_3-2-1_096071_2022-12-26_final.stac-item
2023-01-01 09:22:20	ga_ls9c_ard_3-2-1_090088_2022-12-31_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-02 11:38:54	ga_ls9c_ard_3-2-1_113074_2023-01-02_final.stac-item
2023-01-07 10:19:45	ga_ls9c_ard_3-2-1_100077_2023-01-07_final.stac-item
2023-01-08 11:00:37	ga_ls9c_ard_3-2-1_107071_2023-01-08_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-01-29 11:20:44	ga_ls9c_ard_3-2-1_110075_2023-01-29_final.stac-item
2023-01-30 10:23:32	ga_ls9c_ard_3-2-1_101071_2023-01-30_final.stac-item
2023-01-31 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-01-31_final.stac-item
2023-02-02 09:21:58	ga_ls9c_ard_3-2-1_090087_2023-02-01_final.stac-item
2023-02-08 10:18:37	ga_ls9c_ard_3-2-1_100074_2023-02-08_final.stac-item
2023-02-10 10:03:51	ga_ls9c_ard_3-2-1_098068_2023-02-10_final.stac-item
2023-02-25 11:01:38	ga_ls9c_ard_3-2-1_107074_2023-02-25_final.stac-item
2023-03-07 10:00:57	ga_ls9c_ard_3-2-1_097077_2023-03-07_final.stac-item
2023-03-08 09:07:18	ga_ls9c_ard_3-2-1_088082_2023-03-07_final.stac-item
2023-04-07 10:58:43	ga_ls9c_ard_3-2-1_106083_2023-04-07_final.stac-item
2023-04-15 10:03:35	ga_ls9c_ard_3-2-1_098069_2023-04-15_final.stac-item
2023-04-16 09:11:10	ga_ls9c_ard_3-2-1_089077_2023-04-15_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-05-01 11:44:45	ga_ls9c_ard_3-2-1_114075_2023-05-01_final.stac-item
2023-05-03 09:57:27	ga_ls9c_ard_3-2-1_096085_2023-05-03_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-17 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-05-17_final.stac-item
2023-05-21 09:44:57	ga_ls9c_ard_3-2-1_094085_2023-05-21_final.stac-item
2023-05-23 09:27:22	ga_ls9c_ard_3-2-1_092072_2023-05-22_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-24 09:32:46	ga_ls9c_ard_3-2-1_092086_2023-06-24_final.stac-item
2023-06-26 09:19:37	ga_ls9c_ard_3-2-1_090084_2023-06-25_final.stac-item
2023-08-06 09:14:40	ga_ls9c_ard_3-2-1_089086_2023-08-05_final.stac-item
2023-10-15 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-10-15_final.stac-item
2023-10-19 11:29:56	ga_ls9c_ard_3-2-1_111083_2023-10-19_final.stac-item
2023-10-23 09:23:07	ga_ls9c_ard_3-2-1_091075_2023-10-22_final.stac-item
2023-11-17 10:54:58	ga_ls9c_ard_3-2-1_106073_2023-11-17_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-19 09:06:33	ga_ls9c_ard_3-2-1_088080_2023-11-18_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