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
2021-11-06 10:14:59	ga_ls9c_ard_3-2-1_100072_2021-11-06_final.stac-item
2021-11-13 11:38:10	ga_ls9c_ard_3-2-1_113074_2021-11-13_final.stac-item
2021-12-09 11:20:40	ga_ls9c_ard_3-2-1_110075_2021-12-09_final.stac-item
2021-12-13 10:54:42	ga_ls9c_ard_3-2-1_106072_2021-12-13_final.stac-item
2021-12-18 11:12:00	ga_ls9c_ard_3-2-1_109069_2021-12-18_final.stac-item
2022-01-01 11:23:59	ga_ls9c_ard_3-2-1_111068_2022-01-01_final.stac-item
2022-01-02 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-01-02_final.stac-item
2022-01-10 11:19:45	ga_ls9c_ard_3-2-1_110073_2022-01-10_final.stac-item
2022-01-14 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-01-13_final.stac-item
2022-01-28 09:32:56	ga_ls9c_ard_3-2-1_092084_2022-01-28_final.stac-item
2022-02-02 09:52:40	ga_ls9c_ard_3-2-1_095087_2022-02-02_final.stac-item
2022-02-20 09:36:11	ga_ls9c_ard_3-2-1_093077_2022-02-20_final.stac-item
2022-03-06 09:50:25	ga_ls9c_ard_3-2-1_095082_2022-03-06_final.stac-item
2022-03-22 11:26:04	ga_ls9c_ard_3-2-1_111074_2022-03-22_final.stac-item
2022-03-26 11:00:31	ga_ls9c_ard_3-2-1_107072_2022-03-26_final.stac-item
2022-03-27 10:09:16	ga_ls9c_ard_3-2-1_098083_2022-03-27_final.stac-item
2022-03-31 09:39:46	ga_ls9c_ard_3-2-1_094071_2022-03-31_final.stac-item
2022-04-06 10:40:22	ga_ls9c_ard_3-2-1_104068_2022-04-06_final.stac-item
2022-04-12 10:03:38	ga_ls9c_ard_3-2-1_098069_2022-04-12_final.stac-item
2022-04-18 11:10:09	ga_ls9c_ard_3-2-1_108081_2022-04-18_final.stac-item
2022-04-21 10:03:43	ga_ls9c_ard_3-2-1_097085_2022-04-21_final.stac-item
2022-04-29 09:11:28	ga_ls9c_ard_3-2-1_089078_2022-04-28_final.stac-item
2022-05-14 10:02:33	ga_ls9c_ard_3-2-1_098067_2022-05-14_final.stac-item
2022-05-15 09:12:30	ga_ls9c_ard_3-2-1_089081_2022-05-14_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-03 11:19:02	ga_ls9c_ard_3-2-1_110073_2022-06-03_final.stac-item
2022-06-06 10:10:40	ga_ls9c_ard_3-2-1_099072_2022-06-06_final.stac-item
2022-06-15 11:45:03	ga_ls9c_ard_3-2-1_114076_2022-06-15_final.stac-item
2022-06-28 09:36:19	ga_ls9c_ard_3-2-1_093078_2022-06-28_final.stac-item
2022-07-08 11:53:03	ga_ls9c_ard_3-2-1_115080_2022-07-08_final.stac-item
2022-08-13 09:46:35	ga_ls9c_ard_3-2-1_095072_2022-08-13_final.stac-item
2022-08-14 10:28:16	ga_ls9c_ard_3-2-1_102068_2022-08-14_final.stac-item
2022-08-14 10:28:39	ga_ls9c_ard_3-2-1_102069_2022-08-14_final.stac-item
2022-08-25 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-08-25_final.stac-item
2022-08-25 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-08-25_final.stac-item
2022-08-27 11:38:41	ga_ls9c_ard_3-2-1_113074_2022-08-27_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 11:46:27	ga_ls9c_ard_3-2-1_114078_2022-09-03_final.stac-item
2022-09-12 11:38:42	ga_ls9c_ard_3-2-1_113074_2022-09-12_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-25 11:08:42	ga_ls9c_ard_3-2-1_108076_2022-09-25_final.stac-item
2022-09-29 10:43:59	ga_ls9c_ard_3-2-1_104076_2022-09-29_final.stac-item
2022-09-29 10:46:23	ga_ls9c_ard_3-2-1_104082_2022-09-29_final.stac-item
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_final.stac-item
2022-10-04 09:29:13	ga_ls9c_ard_3-2-1_091090_2022-10-03_final.stac-item
2022-10-10 10:23:29	ga_ls9c_ard_3-2-1_101071_2022-10-10_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-20 11:00:37	ga_ls9c_ard_3-2-1_107071_2022-10-20_final.stac-item
2022-11-05 09:26:29	ga_ls9c_ard_3-2-1_091083_2022-11-04_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-11-30 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-11-30_final.stac-item
2022-12-14 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-14_final.stac-item
2022-12-15 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-15_final.stac-item
2022-12-23 09:29:16	ga_ls9c_ard_3-2-1_091090_2022-12-22_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-11 09:53:25	ga_ls9c_ard_3-2-1_096073_2023-01-11_final.stac-item
2023-01-14 10:23:29	ga_ls9c_ard_3-2-1_101071_2023-01-14_final.stac-item
2023-01-15 09:34:38	ga_ls9c_ard_3-2-1_092088_2023-01-15_final.stac-item
2023-01-19 09:07:27	ga_ls9c_ard_3-2-1_088082_2023-01-18_final.stac-item
2023-01-27 11:36:16	ga_ls9c_ard_3-2-1_112083_2023-01-27_final.stac-item
2023-02-01 10:14:23	ga_ls9c_ard_3-2-1_099079_2023-02-01_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-08 10:18:37	ga_ls9c_ard_3-2-1_100074_2023-02-08_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-02-19 11:40:02	ga_ls9c_ard_3-2-1_113077_2023-02-19_final.stac-item
2023-02-19 11:42:25	ga_ls9c_ard_3-2-1_113083_2023-02-19_final.stac-item
2023-02-27 10:52:04	ga_ls9c_ard_3-2-1_105081_2023-02-27_final.stac-item
2023-03-22 10:58:29	ga_ls9c_ard_3-2-1_106082_2023-03-22_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-04-05 11:09:29	ga_ls9c_ard_3-2-1_108079_2023-04-05_final.stac-item
2023-04-14 11:04:48	ga_ls9c_ard_3-2-1_107083_2023-04-14_final.stac-item
2023-04-20 10:22:56	ga_ls9c_ard_3-2-1_101071_2023-04-20_final.stac-item
2023-04-21 11:07:00	ga_ls9c_ard_3-2-1_108073_2023-04-21_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-05-11 09:06:47	ga_ls9c_ard_3-2-1_088082_2023-05-10_final.stac-item
2023-05-23 11:11:02	ga_ls9c_ard_3-2-1_108084_2023-05-23_final.stac-item
2023-06-04 09:52:02	ga_ls9c_ard_3-2-1_096072_2023-06-04_final.stac-item
2023-06-05 10:33:42	ga_ls9c_ard_3-2-1_103068_2023-06-05_final.stac-item
2023-06-14 10:33:00	ga_ls9c_ard_3-2-1_102082_2023-06-14_final.stac-item
2023-06-17 10:59:05	ga_ls9c_ard_3-2-1_107070_2023-06-17_final.stac-item
2023-06-18 10:03:52	ga_ls9c_ard_3-2-1_098071_2023-06-18_final.stac-item
2023-06-29 09:49:25	ga_ls9c_ard_3-2-1_095081_2023-06-29_final.stac-item
2023-07-12 09:17:05	ga_ls9c_ard_3-2-1_090077_2023-07-11_final.stac-item
2023-07-14 09:07:08	ga_ls9c_ard_3-2-1_088083_2023-07-13_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-16 10:28:04	ga_ls9c_ard_3-2-1_102069_2023-07-16_final.stac-item
2023-07-18 11:57:23	ga_ls9c_ard_3-2-1_116076_2023-07-18_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-11 11:06:55	ga_ls9c_ard_3-2-1_108073_2023-08-11_final.stac-item
2023-08-12 10:09:18	ga_ls9c_ard_3-2-1_099068_2023-08-12_final.stac-item
2023-08-13 09:21:40	ga_ls9c_ard_3-2-1_090088_2023-08-12_final.stac-item
2023-08-17 10:27:50	ga_ls9c_ard_3-2-1_102068_2023-08-17_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_2023-10-13_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-11-02 10:03:41	ga_ls9c_ard_3-2-1_097084_2023-11-02_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