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

98 results

Time (local)	Label
2021-11-06 10:16:35	ga_ls9c_ard_3-2-1_100076_2021-11-06_final.stac-item
2021-11-13 09:58:19	ga_ls9c_ard_3-2-1_097071_2021-11-13_final.stac-item
2021-11-13 11:40:34	ga_ls9c_ard_3-2-1_113080_2021-11-13_final.stac-item
2021-12-13 10:55:06	ga_ls9c_ard_3-2-1_106073_2021-12-13_final.stac-item
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_final.stac-item
2022-01-01 09:46:41	ga_ls9c_ard_3-2-1_095072_2022-01-01_final.stac-item
2022-01-03 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-01-03_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-21 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-01-20_final.stac-item
2022-01-29 10:13:48	ga_ls9c_ard_3-2-1_099078_2022-01-29_final.stac-item
2022-02-13 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-02-13_final.stac-item
2022-03-21 10:40:49	ga_ls9c_ard_3-2-1_104069_2022-03-21_final.stac-item
2022-04-23 09:51:45	ga_ls9c_ard_3-2-1_095086_2022-04-23_final.stac-item
2022-05-05 10:14:49	ga_ls9c_ard_3-2-1_099082_2022-05-05_final.stac-item
2022-05-11 09:39:17	ga_ls9c_ard_3-2-1_093086_2022-05-11_final.stac-item
2022-05-23 10:03:28	ga_ls9c_ard_3-2-1_097085_2022-05-23_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-06-19 11:17:36	ga_ls9c_ard_3-2-1_110069_2022-06-19_final.stac-item
2022-06-20 10:23:13	ga_ls9c_ard_3-2-1_101072_2022-06-20_final.stac-item
2022-06-23 09:20:55	ga_ls9c_ard_3-2-1_090086_2022-06-22_final.stac-item
2022-07-03 11:36:07	ga_ls9c_ard_3-2-1_112084_2022-07-03_final.stac-item
2022-07-27 10:42:25	ga_ls9c_ard_3-2-1_104073_2022-07-27_final.stac-item
2022-08-20 09:53:12	ga_ls9c_ard_3-2-1_096073_2022-08-20_final.stac-item
2022-08-29 11:27:07	ga_ls9c_ard_3-2-1_111076_2022-08-29_final.stac-item
2022-09-01 10:22:20	ga_ls9c_ard_3-2-1_100084_2022-09-01_final.stac-item
2022-09-02 11:02:24	ga_ls9c_ard_3-2-1_107076_2022-09-02_final.stac-item
2022-09-10 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-09-10_final.stac-item
2022-09-11 10:55:02	ga_ls9c_ard_3-2-1_106073_2022-09-11_final.stac-item
2022-09-16 11:15:13	ga_ls9c_ard_3-2-1_109077_2022-09-16_final.stac-item
2022-09-18 11:00:29	ga_ls9c_ard_3-2-1_107071_2022-09-18_final.stac-item
2022-09-23 11:19:27	ga_ls9c_ard_3-2-1_110072_2022-09-23_final.stac-item
2022-09-30 09:50:21	ga_ls9c_ard_3-2-1_095081_2022-09-30_final.stac-item
2022-10-04 09:28:49	ga_ls9c_ard_3-2-1_091089_2022-10-03_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-13 10:55:12	ga_ls9c_ard_3-2-1_106073_2022-10-13_final.stac-item
2022-10-14 11:38:52	ga_ls9c_ard_3-2-1_113074_2022-10-14_final.stac-item
2022-11-05 11:02:34	ga_ls9c_ard_3-2-1_107076_2022-11-05_final.stac-item
2022-11-18 10:29:44	ga_ls9c_ard_3-2-1_102071_2022-11-18_final.stac-item
2022-11-20 10:18:34	ga_ls9c_ard_3-2-1_100074_2022-11-20_final.stac-item
2022-12-09 10:52:15	ga_ls9c_ard_3-2-1_105081_2022-12-09_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-08 11:02:37	ga_ls9c_ard_3-2-1_107076_2023-01-08_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-24 09:25:14	ga_ls9c_ard_3-2-1_091080_2023-01-23_final.stac-item
2023-02-14 09:46:41	ga_ls9c_ard_3-2-1_094087_2023-02-14_final.stac-item
2023-03-10 10:28:36	ga_ls9c_ard_3-2-1_102069_2023-03-10_final.stac-item
2023-03-20 09:34:46	ga_ls9c_ard_3-2-1_092089_2023-03-20_final.stac-item
2023-04-12 11:17:36	ga_ls9c_ard_3-2-1_109084_2023-04-12_final.stac-item
2023-04-21 09:29:18	ga_ls9c_ard_3-2-1_092076_2023-04-20_final.stac-item
2023-04-30 11:03:54	ga_ls9c_ard_3-2-1_107081_2023-04-30_final.stac-item
2023-05-02 09:13:01	ga_ls9c_ard_3-2-1_089082_2023-05-01_final.stac-item
2023-05-09 09:21:08	ga_ls9c_ard_3-2-1_090087_2023-05-08_final.stac-item
2023-05-14 09:39:39	ga_ls9c_ard_3-2-1_093087_2023-05-14_final.stac-item
2023-05-24 11:50:41	ga_ls9c_ard_3-2-1_115075_2023-05-24_final.stac-item
2023-06-24 09:27:59	ga_ls9c_ard_3-2-1_092074_2023-06-23_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-30 09:06:00	ga_ls9c_ard_3-2-1_088080_2023-07-29_final.stac-item
2023-08-06 10:51:33	ga_ls9c_ard_3-2-1_105081_2023-08-06_final.stac-item
2023-08-06 10:51:57	ga_ls9c_ard_3-2-1_105082_2023-08-06_final.stac-item
2023-08-21 10:04:22	ga_ls9c_ard_3-2-1_098071_2023-08-21_final.stac-item
2023-08-25 09:46:05	ga_ls9c_ard_3-2-1_094087_2023-08-25_final.stac-item
2023-08-25 11:18:59	ga_ls9c_ard_3-2-1_110072_2023-08-25_final.stac-item
2023-09-05 09:23:40	ga_ls9c_ard_3-2-1_091077_2023-09-04_final.stac-item
2023-09-13 10:10:24	ga_ls9c_ard_3-2-1_099070_2023-09-13_final.stac-item
2023-09-24 11:36:18	ga_ls9c_ard_3-2-1_112084_2023-09-24_final.stac-item
2023-10-01 11:41:18	ga_ls9c_ard_3-2-1_113081_2023-10-01_final.stac-item
2023-10-02 10:42:54	ga_ls9c_ard_3-2-1_104074_2023-10-02_final.stac-item
2023-10-03 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-10-03_final.stac-item
2023-10-17 09:58:12	ga_ls9c_ard_3-2-1_097070_2023-10-17_final.stac-item
2023-10-22 10:22:20	ga_ls9c_ard_3-2-1_100084_2023-10-22_final.stac-item
2023-10-25 09:13:57	ga_ls9c_ard_3-2-1_089083_2023-10-24_final.stac-item
2023-11-01 09:20:02	ga_ls9c_ard_3-2-1_090083_2023-10-31_final.stac-item
2023-11-06 09:35:24	ga_ls9c_ard_3-2-1_093075_2023-11-06_final.stac-item
2023-11-22 09:37:06	ga_ls9c_ard_3-2-1_093079_2023-11-22_final.stac-item
2023-11-25 10:03:39	ga_ls9c_ard_3-2-1_098068_2023-11-25_final.stac-item
2023-12-12 09:11:36	ga_ls9c_ard_3-2-1_089077_2023-12-11_final.stac-item
2023-12-15 09:46:07	ga_ls9c_ard_3-2-1_094086_2023-12-15_final.stac-item
2023-12-19 09:17:50	ga_ls9c_ard_3-2-1_090077_2023-12-18_final.stac-item
2023-12-28 09:12:27	ga_ls9c_ard_3-2-1_089079_2023-12-27_final.stac-item
2024-01-23 09:46:13	ga_ls9c_ard_3-2-1_095071_2024-01-23_final.stac-item
2024-01-27 11:04:24	ga_ls9c_ard_3-2-1_107081_2024-01-27_final.stac-item
2024-02-06 11:41:09	ga_ls9c_ard_3-2-1_113080_2024-02-06_final.stac-item
2024-02-10 11:17:13	ga_ls9c_ard_3-2-1_109082_2024-02-10_final.stac-item
2024-02-11 10:22:23	ga_ls9c_ard_3-2-1_100084_2024-02-11_final.stac-item
2024-02-19 09:29:14	ga_ls9c_ard_3-2-1_092075_2024-02-18_final.stac-item
2024-02-19 11:08:30	ga_ls9c_ard_3-2-1_108076_2024-02-19_final.stac-item
2024-02-20 10:15:39	ga_ls9c_ard_3-2-1_099083_2024-02-20_final.stac-item
2024-03-04 11:18:53	ga_ls9c_ard_3-2-1_110071_2024-03-04_final.stac-item
2024-03-10 10:44:36	ga_ls9c_ard_3-2-1_104078_2024-03-10_final.stac-item
2024-03-27 11:25:20	ga_ls9c_ard_3-2-1_111072_2024-03-27_final.stac-item
2024-03-29 09:37:14	ga_ls9c_ard_3-2-1_093080_2024-03-29_final.stac-item
2024-04-02 09:14:31	ga_ls9c_ard_3-2-1_089085_2024-04-01_final.stac-item
2024-04-07 11:07:08	ga_ls9c_ard_3-2-1_108073_2024-04-07_final.stac-item
2024-04-12 09:51:08	ga_ls9c_ard_3-2-1_095084_2024-04-12_final.stac-item
2024-05-10 10:14:43	ga_ls9c_ard_3-2-1_099082_2024-05-10_nrt.stac-item
2024-05-16 09:38:43	ga_ls9c_ard_3-2-1_093085_2024-05-16_nrt.stac-item
2024-05-19 10:04:49	ga_ls9c_ard_3-2-1_098073_2024-05-19_nrt.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