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

88 results

Time (local)	Label
2021-11-08 09:55:27	ga_ls9c_ard_3-2-1_097070_2021-11-08_final.stac-item
2021-12-06 09:12:30	ga_ls9c_ard_3-2-1_089079_2021-12-05_final.stac-item
2021-12-06 10:50:11	ga_ls9c_ard_3-2-1_105076_2021-12-06_final.stac-item
2021-12-13 10:59:05	ga_ls9c_ard_3-2-1_106083_2021-12-13_final.stac-item
2021-12-18 09:33:55	ga_ls9c_ard_3-2-1_093071_2021-12-18_final.stac-item
2022-01-09 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-01-09_final.stac-item
2022-01-13 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-01-13_final.stac-item
2022-01-20 11:58:03	ga_ls9c_ard_3-2-1_116076_2022-01-20_final.stac-item
2022-01-22 10:03:13	ga_ls9c_ard_3-2-1_098067_2022-01-22_final.stac-item
2022-01-22 11:44:54	ga_ls9c_ard_3-2-1_114074_2022-01-22_final.stac-item
2022-02-11 11:20:08	ga_ls9c_ard_3-2-1_110074_2022-02-11_final.stac-item
2022-02-13 11:06:58	ga_ls9c_ard_3-2-1_108072_2022-02-13_final.stac-item
2022-04-19 11:52:59	ga_ls9c_ard_3-2-1_115080_2022-04-19_final.stac-item
2022-04-28 10:04:42	ga_ls9c_ard_3-2-1_098072_2022-04-28_final.stac-item
2022-06-05 11:10:16	ga_ls9c_ard_3-2-1_108082_2022-06-05_final.stac-item
2022-06-06 10:08:16	ga_ls9c_ard_3-2-1_099066_2022-06-06_final.stac-item
2022-06-10 11:24:26	ga_ls9c_ard_3-2-1_111071_2022-06-10_final.stac-item
2022-06-21 09:32:01	ga_ls9c_ard_3-2-1_092083_2022-06-21_final.stac-item
2022-06-24 09:59:02	ga_ls9c_ard_3-2-1_097073_2022-06-24_final.stac-item
2022-08-03 10:49:53	ga_ls9c_ard_3-2-1_105076_2022-08-03_final.stac-item
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final.stac-item
2022-08-18 10:04:45	ga_ls9c_ard_3-2-1_098071_2022-08-18_final.stac-item
2022-09-05 11:34:53	ga_ls9c_ard_3-2-1_112080_2022-09-05_final.stac-item
2022-09-08 10:26:06	ga_ls9c_ard_3-2-1_101078_2022-09-08_final.stac-item
2022-09-14 11:24:22	ga_ls9c_ard_3-2-1_111069_2022-09-14_final.stac-item
2022-09-23 09:45:45	ga_ls9c_ard_3-2-1_094085_2022-09-23_final.stac-item
2022-09-25 09:29:49	ga_ls9c_ard_3-2-1_092076_2022-09-24_final.stac-item
2022-09-29 09:07:06	ga_ls9c_ard_3-2-1_088081_2022-09-28_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-10-15 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-10-15_final.stac-item
2022-11-29 10:11:57	ga_ls9c_ard_3-2-1_099073_2022-11-29_final.stac-item
2022-12-23 09:26:52	ga_ls9c_ard_3-2-1_091084_2022-12-22_final.stac-item
2022-12-28 09:46:38	ga_ls9c_ard_3-2-1_094087_2022-12-28_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_final.stac-item
2023-01-03 10:44:28	ga_ls9c_ard_3-2-1_104077_2023-01-03_final.stac-item
2023-01-08 09:22:32	ga_ls9c_ard_3-2-1_091073_2023-01-07_final.stac-item
2023-01-31 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-01-31_final.stac-item
2023-02-01 11:51:40	ga_ls9c_ard_3-2-1_115075_2023-02-01_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-02-25 09:22:45	ga_ls9c_ard_3-2-1_091074_2023-02-24_final.stac-item
2023-03-30 10:09:17	ga_ls9c_ard_3-2-1_098083_2023-03-30_final.stac-item
2023-03-30 11:45:46	ga_ls9c_ard_3-2-1_114077_2023-03-30_final.stac-item
2023-04-03 09:40:59	ga_ls9c_ard_3-2-1_094074_2023-04-03_final.stac-item
2023-04-14 09:28:43	ga_ls9c_ard_3-2-1_091090_2023-04-13_final.stac-item
2023-04-14 11:05:12	ga_ls9c_ard_3-2-1_107084_2023-04-14_final.stac-item
2023-04-17 11:35:43	ga_ls9c_ard_3-2-1_112083_2023-04-17_final.stac-item
2023-04-27 10:28:39	ga_ls9c_ard_3-2-1_102070_2023-04-27_final.stac-item
2023-04-28 11:17:29	ga_ls9c_ard_3-2-1_109084_2023-04-28_final.stac-item
2023-04-30 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-04-29_final.stac-item
2023-05-01 10:07:27	ga_ls9c_ard_3-2-1_098079_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
2023-05-16 09:22:05	ga_ls9c_ard_3-2-1_091074_2023-05-15_final.stac-item
2023-06-11 11:40:13	ga_ls9c_ard_3-2-1_113080_2023-06-11_final.stac-item
2023-06-12 10:42:12	ga_ls9c_ard_3-2-1_104074_2023-06-12_final.stac-item
2023-06-26 09:22:01	ga_ls9c_ard_3-2-1_090090_2023-06-25_final.stac-item
2023-06-27 09:57:19	ga_ls9c_ard_3-2-1_097070_2023-06-27_final.stac-item
2023-07-12 10:57:10	ga_ls9c_ard_3-2-1_106080_2023-07-12_final.stac-item
2023-07-19 09:22:29	ga_ls9c_ard_3-2-1_091075_2023-07-18_final.stac-item
2023-07-24 11:17:29	ga_ls9c_ard_3-2-1_110069_2023-07-24_final.stac-item
2023-07-28 09:21:31	ga_ls9c_ard_3-2-1_090088_2023-07-27_final.stac-item
2023-08-02 09:39:44	ga_ls9c_ard_3-2-1_093087_2023-08-02_final.stac-item
2023-08-16 09:49:22	ga_ls9c_ard_3-2-1_095080_2023-08-16_final.stac-item
2023-08-20 09:21:53	ga_ls9c_ard_3-2-1_091073_2023-08-19_final.stac-item
2023-08-29 10:55:54	ga_ls9c_ard_3-2-1_106076_2023-08-29_final.stac-item
2023-09-05 09:26:27	ga_ls9c_ard_3-2-1_091084_2023-09-04_final.stac-item
2023-09-14 10:54:28	ga_ls9c_ard_3-2-1_106072_2023-09-14_final.stac-item
2023-09-22 10:04:12	ga_ls9c_ard_3-2-1_098070_2023-09-22_final.stac-item
2023-10-07 09:23:48	ga_ls9c_ard_3-2-1_091077_2023-10-06_final.stac-item
2023-10-16 10:58:37	ga_ls9c_ard_3-2-1_106082_2023-10-16_final.stac-item
2023-10-31 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-10-31_final.stac-item
2023-11-10 10:51:59	ga_ls9c_ard_3-2-1_105081_2023-11-10_final.stac-item
2023-11-24 09:23:10	ga_ls9c_ard_3-2-1_091075_2023-11-23_final.stac-item
2023-12-12 10:49:17	ga_ls9c_ard_3-2-1_105074_2023-12-12_final.stac-item
2024-01-09 09:37:29	ga_ls9c_ard_3-2-1_093080_2024-01-09_final.stac-item
2024-01-13 10:49:41	ga_ls9c_ard_3-2-1_105075_2024-01-13_final.stac-item
2024-01-14 09:57:39	ga_ls9c_ard_3-2-1_096084_2024-01-14_final.stac-item
2024-01-19 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-19_final.stac-item
2024-02-08 09:52:42	ga_ls9c_ard_3-2-1_095087_2024-02-08_final.stac-item
2024-02-20 11:51:21	ga_ls9c_ard_3-2-1_115075_2024-02-20_final.stac-item
2024-02-23 09:07:12	ga_ls9c_ard_3-2-1_088082_2024-02-22_final.stac-item
2024-02-29 10:04:18	ga_ls9c_ard_3-2-1_098070_2024-02-29_final.stac-item
2024-03-11 11:30:15	ga_ls9c_ard_3-2-1_111084_2024-03-11_final.stac-item
2024-03-14 10:17:28	ga_ls9c_ard_3-2-1_100072_2024-03-14_final.stac-item
2024-04-03 09:57:23	ga_ls9c_ard_3-2-1_096084_2024-04-03_final.stac-item
2024-04-13 10:33:11	ga_ls9c_ard_3-2-1_102081_2024-04-13_final.stac-item
2024-04-22 10:25:34	ga_ls9c_ard_3-2-1_101078_2024-04-22_final.stac-item
2024-04-24 11:52:49	ga_ls9c_ard_3-2-1_115080_2024-04-24_final.stac-item
2024-05-26 11:52:12	ga_ls9c_ard_3-2-1_115079_2024-05-26_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