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
2021-12-18 09:36:43	ga_ls9c_ard_3-2-1_093078_2021-12-18_final.stac-item
2021-12-19 10:19:58	ga_ls9c_ard_3-2-1_100078_2021-12-19_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-02-27 09:43:04	ga_ls9c_ard_3-2-1_094079_2022-02-27_final.stac-item
2022-03-01 09:31:53	ga_ls9c_ard_3-2-1_092082_2022-03-01_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-03-31 09:43:46	ga_ls9c_ard_3-2-1_094081_2022-03-31_final.stac-item
2022-04-17 10:26:54	ga_ls9c_ard_3-2-1_101081_2022-04-17_final.stac-item
2022-04-23 09:49:21	ga_ls9c_ard_3-2-1_095080_2022-04-23_final.stac-item
2022-05-23 11:40:45	ga_ls9c_ard_3-2-1_113081_2022-05-23_final.stac-item
2022-06-10 09:47:09	ga_ls9c_ard_3-2-1_095075_2022-06-10_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-08-05 10:39:09	ga_ls9c_ard_3-2-1_103080_2022-08-05_final.stac-item
2022-08-28 10:43:51	ga_ls9c_ard_3-2-1_104076_2022-08-28_final.stac-item
2022-09-26 10:12:17	ga_ls9c_ard_3-2-1_099074_2022-09-26_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_final.stac-item
2022-11-19 09:38:30	ga_ls9c_ard_3-2-1_093082_2022-11-19_final.stac-item
2022-12-02 10:44:25	ga_ls9c_ard_3-2-1_104077_2022-12-02_final.stac-item
2022-12-03 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-03_final.stac-item
2022-12-08 10:08:59	ga_ls9c_ard_3-2-1_098081_2022-12-08_final.stac-item
2023-01-08 11:04:12	ga_ls9c_ard_3-2-1_107080_2023-01-08_final.stac-item
2023-01-15 11:11:31	ga_ls9c_ard_3-2-1_108083_2023-01-15_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-26 10:50:59	ga_ls9c_ard_3-2-1_105078_2023-01-26_final.stac-item
2023-01-27 09:54:35	ga_ls9c_ard_3-2-1_096076_2023-01-27_final.stac-item
2023-01-27 11:31:52	ga_ls9c_ard_3-2-1_112072_2023-01-27_final.stac-item
2023-01-31 09:34:42	ga_ls9c_ard_3-2-1_092088_2023-01-31_final.stac-item
2023-02-03 10:01:39	ga_ls9c_ard_3-2-1_097078_2023-02-03_final.stac-item
2023-02-05 09:51:41	ga_ls9c_ard_3-2-1_095084_2023-02-05_final.stac-item
2023-02-06 10:30:10	ga_ls9c_ard_3-2-1_102072_2023-02-06_final.stac-item
2023-02-07 09:36:09	ga_ls9c_ard_3-2-1_093076_2023-02-07_final.stac-item
2023-02-07 09:40:08	ga_ls9c_ard_3-2-1_093086_2023-02-07_final.stac-item
2023-02-10 10:09:03	ga_ls9c_ard_3-2-1_098081_2023-02-10_final.stac-item
2023-02-12 09:54:41	ga_ls9c_ard_3-2-1_096076_2023-02-12_final.stac-item
2023-02-12 11:33:58	ga_ls9c_ard_3-2-1_112077_2023-02-12_final.stac-item
2023-04-22 11:51:03	ga_ls9c_ard_3-2-1_115075_2023-04-22_final.stac-item
2023-04-24 10:00:59	ga_ls9c_ard_3-2-1_097078_2023-04-24_final.stac-item
2023-04-27 10:30:15	ga_ls9c_ard_3-2-1_102074_2023-04-27_final.stac-item
2023-04-27 10:32:39	ga_ls9c_ard_3-2-1_102080_2023-04-27_final.stac-item
2023-04-28 09:35:25	ga_ls9c_ard_3-2-1_093076_2023-04-28_final.stac-item
2023-04-30 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-04-30_final.stac-item
2023-04-30 11:03:06	ga_ls9c_ard_3-2-1_107079_2023-04-30_final.stac-item
2023-05-28 09:47:29	ga_ls9c_ard_3-2-1_095076_2023-05-28_final.stac-item
2023-05-28 11:29:09	ga_ls9c_ard_3-2-1_111083_2023-05-28_final.stac-item
2023-07-05 10:46:08	ga_ls9c_ard_3-2-1_105068_2023-07-05_final.stac-item
2023-07-16 10:30:52	ga_ls9c_ard_3-2-1_102076_2023-07-16_final.stac-item
2023-07-17 09:39:14	ga_ls9c_ard_3-2-1_093086_2023-07-17_final.stac-item
2023-07-17 11:16:07	ga_ls9c_ard_3-2-1_109081_2023-07-17_final.stac-item
2023-07-19 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-07-19_final.stac-item
2023-07-19 11:00:34	ga_ls9c_ard_3-2-1_107073_2023-07-19_final.stac-item
2023-07-19 11:02:10	ga_ls9c_ard_3-2-1_107077_2023-07-19_final.stac-item
2023-07-24 09:42:12	ga_ls9c_ard_3-2-1_094078_2023-07-24_final.stac-item
2023-07-24 11:20:17	ga_ls9c_ard_3-2-1_110076_2023-07-24_final.stac-item
2023-07-24 11:21:53	ga_ls9c_ard_3-2-1_110080_2023-07-24_final.stac-item
2023-07-26 11:08:44	ga_ls9c_ard_3-2-1_108078_2023-07-26_final.stac-item
2023-07-29 11:38:30	ga_ls9c_ard_3-2-1_113075_2023-07-29_final.stac-item
2023-08-02 09:36:57	ga_ls9c_ard_3-2-1_093080_2023-08-02_final.stac-item
2023-08-02 09:37:21	ga_ls9c_ard_3-2-1_093081_2023-08-02_final.stac-item
2023-08-05 11:44:46	ga_ls9c_ard_3-2-1_114075_2023-08-05_final.stac-item
2023-10-15 10:12:09	ga_ls9c_ard_3-2-1_099074_2023-10-15_final.stac-item
2023-10-15 10:12:33	ga_ls9c_ard_3-2-1_099075_2023-10-15_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-17 10:01:00	ga_ls9c_ard_3-2-1_097077_2023-10-17_final.stac-item
2023-10-17 11:38:41	ga_ls9c_ard_3-2-1_113074_2023-10-17_final.stac-item
2023-10-18 10:43:52	ga_ls9c_ard_3-2-1_104076_2023-10-18_final.stac-item
2023-10-18 10:44:16	ga_ls9c_ard_3-2-1_104077_2023-10-18_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-19 09:49:03	ga_ls9c_ard_3-2-1_095078_2023-10-19_final.stac-item
2023-10-19 09:49:51	ga_ls9c_ard_3-2-1_095080_2023-10-19_final.stac-item
2023-10-19 11:28:20	ga_ls9c_ard_3-2-1_111079_2023-10-19_final.stac-item
2023-10-19 11:29:32	ga_ls9c_ard_3-2-1_111082_2023-10-19_final.stac-item
2023-10-20 10:28:19	ga_ls9c_ard_3-2-1_102068_2023-10-20_final.stac-item
2023-10-20 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-10-20_final.stac-item
2023-10-21 09:37:05	ga_ls9c_ard_3-2-1_093079_2023-10-21_final.stac-item
2023-10-22 10:18:45	ga_ls9c_ard_3-2-1_100075_2023-10-22_final.stac-item
2023-10-22 10:20:45	ga_ls9c_ard_3-2-1_100080_2023-10-22_final.stac-item
2023-10-22 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-10-22_final.stac-item
2023-10-25 10:47:38	ga_ls9c_ard_3-2-1_105070_2023-10-25_final.stac-item
2023-10-25 10:51:38	ga_ls9c_ard_3-2-1_105080_2023-10-25_final.stac-item
2023-10-26 11:33:41	ga_ls9c_ard_3-2-1_112077_2023-10-26_final.stac-item
2023-10-28 11:22:30	ga_ls9c_ard_3-2-1_110080_2023-10-28_final.stac-item
2023-10-29 10:23:17	ga_ls9c_ard_3-2-1_101071_2023-10-29_final.stac-item
2023-10-30 11:10:07	ga_ls9c_ard_3-2-1_108080_2023-10-30_final.stac-item
2023-10-31 10:12:05	ga_ls9c_ard_3-2-1_099074_2023-10-31_final.stac-item
2023-11-01 10:58:31	ga_ls9c_ard_3-2-1_106082_2023-11-01_final.stac-item
2023-11-02 10:01:17	ga_ls9c_ard_3-2-1_097078_2023-11-02_final.stac-item
2023-11-04 09:47:44	ga_ls9c_ard_3-2-1_095075_2023-11-04_final.stac-item
2023-11-04 09:48:08	ga_ls9c_ard_3-2-1_095076_2023-11-04_final.stac-item
2023-11-04 11:25:49	ga_ls9c_ard_3-2-1_111073_2023-11-04_final.stac-item
2023-11-05 10:33:00	ga_ls9c_ard_3-2-1_102080_2023-11-05_final.stac-item
2023-11-15 11:10:06	ga_ls9c_ard_3-2-1_108080_2023-11-15_final.stac-item
2023-11-17 09:18:29	ga_ls9c_ard_3-2-1_090079_2023-11-16_final.stac-item
2023-11-19 10:40:39	ga_ls9c_ard_3-2-1_104068_2023-11-19_final.stac-item
2023-11-21 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-11-21_final.stac-item
2023-11-22 11:16:47	ga_ls9c_ard_3-2-1_109081_2023-11-22_final.stac-item
2023-11-23 10:17:35	ga_ls9c_ard_3-2-1_100072_2023-11-23_final.stac-item
2023-11-24 11:05:15	ga_ls9c_ard_3-2-1_107083_2023-11-24_final.stac-item
2023-11-25 10:09:14	ga_ls9c_ard_3-2-1_098082_2023-11-25_final.stac-item
2023-11-26 10:50:54	ga_ls9c_ard_3-2-1_105078_2023-11-26_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