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
2021-11-14 10:41:51	ga_ls9c_ard_3-2-1_103080_2021-11-14_final.stac-item
2021-12-11 11:06:41	ga_ls9c_ard_3-2-1_108071_2021-12-11_final.stac-item
2022-01-01 09:47:53	ga_ls9c_ard_3-2-1_095075_2022-01-01_final.stac-item
2022-01-19 09:35:06	ga_ls9c_ard_3-2-1_093074_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
2022-02-05 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-02-05_final.stac-item
2022-02-06 09:27:08	ga_ls9c_ard_3-2-1_091085_2022-02-05_final.stac-item
2022-02-18 09:47:22	ga_ls9c_ard_3-2-1_095074_2022-02-18_final.stac-item
2022-03-24 09:34:25	ga_ls9c_ard_3-2-1_093073_2022-03-24_final.stac-item
2022-04-02 09:31:00	ga_ls9c_ard_3-2-1_092080_2022-04-02_final.stac-item
2022-04-05 09:57:06	ga_ls9c_ard_3-2-1_097068_2022-04-05_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-04-21 10:00:55	ga_ls9c_ard_3-2-1_097078_2022-04-21_final.stac-item
2022-05-04 09:32:22	ga_ls9c_ard_3-2-1_092084_2022-05-04_final.stac-item
2022-06-24 09:57:50	ga_ls9c_ard_3-2-1_097070_2022-06-24_final.stac-item
2022-06-29 10:17:11	ga_ls9c_ard_3-2-1_100072_2022-06-29_final.stac-item
2022-06-29 10:21:34	ga_ls9c_ard_3-2-1_100083_2022-06-29_final.stac-item
2022-07-16 09:24:41	ga_ls9c_ard_3-2-1_091080_2022-07-15_final.stac-item
2022-10-04 11:00:07	ga_ls9c_ard_3-2-1_107070_2022-10-04_final.stac-item
2022-10-10 10:23:29	ga_ls9c_ard_3-2-1_101071_2022-10-10_final.stac-item
2022-10-15 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-14_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-27 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-10-26_final.stac-item
2022-10-28 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-10-28_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-05 09:28:05	ga_ls9c_ard_3-2-1_091087_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
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-10 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-11-10_final.stac-item
2022-11-12 11:06:49	ga_ls9c_ard_3-2-1_108071_2022-11-12_final.stac-item
2022-11-15 09:57:38	ga_ls9c_ard_3-2-1_097068_2022-11-15_final.stac-item
2022-11-25 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-11-25_final.stac-item
2022-12-14 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-12-13_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-15 11:53:15	ga_ls9c_ard_3-2-1_115079_2022-12-15_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-21 09:34:27	ga_ls9c_ard_3-2-1_093072_2022-12-21_final.stac-item
2022-12-24 10:08:08	ga_ls9c_ard_3-2-1_098079_2022-12-24_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 10:50:36	ga_ls9c_ard_3-2-1_105077_2022-12-25_final.stac-item
2022-12-26 11:31:53	ga_ls9c_ard_3-2-1_112072_2022-12-26_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_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 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-10 10:52:38	ga_ls9c_ard_3-2-1_105082_2023-01-10_final.stac-item
2023-01-18 09:57:30	ga_ls9c_ard_3-2-1_097068_2023-01-18_final.stac-item
2023-01-22 11:16:50	ga_ls9c_ard_3-2-1_109081_2023-01-22_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-25 10:04:55	ga_ls9c_ard_3-2-1_098071_2023-01-25_final.stac-item
2023-01-31 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-01-31_final.stac-item
2023-02-08 10:22:12	ga_ls9c_ard_3-2-1_100083_2023-02-08_final.stac-item
2023-02-10 10:04:15	ga_ls9c_ard_3-2-1_098069_2023-02-10_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-03-02 11:20:33	ga_ls9c_ard_3-2-1_110075_2023-03-02_final.stac-item
2023-03-16 09:52:20	ga_ls9c_ard_3-2-1_096071_2023-03-16_final.stac-item
2023-04-05 11:11:05	ga_ls9c_ard_3-2-1_108083_2023-04-05_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-05 11:19:57	ga_ls9c_ard_3-2-1_110075_2023-05-05_final.stac-item
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final.stac-item
2023-05-18 10:48:35	ga_ls9c_ard_3-2-1_105074_2023-05-18_final.stac-item
2023-05-31 10:21:10	ga_ls9c_ard_3-2-1_100083_2023-05-31_final.stac-item
2023-06-01 09:26:20	ga_ls9c_ard_3-2-1_091085_2023-05-31_final.stac-item
2023-06-02 10:04:01	ga_ls9c_ard_3-2-1_098071_2023-06-02_final.stac-item
2023-06-22 11:19:38	ga_ls9c_ard_3-2-1_110075_2023-06-22_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-06-25 11:50:31	ga_ls9c_ard_3-2-1_115075_2023-06-25_final.stac-item
2023-06-26 10:52:55	ga_ls9c_ard_3-2-1_106070_2023-06-26_final.stac-item
2023-06-27 10:00:55	ga_ls9c_ard_3-2-1_097079_2023-06-27_final.stac-item
2023-06-30 10:28:19	ga_ls9c_ard_3-2-1_102070_2023-06-30_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-03 09:26:22	ga_ls9c_ard_3-2-1_091085_2023-07-02_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-07-24 09:44:59	ga_ls9c_ard_3-2-1_094085_2023-07-24_final.stac-item
2023-07-27 11:52:49	ga_ls9c_ard_3-2-1_115080_2023-07-27_final.stac-item
2023-07-28 09:16:44	ga_ls9c_ard_3-2-1_090076_2023-07-27_final.stac-item
2023-07-29 09:57:13	ga_ls9c_ard_3-2-1_097069_2023-07-29_final.stac-item
2023-07-31 09:51:17	ga_ls9c_ard_3-2-1_095085_2023-07-31_final.stac-item
2023-08-03 11:57:55	ga_ls9c_ard_3-2-1_116077_2023-08-03_final.stac-item
2023-08-11 11:05:43	ga_ls9c_ard_3-2-1_108070_2023-08-11_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-08-14 10:01:44	ga_ls9c_ard_3-2-1_097080_2023-08-14_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-10-16 09:17:44	ga_ls9c_ard_3-2-1_090077_2023-10-15_final.stac-item
2023-10-18 10:40:41	ga_ls9c_ard_3-2-1_104068_2023-10-18_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-10-24 10:03:35	ga_ls9c_ard_3-2-1_098068_2023-10-24_final.stac-item
2023-10-25 09:13:33	ga_ls9c_ard_3-2-1_089082_2023-10-24_final.stac-item
2023-10-27 10:39:39	ga_ls9c_ard_3-2-1_103081_2023-10-27_final.stac-item
2023-10-28 11:19:43	ga_ls9c_ard_3-2-1_110073_2023-10-28_final.stac-item
2023-11-04 11:24:13	ga_ls9c_ard_3-2-1_111069_2023-11-04_final.stac-item
2023-11-14 10:23:16	ga_ls9c_ard_3-2-1_101071_2023-11-14_final.stac-item
2023-11-16 11:51:47	ga_ls9c_ard_3-2-1_115076_2023-11-16_final.stac-item
2023-11-21 10:28:43	ga_ls9c_ard_3-2-1_102069_2023-11-21_final.stac-item
2023-11-23 10:22:23	ga_ls9c_ard_3-2-1_100084_2023-11-23_final.stac-item
2023-11-25 10:04:27	ga_ls9c_ard_3-2-1_098070_2023-11-25_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