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
2021-11-02 10:54:51	ga_ls9c_ard_3-2-1_106078_2021-11-02_final.stac-item
2021-11-06 10:14:59	ga_ls9c_ard_3-2-1_100072_2021-11-06_final.stac-item
2021-11-13 09:56:43	ga_ls9c_ard_3-2-1_097067_2021-11-13_final.stac-item
2021-11-13 10:01:54	ga_ls9c_ard_3-2-1_097080_2021-11-13_final.stac-item
2021-11-15 11:18:38	ga_ls9c_ard_3-2-1_110072_2021-11-15_final.stac-item
2021-11-17 09:25:16	ga_ls9c_ard_3-2-1_091082_2021-11-16_final.stac-item
2021-11-18 11:43:25	ga_ls9c_ard_3-2-1_113081_2021-11-18_final.stac-item
2021-11-22 09:25:16	ga_ls9c_ard_3-2-1_091076_2021-11-21_final.stac-item
2021-12-04 09:24:05	ga_ls9c_ard_3-2-1_091077_2021-12-03_final.stac-item
2021-12-17 10:30:20	ga_ls9c_ard_3-2-1_102073_2021-12-17_final.stac-item
2021-12-18 11:12:48	ga_ls9c_ard_3-2-1_109071_2021-12-18_final.stac-item
2021-12-21 10:07:37	ga_ls9c_ard_3-2-1_098078_2021-12-21_final.stac-item
2021-12-27 09:31:21	ga_ls9c_ard_3-2-1_092080_2021-12-27_final.stac-item
2022-01-14 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-01-13_final.stac-item
2022-01-20 10:20:45	ga_ls9c_ard_3-2-1_100080_2022-01-20_final.stac-item
2022-01-24 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-24_final.stac-item
2022-01-28 09:34:07	ga_ls9c_ard_3-2-1_092087_2022-01-28_final.stac-item
2022-01-29 10:13:00	ga_ls9c_ard_3-2-1_099076_2022-01-29_final.stac-item
2022-01-31 11:42:19	ga_ls9c_ard_3-2-1_113083_2022-01-31_final.stac-item
2022-02-09 11:36:30	ga_ls9c_ard_3-2-1_112084_2022-02-09_final.stac-item
2022-02-23 10:09:27	ga_ls9c_ard_3-2-1_098083_2022-02-23_final.stac-item
2022-03-05 10:40:27	ga_ls9c_ard_3-2-1_104068_2022-03-05_final.stac-item
2022-03-12 09:13:44	ga_ls9c_ard_3-2-1_089083_2022-03-11_final.stac-item
2022-05-05 10:14:02	ga_ls9c_ard_3-2-1_099080_2022-05-05_final.stac-item
2022-05-05 10:15:37	ga_ls9c_ard_3-2-1_099084_2022-05-05_final.stac-item
2022-05-13 11:04:11	ga_ls9c_ard_3-2-1_107082_2022-05-13_final.stac-item
2022-05-16 09:51:46	ga_ls9c_ard_3-2-1_096071_2022-05-16_final.stac-item
2022-05-22 10:52:42	ga_ls9c_ard_3-2-1_106069_2022-05-22_final.stac-item
2022-05-22 10:57:05	ga_ls9c_ard_3-2-1_106080_2022-05-22_final.stac-item
2022-05-24 09:06:39	ga_ls9c_ard_3-2-1_088082_2022-05-23_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-05 11:18:58	ga_ls9c_ard_3-2-1_110072_2022-07-05_final.stac-item
2022-07-15 11:57:35	ga_ls9c_ard_3-2-1_116076_2022-07-15_final.stac-item
2022-07-28 11:25:42	ga_ls9c_ard_3-2-1_111073_2022-07-28_final.stac-item
2022-08-04 09:57:28	ga_ls9c_ard_3-2-1_096084_2022-08-04_final.stac-item
2022-08-22 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-08-22_final.stac-item
2022-09-04 10:46:27	ga_ls9c_ard_3-2-1_105067_2022-09-04_final.stac-item
2022-09-15 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-09-15_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-09-19 10:03:16	ga_ls9c_ard_3-2-1_098067_2022-09-19_final.stac-item
2022-09-19 11:44:57	ga_ls9c_ard_3-2-1_114074_2022-09-19_final.stac-item
2022-09-20 09:11:39	ga_ls9c_ard_3-2-1_089077_2022-09-19_final.stac-item
2022-09-30 09:52:21	ga_ls9c_ard_3-2-1_095086_2022-09-30_final.stac-item
2022-10-05 10:07:41	ga_ls9c_ard_3-2-1_098078_2022-10-05_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-15 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-14_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-16 11:26:32	ga_ls9c_ard_3-2-1_111074_2022-10-16_final.stac-item
2022-10-17 10:33:18	ga_ls9c_ard_3-2-1_102080_2022-10-17_final.stac-item
2022-10-28 11:53:39	ga_ls9c_ard_3-2-1_115080_2022-10-28_final.stac-item
2022-11-10 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-11-10_final.stac-item
2022-11-25 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-25_final.stac-item
2022-11-27 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-11-27_final.stac-item
2022-11-28 09:33:29	ga_ls9c_ard_3-2-1_092085_2022-11-28_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-03 09:52:48	ga_ls9c_ard_3-2-1_095087_2022-12-03_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-12 11:19:34	ga_ls9c_ard_3-2-1_110072_2022-12-12_final.stac-item
2022-12-14 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-14_final.stac-item
2022-12-18 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-12-18_final.stac-item
2022-12-22 10:17:42	ga_ls9c_ard_3-2-1_100072_2022-12-22_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-23 11:02:33	ga_ls9c_ard_3-2-1_107076_2022-12-23_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2023-01-08 11:00:37	ga_ls9c_ard_3-2-1_107071_2023-01-08_final.stac-item
2023-01-09 10:07:23	ga_ls9c_ard_3-2-1_098077_2023-01-09_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_2023-01-09_final.stac-item
2023-01-10 09:14:09	ga_ls9c_ard_3-2-1_089083_2023-01-09_final.stac-item
2023-01-21 10:29:09	ga_ls9c_ard_3-2-1_102070_2023-01-21_final.stac-item
2023-01-21 10:30:21	ga_ls9c_ard_3-2-1_102073_2023-01-21_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-01-27 11:35:52	ga_ls9c_ard_3-2-1_112082_2023-01-27_final.stac-item
2023-02-14 11:20:23	ga_ls9c_ard_3-2-1_110074_2023-02-14_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-02-24 10:18:22	ga_ls9c_ard_3-2-1_100074_2023-02-24_final.stac-item
2023-02-26 11:44:54	ga_ls9c_ard_3-2-1_114074_2023-02-26_final.stac-item
2023-03-06 09:22:54	ga_ls9c_ard_3-2-1_090090_2023-03-05_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-10 10:30:12	ga_ls9c_ard_3-2-1_102073_2023-03-10_final.stac-item
2023-04-05 11:07:54	ga_ls9c_ard_3-2-1_108075_2023-04-05_final.stac-item
2023-04-05 11:08:18	ga_ls9c_ard_3-2-1_108076_2023-04-05_final.stac-item
2023-04-30 09:27:24	ga_ls9c_ard_3-2-1_091087_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
2023-05-12 09:46:26	ga_ls9c_ard_3-2-1_095073_2023-05-12_final.stac-item
2023-05-30 11:11:12	ga_ls9c_ard_3-2-1_109069_2023-05-30_final.stac-item
2023-05-31 10:21:10	ga_ls9c_ard_3-2-1_100083_2023-05-31_final.stac-item
2023-06-02 10:03:13	ga_ls9c_ard_3-2-1_098069_2023-06-02_final.stac-item
2023-06-03 10:52:03	ga_ls9c_ard_3-2-1_105083_2023-06-03_final.stac-item
2023-07-01 09:38:42	ga_ls9c_ard_3-2-1_093085_2023-07-01_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-01 10:29:46	ga_ls9c_ard_3-2-1_102073_2023-08-01_final.stac-item
2023-08-06 10:46:22	ga_ls9c_ard_3-2-1_105068_2023-08-06_final.stac-item
2023-08-07 09:51:33	ga_ls9c_ard_3-2-1_096070_2023-08-07_final.stac-item
2023-10-16 09:22:31	ga_ls9c_ard_3-2-1_090089_2023-10-15_final.stac-item
2023-10-25 09:13:33	ga_ls9c_ard_3-2-1_089082_2023-10-24_final.stac-item
2023-10-28 11:19:43	ga_ls9c_ard_3-2-1_110073_2023-10-28_final.stac-item
2023-10-28 11:20:31	ga_ls9c_ard_3-2-1_110075_2023-10-28_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_final.stac-item
2023-11-23 10:22:23	ga_ls9c_ard_3-2-1_100084_2023-11-23_final.stac-item
2023-11-24 09:25:10	ga_ls9c_ard_3-2-1_091080_2023-11-23_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