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

97 results

Time (local)	Label
2021-11-13 09:56:43	ga_ls9c_ard_3-2-1_097067_2021-11-13_final.stac-item
2021-12-14 09:57:52	ga_ls9c_ard_3-2-1_097069_2021-12-14_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-19 10:58:47	ga_ls9c_ard_3-2-1_106083_2022-03-19_final.stac-item
2022-04-06 09:07:04	ga_ls9c_ard_3-2-1_088082_2022-04-05_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-05-14 10:03:45	ga_ls9c_ard_3-2-1_098070_2022-05-14_final.stac-item
2022-05-23 09:57:05	ga_ls9c_ard_3-2-1_097069_2022-05-23_final.stac-item
2022-05-25 11:23:36	ga_ls9c_ard_3-2-1_111069_2022-05-25_final.stac-item
2022-05-27 09:33:33	ga_ls9c_ard_3-2-1_093072_2022-05-27_final.stac-item
2022-06-16 09:11:45	ga_ls9c_ard_3-2-1_089079_2022-06-15_final.stac-item
2022-06-19 11:18:00	ga_ls9c_ard_3-2-1_110070_2022-06-19_final.stac-item
2022-06-21 09:34:25	ga_ls9c_ard_3-2-1_092089_2022-06-21_final.stac-item
2022-07-06 10:27:44	ga_ls9c_ard_3-2-1_101083_2022-07-06_final.stac-item
2022-07-10 09:57:24	ga_ls9c_ard_3-2-1_097069_2022-07-10_final.stac-item
2022-07-10 11:41:52	ga_ls9c_ard_3-2-1_113083_2022-07-10_final.stac-item
2022-07-17 10:07:10	ga_ls9c_ard_3-2-1_098078_2022-07-17_final.stac-item
2022-07-18 10:49:15	ga_ls9c_ard_3-2-1_105075_2022-07-18_final.stac-item
2022-07-28 11:24:30	ga_ls9c_ard_3-2-1_111070_2022-07-28_final.stac-item
2022-08-12 09:06:54	ga_ls9c_ard_3-2-1_088081_2022-08-11_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-09-04 10:49:14	ga_ls9c_ard_3-2-1_105074_2022-09-04_final.stac-item
2022-09-11 09:17:45	ga_ls9c_ard_3-2-1_090077_2022-09-10_final.stac-item
2022-09-11 09:22:56	ga_ls9c_ard_3-2-1_090090_2022-09-10_final.stac-item
2022-10-02 11:16:29	ga_ls9c_ard_3-2-1_109080_2022-10-02_final.stac-item
2022-10-12 10:10:44	ga_ls9c_ard_3-2-1_099070_2022-10-12_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 09:46:27	ga_ls9c_ard_3-2-1_095071_2022-10-16_final.stac-item
2022-10-22 10:49:28	ga_ls9c_ard_3-2-1_105074_2022-10-22_final.stac-item
2022-10-22 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-10-22_final.stac-item
2022-10-31 09:06:46	ga_ls9c_ard_3-2-1_088080_2022-10-30_final.stac-item
2022-11-01 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-11-01_final.stac-item
2022-11-06 10:04:10	ga_ls9c_ard_3-2-1_098069_2022-11-06_final.stac-item
2022-11-15 09:57:14	ga_ls9c_ard_3-2-1_097067_2022-11-15_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-03 10:42:29	ga_ls9c_ard_3-2-1_104072_2023-01-03_final.stac-item
2023-02-02 09:22:46	ga_ls9c_ard_3-2-1_090089_2023-02-01_final.stac-item
2023-02-14 11:18:47	ga_ls9c_ard_3-2-1_110070_2023-02-14_final.stac-item
2023-02-18 09:23:06	ga_ls9c_ard_3-2-1_090090_2023-02-17_final.stac-item
2023-02-20 09:07:30	ga_ls9c_ard_3-2-1_088082_2023-02-19_final.stac-item
2023-02-27 09:12:23	ga_ls9c_ard_3-2-1_089079_2023-02-26_final.stac-item
2023-03-15 09:16:40	ga_ls9c_ard_3-2-1_089090_2023-03-14_final.stac-item
2023-04-10 09:51:54	ga_ls9c_ard_3-2-1_095086_2023-04-10_final.stac-item
2023-04-23 09:20:56	ga_ls9c_ard_3-2-1_090086_2023-04-22_final.stac-item
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final.stac-item
2023-04-28 09:40:12	ga_ls9c_ard_3-2-1_093088_2023-04-28_final.stac-item
2023-05-02 10:51:54	ga_ls9c_ard_3-2-1_105082_2023-05-02_final.stac-item
2023-05-30 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-05-30_final.stac-item
2023-05-31 10:19:10	ga_ls9c_ard_3-2-1_100078_2023-05-31_final.stac-item
2023-06-13 11:29:02	ga_ls9c_ard_3-2-1_111083_2023-06-13_final.stac-item
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-06-26 09:16:25	ga_ls9c_ard_3-2-1_090076_2023-06-25_final.stac-item
2023-07-01 09:39:30	ga_ls9c_ard_3-2-1_093087_2023-07-01_final.stac-item
2023-07-15 09:46:00	ga_ls9c_ard_3-2-1_095072_2023-07-15_final.stac-item
2023-07-20 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-07-20_final.stac-item
2023-07-21 09:11:43	ga_ls9c_ard_3-2-1_089079_2023-07-20_final.stac-item
2023-07-21 10:49:24	ga_ls9c_ard_3-2-1_105076_2023-07-21_final.stac-item
2023-07-27 10:09:57	ga_ls9c_ard_3-2-1_099070_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
2023-08-05 11:47:10	ga_ls9c_ard_3-2-1_114081_2023-08-05_final.stac-item
2023-08-09 11:18:05	ga_ls9c_ard_3-2-1_110070_2023-08-09_final.stac-item
2023-08-12 10:10:06	ga_ls9c_ard_3-2-1_099070_2023-08-12_final.stac-item
2023-08-15 09:06:54	ga_ls9c_ard_3-2-1_088082_2023-08-14_final.stac-item
2023-08-20 09:27:28	ga_ls9c_ard_3-2-1_091087_2023-08-19_final.stac-item
2023-08-28 10:13:02	ga_ls9c_ard_3-2-1_099077_2023-08-28_final.stac-item
2023-08-29 09:21:49	ga_ls9c_ard_3-2-1_090088_2023-08-28_final.stac-item
2023-09-15 09:57:39	ga_ls9c_ard_3-2-1_097069_2023-09-15_final.stac-item
2023-09-23 10:49:51	ga_ls9c_ard_3-2-1_105076_2023-09-23_final.stac-item
2023-09-29 10:09:08	ga_ls9c_ard_3-2-1_099067_2023-09-29_final.stac-item
2023-10-24 10:04:23	ga_ls9c_ard_3-2-1_098070_2023-10-24_final.stac-item
2023-10-25 10:49:38	ga_ls9c_ard_3-2-1_105075_2023-10-25_final.stac-item
2023-11-04 11:24:13	ga_ls9c_ard_3-2-1_111069_2023-11-04_final.stac-item
2023-11-04 11:29:48	ga_ls9c_ard_3-2-1_111083_2023-11-04_final.stac-item
2023-11-06 09:33:48	ga_ls9c_ard_3-2-1_093071_2023-11-06_final.stac-item
2023-11-07 11:57:33	ga_ls9c_ard_3-2-1_116075_2023-11-07_final.stac-item
2023-11-09 10:04:19	ga_ls9c_ard_3-2-1_098070_2023-11-09_final.stac-item
2023-11-14 10:26:03	ga_ls9c_ard_3-2-1_101078_2023-11-14_final.stac-item
2023-11-27 11:36:10	ga_ls9c_ard_3-2-1_112083_2023-11-27_final.stac-item
2023-12-02 10:09:02	ga_ls9c_ard_3-2-1_099066_2023-12-02_final.stac-item
2023-12-11 10:04:01	ga_ls9c_ard_3-2-1_098069_2023-12-11_final.stac-item
2023-12-14 10:39:44	ga_ls9c_ard_3-2-1_103081_2023-12-14_final.stac-item
2023-12-28 09:15:14	ga_ls9c_ard_3-2-1_089086_2023-12-27_final.stac-item
2024-01-06 10:46:14	ga_ls9c_ard_3-2-1_104082_2024-01-06_final.stac-item
2024-01-11 09:29:08	ga_ls9c_ard_3-2-1_091090_2024-01-10_final.stac-item
2024-01-26 11:57:37	ga_ls9c_ard_3-2-1_116075_2024-01-26_final.stac-item
2024-01-26 11:58:01	ga_ls9c_ard_3-2-1_116076_2024-01-26_final.stac-item
2024-02-10 09:34:45	ga_ls9c_ard_3-2-1_093073_2024-02-10_final.stac-item
2024-02-21 09:22:24	ga_ls9c_ard_3-2-1_090089_2024-02-20_final.stac-item
2024-02-26 11:11:51	ga_ls9c_ard_3-2-1_109069_2024-02-26_final.stac-item
2024-03-13 09:40:35	ga_ls9c_ard_3-2-1_093088_2024-03-13_final.stac-item
2024-03-13 11:12:41	ga_ls9c_ard_3-2-1_109071_2024-03-13_final.stac-item
2024-03-14 08:42:34	ga_ls9c_ard_3-2-1_084082_2024-03-13_final.stac-item
2024-03-16 10:07:30	ga_ls9c_ard_3-2-1_098078_2024-03-16_final.stac-item
2024-04-18 09:16:20	ga_ls9c_ard_3-2-1_089090_2024-04-17_final.stac-item
2024-05-09 09:34:15	ga_ls9c_ard_3-2-1_092089_2024-05-09_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