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

85 results

Time (local)	Label
2021-11-11 10:19:03	ga_ls9c_ard_3-2-1_100076_2021-11-11_final.stac-item
2021-12-22 10:49:41	ga_ls9c_ard_3-2-1_105075_2021-12-22_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-01-23 09:10:23	ga_ls9c_ard_3-2-1_089074_2022-01-22_final.stac-item
2022-02-15 09:18:06	ga_ls9c_ard_3-2-1_090078_2022-02-14_final.stac-item
2022-03-06 09:46:02	ga_ls9c_ard_3-2-1_095071_2022-03-06_final.stac-item
2022-04-25 11:11:29	ga_ls9c_ard_3-2-1_109069_2022-04-25_final.stac-item
2022-04-28 10:04:18	ga_ls9c_ard_3-2-1_098071_2022-04-28_final.stac-item
2022-05-10 10:28:32	ga_ls9c_ard_3-2-1_102070_2022-05-10_final.stac-item
2022-05-21 11:50:19	ga_ls9c_ard_3-2-1_115074_2022-05-21_final.stac-item
2022-05-25 09:45:31	ga_ls9c_ard_3-2-1_095071_2022-05-25_final.stac-item
2022-06-05 11:07:05	ga_ls9c_ard_3-2-1_108074_2022-06-05_final.stac-item
2022-06-19 11:22:48	ga_ls9c_ard_3-2-1_110082_2022-06-19_final.stac-item
2022-06-30 09:27:09	ga_ls9c_ard_3-2-1_091086_2022-06-29_final.stac-item
2022-08-11 11:38:37	ga_ls9c_ard_3-2-1_113074_2022-08-11_final.stac-item
2022-08-22 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-08-22_final.stac-item
2022-08-28 10:46:15	ga_ls9c_ard_3-2-1_104082_2022-08-28_final.stac-item
2022-09-13 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-09-13_final.stac-item
2022-10-06 09:10:28	ga_ls9c_ard_3-2-1_089074_2022-10-05_final.stac-item
2022-10-11 09:29:28	ga_ls9c_ard_3-2-1_092075_2022-10-10_final.stac-item
2022-10-11 11:07:33	ga_ls9c_ard_3-2-1_108073_2022-10-11_final.stac-item
2022-10-21 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-10-21_final.stac-item
2022-10-22 09:14:58	ga_ls9c_ard_3-2-1_089085_2022-10-21_final.stac-item
2022-10-28 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-10-28_final.stac-item
2022-11-15 11:38:07	ga_ls9c_ard_3-2-1_113072_2022-11-15_final.stac-item
2022-12-12 09:41:04	ga_ls9c_ard_3-2-1_094073_2022-12-12_final.stac-item
2022-12-17 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-12-17_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-24 10:09:43	ga_ls9c_ard_3-2-1_098083_2022-12-24_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_final.stac-item
2022-12-31 10:16:21	ga_ls9c_ard_3-2-1_099084_2022-12-31_final.stac-item
2023-01-05 10:29:19	ga_ls9c_ard_3-2-1_102070_2023-01-05_final.stac-item
2023-01-12 10:39:51	ga_ls9c_ard_3-2-1_103081_2023-01-12_final.stac-item
2023-01-16 10:15:53	ga_ls9c_ard_3-2-1_099083_2023-01-16_final.stac-item
2023-01-24 11:00:31	ga_ls9c_ard_3-2-1_107071_2023-01-24_final.stac-item
2023-02-01 10:14:23	ga_ls9c_ard_3-2-1_099079_2023-02-01_final.stac-item
2023-02-20 09:07:30	ga_ls9c_ard_3-2-1_088082_2023-02-19_final.stac-item
2023-02-20 09:07:54	ga_ls9c_ard_3-2-1_088083_2023-02-19_final.stac-item
2023-02-27 10:50:04	ga_ls9c_ard_3-2-1_105076_2023-02-27_final.stac-item
2023-03-05 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-03-05_final.stac-item
2023-03-06 09:21:18	ga_ls9c_ard_3-2-1_090086_2023-03-05_final.stac-item
2023-03-21 10:08:51	ga_ls9c_ard_3-2-1_099066_2023-03-21_final.stac-item
2023-03-27 11:14:08	ga_ls9c_ard_3-2-1_109075_2023-03-27_final.stac-item
2023-05-21 09:39:22	ga_ls9c_ard_3-2-1_094071_2023-05-21_final.stac-item
2023-05-25 10:55:27	ga_ls9c_ard_3-2-1_106076_2023-05-25_final.stac-item
2023-05-28 09:45:53	ga_ls9c_ard_3-2-1_095072_2023-05-28_final.stac-item
2023-06-10 10:52:11	ga_ls9c_ard_3-2-1_106068_2023-06-10_final.stac-item
2023-06-11 11:37:50	ga_ls9c_ard_3-2-1_113074_2023-06-11_final.stac-item
2023-06-11 11:41:25	ga_ls9c_ard_3-2-1_113083_2023-06-11_final.stac-item
2023-06-14 10:27:24	ga_ls9c_ard_3-2-1_102068_2023-06-14_final.stac-item
2023-06-24 09:32:46	ga_ls9c_ard_3-2-1_092086_2023-06-24_final.stac-item
2023-06-25 10:10:02	ga_ls9c_ard_3-2-1_099071_2023-06-25_final.stac-item
2023-06-25 10:14:50	ga_ls9c_ard_3-2-1_099083_2023-06-25_final.stac-item
2023-06-26 10:52:31	ga_ls9c_ard_3-2-1_106069_2023-06-26_final.stac-item
2023-07-04 10:09:15	ga_ls9c_ard_3-2-1_098084_2023-07-04_final.stac-item
2023-07-31 09:51:40	ga_ls9c_ard_3-2-1_095086_2023-07-31_final.stac-item
2023-07-31 11:24:10	ga_ls9c_ard_3-2-1_111070_2023-07-31_final.stac-item
2023-08-20 09:22:17	ga_ls9c_ard_3-2-1_091074_2023-08-19_final.stac-item
2023-08-20 10:59:34	ga_ls9c_ard_3-2-1_107070_2023-08-20_final.stac-item
2023-09-12 09:29:07	ga_ls9c_ard_3-2-1_092075_2023-09-11_final.stac-item
2023-10-05 11:11:50	ga_ls9c_ard_3-2-1_109069_2023-10-05_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2023-10-24 10:03:35	ga_ls9c_ard_3-2-1_098068_2023-10-24_final.stac-item
2023-10-24 10:04:47	ga_ls9c_ard_3-2-1_098071_2023-10-24_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-10-31 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-10-31_final.stac-item
2023-11-07 10:17:04	ga_ls9c_ard_3-2-1_100071_2023-11-07_final.stac-item
2023-11-11 11:32:27	ga_ls9c_ard_3-2-1_112074_2023-11-11_final.stac-item
2023-11-16 10:10:06	ga_ls9c_ard_3-2-1_099069_2023-11-16_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_final.stac-item
2023-12-20 11:38:47	ga_ls9c_ard_3-2-1_113074_2023-12-20_final.stac-item
2024-01-03 10:09:47	ga_ls9c_ard_3-2-1_099068_2024-01-03_final.stac-item
2024-01-19 10:09:00	ga_ls9c_ard_3-2-1_099066_2024-01-19_final.stac-item
2024-01-22 09:06:58	ga_ls9c_ard_3-2-1_088081_2024-01-21_final.stac-item
2024-02-04 11:51:07	ga_ls9c_ard_3-2-1_115074_2024-02-04_final.stac-item
2024-02-14 10:46:28	ga_ls9c_ard_3-2-1_105067_2024-02-14_final.stac-item
2024-02-26 11:13:50	ga_ls9c_ard_3-2-1_109074_2024-02-26_final.stac-item
2024-02-27 11:58:19	ga_ls9c_ard_3-2-1_116077_2024-02-27_final.stac-item
2024-02-28 10:59:54	ga_ls9c_ard_3-2-1_107070_2024-02-28_final.stac-item
2024-03-08 10:53:46	ga_ls9c_ard_3-2-1_106070_2024-03-08_final.stac-item
2024-03-13 09:40:35	ga_ls9c_ard_3-2-1_093088_2024-03-13_final.stac-item
2024-03-24 10:53:18	ga_ls9c_ard_3-2-1_106069_2024-03-24_final.stac-item
2024-03-27 09:46:27	ga_ls9c_ard_3-2-1_095072_2024-03-27_final.stac-item
2024-04-01 10:03:22	ga_ls9c_ard_3-2-1_098068_2024-04-01_final.stac-item
2024-04-24 10:13:32	ga_ls9c_ard_3-2-1_099079_2024-04-24_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