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

75 results

Time (local)	Label
2021-11-13 10:03:29	ga_ls9c_ard_3-2-1_097084_2021-11-13_final.stac-item
2021-12-16 11:24:46	ga_ls9c_ard_3-2-1_111070_2021-12-16_final.stac-item
2021-12-18 11:14:24	ga_ls9c_ard_3-2-1_109075_2021-12-18_final.stac-item
2021-12-22 09:12:00	ga_ls9c_ard_3-2-1_089078_2021-12-21_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-28 11:08:13	ga_ls9c_ard_3-2-1_108075_2022-01-28_final.stac-item
2022-02-04 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-02-04_final.stac-item
2022-02-06 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-02-06_final.stac-item
2022-02-07 10:09:35	ga_ls9c_ard_3-2-1_098083_2022-02-07_final.stac-item
2022-03-01 11:07:58	ga_ls9c_ard_3-2-1_108075_2022-03-01_final.stac-item
2022-03-05 09:07:09	ga_ls9c_ard_3-2-1_088082_2022-03-04_final.stac-item
2022-04-25 11:13:05	ga_ls9c_ard_3-2-1_109073_2022-04-25_final.stac-item
2022-04-27 11:03:31	ga_ls9c_ard_3-2-1_107080_2022-04-27_final.stac-item
2022-05-06 10:55:41	ga_ls9c_ard_3-2-1_106076_2022-05-06_final.stac-item
2022-05-15 10:49:00	ga_ls9c_ard_3-2-1_105075_2022-05-15_final.stac-item
2022-06-12 09:39:12	ga_ls9c_ard_3-2-1_093086_2022-06-12_final.stac-item
2022-06-15 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-06-15_final.stac-item
2022-06-16 09:10:57	ga_ls9c_ard_3-2-1_089077_2022-06-15_final.stac-item
2022-06-19 09:45:30	ga_ls9c_ard_3-2-1_094086_2022-06-19_final.stac-item
2022-08-01 09:22:09	ga_ls9c_ard_3-2-1_091073_2022-07-31_final.stac-item
2022-08-10 09:17:15	ga_ls9c_ard_3-2-1_090076_2022-08-09_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-30 10:29:30	ga_ls9c_ard_3-2-1_102071_2022-08-30_final.stac-item
2022-10-02 11:12:53	ga_ls9c_ard_3-2-1_109071_2022-10-02_final.stac-item
2022-10-07 11:32:37	ga_ls9c_ard_3-2-1_112074_2022-10-07_final.stac-item
2022-10-08 10:36:12	ga_ls9c_ard_3-2-1_103072_2022-10-08_final.stac-item
2022-10-08 10:39:48	ga_ls9c_ard_3-2-1_103081_2022-10-08_final.stac-item
2022-10-16 11:24:56	ga_ls9c_ard_3-2-1_111070_2022-10-16_final.stac-item
2022-10-24 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-10-24_final.stac-item
2022-11-01 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-11-01_final.stac-item
2022-11-07 09:12:09	ga_ls9c_ard_3-2-1_089078_2022-11-06_final.stac-item
2022-11-07 09:12:33	ga_ls9c_ard_3-2-1_089079_2022-11-06_final.stac-item
2022-11-29 10:11:33	ga_ls9c_ard_3-2-1_099072_2022-11-29_final.stac-item
2023-01-07 10:22:09	ga_ls9c_ard_3-2-1_100083_2023-01-07_final.stac-item
2023-01-23 10:20:02	ga_ls9c_ard_3-2-1_100078_2023-01-23_final.stac-item
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-04 10:40:55	ga_ls9c_ard_3-2-1_104068_2023-02-04_final.stac-item
2023-03-15 09:11:52	ga_ls9c_ard_3-2-1_089078_2023-03-14_final.stac-item
2023-03-21 10:08:51	ga_ls9c_ard_3-2-1_099066_2023-03-21_final.stac-item
2023-03-21 10:09:39	ga_ls9c_ard_3-2-1_099068_2023-03-21_final.stac-item
2023-03-29 09:22:02	ga_ls9c_ard_3-2-1_091073_2023-03-28_final.stac-item
2023-03-31 10:46:34	ga_ls9c_ard_3-2-1_105068_2023-03-31_final.stac-item
2023-04-14 10:59:37	ga_ls9c_ard_3-2-1_107070_2023-04-14_final.stac-item
2023-04-21 09:27:43	ga_ls9c_ard_3-2-1_092072_2023-04-20_final.stac-item
2023-04-22 10:15:21	ga_ls9c_ard_3-2-1_099083_2023-04-22_final.stac-item
2023-04-30 09:21:25	ga_ls9c_ard_3-2-1_091072_2023-04-29_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-05-28 11:23:58	ga_ls9c_ard_3-2-1_111070_2023-05-28_final.stac-item
2023-06-08 09:32:52	ga_ls9c_ard_3-2-1_092086_2023-06-08_final.stac-item
2023-06-08 11:06:58	ga_ls9c_ard_3-2-1_108074_2023-06-08_final.stac-item
2023-06-09 10:08:09	ga_ls9c_ard_3-2-1_099066_2023-06-09_final.stac-item
2023-07-31 11:25:46	ga_ls9c_ard_3-2-1_111074_2023-07-31_final.stac-item
2023-08-12 10:13:17	ga_ls9c_ard_3-2-1_099078_2023-08-12_final.stac-item
2023-08-16 11:23:28	ga_ls9c_ard_3-2-1_111068_2023-08-16_final.stac-item
2023-09-03 09:40:23	ga_ls9c_ard_3-2-1_093088_2023-09-03_final.stac-item
2023-09-08 09:57:24	ga_ls9c_ard_3-2-1_096084_2023-09-08_final.stac-item
2023-10-06 10:22:13	ga_ls9c_ard_3-2-1_100084_2023-10-06_final.stac-item
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final.stac-item
2023-10-31 10:11:17	ga_ls9c_ard_3-2-1_099072_2023-10-31_final.stac-item
2023-11-13 11:20:05	ga_ls9c_ard_3-2-1_110074_2023-11-13_final.stac-item
2023-12-04 09:57:26	ga_ls9c_ard_3-2-1_097068_2023-12-04_final.stac-item
2023-12-08 11:11:57	ga_ls9c_ard_3-2-1_109069_2023-12-08_final.stac-item
2023-12-18 10:09:28	ga_ls9c_ard_3-2-1_099067_2023-12-18_final.stac-item
2023-12-24 09:37:11	ga_ls9c_ard_3-2-1_093079_2023-12-24_final.stac-item
2023-12-31 09:40:31	ga_ls9c_ard_3-2-1_094072_2023-12-31_final.stac-item
2023-12-31 11:18:37	ga_ls9c_ard_3-2-1_110070_2023-12-31_final.stac-item
2024-01-14 11:31:45	ga_ls9c_ard_3-2-1_112072_2024-01-14_final.stac-item
2024-01-18 09:29:44	ga_ls9c_ard_3-2-1_092076_2024-01-17_final.stac-item
2024-02-02 10:24:35	ga_ls9c_ard_3-2-1_101074_2024-02-02_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 09:20:48	ga_ls9c_ard_3-2-1_090085_2024-02-20_final.stac-item
2024-03-08 10:52:58	ga_ls9c_ard_3-2-1_106068_2024-03-08_final.stac-item
2024-03-25 10:01:15	ga_ls9c_ard_3-2-1_097078_2024-03-25_final.stac-item
2024-03-29 09:33:39	ga_ls9c_ard_3-2-1_093071_2024-03-29_final.stac-item
2024-05-03 10:09:20	ga_ls9c_ard_3-2-1_098084_2024-05-03_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years