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

61 results

Time (local)	Label
2021-12-06 10:49:24	ga_ls9c_ard_3-2-1_105074_2021-12-06_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2022-01-01 11:24:46	ga_ls9c_ard_3-2-1_111070_2022-01-01_final.stac-item
2022-01-05 11:05:38	ga_ls9c_ard_3-2-1_107084_2022-01-05_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-01-30 09:17:22	ga_ls9c_ard_3-2-1_090076_2022-01-29_final.stac-item
2022-02-04 11:14:00	ga_ls9c_ard_3-2-1_109074_2022-02-04_final.stac-item
2022-02-13 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-02-12_final.stac-item
2022-03-28 10:48:57	ga_ls9c_ard_3-2-1_105074_2022-03-28_final.stac-item
2022-04-04 10:55:31	ga_ls9c_ard_3-2-1_106075_2022-04-04_final.stac-item
2022-04-16 11:19:20	ga_ls9c_ard_3-2-1_110073_2022-04-16_final.stac-item
2022-05-18 11:23:02	ga_ls9c_ard_3-2-1_110083_2022-05-18_final.stac-item
2022-08-01 09:22:33	ga_ls9c_ard_3-2-1_091074_2022-07-31_final.stac-item
2022-09-11 09:22:08	ga_ls9c_ard_3-2-1_090088_2022-09-10_final.stac-item
2022-09-19 10:10:03	ga_ls9c_ard_3-2-1_098084_2022-09-19_final.stac-item
2022-10-02 11:17:17	ga_ls9c_ard_3-2-1_109082_2022-10-02_final.stac-item
2022-10-06 10:52:32	ga_ls9c_ard_3-2-1_105082_2022-10-06_final.stac-item
2022-11-22 10:10:36	ga_ls9c_ard_3-2-1_098085_2022-11-22_final.stac-item
2022-12-09 09:10:34	ga_ls9c_ard_3-2-1_089074_2022-12-08_final.stac-item
2022-12-25 10:47:25	ga_ls9c_ard_3-2-1_105069_2022-12-25_final.stac-item
2022-12-27 10:36:16	ga_ls9c_ard_3-2-1_103072_2022-12-27_final.stac-item
2023-01-08 09:23:20	ga_ls9c_ard_3-2-1_091075_2023-01-07_final.stac-item
2023-01-17 09:21:27	ga_ls9c_ard_3-2-1_090086_2023-01-16_final.stac-item
2023-01-29 09:40:39	ga_ls9c_ard_3-2-1_094072_2023-01-29_final.stac-item
2023-01-31 11:07:12	ga_ls9c_ard_3-2-1_108072_2023-01-31_final.stac-item
2023-02-22 10:29:35	ga_ls9c_ard_3-2-1_102071_2023-02-22_final.stac-item
2023-02-24 10:19:34	ga_ls9c_ard_3-2-1_100077_2023-02-24_final.stac-item
2023-03-11 11:11:52	ga_ls9c_ard_3-2-1_109069_2023-03-11_final.stac-item
2023-03-14 10:02:42	ga_ls9c_ard_3-2-1_098066_2023-03-14_final.stac-item
2023-04-06 10:08:41	ga_ls9c_ard_3-2-1_099066_2023-04-06_final.stac-item
2023-04-12 09:33:56	ga_ls9c_ard_3-2-1_093072_2023-04-12_final.stac-item
2023-04-16 10:46:51	ga_ls9c_ard_3-2-1_105069_2023-04-16_final.stac-item
2023-04-30 09:21:49	ga_ls9c_ard_3-2-1_091073_2023-04-29_final.stac-item
2023-05-22 10:25:24	ga_ls9c_ard_3-2-1_101078_2023-05-22_final.stac-item
2023-05-27 10:42:18	ga_ls9c_ard_3-2-1_104074_2023-05-27_final.stac-item
2023-05-30 09:33:31	ga_ls9c_ard_3-2-1_093072_2023-05-30_final.stac-item
2023-06-04 09:56:50	ga_ls9c_ard_3-2-1_096084_2023-06-04_final.stac-item
2023-06-08 11:10:33	ga_ls9c_ard_3-2-1_108083_2023-06-08_final.stac-item
2023-06-13 11:25:26	ga_ls9c_ard_3-2-1_111074_2023-06-13_final.stac-item
2023-07-06 11:31:00	ga_ls9c_ard_3-2-1_112072_2023-07-06_final.stac-item
2023-07-07 10:38:59	ga_ls9c_ard_3-2-1_103081_2023-07-07_final.stac-item
2023-09-03 11:11:41	ga_ls9c_ard_3-2-1_109069_2023-09-03_final.stac-item
2023-09-20 10:19:46	ga_ls9c_ard_3-2-1_100078_2023-09-20_final.stac-item
2023-09-30 09:17:08	ga_ls9c_ard_3-2-1_090076_2023-09-29_final.stac-item
2023-10-05 11:13:50	ga_ls9c_ard_3-2-1_109074_2023-10-05_final.stac-item
2023-11-05 10:33:48	ga_ls9c_ard_3-2-1_102082_2023-11-05_final.stac-item
2023-12-12 10:46:53	ga_ls9c_ard_3-2-1_105068_2023-12-12_final.stac-item
2023-12-12 10:51:40	ga_ls9c_ard_3-2-1_105080_2023-12-12_final.stac-item
2023-12-18 10:11:03	ga_ls9c_ard_3-2-1_099071_2023-12-18_final.stac-item
2024-02-12 11:01:39	ga_ls9c_ard_3-2-1_107074_2024-02-12_final.stac-item
2024-02-13 10:05:37	ga_ls9c_ard_3-2-1_098073_2024-02-13_final.stac-item
2024-02-14 09:10:23	ga_ls9c_ard_3-2-1_089074_2024-02-13_final.stac-item
2024-02-27 10:19:25	ga_ls9c_ard_3-2-1_100077_2024-02-27_final.stac-item
2024-03-11 11:25:28	ga_ls9c_ard_3-2-1_111072_2024-03-11_final.stac-item
2024-03-22 11:07:41	ga_ls9c_ard_3-2-1_108074_2024-03-22_final.stac-item
2024-03-23 10:08:51	ga_ls9c_ard_3-2-1_099066_2024-03-23_final.stac-item
2024-04-21 11:20:26	ga_ls9c_ard_3-2-1_110076_2024-04-21_final.stac-item
2024-04-30 11:13:20	ga_ls9c_ard_3-2-1_109074_2024-04-30_final.stac-item
2024-05-04 10:49:24	ga_ls9c_ard_3-2-1_105076_2024-05-04_final.stac-item
2024-05-13 10:45:35	ga_ls9c_ard_3-2-1_104082_2024-05-13_final.stac-item
2024-05-27 09:22:04	ga_ls9c_ard_3-2-1_090090_2024-05-26_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