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
2021-12-06 10:47:00	ga_ls9c_ard_3-2-1_105068_2021-12-06_final.stac-item
2021-12-16 11:26:22	ga_ls9c_ard_3-2-1_111074_2021-12-16_final.stac-item
2021-12-29 10:56:16	ga_ls9c_ard_3-2-1_106076_2021-12-29_final.stac-item
2022-01-13 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-01-13_final.stac-item
2022-01-14 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-01-14_final.stac-item
2022-01-28 09:28:56	ga_ls9c_ard_3-2-1_092074_2022-01-27_final.stac-item
2022-02-11 09:40:27	ga_ls9c_ard_3-2-1_094072_2022-02-11_final.stac-item
2022-02-15 10:55:47	ga_ls9c_ard_3-2-1_106075_2022-02-15_final.stac-item
2022-02-16 09:57:45	ga_ls9c_ard_3-2-1_097069_2022-02-16_final.stac-item
2022-02-22 09:23:00	ga_ls9c_ard_3-2-1_091075_2022-02-21_final.stac-item
2022-03-01 09:29:05	ga_ls9c_ard_3-2-1_092075_2022-02-28_final.stac-item
2022-03-03 09:17:31	ga_ls9c_ard_3-2-1_090077_2022-03-02_final.stac-item
2022-03-03 10:55:36	ga_ls9c_ard_3-2-1_106075_2022-03-03_final.stac-item
2022-03-05 09:07:09	ga_ls9c_ard_3-2-1_088082_2022-03-04_final.stac-item
2022-03-06 09:46:02	ga_ls9c_ard_3-2-1_095071_2022-03-06_final.stac-item
2022-03-22 11:29:16	ga_ls9c_ard_3-2-1_111082_2022-03-22_final.stac-item
2022-03-24 09:34:25	ga_ls9c_ard_3-2-1_093073_2022-03-24_final.stac-item
2022-04-03 10:09:04	ga_ls9c_ard_3-2-1_099067_2022-04-03_final.stac-item
2022-04-11 09:21:58	ga_ls9c_ard_3-2-1_091073_2022-04-10_final.stac-item
2022-04-17 10:22:54	ga_ls9c_ard_3-2-1_101071_2022-04-17_final.stac-item
2022-04-20 09:21:40	ga_ls9c_ard_3-2-1_090088_2022-04-19_final.stac-item
2022-04-23 11:24:38	ga_ls9c_ard_3-2-1_111071_2022-04-23_final.stac-item
2022-05-27 11:14:26	ga_ls9c_ard_3-2-1_109077_2022-05-27_final.stac-item
2022-06-07 10:55:31	ga_ls9c_ard_3-2-1_106076_2022-06-07_final.stac-item
2022-06-13 10:18:53	ga_ls9c_ard_3-2-1_100077_2022-06-13_final.stac-item
2022-07-08 11:53:03	ga_ls9c_ard_3-2-1_115080_2022-07-08_final.stac-item
2022-07-24 10:13:28	ga_ls9c_ard_3-2-1_099078_2022-07-24_final.stac-item
2022-08-19 10:49:13	ga_ls9c_ard_3-2-1_105074_2022-08-19_final.stac-item
2022-08-19 10:50:01	ga_ls9c_ard_3-2-1_105076_2022-08-19_final.stac-item
2022-09-05 09:58:24	ga_ls9c_ard_3-2-1_096086_2022-09-05_final.stac-item
2022-09-09 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-09-09_final.stac-item
2022-09-10 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-09-10_final.stac-item
2022-09-15 10:33:57	ga_ls9c_ard_3-2-1_102082_2022-09-15_final.stac-item
2022-09-26 10:11:29	ga_ls9c_ard_3-2-1_099072_2022-09-26_final.stac-item
2022-09-26 11:53:33	ga_ls9c_ard_3-2-1_115080_2022-09-26_final.stac-item
2022-09-27 09:22:15	ga_ls9c_ard_3-2-1_090088_2022-09-26_final.stac-item
2022-10-01 10:33:37	ga_ls9c_ard_3-2-1_102081_2022-10-01_final.stac-item
2022-11-01 11:24:31	ga_ls9c_ard_3-2-1_111069_2022-11-01_final.stac-item
2022-11-15 11:38:07	ga_ls9c_ard_3-2-1_113072_2022-11-15_final.stac-item
2022-12-24 10:03:20	ga_ls9c_ard_3-2-1_098067_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
2023-02-01 10:10:24	ga_ls9c_ard_3-2-1_099069_2023-02-01_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-02-07 11:14:14	ga_ls9c_ard_3-2-1_109074_2023-02-07_final.stac-item
2023-02-09 09:23:47	ga_ls9c_ard_3-2-1_091076_2023-02-08_final.stac-item
2023-02-21 09:46:44	ga_ls9c_ard_3-2-1_095072_2023-02-21_final.stac-item
2023-04-06 10:10:40	ga_ls9c_ard_3-2-1_099071_2023-04-06_final.stac-item
2023-04-06 11:53:09	ga_ls9c_ard_3-2-1_115080_2023-04-06_final.stac-item
2023-05-15 10:18:55	ga_ls9c_ard_3-2-1_100077_2023-05-15_final.stac-item
2023-05-24 10:12:36	ga_ls9c_ard_3-2-1_099077_2023-05-24_final.stac-item
2023-06-06 09:45:15	ga_ls9c_ard_3-2-1_094086_2023-06-06_final.stac-item
2023-06-30 10:33:06	ga_ls9c_ard_3-2-1_102082_2023-06-30_final.stac-item
2023-07-19 09:27:16	ga_ls9c_ard_3-2-1_091087_2023-07-18_final.stac-item
2023-07-27 11:52:49	ga_ls9c_ard_3-2-1_115080_2023-07-27_final.stac-item
2023-07-29 09:56:49	ga_ls9c_ard_3-2-1_097068_2023-07-29_final.stac-item
2023-08-15 09:06:06	ga_ls9c_ard_3-2-1_088080_2023-08-14_final.stac-item
2023-08-16 09:45:46	ga_ls9c_ard_3-2-1_095071_2023-08-16_final.stac-item
2023-08-17 10:33:25	ga_ls9c_ard_3-2-1_102082_2023-08-17_final.stac-item
2023-09-03 11:11:41	ga_ls9c_ard_3-2-1_109069_2023-09-03_final.stac-item
2023-10-08 11:47:33	ga_ls9c_ard_3-2-1_114081_2023-10-08_final.stac-item
2023-10-15 10:14:09	ga_ls9c_ard_3-2-1_099079_2023-10-15_final.stac-item
2023-10-31 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-10-31_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-29 11:24:12	ga_ls9c_ard_3-2-1_110084_2023-11-29_final.stac-item
2023-12-03 09:22:10	ga_ls9c_ard_3-2-1_090088_2023-12-02_final.stac-item
2023-12-06 09:46:15	ga_ls9c_ard_3-2-1_095071_2023-12-06_final.stac-item
2023-12-07 10:28:18	ga_ls9c_ard_3-2-1_102068_2023-12-07_final.stac-item
2023-12-24 09:34:23	ga_ls9c_ard_3-2-1_093072_2023-12-24_final.stac-item
2024-01-02 11:08:13	ga_ls9c_ard_3-2-1_108075_2024-01-02_final.stac-item
2024-01-09 11:14:23	ga_ls9c_ard_3-2-1_109075_2024-01-09_final.stac-item
2024-01-14 11:31:45	ga_ls9c_ard_3-2-1_112072_2024-01-14_final.stac-item
2024-01-17 10:28:09	ga_ls9c_ard_3-2-1_101083_2024-01-17_final.stac-item
2024-02-05 09:17:25	ga_ls9c_ard_3-2-1_090076_2024-02-04_final.stac-item
2024-02-08 11:24:24	ga_ls9c_ard_3-2-1_111069_2024-02-08_final.stac-item
2024-02-26 11:14:14	ga_ls9c_ard_3-2-1_109075_2024-02-26_final.stac-item
2024-02-29 10:05:29	ga_ls9c_ard_3-2-1_098073_2024-02-29_final.stac-item
2024-03-01 09:15:04	ga_ls9c_ard_3-2-1_089086_2024-02-29_final.stac-item
2024-03-13 09:34:12	ga_ls9c_ard_3-2-1_093072_2024-03-13_final.stac-item
2024-03-27 11:24:32	ga_ls9c_ard_3-2-1_111070_2024-03-27_final.stac-item
2024-03-29 09:40:26	ga_ls9c_ard_3-2-1_093088_2024-03-29_final.stac-item
2024-04-14 11:17:37	ga_ls9c_ard_3-2-1_109084_2024-04-14_final.stac-item
2024-04-26 09:56:24	ga_ls9c_ard_3-2-1_097067_2024-04-26_final.stac-item
2024-04-27 09:07:09	ga_ls9c_ard_3-2-1_088083_2024-04-26_final.stac-item
2024-04-30 09:34:03	ga_ls9c_ard_3-2-1_093073_2024-04-30_final.stac-item
2024-04-30 11:13:20	ga_ls9c_ard_3-2-1_109074_2024-04-30_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