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

76 results

Time (local)	Label
2021-11-08 11:35:42	ga_ls9c_ard_3-2-1_113074_2021-11-08_final.stac-item
2021-12-26 10:25:46	ga_ls9c_ard_3-2-1_101077_2021-12-26_final.stac-item
2022-01-19 11:12:47	ga_ls9c_ard_3-2-1_109071_2022-01-19_final.stac-item
2022-02-18 09:46:58	ga_ls9c_ard_3-2-1_095073_2022-02-18_final.stac-item
2022-02-24 10:49:30	ga_ls9c_ard_3-2-1_105075_2022-02-24_final.stac-item
2022-03-03 09:17:31	ga_ls9c_ard_3-2-1_090077_2022-03-02_final.stac-item
2022-03-06 09:46:26	ga_ls9c_ard_3-2-1_095072_2022-03-06_final.stac-item
2022-03-12 10:49:50	ga_ls9c_ard_3-2-1_105076_2022-03-12_final.stac-item
2022-03-24 09:34:01	ga_ls9c_ard_3-2-1_093072_2022-03-24_final.stac-item
2022-03-24 09:35:12	ga_ls9c_ard_3-2-1_093075_2022-03-24_final.stac-item
2022-03-31 11:23:03	ga_ls9c_ard_3-2-1_110082_2022-03-31_final.stac-item
2022-04-02 11:10:17	ga_ls9c_ard_3-2-1_108081_2022-04-02_final.stac-item
2022-04-06 09:07:28	ga_ls9c_ard_3-2-1_088083_2022-04-05_final.stac-item
2022-05-09 11:25:21	ga_ls9c_ard_3-2-1_111073_2022-05-09_final.stac-item
2022-05-25 11:24:00	ga_ls9c_ard_3-2-1_111070_2022-05-25_final.stac-item
2022-06-05 09:27:24	ga_ls9c_ard_3-2-1_092072_2022-06-04_final.stac-item
2022-06-07 09:22:13	ga_ls9c_ard_3-2-1_090090_2022-06-06_final.stac-item
2022-07-26 09:57:09	ga_ls9c_ard_3-2-1_097068_2022-07-26_final.stac-item
2022-08-08 09:34:23	ga_ls9c_ard_3-2-1_092088_2022-08-08_final.stac-item
2022-08-17 09:28:40	ga_ls9c_ard_3-2-1_091089_2022-08-16_final.stac-item
2022-09-05 11:31:42	ga_ls9c_ard_3-2-1_112072_2022-09-05_final.stac-item
2022-09-10 10:14:09	ga_ls9c_ard_3-2-1_099079_2022-09-10_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_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 09:29:04	ga_ls9c_ard_3-2-1_092074_2022-10-10_final.stac-item
2022-10-17 10:33:18	ga_ls9c_ard_3-2-1_102080_2022-10-17_final.stac-item
2022-11-12 09:31:31	ga_ls9c_ard_3-2-1_092080_2022-11-12_final.stac-item
2022-11-14 10:53:16	ga_ls9c_ard_3-2-1_106068_2022-11-14_final.stac-item
2022-11-15 09:57:38	ga_ls9c_ard_3-2-1_097068_2022-11-15_final.stac-item
2022-11-20 10:19:46	ga_ls9c_ard_3-2-1_100077_2022-11-20_final.stac-item
2022-11-30 10:53:36	ga_ls9c_ard_3-2-1_106069_2022-11-30_final.stac-item
2022-12-07 11:02:12	ga_ls9c_ard_3-2-1_107075_2022-12-07_final.stac-item
2022-12-19 11:24:31	ga_ls9c_ard_3-2-1_111069_2022-12-19_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-01-24 09:22:26	ga_ls9c_ard_3-2-1_091073_2023-01-23_final.stac-item
2023-02-16 11:08:23	ga_ls9c_ard_3-2-1_108075_2023-02-16_final.stac-item
2023-02-18 10:55:59	ga_ls9c_ard_3-2-1_106075_2023-02-18_final.stac-item
2023-02-25 09:23:09	ga_ls9c_ard_3-2-1_091075_2023-02-24_final.stac-item
2023-02-25 11:05:13	ga_ls9c_ard_3-2-1_107083_2023-02-25_final.stac-item
2023-03-04 09:28:54	ga_ls9c_ard_3-2-1_092074_2023-03-03_final.stac-item
2023-03-11 09:34:35	ga_ls9c_ard_3-2-1_093073_2023-03-11_final.stac-item
2023-03-23 09:58:03	ga_ls9c_ard_3-2-1_097070_2023-03-23_final.stac-item
2023-03-27 09:33:39	ga_ls9c_ard_3-2-1_093071_2023-03-27_final.stac-item
2023-06-07 10:27:18	ga_ls9c_ard_3-2-1_101083_2023-06-07_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-07-11 10:15:30	ga_ls9c_ard_3-2-1_099084_2023-07-11_final.stac-item
2023-07-28 09:16:20	ga_ls9c_ard_3-2-1_090075_2023-07-27_final.stac-item
2023-07-30 09:06:48	ga_ls9c_ard_3-2-1_088082_2023-07-29_final.stac-item
2023-08-13 10:55:21	ga_ls9c_ard_3-2-1_106075_2023-08-13_final.stac-item
2023-08-19 10:21:05	ga_ls9c_ard_3-2-1_100082_2023-08-19_final.stac-item
2023-09-12 09:27:56	ga_ls9c_ard_3-2-1_092072_2023-09-11_final.stac-item
2023-09-28 11:07:32	ga_ls9c_ard_3-2-1_108074_2023-09-28_final.stac-item
2023-10-03 09:52:28	ga_ls9c_ard_3-2-1_095087_2023-10-03_final.stac-item
2023-11-04 11:24:37	ga_ls9c_ard_3-2-1_111070_2023-11-04_final.stac-item
2023-11-21 10:30:19	ga_ls9c_ard_3-2-1_102073_2023-11-21_final.stac-item
2023-11-23 10:21:59	ga_ls9c_ard_3-2-1_100083_2023-11-23_final.stac-item
2023-12-03 09:22:34	ga_ls9c_ard_3-2-1_090089_2023-12-02_final.stac-item
2023-12-14 10:39:44	ga_ls9c_ard_3-2-1_103081_2023-12-14_final.stac-item
2023-12-25 10:19:39	ga_ls9c_ard_3-2-1_100077_2023-12-25_final.stac-item
2024-01-02 09:28:56	ga_ls9c_ard_3-2-1_092074_2024-01-01_final.stac-item
2024-01-03 10:14:11	ga_ls9c_ard_3-2-1_099079_2024-01-03_final.stac-item
2024-01-27 09:23:07	ga_ls9c_ard_3-2-1_091075_2024-01-26_final.stac-item
2024-01-29 10:50:04	ga_ls9c_ard_3-2-1_105076_2024-01-29_final.stac-item
2024-02-05 09:19:48	ga_ls9c_ard_3-2-1_090082_2024-02-04_final.stac-item
2024-02-12 09:23:10	ga_ls9c_ard_3-2-1_091075_2024-02-11_final.stac-item
2024-02-26 11:14:38	ga_ls9c_ard_3-2-1_109076_2024-02-26_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-08 10:53:22	ga_ls9c_ard_3-2-1_106069_2024-03-08_final.stac-item
2024-03-08 10:56:10	ga_ls9c_ard_3-2-1_106076_2024-03-08_final.stac-item
2024-03-10 10:41:24	ga_ls9c_ard_3-2-1_104070_2024-03-10_final.stac-item
2024-03-15 09:23:02	ga_ls9c_ard_3-2-1_091075_2024-03-14_final.stac-item
2024-03-27 09:52:02	ga_ls9c_ard_3-2-1_095086_2024-03-27_final.stac-item
2024-03-29 09:34:27	ga_ls9c_ard_3-2-1_093073_2024-03-29_final.stac-item
2024-04-08 10:10:42	ga_ls9c_ard_3-2-1_099071_2024-04-08_final.stac-item
2024-04-11 10:42:22	ga_ls9c_ard_3-2-1_104073_2024-04-11_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