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

79 results

Time (local)	Label
2021-11-06 10:19:22	ga_ls9c_ard_3-2-1_100083_2021-11-06_final.stac-item
2021-11-18 09:59:11	ga_ls9c_ard_3-2-1_097067_2021-11-18_final.stac-item
2021-12-06 09:16:54	ga_ls9c_ard_3-2-1_089090_2021-12-05_final.stac-item
2021-12-29 10:53:29	ga_ls9c_ard_3-2-1_106069_2021-12-29_final.stac-item
2022-01-05 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-04_final.stac-item
2022-01-05 11:04:02	ga_ls9c_ard_3-2-1_107080_2022-01-05_final.stac-item
2022-01-21 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-01-20_final.stac-item
2022-01-23 09:10:23	ga_ls9c_ard_3-2-1_089074_2022-01-22_final.stac-item
2022-01-24 09:57:39	ga_ls9c_ard_3-2-1_096084_2022-01-24_final.stac-item
2022-02-21 10:21:26	ga_ls9c_ard_3-2-1_100082_2022-02-21_final.stac-item
2022-02-22 09:21:48	ga_ls9c_ard_3-2-1_091072_2022-02-21_final.stac-item
2022-02-27 09:40:41	ga_ls9c_ard_3-2-1_094073_2022-02-27_final.stac-item
2022-03-05 09:07:09	ga_ls9c_ard_3-2-1_088082_2022-03-04_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-04-03 10:09:52	ga_ls9c_ard_3-2-1_099069_2022-04-03_final.stac-item
2022-04-10 10:19:36	ga_ls9c_ard_3-2-1_100078_2022-04-10_final.stac-item
2022-04-23 11:24:14	ga_ls9c_ard_3-2-1_111070_2022-04-23_final.stac-item
2022-06-05 09:27:24	ga_ls9c_ard_3-2-1_092072_2022-06-04_final.stac-item
2022-06-21 09:27:38	ga_ls9c_ard_3-2-1_092072_2022-06-20_final.stac-item
2022-08-29 09:52:14	ga_ls9c_ard_3-2-1_095086_2022-08-29_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-12 10:04:13	ga_ls9c_ard_3-2-1_097085_2022-09-12_final.stac-item
2022-09-25 09:33:24	ga_ls9c_ard_3-2-1_092085_2022-09-25_final.stac-item
2022-09-29 10:40:47	ga_ls9c_ard_3-2-1_104068_2022-09-29_final.stac-item
2022-10-05 10:09:41	ga_ls9c_ard_3-2-1_098083_2022-10-05_final.stac-item
2022-10-06 09:12:04	ga_ls9c_ard_3-2-1_089078_2022-10-05_final.stac-item
2022-10-12 10:11:08	ga_ls9c_ard_3-2-1_099071_2022-10-12_final.stac-item
2022-10-16 11:26:32	ga_ls9c_ard_3-2-1_111074_2022-10-16_final.stac-item
2022-10-20 09:22:08	ga_ls9c_ard_3-2-1_091072_2022-10-19_final.stac-item
2022-10-22 10:49:52	ga_ls9c_ard_3-2-1_105075_2022-10-22_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-10-28 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-10-28_final.stac-item
2022-10-30 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-30_final.stac-item
2022-11-03 09:38:50	ga_ls9c_ard_3-2-1_093083_2022-11-03_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_interim.stac-item
2022-11-13 10:16:23	ga_ls9c_ard_3-2-1_099084_2022-11-13_final.stac-item
2022-11-22 10:05:01	ga_ls9c_ard_3-2-1_098071_2022-11-22_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-07 09:29:18	ga_ls9c_ard_3-2-1_091090_2022-12-06_final.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-18 10:44:27	ga_ls9c_ard_3-2-1_104077_2022-12-18_final.stac-item
2022-12-19 11:24:31	ga_ls9c_ard_3-2-1_111069_2022-12-19_final.stac-item
2023-01-15 11:07:56	ga_ls9c_ard_3-2-1_108074_2023-01-15_final.stac-item
2023-01-16 10:12:18	ga_ls9c_ard_3-2-1_099074_2023-01-16_final.stac-item
2023-01-24 09:24:02	ga_ls9c_ard_3-2-1_091077_2023-01-23_final.stac-item
2023-02-02 09:18:46	ga_ls9c_ard_3-2-1_090079_2023-02-01_final.stac-item
2023-02-18 09:17:54	ga_ls9c_ard_3-2-1_090077_2023-02-17_final.stac-item
2023-03-13 09:21:50	ga_ls9c_ard_3-2-1_091072_2023-03-12_final.stac-item
2023-03-20 09:33:10	ga_ls9c_ard_3-2-1_092085_2023-03-20_final.stac-item
2023-04-18 10:39:17	ga_ls9c_ard_3-2-1_103081_2023-04-18_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-06-09 10:10:08	ga_ls9c_ard_3-2-1_099071_2023-06-09_final.stac-item
2023-06-19 09:10:39	ga_ls9c_ard_3-2-1_089077_2023-06-18_final.stac-item
2023-07-31 11:23:47	ga_ls9c_ard_3-2-1_111069_2023-07-31_final.stac-item
2023-08-16 11:25:27	ga_ls9c_ard_3-2-1_111073_2023-08-16_final.stac-item
2023-09-11 10:27:32	ga_ls9c_ard_3-2-1_101082_2023-09-11_final.stac-item
2023-09-17 11:26:10	ga_ls9c_ard_3-2-1_111074_2023-09-17_final.stac-item
2023-09-30 10:56:01	ga_ls9c_ard_3-2-1_106076_2023-09-30_final.stac-item
2023-10-18 10:42:40	ga_ls9c_ard_3-2-1_104073_2023-10-18_final.stac-item
2023-10-19 11:30:20	ga_ls9c_ard_3-2-1_111084_2023-10-19_final.stac-item
2023-10-31 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-10-31_final.stac-item
2023-11-11 11:31:39	ga_ls9c_ard_3-2-1_112072_2023-11-11_final.stac-item
2023-11-23 10:19:35	ga_ls9c_ard_3-2-1_100077_2023-11-23_final.stac-item
2023-12-05 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-12-04_final.stac-item
2023-12-11 10:03:13	ga_ls9c_ard_3-2-1_098067_2023-12-11_final.stac-item
2023-12-18 10:11:03	ga_ls9c_ard_3-2-1_099071_2023-12-18_final.stac-item
2023-12-26 09:22:49	ga_ls9c_ard_3-2-1_091074_2023-12-25_final.stac-item
2023-12-30 10:36:09	ga_ls9c_ard_3-2-1_103072_2023-12-30_final.stac-item
2024-01-03 10:11:23	ga_ls9c_ard_3-2-1_099072_2024-01-03_final.stac-item
2024-01-13 09:12:24	ga_ls9c_ard_3-2-1_089079_2024-01-12_final.stac-item
2024-02-21 09:21:36	ga_ls9c_ard_3-2-1_090087_2024-02-20_final.stac-item
2024-03-05 10:28:03	ga_ls9c_ard_3-2-1_101083_2024-03-05_final.stac-item
2024-03-08 09:21:40	ga_ls9c_ard_3-2-1_090087_2024-03-07_final.stac-item
2024-03-22 09:29:12	ga_ls9c_ard_3-2-1_092075_2024-03-21_final.stac-item
2024-03-27 09:46:27	ga_ls9c_ard_3-2-1_095072_2024-03-27_final.stac-item
2024-04-19 09:52:47	ga_ls9c_ard_3-2-1_096073_2024-04-19_final.stac-item
2024-04-21 09:39:33	ga_ls9c_ard_3-2-1_094071_2024-04-21_final.stac-item
2024-04-21 09:39:33	ga_ls9c_ard_3-2-1_094071_2024-04-21_interim.stac-item
2024-04-26 10:03:35	ga_ls9c_ard_3-2-1_097085_2024-04-26_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