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

78 results

Time (local)	Label
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-23 09:58:04	ga_ls9c_ard_3-2-1_096085_2021-12-23_final.stac-item
2021-12-29 09:17:47	ga_ls9c_ard_3-2-1_090077_2021-12-28_final.stac-item
2022-01-05 09:26:45	ga_ls9c_ard_3-2-1_091084_2022-01-04_final.stac-item
2022-01-20 11:58:51	ga_ls9c_ard_3-2-1_116078_2022-01-20_final.stac-item
2022-01-23 09:11:59	ga_ls9c_ard_3-2-1_089078_2022-01-22_final.stac-item
2022-03-26 09:27:37	ga_ls9c_ard_3-2-1_091087_2022-03-25_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-03-28 10:46:57	ga_ls9c_ard_3-2-1_105069_2022-03-28_final.stac-item
2022-04-12 10:03:38	ga_ls9c_ard_3-2-1_098069_2022-04-12_final.stac-item
2022-04-13 09:11:11	ga_ls9c_ard_3-2-1_089077_2022-04-12_final.stac-item
2022-04-19 11:52:12	ga_ls9c_ard_3-2-1_115078_2022-04-19_final.stac-item
2022-05-19 10:27:00	ga_ls9c_ard_3-2-1_101082_2022-05-19_final.stac-item
2022-05-20 09:34:09	ga_ls9c_ard_3-2-1_092089_2022-05-20_final.stac-item
2022-06-04 10:27:24	ga_ls9c_ard_3-2-1_101083_2022-06-04_final.stac-item
2022-06-23 09:17:44	ga_ls9c_ard_3-2-1_090078_2022-06-22_final.stac-item
2022-06-24 11:41:06	ga_ls9c_ard_3-2-1_113081_2022-06-24_final.stac-item
2022-06-29 10:17:11	ga_ls9c_ard_3-2-1_100072_2022-06-29_final.stac-item
2022-09-09 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-09-09_final.stac-item
2022-09-12 10:00:37	ga_ls9c_ard_3-2-1_097076_2022-09-12_final.stac-item
2022-10-08 10:39:48	ga_ls9c_ard_3-2-1_103081_2022-10-08_final.stac-item
2022-10-11 09:33:03	ga_ls9c_ard_3-2-1_092084_2022-10-11_final.stac-item
2022-10-17 10:29:43	ga_ls9c_ard_3-2-1_102071_2022-10-17_final.stac-item
2022-10-29 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-10-29_final.stac-item
2022-11-03 09:38:02	ga_ls9c_ard_3-2-1_093081_2022-11-03_final.stac-item
2022-11-15 09:59:14	ga_ls9c_ard_3-2-1_097072_2022-11-15_final.stac-item
2022-11-30 10:54:00	ga_ls9c_ard_3-2-1_106070_2022-11-30_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-28 09:44:38	ga_ls9c_ard_3-2-1_094082_2022-12-28_final.stac-item
2023-01-11 09:57:48	ga_ls9c_ard_3-2-1_096084_2023-01-11_final.stac-item
2023-01-29 11:24:20	ga_ls9c_ard_3-2-1_110084_2023-01-29_final.stac-item
2023-02-13 10:38:44	ga_ls9c_ard_3-2-1_103078_2023-02-13_final.stac-item
2023-02-16 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-02-16_final.stac-item
2023-02-18 09:22:18	ga_ls9c_ard_3-2-1_090088_2023-02-17_final.stac-item
2023-03-14 10:07:05	ga_ls9c_ard_3-2-1_098077_2023-03-14_final.stac-item
2023-03-15 09:13:52	ga_ls9c_ard_3-2-1_089083_2023-03-14_final.stac-item
2023-03-24 10:40:30	ga_ls9c_ard_3-2-1_104068_2023-03-24_final.stac-item
2023-03-27 09:37:15	ga_ls9c_ard_3-2-1_093080_2023-03-27_final.stac-item
2023-03-31 10:46:10	ga_ls9c_ard_3-2-1_105067_2023-03-31_final.stac-item
2023-04-30 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-04-29_final.stac-item
2023-05-03 09:51:52	ga_ls9c_ard_3-2-1_096071_2023-05-03_final.stac-item
2023-05-26 09:58:14	ga_ls9c_ard_3-2-1_097072_2023-05-26_final.stac-item
2023-06-01 09:21:57	ga_ls9c_ard_3-2-1_091074_2023-05-31_final.stac-item
2023-06-06 09:43:39	ga_ls9c_ard_3-2-1_094082_2023-06-06_final.stac-item
2023-06-07 10:24:31	ga_ls9c_ard_3-2-1_101076_2023-06-07_final.stac-item
2023-06-11 11:41:01	ga_ls9c_ard_3-2-1_113082_2023-06-11_final.stac-item
2023-06-14 10:29:24	ga_ls9c_ard_3-2-1_102073_2023-06-14_final.stac-item
2023-07-04 10:04:27	ga_ls9c_ard_3-2-1_098072_2023-07-04_final.stac-item
2023-07-06 11:34:36	ga_ls9c_ard_3-2-1_112081_2023-07-06_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-07-11 10:13:54	ga_ls9c_ard_3-2-1_099080_2023-07-11_final.stac-item
2023-07-21 09:15:42	ga_ls9c_ard_3-2-1_089089_2023-07-20_final.stac-item
2023-07-27 11:50:25	ga_ls9c_ard_3-2-1_115074_2023-07-27_final.stac-item
2023-08-01 10:31:22	ga_ls9c_ard_3-2-1_102077_2023-08-01_final.stac-item
2023-08-13 09:17:16	ga_ls9c_ard_3-2-1_090077_2023-08-12_final.stac-item
2023-09-01 09:46:21	ga_ls9c_ard_3-2-1_095072_2023-09-01_final.stac-item
2023-09-17 11:24:34	ga_ls9c_ard_3-2-1_111070_2023-09-17_final.stac-item
2023-09-28 09:28:39	ga_ls9c_ard_3-2-1_092074_2023-09-27_final.stac-item
2023-10-12 11:23:17	ga_ls9c_ard_3-2-1_110082_2023-10-12_final.stac-item
2023-10-23 11:01:36	ga_ls9c_ard_3-2-1_107074_2023-10-23_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final.stac-item
2023-11-15 09:28:50	ga_ls9c_ard_3-2-1_092074_2023-11-14_final.stac-item
2023-11-16 11:51:47	ga_ls9c_ard_3-2-1_115076_2023-11-16_final.stac-item
2023-12-01 11:08:15	ga_ls9c_ard_3-2-1_108075_2023-12-01_final.stac-item
2023-12-19 10:55:31	ga_ls9c_ard_3-2-1_106074_2023-12-19_final.stac-item
2023-12-31 11:19:24	ga_ls9c_ard_3-2-1_110072_2023-12-31_final.stac-item
2024-01-12 11:44:54	ga_ls9c_ard_3-2-1_114074_2024-01-12_final.stac-item
2024-01-26 10:21:56	ga_ls9c_ard_3-2-1_100083_2024-01-26_final.stac-item
2024-03-01 10:46:22	ga_ls9c_ard_3-2-1_105067_2024-03-01_final.stac-item
2024-03-09 11:39:50	ga_ls9c_ard_3-2-1_113077_2024-03-09_final.stac-item
2024-03-13 09:34:12	ga_ls9c_ard_3-2-1_093072_2024-03-13_final.stac-item
2024-03-23 10:12:03	ga_ls9c_ard_3-2-1_099074_2024-03-23_final.stac-item
2024-03-25 09:57:16	ga_ls9c_ard_3-2-1_097068_2024-03-25_final.stac-item
2024-03-31 09:22:53	ga_ls9c_ard_3-2-1_091075_2024-03-30_final.stac-item
2024-04-03 11:35:28	ga_ls9c_ard_3-2-1_112082_2024-04-03_final.stac-item
2024-04-06 10:27:04	ga_ls9c_ard_3-2-1_101081_2024-04-06_final.stac-item
2024-04-09 10:53:57	ga_ls9c_ard_3-2-1_106071_2024-04-09_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years