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

66 results

Time (local)	Label
2021-11-12 11:00:36	ga_ls9c_ard_3-2-1_106080_2021-11-12_final.stac-item
2021-12-09 11:19:04	ga_ls9c_ard_3-2-1_110071_2021-12-09_final.stac-item
2021-12-10 10:27:25	ga_ls9c_ard_3-2-1_101081_2021-12-10_final.stac-item
2021-12-31 10:41:31	ga_ls9c_ard_3-2-1_104070_2021-12-31_final.stac-item
2022-01-14 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-01-13_final.stac-item
2022-01-14 09:18:31	ga_ls9c_ard_3-2-1_090079_2022-01-13_final.stac-item
2022-01-17 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-01-17_final.stac-item
2022-01-26 09:45:17	ga_ls9c_ard_3-2-1_094084_2022-01-26_final.stac-item
2022-03-27 11:46:10	ga_ls9c_ard_3-2-1_114078_2022-03-27_final.stac-item
2022-04-11 11:05:15	ga_ls9c_ard_3-2-1_107084_2022-04-11_final.stac-item
2022-04-18 09:34:27	ga_ls9c_ard_3-2-1_092089_2022-04-18_final.stac-item
2022-04-25 11:11:29	ga_ls9c_ard_3-2-1_109069_2022-04-25_final.stac-item
2022-05-05 11:50:55	ga_ls9c_ard_3-2-1_115075_2022-05-05_final.stac-item
2022-05-23 11:39:57	ga_ls9c_ard_3-2-1_113079_2022-05-23_final.stac-item
2022-05-28 10:17:13	ga_ls9c_ard_3-2-1_100073_2022-05-28_final.stac-item
2022-06-09 10:42:45	ga_ls9c_ard_3-2-1_104075_2022-06-09_final.stac-item
2022-06-16 09:13:21	ga_ls9c_ard_3-2-1_089083_2022-06-15_final.stac-item
2022-09-03 10:09:34	ga_ls9c_ard_3-2-1_098083_2022-09-03_final.stac-item
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final.stac-item
2022-09-16 09:33:56	ga_ls9c_ard_3-2-1_093071_2022-09-16_final.stac-item
2022-10-16 11:25:44	ga_ls9c_ard_3-2-1_111072_2022-10-16_final.stac-item
2022-10-25 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-10-25_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-12-01 09:58:22	ga_ls9c_ard_3-2-1_097070_2022-12-01_final.stac-item
2022-12-04 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-12-04_final.stac-item
2022-12-08 10:09:47	ga_ls9c_ard_3-2-1_098083_2022-12-08_final.stac-item
2022-12-31 10:14:46	ga_ls9c_ard_3-2-1_099080_2022-12-31_final.stac-item
2023-01-02 11:39:18	ga_ls9c_ard_3-2-1_113075_2023-01-02_final.stac-item
2023-02-05 09:51:18	ga_ls9c_ard_3-2-1_095083_2023-02-05_final.stac-item
2023-02-07 09:35:45	ga_ls9c_ard_3-2-1_093075_2023-02-07_final.stac-item
2023-02-12 11:36:45	ga_ls9c_ard_3-2-1_112084_2023-02-12_final.stac-item
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final.stac-item
2023-03-10 10:28:36	ga_ls9c_ard_3-2-1_102069_2023-03-10_final.stac-item
2023-03-21 10:14:26	ga_ls9c_ard_3-2-1_099080_2023-03-21_final.stac-item
2023-04-16 10:47:15	ga_ls9c_ard_3-2-1_105070_2023-04-16_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-04-22 11:52:15	ga_ls9c_ard_3-2-1_115078_2023-04-22_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-16 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-05-16_final.stac-item
2023-05-23 11:11:02	ga_ls9c_ard_3-2-1_108084_2023-05-23_final.stac-item
2023-05-29 10:27:57	ga_ls9c_ard_3-2-1_102069_2023-05-29_final.stac-item
2023-06-04 09:52:02	ga_ls9c_ard_3-2-1_096072_2023-06-04_final.stac-item
2023-07-03 11:03:39	ga_ls9c_ard_3-2-1_107081_2023-07-03_final.stac-item
2023-07-30 10:42:30	ga_ls9c_ard_3-2-1_104074_2023-07-30_final.stac-item
2023-08-13 10:53:46	ga_ls9c_ard_3-2-1_106071_2023-08-13_final.stac-item
2023-08-21 10:07:09	ga_ls9c_ard_3-2-1_098078_2023-08-21_final.stac-item
2023-09-16 10:40:31	ga_ls9c_ard_3-2-1_104068_2023-09-16_final.stac-item
2023-09-17 09:52:28	ga_ls9c_ard_3-2-1_095087_2023-09-17_final.stac-item
2023-10-02 10:42:30	ga_ls9c_ard_3-2-1_104073_2023-10-02_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-10-17 09:58:12	ga_ls9c_ard_3-2-1_097070_2023-10-17_final.stac-item
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final.stac-item
2023-11-19 10:40:39	ga_ls9c_ard_3-2-1_104068_2023-11-19_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-24 11:05:39	ga_ls9c_ard_3-2-1_107084_2023-11-24_final.stac-item
2024-01-19 10:16:11	ga_ls9c_ard_3-2-1_099084_2024-01-19_final.stac-item
2024-01-19 11:51:28	ga_ls9c_ard_3-2-1_115075_2024-01-19_final.stac-item
2024-01-23 11:28:42	ga_ls9c_ard_3-2-1_111080_2024-01-23_final.stac-item
2024-01-27 09:25:07	ga_ls9c_ard_3-2-1_091080_2024-01-26_final.stac-item
2024-02-29 10:10:17	ga_ls9c_ard_3-2-1_098085_2024-02-29_final.stac-item
2024-03-13 09:35:00	ga_ls9c_ard_3-2-1_093074_2024-03-13_final.stac-item
2024-03-31 11:00:11	ga_ls9c_ard_3-2-1_107071_2024-03-31_final.stac-item
2024-04-01 10:02:58	ga_ls9c_ard_3-2-1_098067_2024-04-01_final.stac-item
2024-04-24 11:51:13	ga_ls9c_ard_3-2-1_115076_2024-04-24_final.stac-item
2024-04-30 09:37:15	ga_ls9c_ard_3-2-1_093081_2024-04-30_final.stac-item
2024-05-05 11:35:28	ga_ls9c_ard_3-2-1_112083_2024-05-05_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