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

73 results

Time (local)	Label
2021-11-22 09:26:27	ga_ls9c_ard_3-2-1_091079_2021-11-21_final.stac-item
2021-12-17 10:29:56	ga_ls9c_ard_3-2-1_102072_2021-12-17_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-03 10:28:44	ga_ls9c_ard_3-2-1_102069_2022-02-03_final.stac-item
2022-02-07 10:08:24	ga_ls9c_ard_3-2-1_098080_2022-02-07_final.stac-item
2022-02-14 10:14:32	ga_ls9c_ard_3-2-1_099080_2022-02-14_final.stac-item
2022-03-03 10:54:00	ga_ls9c_ard_3-2-1_106071_2022-03-03_final.stac-item
2022-03-04 11:38:28	ga_ls9c_ard_3-2-1_113074_2022-03-04_final.stac-item
2022-05-29 09:27:11	ga_ls9c_ard_3-2-1_091087_2022-05-28_final.stac-item
2022-06-03 09:39:45	ga_ls9c_ard_3-2-1_094072_2022-06-03_final.stac-item
2022-06-04 10:27:01	ga_ls9c_ard_3-2-1_101082_2022-06-04_final.stac-item
2022-06-15 10:08:57	ga_ls9c_ard_3-2-1_098083_2022-06-15_final.stac-item
2022-07-09 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-07-08_final.stac-item
2022-07-17 10:03:11	ga_ls9c_ard_3-2-1_098068_2022-07-17_final.stac-item
2022-07-24 10:15:04	ga_ls9c_ard_3-2-1_099082_2022-07-24_final.stac-item
2022-07-31 10:17:21	ga_ls9c_ard_3-2-1_100072_2022-07-31_final.stac-item
2022-08-08 09:33:35	ga_ls9c_ard_3-2-1_092086_2022-08-08_final.stac-item
2022-08-10 10:53:21	ga_ls9c_ard_3-2-1_106069_2022-08-10_final.stac-item
2022-08-11 09:57:44	ga_ls9c_ard_3-2-1_097069_2022-08-11_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 10:53:50	ga_ls9c_ard_3-2-1_106070_2022-09-11_final.stac-item
2022-10-29 10:56:25	ga_ls9c_ard_3-2-1_106076_2022-10-29_final.stac-item
2022-11-01 11:25:19	ga_ls9c_ard_3-2-1_111071_2022-11-01_final.stac-item
2022-11-14 10:59:15	ga_ls9c_ard_3-2-1_106083_2022-11-14_final.stac-item
2022-11-17 11:26:57	ga_ls9c_ard_3-2-1_111075_2022-11-17_final.stac-item
2022-11-20 10:22:34	ga_ls9c_ard_3-2-1_100084_2022-11-20_final.stac-item
2022-11-29 11:52:26	ga_ls9c_ard_3-2-1_115077_2022-11-29_final.stac-item
2022-12-15 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-12-15_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2022-12-26 11:31:53	ga_ls9c_ard_3-2-1_112072_2022-12-26_final.stac-item
2022-12-31 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-31_final.stac-item
2023-01-14 10:24:41	ga_ls9c_ard_3-2-1_101074_2023-01-14_final.stac-item
2023-01-18 10:01:05	ga_ls9c_ard_3-2-1_097077_2023-01-18_final.stac-item
2023-01-22 09:34:21	ga_ls9c_ard_3-2-1_093072_2023-01-22_final.stac-item
2023-02-09 09:24:11	ga_ls9c_ard_3-2-1_091077_2023-02-08_final.stac-item
2023-03-13 09:23:02	ga_ls9c_ard_3-2-1_091075_2023-03-12_final.stac-item
2023-03-26 10:30:06	ga_ls9c_ard_3-2-1_102073_2023-03-26_final.stac-item
2023-04-08 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-04-08_final.stac-item
2023-05-03 09:57:03	ga_ls9c_ard_3-2-1_096084_2023-05-03_final.stac-item
2023-05-21 11:23:26	ga_ls9c_ard_3-2-1_110084_2023-05-21_final.stac-item
2023-06-02 10:08:00	ga_ls9c_ard_3-2-1_098081_2023-06-02_final.stac-item
2023-06-19 10:48:20	ga_ls9c_ard_3-2-1_105074_2023-06-19_final.stac-item
2023-06-22 11:17:38	ga_ls9c_ard_3-2-1_110070_2023-06-22_final.stac-item
2023-06-30 10:27:31	ga_ls9c_ard_3-2-1_102068_2023-06-30_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-15 09:45:36	ga_ls9c_ard_3-2-1_095071_2023-07-15_final.stac-item
2023-07-16 10:28:28	ga_ls9c_ard_3-2-1_102070_2023-07-16_final.stac-item
2023-07-19 10:59:22	ga_ls9c_ard_3-2-1_107070_2023-07-19_final.stac-item
2023-08-01 10:27:46	ga_ls9c_ard_3-2-1_102068_2023-08-01_final.stac-item
2023-08-02 11:14:14	ga_ls9c_ard_3-2-1_109076_2023-08-02_final.stac-item
2023-08-06 10:48:45	ga_ls9c_ard_3-2-1_105074_2023-08-06_final.stac-item
2023-08-21 10:06:45	ga_ls9c_ard_3-2-1_098077_2023-08-21_final.stac-item
2023-08-25 09:45:17	ga_ls9c_ard_3-2-1_094085_2023-08-25_final.stac-item
2023-08-30 11:38:23	ga_ls9c_ard_3-2-1_113074_2023-08-30_final.stac-item
2023-09-05 09:23:40	ga_ls9c_ard_3-2-1_091077_2023-09-04_final.stac-item
2023-09-05 09:28:03	ga_ls9c_ard_3-2-1_091088_2023-09-04_final.stac-item
2023-11-08 09:24:39	ga_ls9c_ard_3-2-1_091079_2023-11-07_final.stac-item
2023-11-09 10:03:08	ga_ls9c_ard_3-2-1_098067_2023-11-09_final.stac-item
2023-11-16 10:10:54	ga_ls9c_ard_3-2-1_099071_2023-11-16_final.stac-item
2023-11-26 09:13:13	ga_ls9c_ard_3-2-1_089081_2023-11-25_final.stac-item
2023-12-14 10:36:09	ga_ls9c_ard_3-2-1_103072_2023-12-14_final.stac-item
2024-01-25 11:14:20	ga_ls9c_ard_3-2-1_109075_2024-01-25_final.stac-item
2024-01-30 09:58:27	ga_ls9c_ard_3-2-1_096086_2024-01-30_final.stac-item
2024-02-06 09:57:29	ga_ls9c_ard_3-2-1_097068_2024-02-06_final.stac-item
2024-03-07 11:52:59	ga_ls9c_ard_3-2-1_115079_2024-03-07_final.stac-item
2024-03-08 10:58:34	ga_ls9c_ard_3-2-1_106082_2024-03-08_final.stac-item
2024-03-17 09:16:40	ga_ls9c_ard_3-2-1_089090_2024-03-16_final.stac-item
2024-03-31 09:27:41	ga_ls9c_ard_3-2-1_091087_2024-03-30_final.stac-item
2024-04-15 10:18:00	ga_ls9c_ard_3-2-1_100074_2024-04-15_final.stac-item
2024-05-11 10:55:35	ga_ls9c_ard_3-2-1_106076_2024-05-11_final.stac-item
2024-05-14 11:28:25	ga_ls9c_ard_3-2-1_111081_2024-05-14_final.stac-item
2024-05-20 09:13:59	ga_ls9c_ard_3-2-1_089085_2024-05-19_nrt.stac-item
2024-05-27 09:16:53	ga_ls9c_ard_3-2-1_090077_2024-05-26_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years