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

61 results

Time (local)	Label
2021-11-07 09:18:16	ga_ls9c_ard_3-2-1_090077_2021-11-06_final.stac-item
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final.stac-item
2021-12-20 09:27:57	ga_ls9c_ard_3-2-1_091087_2021-12-19_final.stac-item
2022-01-04 10:19:11	ga_ls9c_ard_3-2-1_100076_2022-01-04_final.stac-item
2022-01-12 11:08:35	ga_ls9c_ard_3-2-1_108076_2022-01-12_final.stac-item
2022-02-01 09:07:24	ga_ls9c_ard_3-2-1_088082_2022-01-31_final.stac-item
2022-02-13 09:28:05	ga_ls9c_ard_3-2-1_092072_2022-02-12_final.stac-item
2022-02-20 11:11:53	ga_ls9c_ard_3-2-1_109069_2022-02-20_final.stac-item
2022-04-04 09:17:50	ga_ls9c_ard_3-2-1_090078_2022-04-03_final.stac-item
2022-05-07 10:03:39	ga_ls9c_ard_3-2-1_097085_2022-05-07_final.stac-item
2022-05-20 09:34:09	ga_ls9c_ard_3-2-1_092089_2022-05-20_final.stac-item
2022-05-29 09:21:36	ga_ls9c_ard_3-2-1_091073_2022-05-28_final.stac-item
2022-06-10 09:45:33	ga_ls9c_ard_3-2-1_095071_2022-06-10_final.stac-item
2022-07-01 10:03:13	ga_ls9c_ard_3-2-1_098068_2022-07-01_final.stac-item
2022-07-01 11:44:30	ga_ls9c_ard_3-2-1_114074_2022-07-01_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-08-26 09:22:07	ga_ls9c_ard_3-2-1_090088_2022-08-25_final.stac-item
2022-08-27 11:42:16	ga_ls9c_ard_3-2-1_113083_2022-08-27_final.stac-item
2022-09-11 10:56:14	ga_ls9c_ard_3-2-1_106076_2022-09-11_final.stac-item
2022-09-14 09:51:28	ga_ls9c_ard_3-2-1_095084_2022-09-14_final.stac-item
2022-09-26 10:11:05	ga_ls9c_ard_3-2-1_099071_2022-09-26_final.stac-item
2022-10-29 10:55:38	ga_ls9c_ard_3-2-1_106074_2022-10-29_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-12-03 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-12-03_final.stac-item
2022-12-15 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-12-15_final.stac-item
2022-12-26 09:52:12	ga_ls9c_ard_3-2-1_096070_2022-12-26_final.stac-item
2022-12-30 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-30_final.stac-item
2023-01-02 10:04:24	ga_ls9c_ard_3-2-1_097085_2023-01-02_final.stac-item
2023-02-09 09:24:11	ga_ls9c_ard_3-2-1_091077_2023-02-08_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-03-16 09:52:20	ga_ls9c_ard_3-2-1_096071_2023-03-16_final.stac-item
2023-03-20 09:33:58	ga_ls9c_ard_3-2-1_092087_2023-03-20_final.stac-item
2023-03-22 10:53:41	ga_ls9c_ard_3-2-1_106070_2023-03-22_final.stac-item
2023-04-14 09:27:07	ga_ls9c_ard_3-2-1_091086_2023-04-13_final.stac-item
2023-04-24 10:00:35	ga_ls9c_ard_3-2-1_097077_2023-04-24_final.stac-item
2023-05-08 10:10:23	ga_ls9c_ard_3-2-1_099071_2023-05-08_final.stac-item
2023-05-25 10:54:39	ga_ls9c_ard_3-2-1_106074_2023-05-25_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-07-28 09:21:31	ga_ls9c_ard_3-2-1_090088_2023-07-27_final.stac-item
2023-08-11 09:32:49	ga_ls9c_ard_3-2-1_092085_2023-08-11_final.stac-item
2023-09-08 09:52:12	ga_ls9c_ard_3-2-1_096071_2023-09-08_final.stac-item
2023-09-14 10:58:27	ga_ls9c_ard_3-2-1_106082_2023-09-14_final.stac-item
2023-10-05 11:13:26	ga_ls9c_ard_3-2-1_109073_2023-10-05_final.stac-item
2023-10-07 09:25:00	ga_ls9c_ard_3-2-1_091080_2023-10-06_final.stac-item
2023-10-14 11:11:45	ga_ls9c_ard_3-2-1_108084_2023-10-14_final.stac-item
2023-10-16 10:53:02	ga_ls9c_ard_3-2-1_106068_2023-10-16_final.stac-item
2023-10-23 09:26:43	ga_ls9c_ard_3-2-1_091084_2023-10-22_final.stac-item
2023-11-02 10:03:41	ga_ls9c_ard_3-2-1_097084_2023-11-02_final.stac-item
2023-11-09 10:04:43	ga_ls9c_ard_3-2-1_098071_2023-11-09_final.stac-item
2023-11-17 09:20:53	ga_ls9c_ard_3-2-1_090085_2023-11-16_final.stac-item
2023-11-22 09:38:42	ga_ls9c_ard_3-2-1_093083_2023-11-22_final.stac-item
2023-12-08 09:38:39	ga_ls9c_ard_3-2-1_093083_2023-12-08_final.stac-item
2023-12-12 09:16:23	ga_ls9c_ard_3-2-1_089089_2023-12-11_final.stac-item
2023-12-17 11:05:52	ga_ls9c_ard_3-2-1_108069_2023-12-17_final.stac-item
2023-12-26 09:22:49	ga_ls9c_ard_3-2-1_091074_2023-12-25_final.stac-item
2024-02-08 09:47:31	ga_ls9c_ard_3-2-1_095074_2024-02-08_final.stac-item
2024-04-07 09:32:38	ga_ls9c_ard_3-2-1_092084_2024-04-07_final.stac-item
2024-04-14 09:39:56	ga_ls9c_ard_3-2-1_093087_2024-04-14_final.stac-item
2024-04-25 09:22:18	ga_ls9c_ard_3-2-1_090090_2024-04-24_final.stac-item
2024-04-27 09:06:46	ga_ls9c_ard_3-2-1_088082_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