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

75 results

Time (local)	Label
2021-11-22 09:26:27	ga_ls9c_ard_3-2-1_091079_2021-11-21_final.stac-item
2021-12-04 11:05:46	ga_ls9c_ard_3-2-1_107084_2021-12-04_final.stac-item
2021-12-05 11:46:13	ga_ls9c_ard_3-2-1_114077_2021-12-05_final.stac-item
2021-12-29 09:20:11	ga_ls9c_ard_3-2-1_090083_2021-12-28_final.stac-item
2022-01-04 10:21:34	ga_ls9c_ard_3-2-1_100082_2022-01-04_final.stac-item
2022-01-10 11:23:21	ga_ls9c_ard_3-2-1_110082_2022-01-10_final.stac-item
2022-02-16 11:41:02	ga_ls9c_ard_3-2-1_113080_2022-02-16_final.stac-item
2022-03-06 11:28:54	ga_ls9c_ard_3-2-1_111081_2022-03-06_final.stac-item
2022-03-26 09:23:14	ga_ls9c_ard_3-2-1_091076_2022-03-25_final.stac-item
2022-04-12 11:46:54	ga_ls9c_ard_3-2-1_114080_2022-04-12_final.stac-item
2022-05-11 11:17:22	ga_ls9c_ard_3-2-1_109084_2022-05-11_final.stac-item
2022-05-18 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-05-18_final.stac-item
2022-05-22 10:53:30	ga_ls9c_ard_3-2-1_106071_2022-05-22_final.stac-item
2022-05-28 10:21:36	ga_ls9c_ard_3-2-1_100084_2022-05-28_final.stac-item
2022-05-31 09:12:26	ga_ls9c_ard_3-2-1_089081_2022-05-30_final.stac-item
2022-07-01 11:44:30	ga_ls9c_ard_3-2-1_114074_2022-07-01_final.stac-item
2022-07-02 10:46:53	ga_ls9c_ard_3-2-1_105069_2022-07-02_final.stac-item
2022-07-08 10:10:10	ga_ls9c_ard_3-2-1_099070_2022-07-08_final.stac-item
2022-08-01 11:01:26	ga_ls9c_ard_3-2-1_107074_2022-08-01_final.stac-item
2022-08-15 09:34:38	ga_ls9c_ard_3-2-1_093073_2022-08-15_final.stac-item
2022-09-04 10:46:50	ga_ls9c_ard_3-2-1_105068_2022-09-04_final.stac-item
2022-09-09 11:06:10	ga_ls9c_ard_3-2-1_108070_2022-09-09_final.stac-item
2022-09-15 10:31:09	ga_ls9c_ard_3-2-1_102075_2022-09-15_final.stac-item
2022-12-02 10:41:14	ga_ls9c_ard_3-2-1_104069_2022-12-02_final.stac-item
2022-12-07 09:23:19	ga_ls9c_ard_3-2-1_091075_2022-12-06_final.stac-item
2022-12-07 09:28:54	ga_ls9c_ard_3-2-1_091089_2022-12-06_final.stac-item
2022-12-31 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-12-31_final.stac-item
2023-01-02 11:38:54	ga_ls9c_ard_3-2-1_113074_2023-01-02_final.stac-item
2023-01-18 10:01:05	ga_ls9c_ard_3-2-1_097077_2023-01-18_final.stac-item
2023-01-25 10:09:42	ga_ls9c_ard_3-2-1_098083_2023-01-25_final.stac-item
2023-03-22 10:56:05	ga_ls9c_ard_3-2-1_106076_2023-03-22_final.stac-item
2023-04-06 10:15:28	ga_ls9c_ard_3-2-1_099083_2023-04-06_final.stac-item
2023-04-15 10:09:58	ga_ls9c_ard_3-2-1_098085_2023-04-15_final.stac-item
2023-04-16 10:49:15	ga_ls9c_ard_3-2-1_105075_2023-04-16_final.stac-item
2023-05-01 11:44:21	ga_ls9c_ard_3-2-1_114074_2023-05-01_final.stac-item
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final.stac-item
2023-05-10 09:58:25	ga_ls9c_ard_3-2-1_097072_2023-05-10_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-25 10:52:40	ga_ls9c_ard_3-2-1_106069_2023-05-25_final.stac-item
2023-05-25 10:53:04	ga_ls9c_ard_3-2-1_106070_2023-05-25_final.stac-item
2023-06-02 10:08:00	ga_ls9c_ard_3-2-1_098081_2023-06-02_final.stac-item
2023-06-07 10:24:31	ga_ls9c_ard_3-2-1_101076_2023-06-07_final.stac-item
2023-06-13 11:24:38	ga_ls9c_ard_3-2-1_111072_2023-06-13_final.stac-item
2023-07-12 09:20:41	ga_ls9c_ard_3-2-1_090086_2023-07-11_final.stac-item
2023-07-12 10:53:11	ga_ls9c_ard_3-2-1_106070_2023-07-12_final.stac-item
2023-07-20 10:02:57	ga_ls9c_ard_3-2-1_098068_2023-07-20_final.stac-item
2023-07-27 11:52:01	ga_ls9c_ard_3-2-1_115078_2023-07-27_final.stac-item
2023-08-03 10:21:25	ga_ls9c_ard_3-2-1_100083_2023-08-03_final.stac-item
2023-08-13 10:53:22	ga_ls9c_ard_3-2-1_106070_2023-08-13_final.stac-item
2023-09-01 11:25:14	ga_ls9c_ard_3-2-1_111072_2023-09-01_final.stac-item
2023-09-04 10:22:04	ga_ls9c_ard_3-2-1_100084_2023-09-04_final.stac-item
2023-09-12 11:07:13	ga_ls9c_ard_3-2-1_108073_2023-09-12_final.stac-item
2023-09-16 09:06:25	ga_ls9c_ard_3-2-1_088080_2023-09-15_final.stac-item
2023-09-28 09:27:51	ga_ls9c_ard_3-2-1_092072_2023-09-27_final.stac-item
2023-10-12 11:19:18	ga_ls9c_ard_3-2-1_110072_2023-10-12_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_2023-10-13_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-10-17 09:57:01	ga_ls9c_ard_3-2-1_097067_2023-10-17_final.stac-item
2023-10-23 09:27:07	ga_ls9c_ard_3-2-1_091085_2023-10-22_final.stac-item
2023-10-26 11:31:42	ga_ls9c_ard_3-2-1_112072_2023-10-26_final.stac-item
2023-11-21 10:29:07	ga_ls9c_ard_3-2-1_102070_2023-11-21_final.stac-item
2023-12-01 09:32:57	ga_ls9c_ard_3-2-1_092084_2023-12-01_final.stac-item
2024-01-02 09:32:56	ga_ls9c_ard_3-2-1_092084_2024-01-02_final.stac-item
2024-01-05 10:01:23	ga_ls9c_ard_3-2-1_097078_2024-01-05_final.stac-item
2024-01-12 11:44:54	ga_ls9c_ard_3-2-1_114074_2024-01-12_final.stac-item
2024-02-13 10:03:14	ga_ls9c_ard_3-2-1_098067_2024-02-13_final.stac-item
2024-02-28 09:27:00	ga_ls9c_ard_3-2-1_091085_2024-02-27_final.stac-item
2024-03-17 10:48:22	ga_ls9c_ard_3-2-1_105072_2024-03-17_final.stac-item
2024-03-23 10:15:38	ga_ls9c_ard_3-2-1_099083_2024-03-23_final.stac-item
2024-03-24 09:20:24	ga_ls9c_ard_3-2-1_090084_2024-03-23_final.stac-item
2024-04-05 09:40:37	ga_ls9c_ard_3-2-1_094073_2024-04-05_final.stac-item
2024-04-09 09:21:28	ga_ls9c_ard_3-2-1_090087_2024-04-08_final.stac-item
2024-04-12 09:46:44	ga_ls9c_ard_3-2-1_095073_2024-04-12_final.stac-item
2024-04-16 11:05:14	ga_ls9c_ard_3-2-1_107084_2024-04-16_final.stac-item
2024-04-17 10:09:11	ga_ls9c_ard_3-2-1_098083_2024-04-17_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