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

First 100 results (query limit)

Time (local)	Label
2021-11-02 09:17:23	ga_ls9c_ard_3-2-1_090081_2021-11-01_final.stac-item
2021-11-03 09:56:57	ga_ls9c_ard_3-2-1_096080_2021-11-03_final.stac-item
2021-11-07 09:19:52	ga_ls9c_ard_3-2-1_090081_2021-11-06_final.stac-item
2021-11-08 09:59:26	ga_ls9c_ard_3-2-1_097080_2021-11-08_final.stac-item
2021-11-12 09:22:20	ga_ls9c_ard_3-2-1_091081_2021-11-11_final.stac-item
2021-12-29 09:19:23	ga_ls9c_ard_3-2-1_090081_2021-12-28_final.stac-item
2021-12-30 10:02:39	ga_ls9c_ard_3-2-1_097081_2021-12-30_final.stac-item
2022-01-14 09:19:19	ga_ls9c_ard_3-2-1_090081_2022-01-13_final.stac-item
2022-01-30 09:19:22	ga_ls9c_ard_3-2-1_090081_2022-01-29_final.stac-item
2022-01-31 10:02:38	ga_ls9c_ard_3-2-1_097081_2022-01-31_final.stac-item
2022-02-14 10:14:55	ga_ls9c_ard_3-2-1_099081_2022-02-14_final.stac-item
2022-02-15 09:19:18	ga_ls9c_ard_3-2-1_090081_2022-02-14_final.stac-item
2022-03-02 10:14:44	ga_ls9c_ard_3-2-1_099081_2022-03-02_final.stac-item
2022-03-03 09:19:07	ga_ls9c_ard_3-2-1_090081_2022-03-02_final.stac-item
2022-03-27 10:08:28	ga_ls9c_ard_3-2-1_098081_2022-03-27_final.stac-item
2022-04-04 09:19:02	ga_ls9c_ard_3-2-1_090081_2022-04-03_final.stac-item
2022-04-05 10:02:17	ga_ls9c_ard_3-2-1_097081_2022-04-05_final.stac-item
2022-04-16 09:43:39	ga_ls9c_ard_3-2-1_094081_2022-04-16_final.stac-item
2022-04-20 09:18:52	ga_ls9c_ard_3-2-1_090081_2022-04-19_final.stac-item
2022-04-21 10:02:07	ga_ls9c_ard_3-2-1_097081_2022-04-21_final.stac-item
2022-05-02 09:43:33	ga_ls9c_ard_3-2-1_094081_2022-05-02_final.stac-item
2022-05-03 10:26:48	ga_ls9c_ard_3-2-1_101081_2022-05-03_final.stac-item
2022-05-05 10:14:26	ga_ls9c_ard_3-2-1_099081_2022-05-05_final.stac-item
2022-05-06 09:18:48	ga_ls9c_ard_3-2-1_090081_2022-05-05_final.stac-item
2022-05-14 10:08:09	ga_ls9c_ard_3-2-1_098081_2022-05-14_final.stac-item
2022-05-16 09:55:45	ga_ls9c_ard_3-2-1_096081_2022-05-16_final.stac-item
2022-05-22 09:18:36	ga_ls9c_ard_3-2-1_090081_2022-05-21_final.stac-item
2022-05-23 10:01:52	ga_ls9c_ard_3-2-1_097081_2022-05-23_final.stac-item
2022-06-01 09:55:18	ga_ls9c_ard_3-2-1_096080_2022-06-01_final.stac-item
2022-06-06 10:13:51	ga_ls9c_ard_3-2-1_099080_2022-06-06_final.stac-item
2022-06-06 10:14:15	ga_ls9c_ard_3-2-1_099081_2022-06-06_final.stac-item
2022-06-07 09:18:38	ga_ls9c_ard_3-2-1_090081_2022-06-06_final.stac-item
2022-06-08 10:01:30	ga_ls9c_ard_3-2-1_097080_2022-06-08_final.stac-item
2022-06-13 10:20:05	ga_ls9c_ard_3-2-1_100080_2022-06-13_final.stac-item
2022-06-23 09:18:55	ga_ls9c_ard_3-2-1_090081_2022-06-22_final.stac-item
2022-07-01 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-07-01_final.stac-item
2022-07-09 09:18:56	ga_ls9c_ard_3-2-1_090081_2022-07-08_final.stac-item
2022-07-10 10:02:11	ga_ls9c_ard_3-2-1_097081_2022-07-10_final.stac-item
2022-07-15 10:20:18	ga_ls9c_ard_3-2-1_100080_2022-07-15_final.stac-item
2022-07-17 10:08:22	ga_ls9c_ard_3-2-1_098081_2022-07-17_final.stac-item
2022-07-25 09:19:04	ga_ls9c_ard_3-2-1_090081_2022-07-24_final.stac-item
2022-08-07 10:26:48	ga_ls9c_ard_3-2-1_101080_2022-08-07_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-11 10:02:31	ga_ls9c_ard_3-2-1_097081_2022-08-11_final.stac-item
2022-08-25 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-08-25_final.stac-item
2022-08-25 10:14:57	ga_ls9c_ard_3-2-1_099081_2022-08-25_final.stac-item
2022-08-26 09:19:20	ga_ls9c_ard_3-2-1_090081_2022-08-25_final.stac-item
2022-08-27 10:02:35	ga_ls9c_ard_3-2-1_097081_2022-08-27_final.stac-item
2022-09-10 10:14:57	ga_ls9c_ard_3-2-1_099081_2022-09-10_final.stac-item
2022-09-11 09:19:20	ga_ls9c_ard_3-2-1_090081_2022-09-10_final.stac-item
2022-09-19 10:08:51	ga_ls9c_ard_3-2-1_098081_2022-09-19_final.stac-item
2022-09-27 09:19:27	ga_ls9c_ard_3-2-1_090081_2022-09-26_final.stac-item
2022-09-28 10:02:43	ga_ls9c_ard_3-2-1_097081_2022-09-28_final.stac-item
2022-10-03 10:20:51	ga_ls9c_ard_3-2-1_100080_2022-10-03_final.stac-item
2022-10-13 09:19:31	ga_ls9c_ard_3-2-1_090081_2022-10-12_final.stac-item
2022-10-21 10:08:59	ga_ls9c_ard_3-2-1_098081_2022-10-21_final.stac-item
2022-10-29 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-10-28_final.stac-item
2022-11-14 09:19:34	ga_ls9c_ard_3-2-1_090081_2022-11-13_final.stac-item
2022-11-15 10:02:50	ga_ls9c_ard_3-2-1_097081_2022-11-15_final.stac-item
2022-11-30 09:19:31	ga_ls9c_ard_3-2-1_090081_2022-11-29_final.stac-item
2022-12-01 10:02:46	ga_ls9c_ard_3-2-1_097081_2022-12-01_final.stac-item
2022-12-08 10:08:59	ga_ls9c_ard_3-2-1_098081_2022-12-08_final.stac-item
2022-12-16 09:19:32	ga_ls9c_ard_3-2-1_090081_2022-12-15_final.stac-item
2022-12-17 10:02:48	ga_ls9c_ard_3-2-1_097081_2022-12-17_final.stac-item
2022-12-24 10:08:55	ga_ls9c_ard_3-2-1_098081_2022-12-24_final.stac-item
2023-01-01 09:19:33	ga_ls9c_ard_3-2-1_090081_2022-12-31_final.stac-item
2023-01-09 10:08:59	ga_ls9c_ard_3-2-1_098081_2023-01-09_final.stac-item
2023-01-17 09:19:27	ga_ls9c_ard_3-2-1_090081_2023-01-16_final.stac-item
2023-02-02 09:19:34	ga_ls9c_ard_3-2-1_090081_2023-02-01_final.stac-item
2023-02-18 09:19:30	ga_ls9c_ard_3-2-1_090081_2023-02-17_final.stac-item
2023-03-06 09:19:18	ga_ls9c_ard_3-2-1_090081_2023-03-05_final.stac-item
2023-03-21 10:14:50	ga_ls9c_ard_3-2-1_099081_2023-03-21_final.stac-item
2023-03-22 09:19:12	ga_ls9c_ard_3-2-1_090081_2023-03-21_final.stac-item
2023-03-23 10:02:27	ga_ls9c_ard_3-2-1_097081_2023-03-23_final.stac-item
2023-04-15 10:08:23	ga_ls9c_ard_3-2-1_098081_2023-04-15_final.stac-item
2023-04-22 10:14:33	ga_ls9c_ard_3-2-1_099081_2023-04-22_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-05-01 10:08:15	ga_ls9c_ard_3-2-1_098081_2023-05-01_final.stac-item
2023-05-08 10:14:22	ga_ls9c_ard_3-2-1_099081_2023-05-08_final.stac-item
2023-05-09 09:18:45	ga_ls9c_ard_3-2-1_090081_2023-05-08_final.stac-item
2023-05-10 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-05-10_final.stac-item
2023-05-17 10:08:08	ga_ls9c_ard_3-2-1_098081_2023-05-17_final.stac-item
2023-05-24 10:14:12	ga_ls9c_ard_3-2-1_099081_2023-05-24_final.stac-item
2023-05-25 09:18:34	ga_ls9c_ard_3-2-1_090081_2023-05-24_final.stac-item
2023-06-02 10:08:00	ga_ls9c_ard_3-2-1_098081_2023-06-02_final.stac-item
2023-06-09 10:14:08	ga_ls9c_ard_3-2-1_099081_2023-06-09_final.stac-item
2023-06-10 09:18:30	ga_ls9c_ard_3-2-1_090081_2023-06-09_final.stac-item
2023-06-11 10:01:44	ga_ls9c_ard_3-2-1_097081_2023-06-11_final.stac-item
2023-06-25 10:14:02	ga_ls9c_ard_3-2-1_099081_2023-06-25_final.stac-item
2023-06-26 09:18:25	ga_ls9c_ard_3-2-1_090081_2023-06-25_final.stac-item
2023-06-27 10:01:43	ga_ls9c_ard_3-2-1_097081_2023-06-27_final.stac-item
2023-07-04 10:08:03	ga_ls9c_ard_3-2-1_098081_2023-07-04_final.stac-item
2023-07-12 09:18:41	ga_ls9c_ard_3-2-1_090081_2023-07-11_final.stac-item
2023-07-18 10:20:06	ga_ls9c_ard_3-2-1_100080_2023-07-18_final.stac-item
2023-07-27 10:13:56	ga_ls9c_ard_3-2-1_099080_2023-07-27_final.stac-item
2023-08-19 10:20:17	ga_ls9c_ard_3-2-1_100080_2023-08-19_final.stac-item
2023-08-28 10:14:14	ga_ls9c_ard_3-2-1_099080_2023-08-28_final.stac-item
2023-09-04 10:20:28	ga_ls9c_ard_3-2-1_100080_2023-09-04_final.stac-item
2023-09-06 10:08:08	ga_ls9c_ard_3-2-1_098080_2023-09-06_final.stac-item
2023-09-29 10:14:20	ga_ls9c_ard_3-2-1_099080_2023-09-29_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