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
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-17 10:29:56	ga_ls9c_ard_3-2-1_102072_2021-12-17_final.stac-item
2021-12-26 10:23:47	ga_ls9c_ard_3-2-1_101072_2021-12-26_final.stac-item
2021-12-28 10:15:24	ga_ls9c_ard_3-2-1_099082_2021-12-28_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2022-01-02 10:29:57	ga_ls9c_ard_3-2-1_102072_2022-01-02_final.stac-item
2022-01-06 10:10:00	ga_ls9c_ard_3-2-1_098084_2022-01-06_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-01-29 10:15:23	ga_ls9c_ard_3-2-1_099082_2022-01-29_final.stac-item
2022-01-29 10:16:11	ga_ls9c_ard_3-2-1_099084_2022-01-29_final.stac-item
2022-02-03 10:29:56	ga_ls9c_ard_3-2-1_102072_2022-02-03_final.stac-item
2022-02-07 10:09:59	ga_ls9c_ard_3-2-1_098084_2022-02-07_final.stac-item
2022-02-12 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-02-12_final.stac-item
2022-02-14 10:15:19	ga_ls9c_ard_3-2-1_099082_2022-02-14_final.stac-item
2022-02-19 10:29:49	ga_ls9c_ard_3-2-1_102072_2022-02-19_final.stac-item
2022-02-23 10:09:51	ga_ls9c_ard_3-2-1_098084_2022-02-23_final.stac-item
2022-02-28 10:25:31	ga_ls9c_ard_3-2-1_101077_2022-02-28_final.stac-item
2022-03-02 10:15:56	ga_ls9c_ard_3-2-1_099084_2022-03-02_final.stac-item
2022-03-07 10:29:42	ga_ls9c_ard_3-2-1_102072_2022-03-07_final.stac-item
2022-03-09 10:19:20	ga_ls9c_ard_3-2-1_100077_2022-03-09_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-04-08 10:29:35	ga_ls9c_ard_3-2-1_102072_2022-04-08_final.stac-item
2022-04-12 10:09:37	ga_ls9c_ard_3-2-1_098084_2022-04-12_final.stac-item
2022-04-17 10:23:18	ga_ls9c_ard_3-2-1_101072_2022-04-17_final.stac-item
2022-04-17 10:24:54	ga_ls9c_ard_3-2-1_101076_2022-04-17_final.stac-item
2022-04-17 10:25:18	ga_ls9c_ard_3-2-1_101077_2022-04-17_final.stac-item
2022-04-19 10:14:54	ga_ls9c_ard_3-2-1_099082_2022-04-19_final.stac-item
2022-04-24 10:29:25	ga_ls9c_ard_3-2-1_102072_2022-04-24_final.stac-item
2022-05-03 10:24:48	ga_ls9c_ard_3-2-1_101076_2022-05-03_final.stac-item
2022-05-05 10:16:01	ga_ls9c_ard_3-2-1_099085_2022-05-05_final.stac-item
2022-05-10 10:29:19	ga_ls9c_ard_3-2-1_102072_2022-05-10_final.stac-item
2022-05-14 10:09:20	ga_ls9c_ard_3-2-1_098084_2022-05-14_final.stac-item
2022-05-19 10:24:36	ga_ls9c_ard_3-2-1_101076_2022-05-19_final.stac-item
2022-05-19 10:25:00	ga_ls9c_ard_3-2-1_101077_2022-05-19_final.stac-item
2022-05-26 10:29:10	ga_ls9c_ard_3-2-1_102072_2022-05-26_final.stac-item
2022-05-30 10:09:15	ga_ls9c_ard_3-2-1_098084_2022-05-30_final.stac-item
2022-06-06 10:14:39	ga_ls9c_ard_3-2-1_099082_2022-06-06_final.stac-item
2022-06-15 10:09:21	ga_ls9c_ard_3-2-1_098084_2022-06-15_final.stac-item
2022-06-20 10:24:49	ga_ls9c_ard_3-2-1_101076_2022-06-20_final.stac-item
2022-06-22 10:14:55	ga_ls9c_ard_3-2-1_099082_2022-06-22_final.stac-item
2022-06-22 10:15:43	ga_ls9c_ard_3-2-1_099084_2022-06-22_final.stac-item
2022-07-01 10:09:36	ga_ls9c_ard_3-2-1_098084_2022-07-01_final.stac-item
2022-07-08 10:15:45	ga_ls9c_ard_3-2-1_099084_2022-07-08_final.stac-item
2022-07-13 10:29:28	ga_ls9c_ard_3-2-1_102072_2022-07-13_final.stac-item
2022-07-24 10:15:04	ga_ls9c_ard_3-2-1_099082_2022-07-24_final.stac-item
2022-07-29 10:29:41	ga_ls9c_ard_3-2-1_102072_2022-07-29_final.stac-item
2022-08-07 10:23:37	ga_ls9c_ard_3-2-1_101072_2022-08-07_final.stac-item
2022-08-09 10:15:16	ga_ls9c_ard_3-2-1_099082_2022-08-09_final.stac-item
2022-08-14 10:29:51	ga_ls9c_ard_3-2-1_102072_2022-08-14_final.stac-item
2022-08-25 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-08-25_final.stac-item
2022-08-25 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-08-25_final.stac-item
2022-08-30 10:29:54	ga_ls9c_ard_3-2-1_102072_2022-08-30_final.stac-item
2022-09-03 10:09:58	ga_ls9c_ard_3-2-1_098084_2022-09-03_final.stac-item
2022-09-08 10:23:42	ga_ls9c_ard_3-2-1_101072_2022-09-08_final.stac-item
2022-09-10 10:15:21	ga_ls9c_ard_3-2-1_099082_2022-09-10_final.stac-item
2022-09-10 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-09-10_final.stac-item
2022-09-19 10:10:03	ga_ls9c_ard_3-2-1_098084_2022-09-19_final.stac-item
2022-09-24 10:23:50	ga_ls9c_ard_3-2-1_101072_2022-09-24_final.stac-item
2022-09-26 10:15:28	ga_ls9c_ard_3-2-1_099082_2022-09-26_final.stac-item
2022-09-26 10:16:16	ga_ls9c_ard_3-2-1_099084_2022-09-26_final.stac-item
2022-10-10 10:23:52	ga_ls9c_ard_3-2-1_101072_2022-10-10_final.stac-item
2022-10-12 10:16:19	ga_ls9c_ard_3-2-1_099084_2022-10-12_final.stac-item
2022-10-19 10:19:21	ga_ls9c_ard_3-2-1_100076_2022-10-19_final.stac-item
2022-10-26 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-10-26_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_nrt.stac-item
2022-11-20 10:19:22	ga_ls9c_ard_3-2-1_100076_2022-11-20_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_nrt.stac-item
2022-12-08 10:10:11	ga_ls9c_ard_3-2-1_098084_2022-12-08_final.stac-item
2022-12-13 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-12-13_final.stac-item
2022-12-15 10:16:22	ga_ls9c_ard_3-2-1_099084_2022-12-15_final.stac-item
2022-12-31 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-12-31_final.stac-item
2023-01-09 10:10:11	ga_ls9c_ard_3-2-1_098084_2023-01-09_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-01-23 10:19:14	ga_ls9c_ard_3-2-1_100076_2023-01-23_final.stac-item
2023-02-01 10:15:35	ga_ls9c_ard_3-2-1_099082_2023-02-01_final.stac-item
2023-02-01 10:16:23	ga_ls9c_ard_3-2-1_099084_2023-02-01_final.stac-item
2023-02-06 10:28:11	ga_ls9c_ard_3-2-1_102067_2023-02-06_interim.stac-item
2023-02-10 10:10:15	ga_ls9c_ard_3-2-1_098084_2023-02-10_final.stac-item
2023-02-26 10:10:00	ga_ls9c_ard_3-2-1_098084_2023-02-26_final.stac-item
2023-03-05 10:16:08	ga_ls9c_ard_3-2-1_099084_2023-03-05_final.stac-item
2023-03-12 10:19:03	ga_ls9c_ard_3-2-1_100076_2023-03-12_final.stac-item
2023-03-14 10:09:53	ga_ls9c_ard_3-2-1_098084_2023-03-14_final.stac-item
2023-03-19 10:25:13	ga_ls9c_ard_3-2-1_101076_2023-03-19_final.stac-item
2023-03-21 10:16:02	ga_ls9c_ard_3-2-1_099084_2023-03-21_final.stac-item
2023-04-20 10:24:56	ga_ls9c_ard_3-2-1_101076_2023-04-20_final.stac-item
2023-04-22 10:14:57	ga_ls9c_ard_3-2-1_099082_2023-04-22_final.stac-item
2023-05-06 10:24:44	ga_ls9c_ard_3-2-1_101076_2023-05-06_final.stac-item
2023-05-08 10:15:34	ga_ls9c_ard_3-2-1_099084_2023-05-08_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-22 10:24:36	ga_ls9c_ard_3-2-1_101076_2023-05-22_final.stac-item
2023-05-24 10:14:36	ga_ls9c_ard_3-2-1_099082_2023-05-24_final.stac-item
2023-06-02 10:09:12	ga_ls9c_ard_3-2-1_098084_2023-06-02_final.stac-item
2023-06-09 10:14:31	ga_ls9c_ard_3-2-1_099082_2023-06-09_final.stac-item
2023-06-23 10:24:24	ga_ls9c_ard_3-2-1_101076_2023-06-23_final.stac-item
2023-06-25 10:15:14	ga_ls9c_ard_3-2-1_099084_2023-06-25_final.stac-item
2023-07-11 10:14:42	ga_ls9c_ard_3-2-1_099082_2023-07-11_final.stac-item
2023-09-13 10:15:11	ga_ls9c_ard_3-2-1_099082_2023-09-13_final.stac-item
2023-09-29 10:15:08	ga_ls9c_ard_3-2-1_099082_2023-09-29_final.stac-item
2024-04-24 10:15:32	ga_ls9c_ard_3-2-1_099084_2024-04-24_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