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
2021-11-05 09:39:00	ga_ls9c_ard_3-2-1_093082_2021-11-05_final.stac-item
2021-11-10 09:41:29	ga_ls9c_ard_3-2-1_094082_2021-11-10_final.stac-item
2021-11-11 10:21:26	ga_ls9c_ard_3-2-1_100082_2021-11-11_final.stac-item
2021-11-12 09:22:44	ga_ls9c_ard_3-2-1_091082_2021-11-11_final.stac-item
2021-11-15 09:43:57	ga_ls9c_ard_3-2-1_094082_2021-11-15_final.stac-item
2021-11-16 10:23:54	ga_ls9c_ard_3-2-1_100082_2021-11-16_final.stac-item
2021-11-19 09:06:27	ga_ls9c_ard_3-2-1_088082_2021-11-18_final.stac-item
2021-11-22 09:27:39	ga_ls9c_ard_3-2-1_091082_2021-11-21_final.stac-item
2021-11-24 10:47:34	ga_ls9c_ard_3-2-1_104082_2021-11-24_final.stac-item
2021-11-25 09:48:51	ga_ls9c_ard_3-2-1_095082_2021-11-25_final.stac-item
2021-12-04 09:26:05	ga_ls9c_ard_3-2-1_091082_2021-12-03_final.stac-item
2021-12-15 10:46:18	ga_ls9c_ard_3-2-1_104082_2021-12-15_final.stac-item
2021-12-17 10:33:55	ga_ls9c_ard_3-2-1_102082_2021-12-17_final.stac-item
2021-12-19 10:21:34	ga_ls9c_ard_3-2-1_100082_2021-12-19_final.stac-item
2021-12-24 10:40:07	ga_ls9c_ard_3-2-1_103082_2021-12-24_final.stac-item
2022-01-05 09:25:57	ga_ls9c_ard_3-2-1_091082_2022-01-04_final.stac-item
2022-01-18 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-01-18_final.stac-item
2022-05-29 09:25:11	ga_ls9c_ard_3-2-1_091082_2022-05-28_final.stac-item
2022-06-02 10:39:22	ga_ls9c_ard_3-2-1_103082_2022-06-02_final.stac-item
2022-06-10 09:49:56	ga_ls9c_ard_3-2-1_095082_2022-06-10_final.stac-item
2022-06-13 10:20:53	ga_ls9c_ard_3-2-1_100082_2022-06-13_final.stac-item
2022-06-14 09:25:17	ga_ls9c_ard_3-2-1_091082_2022-06-13_final.stac-item
2022-06-19 09:43:54	ga_ls9c_ard_3-2-1_094082_2022-06-19_final.stac-item
2022-06-20 08:48:19	ga_ls9c_ard_3-2-1_085082_2022-06-19_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-06-30 09:25:33	ga_ls9c_ard_3-2-1_091082_2022-06-29_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-16 09:25:29	ga_ls9c_ard_3-2-1_091082_2022-07-15_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-21 09:44:07	ga_ls9c_ard_3-2-1_094082_2022-07-21_final.stac-item
2022-07-22 10:27:24	ga_ls9c_ard_3-2-1_101082_2022-07-22_final.stac-item
2022-07-28 09:50:24	ga_ls9c_ard_3-2-1_095082_2022-07-28_final.stac-item
2022-07-30 09:38:04	ga_ls9c_ard_3-2-1_093082_2022-07-30_final.stac-item
2022-08-01 09:25:44	ga_ls9c_ard_3-2-1_091082_2022-07-31_final.stac-item
2022-08-06 09:44:20	ga_ls9c_ard_3-2-1_094082_2022-08-06_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-08-22 09:44:26	ga_ls9c_ard_3-2-1_094082_2022-08-22_final.stac-item
2022-08-23 10:27:42	ga_ls9c_ard_3-2-1_101082_2022-08-23_final.stac-item
2022-08-30 10:33:54	ga_ls9c_ard_3-2-1_102082_2022-08-30_final.stac-item
2022-09-08 08:48:49	ga_ls9c_ard_3-2-1_085082_2022-09-07_final.stac-item
2022-09-16 09:38:20	ga_ls9c_ard_3-2-1_093082_2022-09-16_final.stac-item
2022-09-18 09:25:59	ga_ls9c_ard_3-2-1_091082_2022-09-17_final.stac-item
2022-09-24 10:27:49	ga_ls9c_ard_3-2-1_101082_2022-09-24_final.stac-item
2022-10-02 09:38:24	ga_ls9c_ard_3-2-1_093082_2022-10-02_final.stac-item
2022-10-17 10:34:06	ga_ls9c_ard_3-2-1_102082_2022-10-17_final.stac-item
2022-10-18 09:38:29	ga_ls9c_ard_3-2-1_093082_2022-10-18_final.stac-item
2022-11-05 09:26:05	ga_ls9c_ard_3-2-1_091082_2022-11-04_final.stac-item
2022-11-09 10:40:17	ga_ls9c_ard_3-2-1_103082_2022-11-09_final.stac-item
2022-11-21 09:26:08	ga_ls9c_ard_3-2-1_091082_2022-11-20_final.stac-item
2022-11-27 08:49:02	ga_ls9c_ard_3-2-1_085082_2022-11-26_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_final.stac-item
2022-12-06 10:21:44	ga_ls9c_ard_3-2-1_100082_2022-12-06_nrt.stac-item
2022-12-07 09:26:07	ga_ls9c_ard_3-2-1_091082_2022-12-06_nrt.stac-item
2022-12-13 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-12-13_final.stac-item
2022-12-22 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-12-22_final.stac-item
2023-01-07 10:21:45	ga_ls9c_ard_3-2-1_100082_2023-01-07_final.stac-item
2023-01-13 09:44:38	ga_ls9c_ard_3-2-1_094082_2023-01-13_final.stac-item
2023-06-17 09:25:00	ga_ls9c_ard_3-2-1_091082_2023-06-16_final.stac-item
2023-06-21 10:39:10	ga_ls9c_ard_3-2-1_103082_2023-06-21_final.stac-item
2023-06-22 09:43:32	ga_ls9c_ard_3-2-1_094082_2023-06-22_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-30 10:33:06	ga_ls9c_ard_3-2-1_102082_2023-06-30_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-03 09:25:10	ga_ls9c_ard_3-2-1_091082_2023-07-02_final.stac-item
2023-07-08 09:43:46	ga_ls9c_ard_3-2-1_094082_2023-07-08_final.stac-item
2023-07-14 09:06:44	ga_ls9c_ard_3-2-1_088082_2023-07-13_final.stac-item
2023-07-15 09:50:00	ga_ls9c_ard_3-2-1_095082_2023-07-15_final.stac-item
2023-07-17 09:37:38	ga_ls9c_ard_3-2-1_093082_2023-07-17_final.stac-item
2023-07-19 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-07-18_final.stac-item
2023-07-24 09:43:48	ga_ls9c_ard_3-2-1_094082_2023-07-24_final.stac-item
2023-07-28 09:19:08	ga_ls9c_ard_3-2-1_090082_2023-07-27_final.stac-item
2023-07-30 09:06:48	ga_ls9c_ard_3-2-1_088082_2023-07-29_final.stac-item
2023-07-31 09:50:05	ga_ls9c_ard_3-2-1_095082_2023-07-31_final.stac-item
2023-08-02 09:37:45	ga_ls9c_ard_3-2-1_093082_2023-08-02_final.stac-item
2023-08-04 09:25:24	ga_ls9c_ard_3-2-1_091082_2023-08-03_final.stac-item
2023-08-13 09:19:16	ga_ls9c_ard_3-2-1_090082_2023-08-12_final.stac-item
2023-08-15 09:06:54	ga_ls9c_ard_3-2-1_088082_2023-08-14_final.stac-item
2023-08-16 09:50:10	ga_ls9c_ard_3-2-1_095082_2023-08-16_final.stac-item
2023-08-18 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-08-18_final.stac-item
2023-08-20 09:25:28	ga_ls9c_ard_3-2-1_091082_2023-08-19_final.stac-item
2023-08-25 09:44:05	ga_ls9c_ard_3-2-1_094082_2023-08-25_final.stac-item
2023-08-31 09:07:04	ga_ls9c_ard_3-2-1_088082_2023-08-30_final.stac-item
2023-09-05 09:25:39	ga_ls9c_ard_3-2-1_091082_2023-09-04_final.stac-item
2023-09-10 09:44:16	ga_ls9c_ard_3-2-1_094082_2023-09-10_final.stac-item
2023-09-14 09:19:34	ga_ls9c_ard_3-2-1_090082_2023-09-13_final.stac-item
2023-09-16 09:07:13	ga_ls9c_ard_3-2-1_088082_2023-09-15_final.stac-item
2023-09-21 09:25:45	ga_ls9c_ard_3-2-1_091082_2023-09-20_final.stac-item
2023-09-26 09:44:14	ga_ls9c_ard_3-2-1_094082_2023-09-26_final.stac-item
2023-10-03 09:50:29	ga_ls9c_ard_3-2-1_095082_2023-10-03_final.stac-item
2023-10-03 09:50:29	ga_ls9c_ard_3-2-1_095082_2023-10-03_interim.stac-item
2023-10-07 09:25:48	ga_ls9c_ard_3-2-1_091082_2023-10-06_final.stac-item
2023-10-18 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-10-17_final.stac-item
2023-10-19 09:50:39	ga_ls9c_ard_3-2-1_095082_2023-10-19_final.stac-item
2023-10-28 09:44:25	ga_ls9c_ard_3-2-1_094082_2023-10-28_final.stac-item
2023-11-04 09:50:31	ga_ls9c_ard_3-2-1_095082_2023-11-04_final.stac-item
2023-11-13 09:44:23	ga_ls9c_ard_3-2-1_094082_2023-11-13_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-12-03 09:19:47	ga_ls9c_ard_3-2-1_090082_2023-12-02_final.stac-item
2023-12-31 09:44:31	ga_ls9c_ard_3-2-1_094082_2023-12-31_final.stac-item
2024-01-16 09:44:30	ga_ls9c_ard_3-2-1_094082_2024-01-16_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