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

89 results

Time (local)	Label
2021-11-13 10:02:18	ga_ls9c_ard_3-2-1_097081_2021-11-13_final.stac-item
2021-12-12 10:16:38	ga_ls9c_ard_3-2-1_099085_2021-12-12_final.stac-item
2021-12-16 11:23:58	ga_ls9c_ard_3-2-1_111068_2021-12-16_final.stac-item
2021-12-29 09:18:11	ga_ls9c_ard_3-2-1_090078_2021-12-28_final.stac-item
2022-01-09 10:36:06	ga_ls9c_ard_3-2-1_103072_2022-01-09_final.stac-item
2022-01-19 11:13:59	ga_ls9c_ard_3-2-1_109074_2022-01-19_final.stac-item
2022-01-21 11:00:26	ga_ls9c_ard_3-2-1_107071_2022-01-21_final.stac-item
2022-01-28 09:33:20	ga_ls9c_ard_3-2-1_092085_2022-01-28_final.stac-item
2022-02-11 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-02-11_final.stac-item
2022-02-20 09:39:23	ga_ls9c_ard_3-2-1_093085_2022-02-20_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_2022-03-09_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-30 10:35:47	ga_ls9c_ard_3-2-1_103072_2022-03-30_final.stac-item
2022-04-03 10:13:04	ga_ls9c_ard_3-2-1_099077_2022-04-03_final.stac-item
2022-04-10 10:22:00	ga_ls9c_ard_3-2-1_100084_2022-04-10_final.stac-item
2022-04-24 10:33:24	ga_ls9c_ard_3-2-1_102082_2022-04-24_final.stac-item
2022-04-25 11:11:29	ga_ls9c_ard_3-2-1_109069_2022-04-25_final.stac-item
2022-05-02 11:19:38	ga_ls9c_ard_3-2-1_110074_2022-05-02_final.stac-item
2022-05-07 09:59:15	ga_ls9c_ard_3-2-1_097074_2022-05-07_final.stac-item
2022-05-25 11:28:23	ga_ls9c_ard_3-2-1_111081_2022-05-25_final.stac-item
2022-06-03 11:19:26	ga_ls9c_ard_3-2-1_110074_2022-06-03_final.stac-item
2022-07-08 11:51:03	ga_ls9c_ard_3-2-1_115075_2022-07-08_final.stac-item
2022-07-23 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-07-22_final.stac-item
2022-09-05 11:34:53	ga_ls9c_ard_3-2-1_112080_2022-09-05_final.stac-item
2022-09-18 09:22:48	ga_ls9c_ard_3-2-1_091074_2022-09-17_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-18 11:18:10	ga_ls9c_ard_3-2-1_109084_2022-10-18_final.stac-item
2022-10-25 11:20:46	ga_ls9c_ard_3-2-1_110075_2022-10-25_final.stac-item
2022-11-23 09:12:35	ga_ls9c_ard_3-2-1_089079_2022-11-22_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_final.stac-item
2022-12-12 11:20:45	ga_ls9c_ard_3-2-1_110075_2022-12-12_final.stac-item
2022-12-21 09:36:03	ga_ls9c_ard_3-2-1_093076_2022-12-21_final.stac-item
2022-12-21 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-12-21_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-24 09:22:26	ga_ls9c_ard_3-2-1_091073_2023-01-23_final.stac-item
2023-01-31 09:34:18	ga_ls9c_ard_3-2-1_092087_2023-01-31_final.stac-item
2023-02-08 10:19:01	ga_ls9c_ard_3-2-1_100075_2023-02-08_final.stac-item
2023-02-14 11:19:11	ga_ls9c_ard_3-2-1_110071_2023-02-14_final.stac-item
2023-02-14 11:20:23	ga_ls9c_ard_3-2-1_110074_2023-02-14_final.stac-item
2023-02-17 10:14:21	ga_ls9c_ard_3-2-1_099079_2023-02-17_final.stac-item
2023-03-04 09:28:06	ga_ls9c_ard_3-2-1_092072_2023-03-03_final.stac-item
2023-03-05 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-03-05_final.stac-item
2023-03-25 09:46:04	ga_ls9c_ard_3-2-1_095071_2023-03-25_final.stac-item
2023-04-26 09:46:36	ga_ls9c_ard_3-2-1_095073_2023-04-26_final.stac-item
2023-04-26 11:25:29	ga_ls9c_ard_3-2-1_111073_2023-04-26_final.stac-item
2023-05-05 11:19:57	ga_ls9c_ard_3-2-1_110075_2023-05-05_final.stac-item
2023-05-20 10:35:24	ga_ls9c_ard_3-2-1_103072_2023-05-20_final.stac-item
2023-05-28 11:25:34	ga_ls9c_ard_3-2-1_111074_2023-05-28_final.stac-item
2023-06-13 09:51:45	ga_ls9c_ard_3-2-1_095087_2023-06-13_final.stac-item
2023-07-05 09:14:02	ga_ls9c_ard_3-2-1_089085_2023-07-04_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-08-20 09:27:28	ga_ls9c_ard_3-2-1_091087_2023-08-19_final.stac-item
2023-09-08 11:31:30	ga_ls9c_ard_3-2-1_112072_2023-09-08_final.stac-item
2023-09-13 10:13:11	ga_ls9c_ard_3-2-1_099077_2023-09-13_final.stac-item
2023-09-23 09:16:10	ga_ls9c_ard_3-2-1_089089_2023-09-22_final.stac-item
2023-10-28 11:19:43	ga_ls9c_ard_3-2-1_110073_2023-10-28_final.stac-item
2023-10-31 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-10-31_final.stac-item
2023-11-17 09:16:53	ga_ls9c_ard_3-2-1_090075_2023-11-16_final.stac-item
2023-11-25 10:05:15	ga_ls9c_ard_3-2-1_098072_2023-11-25_final.stac-item
2023-12-05 09:06:36	ga_ls9c_ard_3-2-1_088080_2023-12-04_final.stac-item
2023-12-06 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-12-06_final.stac-item
2023-12-07 10:30:17	ga_ls9c_ard_3-2-1_102073_2023-12-07_final.stac-item
2023-12-11 10:05:12	ga_ls9c_ard_3-2-1_098072_2023-12-11_final.stac-item
2023-12-17 09:34:10	ga_ls9c_ard_3-2-1_092087_2023-12-17_final.stac-item
2024-01-07 11:23:55	ga_ls9c_ard_3-2-1_111068_2024-01-07_final.stac-item
2024-01-18 11:05:49	ga_ls9c_ard_3-2-1_108069_2024-01-18_final.stac-item
2024-01-26 10:17:32	ga_ls9c_ard_3-2-1_100072_2024-01-26_final.stac-item
2024-01-26 10:21:56	ga_ls9c_ard_3-2-1_100083_2024-01-26_final.stac-item
2024-02-06 09:59:05	ga_ls9c_ard_3-2-1_097072_2024-02-06_final.stac-item
2024-02-09 10:28:47	ga_ls9c_ard_3-2-1_102069_2024-02-09_final.stac-item
2024-02-18 10:25:40	ga_ls9c_ard_3-2-1_101077_2024-02-18_final.stac-item
2024-02-23 10:42:29	ga_ls9c_ard_3-2-1_104073_2024-02-23_final.stac-item
2024-03-01 09:11:28	ga_ls9c_ard_3-2-1_089077_2024-02-29_final.stac-item
2024-03-04 09:41:12	ga_ls9c_ard_3-2-1_094074_2024-03-04_final.stac-item
2024-03-05 10:23:40	ga_ls9c_ard_3-2-1_101072_2024-03-05_final.stac-item
2024-03-08 10:58:58	ga_ls9c_ard_3-2-1_106083_2024-03-08_final.stac-item
2024-03-29 11:11:44	ga_ls9c_ard_3-2-1_109069_2024-03-29_final.stac-item
2024-04-16 09:24:21	ga_ls9c_ard_3-2-1_091079_2024-04-15_final.stac-item
2024-04-18 10:49:14	ga_ls9c_ard_3-2-1_105075_2024-04-18_final.stac-item
2024-04-23 11:10:23	ga_ls9c_ard_3-2-1_108082_2024-04-23_final.stac-item
2024-04-24 10:15:08	ga_ls9c_ard_3-2-1_099083_2024-04-24_final.stac-item
2024-04-25 09:19:07	ga_ls9c_ard_3-2-1_090082_2024-04-24_final.stac-item
2024-04-28 11:24:31	ga_ls9c_ard_3-2-1_111071_2024-04-28_final.stac-item
2024-04-28 11:25:19	ga_ls9c_ard_3-2-1_111073_2024-04-28_final.stac-item
2024-05-05 11:31:52	ga_ls9c_ard_3-2-1_112074_2024-05-05_nrt.stac-item
2024-05-09 09:30:40	ga_ls9c_ard_3-2-1_092080_2024-05-09_nrt.stac-item
2024-05-10 10:10:20	ga_ls9c_ard_3-2-1_099071_2024-05-10_nrt.stac-item
2024-05-11 09:16:18	ga_ls9c_ard_3-2-1_090075_2024-05-10_nrt.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