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

79 results

Time (local)	Label
2021-11-08 09:59:50	ga_ls9c_ard_3-2-1_097081_2021-11-08_final.stac-item
2021-11-25 09:46:52	ga_ls9c_ard_3-2-1_095077_2021-11-25_final.stac-item
2021-12-12 10:11:03	ga_ls9c_ard_3-2-1_099071_2021-12-12_final.stac-item
2021-12-31 10:43:07	ga_ls9c_ard_3-2-1_104074_2021-12-31_final.stac-item
2022-01-17 11:25:08	ga_ls9c_ard_3-2-1_111071_2022-01-17_final.stac-item
2022-02-20 11:13:52	ga_ls9c_ard_3-2-1_109074_2022-02-20_final.stac-item
2022-04-10 10:19:36	ga_ls9c_ard_3-2-1_100078_2022-04-10_final.stac-item
2022-05-06 09:21:11	ga_ls9c_ard_3-2-1_090087_2022-05-05_final.stac-item
2022-06-05 09:29:24	ga_ls9c_ard_3-2-1_092077_2022-06-04_final.stac-item
2022-06-09 10:41:58	ga_ls9c_ard_3-2-1_104073_2022-06-09_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-06-19 11:22:24	ga_ls9c_ard_3-2-1_110081_2022-06-19_final.stac-item
2022-06-25 09:06:13	ga_ls9c_ard_3-2-1_088080_2022-06-24_final.stac-item
2022-07-02 10:46:05	ga_ls9c_ard_3-2-1_105067_2022-07-02_final.stac-item
2022-07-28 11:29:17	ga_ls9c_ard_3-2-1_111082_2022-07-28_final.stac-item
2022-08-02 11:44:42	ga_ls9c_ard_3-2-1_114074_2022-08-02_final.stac-item
2022-08-12 10:42:36	ga_ls9c_ard_3-2-1_104073_2022-08-12_final.stac-item
2022-08-26 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-08-25_final.stac-item
2022-09-09 09:34:04	ga_ls9c_ard_3-2-1_092087_2022-09-09_final.stac-item
2022-10-17 10:33:42	ga_ls9c_ard_3-2-1_102081_2022-10-17_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-11-03 09:38:02	ga_ls9c_ard_3-2-1_093081_2022-11-03_final.stac-item
2022-11-15 11:38:55	ga_ls9c_ard_3-2-1_113074_2022-11-15_final.stac-item
2022-11-19 09:38:54	ga_ls9c_ard_3-2-1_093083_2022-11-19_final.stac-item
2022-12-14 09:34:18	ga_ls9c_ard_3-2-1_092087_2022-12-14_final.stac-item
2023-01-16 10:16:41	ga_ls9c_ard_3-2-1_099085_2023-01-16_final.stac-item
2023-01-25 10:04:31	ga_ls9c_ard_3-2-1_098070_2023-01-25_final.stac-item
2023-01-27 11:32:16	ga_ls9c_ard_3-2-1_112073_2023-01-27_final.stac-item
2023-02-03 09:58:03	ga_ls9c_ard_3-2-1_097069_2023-02-03_final.stac-item
2023-02-03 09:59:15	ga_ls9c_ard_3-2-1_097072_2023-02-03_final.stac-item
2023-02-08 10:19:49	ga_ls9c_ard_3-2-1_100077_2023-02-08_final.stac-item
2023-02-11 10:47:07	ga_ls9c_ard_3-2-1_105068_2023-02-11_final.stac-item
2023-02-14 11:21:11	ga_ls9c_ard_3-2-1_110076_2023-02-14_final.stac-item
2023-02-24 10:19:34	ga_ls9c_ard_3-2-1_100077_2023-02-24_final.stac-item
2023-02-27 10:46:53	ga_ls9c_ard_3-2-1_105068_2023-02-27_final.stac-item
2023-03-02 11:19:22	ga_ls9c_ard_3-2-1_110072_2023-03-02_final.stac-item
2023-03-11 09:36:34	ga_ls9c_ard_3-2-1_093078_2023-03-11_final.stac-item
2023-03-14 10:03:30	ga_ls9c_ard_3-2-1_098068_2023-03-14_final.stac-item
2023-03-19 10:28:00	ga_ls9c_ard_3-2-1_101083_2023-03-19_final.stac-item
2023-04-09 09:07:03	ga_ls9c_ard_3-2-1_088082_2023-04-08_final.stac-item
2023-04-12 09:38:43	ga_ls9c_ard_3-2-1_093084_2023-04-12_final.stac-item
2023-04-16 09:11:10	ga_ls9c_ard_3-2-1_089077_2023-04-15_final.stac-item
2023-04-23 09:16:32	ga_ls9c_ard_3-2-1_090075_2023-04-22_final.stac-item
2023-04-29 10:18:39	ga_ls9c_ard_3-2-1_100076_2023-04-29_final.stac-item
2023-05-05 09:39:52	ga_ls9c_ard_3-2-1_094072_2023-05-05_final.stac-item
2023-05-27 09:06:36	ga_ls9c_ard_3-2-1_088082_2023-05-26_final.stac-item
2023-06-18 11:45:57	ga_ls9c_ard_3-2-1_114079_2023-06-18_final.stac-item
2023-07-08 11:22:39	ga_ls9c_ard_3-2-1_110082_2023-07-08_final.stac-item
2023-07-15 09:45:36	ga_ls9c_ard_3-2-1_095071_2023-07-15_final.stac-item
2023-07-17 11:14:08	ga_ls9c_ard_3-2-1_109076_2023-07-17_final.stac-item
2023-08-06 09:11:04	ga_ls9c_ard_3-2-1_089077_2023-08-05_final.stac-item
2023-08-27 11:07:51	ga_ls9c_ard_3-2-1_108075_2023-08-27_final.stac-item
2023-08-29 09:22:13	ga_ls9c_ard_3-2-1_090089_2023-08-28_final.stac-item
2023-08-29 10:58:18	ga_ls9c_ard_3-2-1_106082_2023-08-29_final.stac-item
2023-09-07 09:11:20	ga_ls9c_ard_3-2-1_089077_2023-09-06_final.stac-item
2023-10-19 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-10-19_final.stac-item
2023-10-22 10:19:33	ga_ls9c_ard_3-2-1_100077_2023-10-22_final.stac-item
2023-10-30 11:11:43	ga_ls9c_ard_3-2-1_108084_2023-10-30_final.stac-item
2023-11-16 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-11-16_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-12-17 11:08:16	ga_ls9c_ard_3-2-1_108075_2023-12-17_final.stac-item
2023-12-22 11:24:50	ga_ls9c_ard_3-2-1_111070_2023-12-22_final.stac-item
2024-01-18 11:06:13	ga_ls9c_ard_3-2-1_108070_2024-01-18_final.stac-item
2024-02-06 09:58:17	ga_ls9c_ard_3-2-1_097070_2024-02-06_final.stac-item
2024-02-21 09:20:24	ga_ls9c_ard_3-2-1_090084_2024-02-20_final.stac-item
2024-02-29 10:03:30	ga_ls9c_ard_3-2-1_098068_2024-02-29_final.stac-item
2024-03-01 10:47:10	ga_ls9c_ard_3-2-1_105069_2024-03-01_final.stac-item
2024-03-20 09:40:22	ga_ls9c_ard_3-2-1_094072_2024-03-20_final.stac-item
2024-03-20 11:21:39	ga_ls9c_ard_3-2-1_110078_2024-03-20_final.stac-item
2024-03-22 09:34:47	ga_ls9c_ard_3-2-1_092089_2024-03-22_final.stac-item
2024-03-30 11:58:36	ga_ls9c_ard_3-2-1_116078_2024-03-30_final.stac-item
2024-04-01 10:03:45	ga_ls9c_ard_3-2-1_098069_2024-04-01_final.stac-item
2024-04-08 10:09:54	ga_ls9c_ard_3-2-1_099069_2024-04-08_final.stac-item
2024-04-15 10:21:35	ga_ls9c_ard_3-2-1_100083_2024-04-15_final.stac-item
2024-05-02 12:37:03	ga_ls9c_ard_3-2-1_123067_2024-05-02_final.stac-item
2024-05-14 11:28:01	ga_ls9c_ard_3-2-1_111080_2024-05-14_final.stac-item
2024-05-16 11:13:13	ga_ls9c_ard_3-2-1_109074_2024-05-16_nrt.stac-item
2024-05-20 09:10:47	ga_ls9c_ard_3-2-1_089077_2024-05-19_nrt.stac-item
2024-06-01 11:13:53	ga_ls9c_ard_3-2-1_109076_2024-06-01_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