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

95 results

Time (local)	Label
2021-12-04 09:29:17	ga_ls9c_ard_3-2-1_091090_2021-12-03_final.stac-item
2022-01-20 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-01-20_final.stac-item
2022-01-24 11:36:08	ga_ls9c_ard_3-2-1_112083_2022-01-24_final.stac-item
2022-02-09 11:36:30	ga_ls9c_ard_3-2-1_112084_2022-02-09_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-03-12 09:12:33	ga_ls9c_ard_3-2-1_089080_2022-03-11_final.stac-item
2022-03-19 10:55:59	ga_ls9c_ard_3-2-1_106076_2022-03-19_final.stac-item
2022-03-25 10:17:40	ga_ls9c_ard_3-2-1_100073_2022-03-25_final.stac-item
2022-04-04 09:22:38	ga_ls9c_ard_3-2-1_090090_2022-04-03_final.stac-item
2022-05-04 11:10:03	ga_ls9c_ard_3-2-1_108081_2022-05-04_final.stac-item
2022-05-29 09:26:47	ga_ls9c_ard_3-2-1_091086_2022-05-28_final.stac-item
2022-06-03 11:19:50	ga_ls9c_ard_3-2-1_110075_2022-06-03_final.stac-item
2022-06-07 09:21:49	ga_ls9c_ard_3-2-1_090089_2022-06-06_final.stac-item
2022-06-19 11:23:11	ga_ls9c_ard_3-2-1_110083_2022-06-19_final.stac-item
2022-06-21 09:34:01	ga_ls9c_ard_3-2-1_092088_2022-06-21_final.stac-item
2022-07-07 09:32:54	ga_ls9c_ard_3-2-1_092085_2022-07-07_final.stac-item
2022-07-11 10:45:50	ga_ls9c_ard_3-2-1_104082_2022-07-11_final.stac-item
2022-07-28 09:46:49	ga_ls9c_ard_3-2-1_095073_2022-07-28_final.stac-item
2022-08-13 09:46:35	ga_ls9c_ard_3-2-1_095072_2022-08-13_final.stac-item
2022-08-13 11:25:52	ga_ls9c_ard_3-2-1_111073_2022-08-13_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-09-09 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-09-08_final.stac-item
2022-09-19 10:03:40	ga_ls9c_ard_3-2-1_098068_2022-09-19_final.stac-item
2022-09-28 09:58:43	ga_ls9c_ard_3-2-1_097071_2022-09-28_final.stac-item
2022-10-04 11:01:43	ga_ls9c_ard_3-2-1_107074_2022-10-04_final.stac-item
2022-10-21 10:07:48	ga_ls9c_ard_3-2-1_098078_2022-10-21_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-25 11:20:46	ga_ls9c_ard_3-2-1_110075_2022-10-25_final.stac-item
2022-11-07 09:15:21	ga_ls9c_ard_3-2-1_089086_2022-11-06_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-14 10:53:40	ga_ls9c_ard_3-2-1_106069_2022-11-14_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-12-10 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-12-10_final.stac-item
2022-12-12 09:41:28	ga_ls9c_ard_3-2-1_094074_2022-12-12_final.stac-item
2022-12-19 11:26:31	ga_ls9c_ard_3-2-1_111074_2022-12-19_final.stac-item
2023-01-01 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-12-31_final.stac-item
2023-01-06 09:40:53	ga_ls9c_ard_3-2-1_093088_2023-01-06_final.stac-item
2023-01-17 09:21:50	ga_ls9c_ard_3-2-1_090087_2023-01-16_final.stac-item
2023-01-17 10:55:08	ga_ls9c_ard_3-2-1_106073_2023-01-17_final.stac-item
2023-01-22 11:17:38	ga_ls9c_ard_3-2-1_109083_2023-01-22_final.stac-item
2023-02-04 09:08:01	ga_ls9c_ard_3-2-1_088083_2023-02-03_final.stac-item
2023-02-08 10:19:01	ga_ls9c_ard_3-2-1_100075_2023-02-08_final.stac-item
2023-02-25 11:02:26	ga_ls9c_ard_3-2-1_107076_2023-02-25_final.stac-item
2023-02-27 09:14:47	ga_ls9c_ard_3-2-1_089085_2023-02-26_final.stac-item
2023-02-27 10:52:28	ga_ls9c_ard_3-2-1_105082_2023-02-27_final.stac-item
2023-03-06 10:55:47	ga_ls9c_ard_3-2-1_106075_2023-03-06_final.stac-item
2023-03-25 09:46:04	ga_ls9c_ard_3-2-1_095071_2023-03-25_final.stac-item
2023-04-08 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-04-08_final.stac-item
2023-04-14 11:00:25	ga_ls9c_ard_3-2-1_107072_2023-04-14_final.stac-item
2023-04-15 10:03:11	ga_ls9c_ard_3-2-1_098068_2023-04-15_final.stac-item
2023-05-02 09:11:01	ga_ls9c_ard_3-2-1_089077_2023-05-01_final.stac-item
2023-05-05 11:23:09	ga_ls9c_ard_3-2-1_110083_2023-05-05_final.stac-item
2023-05-08 10:15:58	ga_ls9c_ard_3-2-1_099085_2023-05-08_final.stac-item
2023-06-14 10:29:24	ga_ls9c_ard_3-2-1_102073_2023-06-14_final.stac-item
2023-06-25 10:10:26	ga_ls9c_ard_3-2-1_099072_2023-06-25_final.stac-item
2023-06-25 10:14:26	ga_ls9c_ard_3-2-1_099082_2023-06-25_final.stac-item
2023-07-03 10:59:16	ga_ls9c_ard_3-2-1_107070_2023-07-03_final.stac-item
2023-08-02 09:39:21	ga_ls9c_ard_3-2-1_093086_2023-08-02_final.stac-item
2023-08-04 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-08-04_final.stac-item
2023-08-18 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-08-18_final.stac-item
2023-08-20 09:22:17	ga_ls9c_ard_3-2-1_091074_2023-08-19_final.stac-item
2023-08-26 10:25:22	ga_ls9c_ard_3-2-1_101077_2023-08-26_final.stac-item
2023-08-29 09:17:25	ga_ls9c_ard_3-2-1_090077_2023-08-28_final.stac-item
2023-08-31 09:06:16	ga_ls9c_ard_3-2-1_088080_2023-08-30_final.stac-item
2023-09-05 09:26:27	ga_ls9c_ard_3-2-1_091084_2023-09-04_final.stac-item
2023-09-11 10:25:32	ga_ls9c_ard_3-2-1_101077_2023-09-11_final.stac-item
2023-10-21 09:40:41	ga_ls9c_ard_3-2-1_093088_2023-10-21_final.stac-item
2023-10-24 11:47:39	ga_ls9c_ard_3-2-1_114081_2023-10-24_final.stac-item
2023-10-30 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-10-29_final.stac-item
2023-10-30 09:33:38	ga_ls9c_ard_3-2-1_092086_2023-10-30_final.stac-item
2023-11-12 10:39:13	ga_ls9c_ard_3-2-1_103080_2023-11-12_final.stac-item
2023-11-14 10:23:16	ga_ls9c_ard_3-2-1_101071_2023-11-14_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final.stac-item
2023-11-18 11:38:39	ga_ls9c_ard_3-2-1_113074_2023-11-18_final.stac-item
2023-12-04 11:41:31	ga_ls9c_ard_3-2-1_113081_2023-12-04_final.stac-item
2023-12-12 10:49:41	ga_ls9c_ard_3-2-1_105075_2023-12-12_final.stac-item
2023-12-17 11:06:40	ga_ls9c_ard_3-2-1_108071_2023-12-17_final.stac-item
2024-01-01 10:23:23	ga_ls9c_ard_3-2-1_101071_2024-01-01_final.stac-item
2024-01-04 09:18:09	ga_ls9c_ard_3-2-1_090078_2024-01-03_final.stac-item
2024-01-04 10:56:38	ga_ls9c_ard_3-2-1_106077_2024-01-04_final.stac-item
2024-01-06 10:43:03	ga_ls9c_ard_3-2-1_104074_2024-01-06_final.stac-item
2024-01-09 09:33:54	ga_ls9c_ard_3-2-1_093071_2024-01-09_final.stac-item
2024-02-02 10:26:11	ga_ls9c_ard_3-2-1_101078_2024-02-02_final.stac-item
2024-02-29 10:03:06	ga_ls9c_ard_3-2-1_098067_2024-02-29_final.stac-item
2024-03-06 09:34:26	ga_ls9c_ard_3-2-1_092088_2024-03-06_final.stac-item
2024-03-15 09:26:14	ga_ls9c_ard_3-2-1_091083_2024-03-14_final.stac-item
2024-04-01 10:02:58	ga_ls9c_ard_3-2-1_098067_2024-04-01_final.stac-item
2024-04-01 11:47:26	ga_ls9c_ard_3-2-1_114081_2024-04-01_final.stac-item
2024-04-14 11:14:26	ga_ls9c_ard_3-2-1_109076_2024-04-14_final.stac-item
2024-04-15 10:17:12	ga_ls9c_ard_3-2-1_100072_2024-04-15_final.stac-item
2024-05-02 09:27:40	ga_ls9c_ard_3-2-1_091088_2024-05-01_final.stac-item
2024-05-06 10:35:27	ga_ls9c_ard_3-2-1_103072_2024-05-06_final.stac-item
2024-05-11 10:54:47	ga_ls9c_ard_3-2-1_106074_2024-05-11_final.stac-item
2024-05-14 09:45:33	ga_ls9c_ard_3-2-1_095071_2024-05-14_interim.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