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

90 results

Time (local)	Label
2021-11-14 10:41:51	ga_ls9c_ard_3-2-1_103080_2021-11-14_final.stac-item
2021-12-22 10:50:29	ga_ls9c_ard_3-2-1_105077_2021-12-22_final.stac-item
2022-01-03 09:35:07	ga_ls9c_ard_3-2-1_093074_2022-01-03_final.stac-item
2022-01-03 11:12:24	ga_ls9c_ard_3-2-1_109070_2022-01-03_final.stac-item
2022-01-05 09:25:33	ga_ls9c_ard_3-2-1_091081_2022-01-04_final.stac-item
2022-01-07 10:50:28	ga_ls9c_ard_3-2-1_105077_2022-01-07_final.stac-item
2022-02-02 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-02-02_final.stac-item
2022-02-06 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-02-06_final.stac-item
2022-02-15 09:19:18	ga_ls9c_ard_3-2-1_090081_2022-02-14_final.stac-item
2022-02-16 11:42:14	ga_ls9c_ard_3-2-1_113083_2022-02-16_final.stac-item
2022-03-08 11:13:21	ga_ls9c_ard_3-2-1_109073_2022-03-08_final.stac-item
2022-03-09 10:18:32	ga_ls9c_ard_3-2-1_100075_2022-03-09_final.stac-item
2022-03-10 09:26:30	ga_ls9c_ard_3-2-1_091084_2022-03-09_final.stac-item
2022-03-24 11:12:06	ga_ls9c_ard_3-2-1_109070_2022-03-24_final.stac-item
2022-04-10 10:21:12	ga_ls9c_ard_3-2-1_100082_2022-04-10_final.stac-item
2022-04-14 09:52:27	ga_ls9c_ard_3-2-1_096072_2022-04-14_final.stac-item
2022-04-21 10:03:19	ga_ls9c_ard_3-2-1_097084_2022-04-21_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-06-04 10:25:25	ga_ls9c_ard_3-2-1_101078_2022-06-04_final.stac-item
2022-06-07 09:18:38	ga_ls9c_ard_3-2-1_090081_2022-06-06_final.stac-item
2022-06-24 11:38:19	ga_ls9c_ard_3-2-1_113074_2022-06-24_final.stac-item
2022-07-30 11:17:45	ga_ls9c_ard_3-2-1_109084_2022-07-30_final.stac-item
2022-08-18 11:44:50	ga_ls9c_ard_3-2-1_114074_2022-08-18_final.stac-item
2022-08-19 10:46:26	ga_ls9c_ard_3-2-1_105067_2022-08-19_final.stac-item
2022-08-27 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-08-27_final.stac-item
2022-08-31 11:17:57	ga_ls9c_ard_3-2-1_109084_2022-08-31_final.stac-item
2022-09-01 10:22:20	ga_ls9c_ard_3-2-1_100084_2022-09-01_final.stac-item
2022-09-20 09:13:14	ga_ls9c_ard_3-2-1_089081_2022-09-19_final.stac-item
2022-09-22 10:35:23	ga_ls9c_ard_3-2-1_103070_2022-09-22_final.stac-item
2022-09-27 10:54:45	ga_ls9c_ard_3-2-1_106072_2022-09-27_final.stac-item
2022-10-06 09:10:52	ga_ls9c_ard_3-2-1_089075_2022-10-05_final.stac-item
2022-10-09 09:40:36	ga_ls9c_ard_3-2-1_094072_2022-10-09_final.stac-item
2022-11-19 09:38:06	ga_ls9c_ard_3-2-1_093081_2022-11-19_final.stac-item
2022-12-17 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-12-17_final.stac-item
2022-12-20 10:30:53	ga_ls9c_ard_3-2-1_102074_2022-12-20_final.stac-item
2022-12-25 10:52:12	ga_ls9c_ard_3-2-1_105081_2022-12-25_final.stac-item
2022-12-30 09:33:29	ga_ls9c_ard_3-2-1_092085_2022-12-30_final.stac-item
2023-01-13 11:19:07	ga_ls9c_ard_3-2-1_110071_2023-01-13_final.stac-item
2023-01-25 11:45:24	ga_ls9c_ard_3-2-1_114075_2023-01-25_final.stac-item
2023-01-31 11:06:24	ga_ls9c_ard_3-2-1_108070_2023-01-31_final.stac-item
2023-02-25 09:26:20	ga_ls9c_ard_3-2-1_091083_2023-02-24_final.stac-item
2023-03-24 09:07:36	ga_ls9c_ard_3-2-1_088083_2023-03-23_final.stac-item
2023-03-25 09:47:15	ga_ls9c_ard_3-2-1_095074_2023-03-25_final.stac-item
2023-03-31 09:12:28	ga_ls9c_ard_3-2-1_089080_2023-03-30_final.stac-item
2023-04-05 11:07:06	ga_ls9c_ard_3-2-1_108073_2023-04-05_final.stac-item
2023-04-08 09:57:30	ga_ls9c_ard_3-2-1_097069_2023-04-08_final.stac-item
2023-04-15 10:04:47	ga_ls9c_ard_3-2-1_098072_2023-04-15_final.stac-item
2023-04-19 09:46:04	ga_ls9c_ard_3-2-1_094087_2023-04-19_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-05-09 10:52:50	ga_ls9c_ard_3-2-1_106069_2023-05-09_final.stac-item
2023-06-10 10:54:11	ga_ls9c_ard_3-2-1_106073_2023-06-10_final.stac-item
2023-06-13 11:28:38	ga_ls9c_ard_3-2-1_111082_2023-06-13_final.stac-item
2023-07-10 09:27:26	ga_ls9c_ard_3-2-1_092072_2023-07-09_final.stac-item
2023-07-17 11:17:19	ga_ls9c_ard_3-2-1_109084_2023-07-17_final.stac-item
2023-07-31 11:26:34	ga_ls9c_ard_3-2-1_111076_2023-07-31_final.stac-item
2023-08-06 10:51:57	ga_ls9c_ard_3-2-1_105082_2023-08-06_final.stac-item
2023-08-13 09:16:28	ga_ls9c_ard_3-2-1_090075_2023-08-12_final.stac-item
2023-08-18 11:13:05	ga_ls9c_ard_3-2-1_109073_2023-08-18_final.stac-item
2023-08-21 10:09:09	ga_ls9c_ard_3-2-1_098083_2023-08-21_final.stac-item
2023-09-21 09:24:57	ga_ls9c_ard_3-2-1_091080_2023-09-20_final.stac-item
2023-09-24 11:36:18	ga_ls9c_ard_3-2-1_112084_2023-09-24_final.stac-item
2023-10-01 09:58:25	ga_ls9c_ard_3-2-1_097071_2023-10-01_final.stac-item
2023-10-09 09:10:15	ga_ls9c_ard_3-2-1_089074_2023-10-08_final.stac-item
2023-10-23 11:01:12	ga_ls9c_ard_3-2-1_107073_2023-10-23_final.stac-item
2023-10-24 11:46:04	ga_ls9c_ard_3-2-1_114077_2023-10-24_final.stac-item
2023-10-28 09:44:25	ga_ls9c_ard_3-2-1_094082_2023-10-28_final.stac-item
2023-10-28 11:18:55	ga_ls9c_ard_3-2-1_110071_2023-10-28_final.stac-item
2023-11-01 09:18:27	ga_ls9c_ard_3-2-1_090079_2023-10-31_final.stac-item
2023-11-09 11:46:00	ga_ls9c_ard_3-2-1_114077_2023-11-09_final.stac-item
2023-11-29 11:23:25	ga_ls9c_ard_3-2-1_110082_2023-11-29_final.stac-item
2023-12-20 10:04:17	ga_ls9c_ard_3-2-1_097085_2023-12-20_final.stac-item
2023-12-25 10:19:15	ga_ls9c_ard_3-2-1_100076_2023-12-25_final.stac-item
2023-12-26 11:01:18	ga_ls9c_ard_3-2-1_107073_2023-12-26_final.stac-item
2023-12-29 09:56:06	ga_ls9c_ard_3-2-1_096080_2023-12-29_final.stac-item
2023-12-31 11:22:12	ga_ls9c_ard_3-2-1_110079_2023-12-31_final.stac-item
2024-01-07 09:49:02	ga_ls9c_ard_3-2-1_095078_2024-01-07_final.stac-item
2024-01-10 11:58:51	ga_ls9c_ard_3-2-1_116078_2024-01-10_final.stac-item
2024-01-25 11:17:32	ga_ls9c_ard_3-2-1_109083_2024-01-25_final.stac-item
2024-01-28 10:08:24	ga_ls9c_ard_3-2-1_098080_2024-01-28_final.stac-item
2024-02-03 09:29:22	ga_ls9c_ard_3-2-1_092075_2024-02-02_final.stac-item
2024-02-06 11:41:09	ga_ls9c_ard_3-2-1_113080_2024-02-06_final.stac-item
2024-02-13 10:08:01	ga_ls9c_ard_3-2-1_098079_2024-02-13_final.stac-item
2024-02-28 09:26:13	ga_ls9c_ard_3-2-1_091083_2024-02-27_final.stac-item
2024-02-28 11:01:06	ga_ls9c_ard_3-2-1_107073_2024-02-28_final.stac-item
2024-03-18 11:35:37	ga_ls9c_ard_3-2-1_112082_2024-03-18_final.stac-item
2024-04-05 09:41:25	ga_ls9c_ard_3-2-1_094075_2024-04-05_final.stac-item
2024-04-12 11:26:25	ga_ls9c_ard_3-2-1_111075_2024-04-12_nrt.stac-item
2024-04-19 11:36:03	ga_ls9c_ard_3-2-1_112084_2024-04-19_nrt.stac-item
2024-04-23 11:09:11	ga_ls9c_ard_3-2-1_108079_2024-04-23_nrt.stac-item
2024-04-27 10:40:03	ga_ls9c_ard_3-2-1_104068_2024-04-27_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