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 09:36:13	ga_ls9c_ard_3-2-1_093075_2021-11-05_final.stac-item
2021-11-24 10:44:46	ga_ls9c_ard_3-2-1_104075_2021-11-24_final.stac-item
2021-12-12 11:51:56	ga_ls9c_ard_3-2-1_115076_2021-12-12_final.stac-item
2021-12-23 09:57:40	ga_ls9c_ard_3-2-1_096084_2021-12-23_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-28 09:33:20	ga_ls9c_ard_3-2-1_092085_2022-01-28_final.stac-item
2022-02-04 11:17:59	ga_ls9c_ard_3-2-1_109084_2022-02-04_final.stac-item
2022-02-22 09:28:36	ga_ls9c_ard_3-2-1_091089_2022-02-21_final.stac-item
2022-04-11 09:23:34	ga_ls9c_ard_3-2-1_091077_2022-04-10_final.stac-item
2022-04-12 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-04-12_final.stac-item
2022-04-20 09:18:04	ga_ls9c_ard_3-2-1_090079_2022-04-19_final.stac-item
2022-05-03 10:22:49	ga_ls9c_ard_3-2-1_101071_2022-05-03_final.stac-item
2022-05-07 10:03:39	ga_ls9c_ard_3-2-1_097085_2022-05-07_final.stac-item
2022-05-14 10:04:33	ga_ls9c_ard_3-2-1_098072_2022-05-14_final.stac-item
2022-05-18 09:40:34	ga_ls9c_ard_3-2-1_094074_2022-05-18_final.stac-item
2022-06-12 09:34:25	ga_ls9c_ard_3-2-1_093074_2022-06-12_final.stac-item
2022-06-30 09:23:33	ga_ls9c_ard_3-2-1_091077_2022-06-29_final.stac-item
2022-07-03 11:35:43	ga_ls9c_ard_3-2-1_112083_2022-07-03_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-08 10:14:57	ga_ls9c_ard_3-2-1_099082_2022-07-08_final.stac-item
2022-07-10 11:41:28	ga_ls9c_ard_3-2-1_113082_2022-07-10_final.stac-item
2022-07-14 11:17:31	ga_ls9c_ard_3-2-1_109084_2022-07-14_final.stac-item
2022-07-21 11:20:37	ga_ls9c_ard_3-2-1_110076_2022-07-21_final.stac-item
2022-08-01 11:01:26	ga_ls9c_ard_3-2-1_107074_2022-08-01_final.stac-item
2022-08-10 10:58:32	ga_ls9c_ard_3-2-1_106082_2022-08-10_final.stac-item
2022-08-27 10:02:11	ga_ls9c_ard_3-2-1_097080_2022-08-27_final.stac-item
2022-09-05 09:55:12	ga_ls9c_ard_3-2-1_096078_2022-09-05_final.stac-item
2022-09-07 11:23:43	ga_ls9c_ard_3-2-1_110083_2022-09-07_final.stac-item
2022-09-14 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-09-14_final.stac-item
2022-09-19 10:10:27	ga_ls9c_ard_3-2-1_098085_2022-09-19_final.stac-item
2022-10-04 09:27:13	ga_ls9c_ard_3-2-1_091085_2022-10-03_final.stac-item
2022-10-25 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-10-25_final.stac-item
2022-10-30 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-10-30_final.stac-item
2022-11-05 09:26:29	ga_ls9c_ard_3-2-1_091083_2022-11-04_final.stac-item
2022-11-06 11:47:51	ga_ls9c_ard_3-2-1_114081_2022-11-06_final.stac-item
2022-11-07 09:13:45	ga_ls9c_ard_3-2-1_089082_2022-11-06_final.stac-item
2022-11-08 11:35:30	ga_ls9c_ard_3-2-1_112081_2022-11-08_final.stac-item
2022-11-13 10:12:47	ga_ls9c_ard_3-2-1_099075_2022-11-13_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-11-17 11:29:21	ga_ls9c_ard_3-2-1_111081_2022-11-17_final.stac-item
2022-11-22 11:45:05	ga_ls9c_ard_3-2-1_114074_2022-11-22_final.stac-item
2022-12-02 10:44:02	ga_ls9c_ard_3-2-1_104076_2022-12-02_final.stac-item
2022-12-06 10:18:08	ga_ls9c_ard_3-2-1_100073_2022-12-06_final.stac-item
2022-12-09 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-12-09_final.stac-item
2022-12-16 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-12-16_final.stac-item
2023-01-16 10:16:41	ga_ls9c_ard_3-2-1_099085_2023-01-16_final.stac-item
2023-01-24 09:26:49	ga_ls9c_ard_3-2-1_091084_2023-01-23_final.stac-item
2023-01-26 09:12:54	ga_ls9c_ard_3-2-1_089080_2023-01-25_final.stac-item
2023-01-27 09:57:47	ga_ls9c_ard_3-2-1_096084_2023-01-27_final.stac-item
2023-01-29 11:20:44	ga_ls9c_ard_3-2-1_110075_2023-01-29_final.stac-item
2023-01-29 11:24:20	ga_ls9c_ard_3-2-1_110084_2023-01-29_final.stac-item
2023-02-09 11:01:53	ga_ls9c_ard_3-2-1_107074_2023-02-09_final.stac-item
2023-02-10 11:46:44	ga_ls9c_ard_3-2-1_114078_2023-02-10_final.stac-item
2023-02-14 11:23:34	ga_ls9c_ard_3-2-1_110082_2023-02-14_final.stac-item
2023-02-24 10:21:33	ga_ls9c_ard_3-2-1_100082_2023-02-24_final.stac-item
2023-03-02 11:23:45	ga_ls9c_ard_3-2-1_110083_2023-03-02_final.stac-item
2023-03-16 09:51:56	ga_ls9c_ard_3-2-1_096070_2023-03-16_final.stac-item
2023-03-27 09:34:51	ga_ls9c_ard_3-2-1_093074_2023-03-27_final.stac-item
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final.stac-item
2023-04-21 09:32:54	ga_ls9c_ard_3-2-1_092085_2023-04-21_final.stac-item
2023-04-22 11:52:15	ga_ls9c_ard_3-2-1_115078_2023-04-22_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-04-26 11:28:41	ga_ls9c_ard_3-2-1_111081_2023-04-26_final.stac-item
2023-05-02 10:46:19	ga_ls9c_ard_3-2-1_105068_2023-05-02_final.stac-item
2023-05-05 11:18:21	ga_ls9c_ard_3-2-1_110071_2023-05-05_final.stac-item
2023-05-09 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-05-08_final.stac-item
2023-05-12 09:50:50	ga_ls9c_ard_3-2-1_095084_2023-05-12_final.stac-item
2023-05-18 09:13:18	ga_ls9c_ard_3-2-1_089083_2023-05-17_final.stac-item
2023-05-19 11:35:49	ga_ls9c_ard_3-2-1_112084_2023-05-19_final.stac-item
2023-05-28 09:46:17	ga_ls9c_ard_3-2-1_095073_2023-05-28_final.stac-item
2023-06-04 09:51:15	ga_ls9c_ard_3-2-1_096070_2023-06-04_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 11:22:49	ga_ls9c_ard_3-2-1_110083_2023-06-22_final.stac-item
2023-06-26 09:20:25	ga_ls9c_ard_3-2-1_090086_2023-06-25_final.stac-item
2023-06-27 11:41:00	ga_ls9c_ard_3-2-1_113082_2023-06-27_final.stac-item
2023-07-06 09:56:31	ga_ls9c_ard_3-2-1_096083_2023-07-06_final.stac-item
2023-07-19 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-07-18_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-07-29 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-07-29_final.stac-item
2023-08-02 11:13:02	ga_ls9c_ard_3-2-1_109073_2023-08-02_final.stac-item
2023-08-04 11:04:41	ga_ls9c_ard_3-2-1_107083_2023-08-04_final.stac-item
2023-08-09 09:45:59	ga_ls9c_ard_3-2-1_094087_2023-08-09_final.stac-item
2023-10-14 11:07:22	ga_ls9c_ard_3-2-1_108073_2023-10-14_final.stac-item
2023-10-17 09:58:12	ga_ls9c_ard_3-2-1_097070_2023-10-17_final.stac-item
2023-10-17 09:59:00	ga_ls9c_ard_3-2-1_097072_2023-10-17_final.stac-item
2023-10-19 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-10-19_final.stac-item
2023-10-21 11:12:23	ga_ls9c_ard_3-2-1_109070_2023-10-21_final.stac-item
2023-10-23 11:00:49	ga_ls9c_ard_3-2-1_107072_2023-10-23_final.stac-item
2023-10-24 11:47:16	ga_ls9c_ard_3-2-1_114080_2023-10-24_final.stac-item
2023-10-25 10:48:02	ga_ls9c_ard_3-2-1_105071_2023-10-25_final.stac-item
2023-10-26 11:35:41	ga_ls9c_ard_3-2-1_112082_2023-10-26_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-11-01 10:57:43	ga_ls9c_ard_3-2-1_106080_2023-11-01_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-02 10:04:05	ga_ls9c_ard_3-2-1_097085_2023-11-02_final.stac-item
2023-11-15 09:33:13	ga_ls9c_ard_3-2-1_092085_2023-11-15_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-19 10:45:27	ga_ls9c_ard_3-2-1_104080_2023-11-19_final.stac-item
2023-11-21 10:28:43	ga_ls9c_ard_3-2-1_102069_2023-11-21_final.stac-item
2023-11-24 09:28:22	ga_ls9c_ard_3-2-1_091088_2023-11-23_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years