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
2021-11-22 11:03:32	ga_ls9c_ard_3-2-1_107075_2021-11-22_final.stac-item
2021-12-28 11:52:18	ga_ls9c_ard_3-2-1_115077_2021-12-28_final.stac-item
2022-01-08 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-08_final.stac-item
2022-01-14 09:18:31	ga_ls9c_ard_3-2-1_090079_2022-01-13_final.stac-item
2022-01-15 09:58:36	ga_ls9c_ard_3-2-1_097071_2022-01-15_final.stac-item
2022-01-20 10:20:45	ga_ls9c_ard_3-2-1_100080_2022-01-20_final.stac-item
2022-01-26 11:20:35	ga_ls9c_ard_3-2-1_110075_2022-01-26_final.stac-item
2022-01-28 09:32:08	ga_ls9c_ard_3-2-1_092082_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
2022-02-09 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-02-09_final.stac-item
2022-02-20 11:12:40	ga_ls9c_ard_3-2-1_109071_2022-02-20_final.stac-item
2022-03-26 09:28:25	ga_ls9c_ard_3-2-1_091089_2022-03-25_final.stac-item
2022-03-27 10:09:16	ga_ls9c_ard_3-2-1_098083_2022-03-27_final.stac-item
2022-04-05 10:00:42	ga_ls9c_ard_3-2-1_097077_2022-04-05_final.stac-item
2022-04-13 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-04-13_final.stac-item
2022-04-13 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-04-13_final.stac-item
2022-05-21 11:51:07	ga_ls9c_ard_3-2-1_115076_2022-05-21_final.stac-item
2022-05-22 09:20:12	ga_ls9c_ard_3-2-1_090085_2022-05-21_final.stac-item
2022-05-22 10:56:41	ga_ls9c_ard_3-2-1_106079_2022-05-22_final.stac-item
2022-06-07 10:53:07	ga_ls9c_ard_3-2-1_106070_2022-06-07_final.stac-item
2022-06-08 11:39:11	ga_ls9c_ard_3-2-1_113077_2022-06-08_final.stac-item
2022-06-21 09:32:01	ga_ls9c_ard_3-2-1_092083_2022-06-21_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-07-24 10:14:16	ga_ls9c_ard_3-2-1_099080_2022-07-24_final.stac-item
2022-08-01 11:00:14	ga_ls9c_ard_3-2-1_107071_2022-08-01_final.stac-item
2022-08-04 11:35:57	ga_ls9c_ard_3-2-1_112083_2022-08-04_final.stac-item
2022-08-08 11:07:17	ga_ls9c_ard_3-2-1_108073_2022-08-08_final.stac-item
2022-08-17 11:00:22	ga_ls9c_ard_3-2-1_107071_2022-08-17_final.stac-item
2022-08-18 10:04:21	ga_ls9c_ard_3-2-1_098070_2022-08-18_final.stac-item
2022-08-18 11:46:50	ga_ls9c_ard_3-2-1_114079_2022-08-18_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-08-29 09:51:26	ga_ls9c_ard_3-2-1_095084_2022-08-29_final.stac-item
2022-09-02 11:00:24	ga_ls9c_ard_3-2-1_107071_2022-09-02_final.stac-item
2022-09-03 10:06:22	ga_ls9c_ard_3-2-1_098075_2022-09-03_final.stac-item
2022-09-16 09:35:08	ga_ls9c_ard_3-2-1_093074_2022-09-16_final.stac-item
2022-09-16 09:37:32	ga_ls9c_ard_3-2-1_093080_2022-09-16_final.stac-item
2022-09-18 09:25:35	ga_ls9c_ard_3-2-1_091081_2022-09-17_final.stac-item
2022-09-18 11:00:29	ga_ls9c_ard_3-2-1_107071_2022-09-18_final.stac-item
2022-09-23 09:41:22	ga_ls9c_ard_3-2-1_094074_2022-09-23_final.stac-item
2022-09-23 11:19:03	ga_ls9c_ard_3-2-1_110071_2022-09-23_final.stac-item
2022-09-25 09:33:00	ga_ls9c_ard_3-2-1_092084_2022-09-25_final.stac-item
2022-09-25 11:06:42	ga_ls9c_ard_3-2-1_108071_2022-09-25_final.stac-item
2022-10-02 09:40:23	ga_ls9c_ard_3-2-1_093087_2022-10-02_final.stac-item
2022-10-09 11:19:53	ga_ls9c_ard_3-2-1_110073_2022-10-09_final.stac-item
2022-10-14 10:01:11	ga_ls9c_ard_3-2-1_097077_2022-10-14_final.stac-item
2022-10-20 11:05:25	ga_ls9c_ard_3-2-1_107083_2022-10-20_final.stac-item
2022-10-27 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-10-27_final.stac-item
2022-10-27 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-10-27_final.stac-item
2022-11-05 09:25:41	ga_ls9c_ard_3-2-1_091081_2022-11-04_final.stac-item
2022-11-06 11:45:03	ga_ls9c_ard_3-2-1_114074_2022-11-06_final.stac-item
2022-11-09 10:39:29	ga_ls9c_ard_3-2-1_103080_2022-11-09_final.stac-item
2022-11-11 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-11-11_final.stac-item
2022-11-12 11:11:12	ga_ls9c_ard_3-2-1_108082_2022-11-12_final.stac-item
2022-11-19 11:13:48	ga_ls9c_ard_3-2-1_109073_2022-11-19_final.stac-item
2022-11-23 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-11-22_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-11-27 10:26:19	ga_ls9c_ard_3-2-1_101078_2022-11-27_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-12-09 10:49:03	ga_ls9c_ard_3-2-1_105073_2022-12-09_final.stac-item
2022-12-12 11:20:21	ga_ls9c_ard_3-2-1_110074_2022-12-12_final.stac-item
2022-12-14 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-14_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2023-01-02 10:00:25	ga_ls9c_ard_3-2-1_097075_2023-01-02_final.stac-item
2023-01-04 11:30:32	ga_ls9c_ard_3-2-1_111084_2023-01-04_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-11 11:33:06	ga_ls9c_ard_3-2-1_112075_2023-01-11_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-01-13 11:23:31	ga_ls9c_ard_3-2-1_110082_2023-01-13_final.stac-item
2023-01-14 10:23:53	ga_ls9c_ard_3-2-1_101072_2023-01-14_final.stac-item
2023-01-25 11:47:24	ga_ls9c_ard_3-2-1_114080_2023-01-25_final.stac-item
2023-01-29 11:24:20	ga_ls9c_ard_3-2-1_110084_2023-01-29_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-14 09:46:41	ga_ls9c_ard_3-2-1_094087_2023-02-14_final.stac-item
2023-02-23 09:40:43	ga_ls9c_ard_3-2-1_093088_2023-02-23_final.stac-item
2023-02-26 11:47:17	ga_ls9c_ard_3-2-1_114080_2023-02-26_final.stac-item
2023-03-27 11:12:08	ga_ls9c_ard_3-2-1_109070_2023-03-27_final.stac-item
2023-03-29 09:28:02	ga_ls9c_ard_3-2-1_091088_2023-03-28_final.stac-item
2023-04-01 11:36:13	ga_ls9c_ard_3-2-1_112084_2023-04-01_final.stac-item
2023-04-07 10:53:32	ga_ls9c_ard_3-2-1_106070_2023-04-07_final.stac-item
2023-04-21 11:05:24	ga_ls9c_ard_3-2-1_108069_2023-04-21_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-04-30 11:04:42	ga_ls9c_ard_3-2-1_107083_2023-04-30_final.stac-item
2023-05-02 10:45:55	ga_ls9c_ard_3-2-1_105067_2023-05-02_final.stac-item
2023-05-05 09:45:03	ga_ls9c_ard_3-2-1_094085_2023-05-05_final.stac-item
2023-05-05 09:45:51	ga_ls9c_ard_3-2-1_094087_2023-05-05_final.stac-item
2023-06-18 10:07:04	ga_ls9c_ard_3-2-1_098079_2023-06-18_final.stac-item
2023-06-25 11:50:07	ga_ls9c_ard_3-2-1_115074_2023-06-25_final.stac-item
2023-07-02 10:21:35	ga_ls9c_ard_3-2-1_100084_2023-07-02_final.stac-item
2023-07-03 10:59:40	ga_ls9c_ard_3-2-1_107071_2023-07-03_final.stac-item
2023-07-17 11:17:19	ga_ls9c_ard_3-2-1_109084_2023-07-17_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_2023-07-20_final.stac-item
2023-08-03 10:18:37	ga_ls9c_ard_3-2-1_100076_2023-08-03_final.stac-item
2023-08-12 10:14:05	ga_ls9c_ard_3-2-1_099080_2023-08-12_final.stac-item
2023-10-14 11:11:45	ga_ls9c_ard_3-2-1_108084_2023-10-14_final.stac-item
2023-10-15 10:14:33	ga_ls9c_ard_3-2-1_099080_2023-10-15_final.stac-item
2023-10-16 10:54:37	ga_ls9c_ard_3-2-1_106072_2023-10-16_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-29 10:23:17	ga_ls9c_ard_3-2-1_101071_2023-10-29_final.stac-item
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final.stac-item
2023-11-04 09:47:20	ga_ls9c_ard_3-2-1_095074_2023-11-04_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