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
2021-11-07 09:18:40	ga_ls9c_ard_3-2-1_090078_2021-11-06_final.stac-item
2021-12-08 10:35:25	ga_ls9c_ard_3-2-1_103070_2021-12-08_final.stac-item
2021-12-13 09:21:48	ga_ls9c_ard_3-2-1_090087_2021-12-12_final.stac-item
2021-12-29 10:54:40	ga_ls9c_ard_3-2-1_106072_2021-12-29_final.stac-item
2021-12-30 10:01:27	ga_ls9c_ard_3-2-1_097078_2021-12-30_final.stac-item
2022-01-02 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-01-02_final.stac-item
2022-01-09 10:36:54	ga_ls9c_ard_3-2-1_103074_2022-01-09_final.stac-item
2022-01-10 11:21:21	ga_ls9c_ard_3-2-1_110077_2022-01-10_final.stac-item
2022-01-18 10:31:31	ga_ls9c_ard_3-2-1_102076_2022-01-18_final.stac-item
2022-01-24 11:35:44	ga_ls9c_ard_3-2-1_112082_2022-01-24_final.stac-item
2022-01-24 11:36:32	ga_ls9c_ard_3-2-1_112084_2022-01-24_final.stac-item
2022-01-30 09:19:22	ga_ls9c_ard_3-2-1_090081_2022-01-29_final.stac-item
2022-02-09 09:53:14	ga_ls9c_ard_3-2-1_096073_2022-02-09_final.stac-item
2022-02-09 11:36:30	ga_ls9c_ard_3-2-1_112084_2022-02-09_final.stac-item
2022-02-14 10:15:43	ga_ls9c_ard_3-2-1_099083_2022-02-14_final.stac-item
2022-02-27 09:43:52	ga_ls9c_ard_3-2-1_094081_2022-02-27_final.stac-item
2022-03-02 11:50:49	ga_ls9c_ard_3-2-1_115074_2022-03-02_final.stac-item
2022-03-08 09:39:40	ga_ls9c_ard_3-2-1_093086_2022-03-08_final.stac-item
2022-03-09 10:17:44	ga_ls9c_ard_3-2-1_100073_2022-03-09_final.stac-item
2022-03-10 09:26:06	ga_ls9c_ard_3-2-1_091083_2022-03-09_final.stac-item
2022-03-20 11:40:50	ga_ls9c_ard_3-2-1_113080_2022-03-20_final.stac-item
2022-03-22 09:51:10	ga_ls9c_ard_3-2-1_095084_2022-03-22_final.stac-item
2022-03-24 09:36:24	ga_ls9c_ard_3-2-1_093078_2022-03-24_final.stac-item
2022-04-05 10:01:30	ga_ls9c_ard_3-2-1_097079_2022-04-05_final.stac-item
2022-04-11 09:26:46	ga_ls9c_ard_3-2-1_091085_2022-04-10_final.stac-item
2022-04-11 09:27:58	ga_ls9c_ard_3-2-1_091088_2022-04-10_final.stac-item
2022-04-19 10:15:42	ga_ls9c_ard_3-2-1_099084_2022-04-19_final.stac-item
2022-05-04 11:07:40	ga_ls9c_ard_3-2-1_108075_2022-05-04_final.stac-item
2022-05-04 11:09:39	ga_ls9c_ard_3-2-1_108080_2022-05-04_final.stac-item
2022-05-14 11:44:38	ga_ls9c_ard_3-2-1_114075_2022-05-14_final.stac-item
2022-05-23 10:03:28	ga_ls9c_ard_3-2-1_097085_2022-05-23_final.stac-item
2022-05-24 09:06:15	ga_ls9c_ard_3-2-1_088081_2022-05-23_final.stac-item
2022-06-26 09:47:29	ga_ls9c_ard_3-2-1_095075_2022-06-26_final.stac-item
2022-07-05 11:20:34	ga_ls9c_ard_3-2-1_110076_2022-07-05_final.stac-item
2022-07-09 10:53:02	ga_ls9c_ard_3-2-1_106069_2022-07-09_final.stac-item
2022-07-13 10:30:16	ga_ls9c_ard_3-2-1_102074_2022-07-13_final.stac-item
2022-07-18 09:13:34	ga_ls9c_ard_3-2-1_089083_2022-07-17_final.stac-item
2022-07-18 10:52:03	ga_ls9c_ard_3-2-1_105082_2022-07-18_final.stac-item
2022-07-23 11:11:05	ga_ls9c_ard_3-2-1_108083_2022-07-23_final.stac-item
2022-08-04 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-08-04_final.stac-item
2022-08-13 09:47:23	ga_ls9c_ard_3-2-1_095074_2022-08-13_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 09:47:50	ga_ls9c_ard_3-2-1_095075_2022-08-29_final.stac-item
2022-09-02 09:27:06	ga_ls9c_ard_3-2-1_091085_2022-09-01_final.stac-item
2022-09-06 10:36:52	ga_ls9c_ard_3-2-1_103074_2022-09-06_final.stac-item
2022-10-07 09:52:32	ga_ls9c_ard_3-2-1_096071_2022-10-07_final.stac-item
2022-10-08 10:37:00	ga_ls9c_ard_3-2-1_103074_2022-10-08_final.stac-item
2022-10-18 09:38:29	ga_ls9c_ard_3-2-1_093082_2022-10-18_final.stac-item
2022-10-29 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-10-28_final.stac-item
2022-11-04 10:21:42	ga_ls9c_ard_3-2-1_100082_2022-11-04_final.stac-item
2022-11-10 11:21:10	ga_ls9c_ard_3-2-1_110076_2022-11-10_final.stac-item
2022-11-30 10:55:36	ga_ls9c_ard_3-2-1_106074_2022-11-30_final.stac-item
2022-12-02 10:44:02	ga_ls9c_ard_3-2-1_104076_2022-12-02_final.stac-item
2022-12-05 11:13:21	ga_ls9c_ard_3-2-1_109072_2022-12-05_final.stac-item
2022-12-08 10:08:11	ga_ls9c_ard_3-2-1_098079_2022-12-08_final.stac-item
2022-12-12 11:23:33	ga_ls9c_ard_3-2-1_110082_2022-12-12_final.stac-item
2022-12-17 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-12-17_final.stac-item
2022-12-18 10:41:16	ga_ls9c_ard_3-2-1_104069_2022-12-18_final.stac-item
2022-12-23 09:27:40	ga_ls9c_ard_3-2-1_091086_2022-12-22_final.stac-item
2022-12-31 10:13:10	ga_ls9c_ard_3-2-1_099076_2022-12-31_final.stac-item
2023-01-04 09:49:39	ga_ls9c_ard_3-2-1_095079_2023-01-04_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-16 11:53:34	ga_ls9c_ard_3-2-1_115080_2023-01-16_final.stac-item
2023-01-22 11:14:02	ga_ls9c_ard_3-2-1_109074_2023-01-22_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-22 10:31:10	ga_ls9c_ard_3-2-1_102075_2023-02-22_final.stac-item
2023-02-26 10:06:25	ga_ls9c_ard_3-2-1_098075_2023-02-26_final.stac-item
2023-03-02 09:45:16	ga_ls9c_ard_3-2-1_094084_2023-03-02_final.stac-item
2023-03-02 11:22:57	ga_ls9c_ard_3-2-1_110081_2023-03-02_final.stac-item
2023-03-06 10:55:47	ga_ls9c_ard_3-2-1_106075_2023-03-06_final.stac-item
2023-03-15 09:16:40	ga_ls9c_ard_3-2-1_089090_2023-03-14_final.stac-item
2023-03-16 09:52:44	ga_ls9c_ard_3-2-1_096072_2023-03-16_final.stac-item
2023-03-18 11:20:03	ga_ls9c_ard_3-2-1_110074_2023-03-18_final.stac-item
2023-04-05 11:07:06	ga_ls9c_ard_3-2-1_108073_2023-04-05_final.stac-item
2023-04-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2023-04-23_final.stac-item
2023-04-26 09:51:24	ga_ls9c_ard_3-2-1_095085_2023-04-26_final.stac-item
2023-04-30 09:23:01	ga_ls9c_ard_3-2-1_091076_2023-04-29_final.stac-item
2023-05-02 10:45:55	ga_ls9c_ard_3-2-1_105067_2023-05-02_final.stac-item
2023-05-03 11:35:56	ga_ls9c_ard_3-2-1_112084_2023-05-03_final.stac-item
2023-05-23 11:10:38	ga_ls9c_ard_3-2-1_108083_2023-05-23_final.stac-item
2023-05-29 10:28:21	ga_ls9c_ard_3-2-1_102070_2023-05-29_final.stac-item
2023-06-19 09:13:50	ga_ls9c_ard_3-2-1_089085_2023-06-18_final.stac-item
2023-07-04 10:08:03	ga_ls9c_ard_3-2-1_098081_2023-07-04_final.stac-item
2023-07-14 09:07:08	ga_ls9c_ard_3-2-1_088083_2023-07-13_final.stac-item
2023-07-20 11:44:14	ga_ls9c_ard_3-2-1_114074_2023-07-20_final.stac-item
2023-07-23 10:37:26	ga_ls9c_ard_3-2-1_103077_2023-07-23_final.stac-item
2023-08-04 09:23:01	ga_ls9c_ard_3-2-1_091076_2023-08-03_final.stac-item
2023-08-10 10:27:39	ga_ls9c_ard_3-2-1_101083_2023-08-10_final.stac-item
2023-08-27 11:07:27	ga_ls9c_ard_3-2-1_108074_2023-08-27_final.stac-item
2023-09-02 10:28:25	ga_ls9c_ard_3-2-1_102069_2023-09-02_final.stac-item
2023-09-04 10:22:04	ga_ls9c_ard_3-2-1_100084_2023-09-04_final.stac-item
2023-09-07 10:48:37	ga_ls9c_ard_3-2-1_105073_2023-09-07_final.stac-item
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_2023-10-17_final.stac-item
2023-10-20 10:30:43	ga_ls9c_ard_3-2-1_102074_2023-10-20_final.stac-item
2023-11-22 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-11-22_final.stac-item
2023-11-22 11:17:35	ga_ls9c_ard_3-2-1_109083_2023-11-22_final.stac-item
2023-11-26 10:48:31	ga_ls9c_ard_3-2-1_105072_2023-11-26_final.stac-item
2023-11-27 09:55:17	ga_ls9c_ard_3-2-1_096078_2023-11-27_final.stac-item
2023-11-29 09:40:32	ga_ls9c_ard_3-2-1_094072_2023-11-29_final.stac-item
2023-11-29 11:19:49	ga_ls9c_ard_3-2-1_110073_2023-11-29_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