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
2021-11-01 10:12:54	ga_ls9c_ard_3-2-1_099073_2021-11-01_final.stac-item
2021-11-15 11:18:14	ga_ls9c_ard_3-2-1_110071_2021-11-15_final.stac-item
2021-12-22 10:50:29	ga_ls9c_ard_3-2-1_105077_2021-12-22_final.stac-item
2022-01-02 10:30:45	ga_ls9c_ard_3-2-1_102074_2022-01-02_final.stac-item
2022-01-13 11:51:02	ga_ls9c_ard_3-2-1_115074_2022-01-13_final.stac-item
2022-01-28 09:32:56	ga_ls9c_ard_3-2-1_092084_2022-01-28_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-19 10:53:59	ga_ls9c_ard_3-2-1_106071_2022-03-19_final.stac-item
2022-03-22 09:47:11	ga_ls9c_ard_3-2-1_095074_2022-03-22_final.stac-item
2022-03-24 11:12:06	ga_ls9c_ard_3-2-1_109070_2022-03-24_final.stac-item
2022-03-29 11:36:12	ga_ls9c_ard_3-2-1_112084_2022-03-29_final.stac-item
2022-04-08 10:28:23	ga_ls9c_ard_3-2-1_102069_2022-04-08_final.stac-item
2022-04-08 10:30:47	ga_ls9c_ard_3-2-1_102075_2022-04-08_final.stac-item
2022-04-10 10:17:12	ga_ls9c_ard_3-2-1_100072_2022-04-10_final.stac-item
2022-04-14 11:35:43	ga_ls9c_ard_3-2-1_112083_2022-04-14_final.stac-item
2022-05-07 10:01:39	ga_ls9c_ard_3-2-1_097080_2022-05-07_final.stac-item
2022-05-13 11:01:23	ga_ls9c_ard_3-2-1_107075_2022-05-13_final.stac-item
2022-05-14 10:02:57	ga_ls9c_ard_3-2-1_098068_2022-05-14_final.stac-item
2022-05-22 10:55:29	ga_ls9c_ard_3-2-1_106076_2022-05-22_final.stac-item
2022-05-27 09:39:56	ga_ls9c_ard_3-2-1_093088_2022-05-27_final.stac-item
2022-06-07 09:19:50	ga_ls9c_ard_3-2-1_090084_2022-06-06_final.stac-item
2022-06-10 09:46:21	ga_ls9c_ard_3-2-1_095073_2022-06-10_final.stac-item
2022-06-25 10:45:06	ga_ls9c_ard_3-2-1_104080_2022-06-25_final.stac-item
2022-07-09 09:18:56	ga_ls9c_ard_3-2-1_090081_2022-07-08_final.stac-item
2022-07-10 09:57:24	ga_ls9c_ard_3-2-1_097069_2022-07-10_final.stac-item
2022-08-01 11:05:01	ga_ls9c_ard_3-2-1_107083_2022-08-01_final.stac-item
2022-08-12 10:41:24	ga_ls9c_ard_3-2-1_104070_2022-08-12_final.stac-item
2022-08-15 11:17:31	ga_ls9c_ard_3-2-1_109083_2022-08-15_final.stac-item
2022-08-20 11:35:17	ga_ls9c_ard_3-2-1_112081_2022-08-20_final.stac-item
2022-09-07 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-09-07_final.stac-item
2022-09-14 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-09-14_final.stac-item
2022-09-15 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-09-15_final.stac-item
2022-09-19 10:05:16	ga_ls9c_ard_3-2-1_098072_2022-09-19_final.stac-item
2022-09-20 10:47:44	ga_ls9c_ard_3-2-1_105070_2022-09-20_final.stac-item
2022-09-22 10:35:23	ga_ls9c_ard_3-2-1_103070_2022-09-22_final.stac-item
2022-09-26 11:51:10	ga_ls9c_ard_3-2-1_115074_2022-09-26_final.stac-item
2022-10-02 09:35:12	ga_ls9c_ard_3-2-1_093074_2022-10-02_final.stac-item
2022-10-06 09:10:52	ga_ls9c_ard_3-2-1_089075_2022-10-05_final.stac-item
2022-10-25 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-10-25_final.stac-item
2022-11-03 11:17:43	ga_ls9c_ard_3-2-1_109083_2022-11-03_final.stac-item
2022-11-04 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-11-04_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-10 11:20:22	ga_ls9c_ard_3-2-1_110074_2022-11-10_final.stac-item
2022-11-16 10:41:18	ga_ls9c_ard_3-2-1_104069_2022-11-16_final.stac-item
2022-11-22 10:08:36	ga_ls9c_ard_3-2-1_098080_2022-11-22_final.stac-item
2022-11-23 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-11-22_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2023-01-02 10:00:49	ga_ls9c_ard_3-2-1_097076_2023-01-02_final.stac-item
2023-01-08 09:28:31	ga_ls9c_ard_3-2-1_091088_2023-01-07_final.stac-item
2023-01-13 09:45:25	ga_ls9c_ard_3-2-1_094084_2023-01-13_final.stac-item
2023-01-15 09:31:50	ga_ls9c_ard_3-2-1_092081_2023-01-15_final.stac-item
2023-01-15 11:08:20	ga_ls9c_ard_3-2-1_108075_2023-01-15_final.stac-item
2023-01-28 10:37:04	ga_ls9c_ard_3-2-1_103074_2023-01-28_final.stac-item
2023-01-31 11:06:24	ga_ls9c_ard_3-2-1_108070_2023-01-31_final.stac-item
2023-02-05 11:28:11	ga_ls9c_ard_3-2-1_111078_2023-02-05_final.stac-item
2023-02-09 11:02:40	ga_ls9c_ard_3-2-1_107076_2023-02-09_final.stac-item
2023-03-11 11:13:28	ga_ls9c_ard_3-2-1_109073_2023-03-11_final.stac-item
2023-03-21 10:16:02	ga_ls9c_ard_3-2-1_099084_2023-03-21_final.stac-item
2023-03-28 11:58:34	ga_ls9c_ard_3-2-1_116078_2023-03-28_final.stac-item
2023-03-31 09:12:28	ga_ls9c_ard_3-2-1_089080_2023-03-30_final.stac-item
2023-04-03 11:18:16	ga_ls9c_ard_3-2-1_110070_2023-04-03_final.stac-item
2023-04-14 09:25:08	ga_ls9c_ard_3-2-1_091081_2023-04-13_final.stac-item
2023-04-19 09:44:52	ga_ls9c_ard_3-2-1_094084_2023-04-19_final.stac-item
2023-04-28 09:37:01	ga_ls9c_ard_3-2-1_093080_2023-04-28_final.stac-item
2023-05-03 11:35:08	ga_ls9c_ard_3-2-1_112082_2023-05-03_final.stac-item
2023-05-05 11:19:33	ga_ls9c_ard_3-2-1_110074_2023-05-05_final.stac-item
2023-05-07 11:09:35	ga_ls9c_ard_3-2-1_108080_2023-05-07_final.stac-item
2023-05-09 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-05-08_final.stac-item
2023-05-18 09:10:54	ga_ls9c_ard_3-2-1_089077_2023-05-17_final.stac-item
2023-05-21 09:40:09	ga_ls9c_ard_3-2-1_094073_2023-05-21_final.stac-item
2023-06-01 09:25:33	ga_ls9c_ard_3-2-1_091083_2023-05-31_final.stac-item
2023-07-13 11:41:14	ga_ls9c_ard_3-2-1_113082_2023-07-13_final.stac-item
2023-07-19 09:23:17	ga_ls9c_ard_3-2-1_091077_2023-07-18_final.stac-item
2023-07-24 09:44:36	ga_ls9c_ard_3-2-1_094084_2023-07-24_final.stac-item
2023-08-07 11:31:14	ga_ls9c_ard_3-2-1_112072_2023-08-07_final.stac-item
2023-08-13 10:55:21	ga_ls9c_ard_3-2-1_106075_2023-08-13_final.stac-item
2023-08-16 09:49:22	ga_ls9c_ard_3-2-1_095080_2023-08-16_final.stac-item
2023-08-21 10:03:34	ga_ls9c_ard_3-2-1_098069_2023-08-21_final.stac-item
2023-08-31 10:42:46	ga_ls9c_ard_3-2-1_104074_2023-08-31_final.stac-item
2023-09-26 11:18:43	ga_ls9c_ard_3-2-1_110071_2023-09-26_final.stac-item
2023-10-04 10:29:22	ga_ls9c_ard_3-2-1_102071_2023-10-04_final.stac-item
2023-10-08 10:05:04	ga_ls9c_ard_3-2-1_098072_2023-10-08_final.stac-item
2023-10-09 09:16:39	ga_ls9c_ard_3-2-1_089090_2023-10-08_final.stac-item
2023-10-12 11:18:54	ga_ls9c_ard_3-2-1_110071_2023-10-12_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_2023-10-13_final.stac-item
2023-10-19 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-10-19_final.stac-item
2023-10-23 09:22:43	ga_ls9c_ard_3-2-1_091074_2023-10-22_final.stac-item
2023-10-28 09:44:25	ga_ls9c_ard_3-2-1_094082_2023-10-28_final.stac-item
2023-10-30 11:08:31	ga_ls9c_ard_3-2-1_108076_2023-10-30_final.stac-item
2023-11-04 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-11-04_final.stac-item
2023-11-04 11:28:37	ga_ls9c_ard_3-2-1_111080_2023-11-04_final.stac-item
2023-11-11 11:35:14	ga_ls9c_ard_3-2-1_112081_2023-11-11_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-20 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-11-20_final.stac-item
2023-11-29 09:43:44	ga_ls9c_ard_3-2-1_094080_2023-11-29_final.stac-item
2023-12-06 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-12-06_final.stac-item
2023-12-10 09:25:07	ga_ls9c_ard_3-2-1_091080_2023-12-09_final.stac-item
2023-12-25 10:22:26	ga_ls9c_ard_3-2-1_100084_2023-12-25_final.stac-item
2023-12-27 11:45:22	ga_ls9c_ard_3-2-1_114075_2023-12-27_final.stac-item
2024-01-09 11:11:59	ga_ls9c_ard_3-2-1_109069_2024-01-09_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