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
2021-12-05 10:03:21	ga_ls9c_ard_3-2-1_098067_2021-12-05_final.stac-item
2021-12-09 09:41:23	ga_ls9c_ard_3-2-1_094074_2021-12-09_final.stac-item
2021-12-12 10:11:27	ga_ls9c_ard_3-2-1_099072_2021-12-12_final.stac-item
2021-12-16 11:25:58	ga_ls9c_ard_3-2-1_111073_2021-12-16_final.stac-item
2021-12-18 09:40:42	ga_ls9c_ard_3-2-1_093088_2021-12-18_final.stac-item
2021-12-22 10:50:05	ga_ls9c_ard_3-2-1_105076_2021-12-22_final.stac-item
2021-12-25 09:40:55	ga_ls9c_ard_3-2-1_094073_2021-12-25_final.stac-item
2021-12-30 11:38:44	ga_ls9c_ard_3-2-1_113074_2021-12-30_final.stac-item
2021-12-31 09:07:01	ga_ls9c_ard_3-2-1_088081_2021-12-30_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_2022-01-01_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-17 11:25:32	ga_ls9c_ard_3-2-1_111072_2022-01-17_final.stac-item
2022-01-19 09:40:41	ga_ls9c_ard_3-2-1_093088_2022-01-19_final.stac-item
2022-01-21 11:00:50	ga_ls9c_ard_3-2-1_107072_2022-01-21_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-15 09:18:06	ga_ls9c_ard_3-2-1_090078_2022-02-14_final.stac-item
2022-02-24 10:49:30	ga_ls9c_ard_3-2-1_105075_2022-02-24_final.stac-item
2022-03-06 11:26:07	ga_ls9c_ard_3-2-1_111074_2022-03-06_final.stac-item
2022-03-08 11:12:33	ga_ls9c_ard_3-2-1_109071_2022-03-08_final.stac-item
2022-03-12 10:49:26	ga_ls9c_ard_3-2-1_105075_2022-03-12_final.stac-item
2022-03-24 09:34:25	ga_ls9c_ard_3-2-1_093073_2022-03-24_final.stac-item
2022-04-03 11:53:09	ga_ls9c_ard_3-2-1_115080_2022-04-03_final.stac-item
2022-04-11 09:27:34	ga_ls9c_ard_3-2-1_091087_2022-04-10_final.stac-item
2022-04-24 10:33:24	ga_ls9c_ard_3-2-1_102082_2022-04-24_final.stac-item
2022-05-08 09:07:13	ga_ls9c_ard_3-2-1_088083_2022-05-07_final.stac-item
2022-05-29 09:26:47	ga_ls9c_ard_3-2-1_091086_2022-05-28_final.stac-item
2022-06-01 09:57:42	ga_ls9c_ard_3-2-1_096086_2022-06-01_final.stac-item
2022-06-05 11:11:04	ga_ls9c_ard_3-2-1_108084_2022-06-05_final.stac-item
2022-06-10 11:23:14	ga_ls9c_ard_3-2-1_111068_2022-06-10_final.stac-item
2022-07-05 11:19:46	ga_ls9c_ard_3-2-1_110074_2022-07-05_final.stac-item
2022-07-17 10:03:11	ga_ls9c_ard_3-2-1_098068_2022-07-17_final.stac-item
2022-07-24 11:51:10	ga_ls9c_ard_3-2-1_115075_2022-07-24_final.stac-item
2022-08-02 10:07:01	ga_ls9c_ard_3-2-1_098077_2022-08-02_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-25 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-08-25_final.stac-item
2022-08-25 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-08-25_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-09-30 11:26:03	ga_ls9c_ard_3-2-1_111073_2022-09-30_final.stac-item
2022-10-03 10:19:15	ga_ls9c_ard_3-2-1_100076_2022-10-03_final.stac-item
2022-10-07 11:36:12	ga_ls9c_ard_3-2-1_112083_2022-10-07_final.stac-item
2022-10-18 11:12:11	ga_ls9c_ard_3-2-1_109069_2022-10-18_final.stac-item
2022-10-29 10:54:02	ga_ls9c_ard_3-2-1_106070_2022-10-29_final.stac-item
2022-10-31 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-30_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-07 09:11:45	ga_ls9c_ard_3-2-1_089077_2022-11-06_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-15 09:57:38	ga_ls9c_ard_3-2-1_097068_2022-11-15_final.stac-item
2022-11-30 09:22:18	ga_ls9c_ard_3-2-1_090088_2022-11-29_final.stac-item
2022-12-03 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-12-03_final.stac-item
2022-12-05 09:34:52	ga_ls9c_ard_3-2-1_093073_2022-12-05_final.stac-item
2022-12-29 10:23:55	ga_ls9c_ard_3-2-1_101072_2022-12-29_final.stac-item
2022-12-31 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-12-31_final.stac-item
2023-01-05 10:29:19	ga_ls9c_ard_3-2-1_102070_2023-01-05_final.stac-item
2023-01-16 10:14:17	ga_ls9c_ard_3-2-1_099079_2023-01-16_final.stac-item
2023-01-26 10:47:00	ga_ls9c_ard_3-2-1_105068_2023-01-26_final.stac-item
2023-02-01 11:53:16	ga_ls9c_ard_3-2-1_115079_2023-02-01_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-16 09:29:30	ga_ls9c_ard_3-2-1_092075_2023-02-15_final.stac-item
2023-03-08 10:42:35	ga_ls9c_ard_3-2-1_104073_2023-03-08_final.stac-item
2023-03-14 10:07:29	ga_ls9c_ard_3-2-1_098078_2023-03-14_final.stac-item
2023-03-23 11:41:20	ga_ls9c_ard_3-2-1_113081_2023-03-23_final.stac-item
2023-04-04 10:25:26	ga_ls9c_ard_3-2-1_101077_2023-04-04_final.stac-item
2023-04-16 09:10:22	ga_ls9c_ard_3-2-1_089075_2023-04-15_final.stac-item
2023-04-16 09:11:34	ga_ls9c_ard_3-2-1_089078_2023-04-15_final.stac-item
2023-04-17 09:52:02	ga_ls9c_ard_3-2-1_096071_2023-04-17_final.stac-item
2023-05-10 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-05-10_final.stac-item
2023-05-22 10:27:24	ga_ls9c_ard_3-2-1_101083_2023-05-22_final.stac-item
2023-05-27 09:06:36	ga_ls9c_ard_3-2-1_088082_2023-05-26_final.stac-item
2023-06-01 09:21:57	ga_ls9c_ard_3-2-1_091074_2023-05-31_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-18 10:09:03	ga_ls9c_ard_3-2-1_098084_2023-06-18_final.stac-item
2023-06-26 09:21:13	ga_ls9c_ard_3-2-1_090088_2023-06-25_final.stac-item
2023-06-27 11:41:24	ga_ls9c_ard_3-2-1_113083_2023-06-27_final.stac-item
2023-07-11 10:09:07	ga_ls9c_ard_3-2-1_099068_2023-07-11_final.stac-item
2023-07-12 10:55:10	ga_ls9c_ard_3-2-1_106075_2023-07-12_final.stac-item
2023-07-28 09:21:31	ga_ls9c_ard_3-2-1_090088_2023-07-27_final.stac-item
2023-07-29 11:41:18	ga_ls9c_ard_3-2-1_113082_2023-07-29_final.stac-item
2023-07-31 11:24:10	ga_ls9c_ard_3-2-1_111070_2023-07-31_final.stac-item
2023-08-06 09:11:04	ga_ls9c_ard_3-2-1_089077_2023-08-05_final.stac-item
2023-08-07 11:33:37	ga_ls9c_ard_3-2-1_112078_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 09:51:45	ga_ls9c_ard_3-2-1_095086_2023-08-16_final.stac-item
2023-08-23 09:58:01	ga_ls9c_ard_3-2-1_096086_2023-08-23_final.stac-item
2023-08-24 10:35:43	ga_ls9c_ard_3-2-1_103072_2023-08-24_final.stac-item
2023-09-05 09:21:40	ga_ls9c_ard_3-2-1_091072_2023-09-04_final.stac-item
2023-09-12 09:29:07	ga_ls9c_ard_3-2-1_092075_2023-09-11_final.stac-item
2023-09-12 09:34:19	ga_ls9c_ard_3-2-1_092088_2023-09-12_final.stac-item
2023-09-24 09:58:13	ga_ls9c_ard_3-2-1_096086_2023-09-24_final.stac-item
2023-10-30 09:34:02	ga_ls9c_ard_3-2-1_092087_2023-10-30_final.stac-item
2023-10-31 11:52:58	ga_ls9c_ard_3-2-1_115079_2023-10-31_final.stac-item
2023-11-01 10:53:20	ga_ls9c_ard_3-2-1_106069_2023-11-01_final.stac-item
2023-11-05 10:29:25	ga_ls9c_ard_3-2-1_102071_2023-11-05_final.stac-item
2023-11-16 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-11-16_final.stac-item
2023-11-16 10:10:06	ga_ls9c_ard_3-2-1_099069_2023-11-16_final.stac-item
2023-11-17 09:20:53	ga_ls9c_ard_3-2-1_090085_2023-11-16_final.stac-item
2023-11-18 11:38:39	ga_ls9c_ard_3-2-1_113074_2023-11-18_final.stac-item
2023-11-20 11:25:32	ga_ls9c_ard_3-2-1_111072_2023-11-20_final.stac-item
2023-11-27 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-11-27_final.stac-item
2023-12-02 10:09:49	ga_ls9c_ard_3-2-1_099068_2023-12-02_final.stac-item
2023-12-02 11:52:42	ga_ls9c_ard_3-2-1_115078_2023-12-02_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