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
2021-11-18 09:59:35	ga_ls9c_ard_3-2-1_097068_2021-11-18_final.stac-item
2021-12-19 10:19:35	ga_ls9c_ard_3-2-1_100077_2021-12-19_final.stac-item
2021-12-31 09:07:25	ga_ls9c_ard_3-2-1_088082_2021-12-30_final.stac-item
2022-01-05 09:27:56	ga_ls9c_ard_3-2-1_091087_2022-01-04_final.stac-item
2022-01-19 11:12:47	ga_ls9c_ard_3-2-1_109071_2022-01-19_final.stac-item
2022-02-02 11:24:22	ga_ls9c_ard_3-2-1_111069_2022-02-02_final.stac-item
2022-02-18 11:26:15	ga_ls9c_ard_3-2-1_111074_2022-02-18_final.stac-item
2022-03-10 09:22:07	ga_ls9c_ard_3-2-1_091073_2022-03-09_final.stac-item
2022-03-22 11:29:16	ga_ls9c_ard_3-2-1_111082_2022-03-22_final.stac-item
2022-03-25 10:19:39	ga_ls9c_ard_3-2-1_100078_2022-03-25_final.stac-item
2022-04-12 10:02:50	ga_ls9c_ard_3-2-1_098067_2022-04-12_final.stac-item
2022-04-29 09:11:04	ga_ls9c_ard_3-2-1_089077_2022-04-28_final.stac-item
2022-05-05 10:09:38	ga_ls9c_ard_3-2-1_099069_2022-05-05_final.stac-item
2022-05-05 11:52:55	ga_ls9c_ard_3-2-1_115080_2022-05-05_final.stac-item
2022-05-21 10:09:50	ga_ls9c_ard_3-2-1_099070_2022-05-21_final.stac-item
2022-06-07 10:55:31	ga_ls9c_ard_3-2-1_106076_2022-06-07_final.stac-item
2022-06-12 11:17:18	ga_ls9c_ard_3-2-1_109084_2022-06-12_final.stac-item
2022-06-15 10:02:34	ga_ls9c_ard_3-2-1_098067_2022-06-15_final.stac-item
2022-06-19 11:22:48	ga_ls9c_ard_3-2-1_110082_2022-06-19_final.stac-item
2022-06-23 09:17:20	ga_ls9c_ard_3-2-1_090077_2022-06-22_final.stac-item
2022-06-29 10:16:47	ga_ls9c_ard_3-2-1_100071_2022-06-29_final.stac-item
2022-07-01 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-07-01_final.stac-item
2022-07-02 10:48:52	ga_ls9c_ard_3-2-1_105074_2022-07-02_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_final.stac-item
2022-07-15 11:57:35	ga_ls9c_ard_3-2-1_116076_2022-07-15_final.stac-item
2022-07-19 11:31:21	ga_ls9c_ard_3-2-1_112072_2022-07-19_final.stac-item
2022-08-17 09:21:53	ga_ls9c_ard_3-2-1_091072_2022-08-16_final.stac-item
2022-09-02 09:27:54	ga_ls9c_ard_3-2-1_091087_2022-09-01_final.stac-item
2022-09-10 10:10:10	ga_ls9c_ard_3-2-1_099069_2022-09-10_final.stac-item
2022-09-11 10:55:50	ga_ls9c_ard_3-2-1_106075_2022-09-11_final.stac-item
2022-09-16 09:34:20	ga_ls9c_ard_3-2-1_093072_2022-09-16_final.stac-item
2022-09-17 11:58:05	ga_ls9c_ard_3-2-1_116076_2022-09-17_final.stac-item
2022-09-23 11:20:15	ga_ls9c_ard_3-2-1_110074_2022-09-23_final.stac-item
2022-09-28 09:57:32	ga_ls9c_ard_3-2-1_097068_2022-09-28_final.stac-item
2022-10-04 09:22:26	ga_ls9c_ard_3-2-1_091073_2022-10-03_final.stac-item
2022-10-06 10:50:09	ga_ls9c_ard_3-2-1_105076_2022-10-06_final.stac-item
2022-10-09 11:24:16	ga_ls9c_ard_3-2-1_110084_2022-10-09_final.stac-item
2022-10-27 11:08:24	ga_ls9c_ard_3-2-1_108075_2022-10-27_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-20 10:17:46	ga_ls9c_ard_3-2-1_100072_2022-11-20_final.stac-item
2022-11-21 09:28:32	ga_ls9c_ard_3-2-1_091088_2022-11-20_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-11-29 10:14:20	ga_ls9c_ard_3-2-1_099079_2022-11-29_final.stac-item
2022-12-09 10:50:15	ga_ls9c_ard_3-2-1_105076_2022-12-09_final.stac-item
2022-12-13 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-12-13_final.stac-item
2022-12-22 10:18:06	ga_ls9c_ard_3-2-1_100073_2022-12-22_final.stac-item
2022-12-24 10:04:32	ga_ls9c_ard_3-2-1_098070_2022-12-24_final.stac-item
2022-12-28 11:24:43	ga_ls9c_ard_3-2-1_110085_2022-12-28_final.stac-item
2023-01-16 10:11:54	ga_ls9c_ard_3-2-1_099073_2023-01-16_final.stac-item
2023-01-17 10:53:08	ga_ls9c_ard_3-2-1_106068_2023-01-17_final.stac-item
2023-01-19 10:40:44	ga_ls9c_ard_3-2-1_104068_2023-01-19_final.stac-item
2023-01-21 10:33:33	ga_ls9c_ard_3-2-1_102081_2023-01-21_final.stac-item
2023-01-23 10:22:25	ga_ls9c_ard_3-2-1_100084_2023-01-23_final.stac-item
2023-02-11 09:09:50	ga_ls9c_ard_3-2-1_089072_2023-02-10_interim.stac-item
2023-02-11 09:13:49	ga_ls9c_ard_3-2-1_089082_2023-02-10_final.stac-item
2023-02-26 10:07:36	ga_ls9c_ard_3-2-1_098078_2023-02-26_final.stac-item
2023-03-29 09:22:50	ga_ls9c_ard_3-2-1_091075_2023-03-28_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-05-15 11:57:00	ga_ls9c_ard_3-2-1_116075_2023-05-15_final.stac-item
2023-05-15 11:57:24	ga_ls9c_ard_3-2-1_116076_2023-05-15_final.stac-item
2023-05-22 10:27:00	ga_ls9c_ard_3-2-1_101082_2023-05-22_final.stac-item
2023-05-29 10:27:33	ga_ls9c_ard_3-2-1_102068_2023-05-29_final.stac-item
2023-06-01 09:27:56	ga_ls9c_ard_3-2-1_091089_2023-05-31_final.stac-item
2023-06-08 11:07:22	ga_ls9c_ard_3-2-1_108075_2023-06-08_final.stac-item
2023-07-03 09:27:10	ga_ls9c_ard_3-2-1_091087_2023-07-02_final.stac-item
2023-07-03 09:27:34	ga_ls9c_ard_3-2-1_091088_2023-07-02_final.stac-item
2023-07-11 10:08:43	ga_ls9c_ard_3-2-1_099067_2023-07-11_final.stac-item
2023-07-26 11:07:32	ga_ls9c_ard_3-2-1_108075_2023-07-26_final.stac-item
2023-07-28 09:21:55	ga_ls9c_ard_3-2-1_090089_2023-07-27_final.stac-item
2023-08-03 10:16:38	ga_ls9c_ard_3-2-1_100071_2023-08-03_final.stac-item
2023-08-20 09:22:41	ga_ls9c_ard_3-2-1_091075_2023-08-19_final.stac-item
2023-09-01 11:24:02	ga_ls9c_ard_3-2-1_111069_2023-09-01_final.stac-item
2023-09-03 11:11:41	ga_ls9c_ard_3-2-1_109069_2023-09-03_final.stac-item
2023-09-07 10:49:01	ga_ls9c_ard_3-2-1_105074_2023-09-07_final.stac-item
2023-09-13 10:10:00	ga_ls9c_ard_3-2-1_099069_2023-09-13_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-10-21 11:13:58	ga_ls9c_ard_3-2-1_109074_2023-10-21_final.stac-item
2023-11-10 10:46:47	ga_ls9c_ard_3-2-1_105068_2023-11-10_final.stac-item
2023-11-17 10:58:58	ga_ls9c_ard_3-2-1_106083_2023-11-17_final.stac-item
2023-11-20 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-11-20_final.stac-item
2023-12-10 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-12-10_final.stac-item
2023-12-12 09:11:36	ga_ls9c_ard_3-2-1_089077_2023-12-11_final.stac-item
2023-12-19 09:22:13	ga_ls9c_ard_3-2-1_090088_2023-12-18_final.stac-item
2024-01-03 10:13:23	ga_ls9c_ard_3-2-1_099077_2024-01-03_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_final.stac-item
2024-01-22 09:07:22	ga_ls9c_ard_3-2-1_088082_2024-01-21_interim.stac-item
2024-02-05 10:55:54	ga_ls9c_ard_3-2-1_106075_2024-02-05_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-02-14 10:46:28	ga_ls9c_ard_3-2-1_105067_2024-02-14_final.stac-item
2024-02-19 11:07:43	ga_ls9c_ard_3-2-1_108074_2024-02-19_final.stac-item
2024-02-20 10:14:04	ga_ls9c_ard_3-2-1_099079_2024-02-20_final.stac-item
2024-02-29 10:05:53	ga_ls9c_ard_3-2-1_098074_2024-02-29_final.stac-item
2024-03-01 10:46:46	ga_ls9c_ard_3-2-1_105068_2024-03-01_final.stac-item
2024-03-11 11:26:40	ga_ls9c_ard_3-2-1_111075_2024-03-11_final.stac-item
2024-03-16 10:09:53	ga_ls9c_ard_3-2-1_098084_2024-03-16_final.stac-item
2024-03-17 10:46:46	ga_ls9c_ard_3-2-1_105068_2024-03-17_final.stac-item
2024-03-22 09:29:12	ga_ls9c_ard_3-2-1_092075_2024-03-21_final.stac-item
2024-03-22 09:34:47	ga_ls9c_ard_3-2-1_092089_2024-03-22_final.stac-item
2024-04-06 10:27:28	ga_ls9c_ard_3-2-1_101082_2024-04-06_final.stac-item
2024-04-15 10:19:35	ga_ls9c_ard_3-2-1_100078_2024-04-15_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years