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 09:20:16	ga_ls9c_ard_3-2-1_090082_2021-11-06_final.stac-item
2021-11-10 11:17:45	ga_ls9c_ard_3-2-1_110076_2021-11-10_final.stac-item
2021-11-17 09:25:16	ga_ls9c_ard_3-2-1_091082_2021-11-16_final.stac-item
2021-12-29 09:19:47	ga_ls9c_ard_3-2-1_090082_2021-12-28_final.stac-item
2022-01-12 09:28:06	ga_ls9c_ard_3-2-1_092072_2022-01-11_final.stac-item
2022-01-12 11:06:35	ga_ls9c_ard_3-2-1_108071_2022-01-12_final.stac-item
2022-01-23 10:50:04	ga_ls9c_ard_3-2-1_105076_2022-01-23_final.stac-item
2022-02-18 11:25:27	ga_ls9c_ard_3-2-1_111072_2022-02-18_final.stac-item
2022-03-03 10:56:00	ga_ls9c_ard_3-2-1_106076_2022-03-03_final.stac-item
2022-03-06 09:46:26	ga_ls9c_ard_3-2-1_095072_2022-03-06_final.stac-item
2022-03-08 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-03-08_final.stac-item
2022-03-20 09:56:46	ga_ls9c_ard_3-2-1_097067_2022-03-20_final.stac-item
2022-03-21 10:42:25	ga_ls9c_ard_3-2-1_104073_2022-03-21_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-04-05 09:57:06	ga_ls9c_ard_3-2-1_097068_2022-04-05_final.stac-item
2022-04-08 10:33:34	ga_ls9c_ard_3-2-1_102082_2022-04-08_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-04-25 09:38:35	ga_ls9c_ard_3-2-1_093084_2022-04-25_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-05-04 09:28:47	ga_ls9c_ard_3-2-1_092075_2022-05-03_final.stac-item
2022-05-04 09:31:10	ga_ls9c_ard_3-2-1_092081_2022-05-04_final.stac-item
2022-05-08 09:06:49	ga_ls9c_ard_3-2-1_088082_2022-05-07_final.stac-item
2022-05-12 10:16:56	ga_ls9c_ard_3-2-1_100072_2022-05-12_final.stac-item
2022-05-26 10:32:46	ga_ls9c_ard_3-2-1_102081_2022-05-26_final.stac-item
2022-06-03 11:17:50	ga_ls9c_ard_3-2-1_110070_2022-06-03_final.stac-item
2022-06-16 09:15:44	ga_ls9c_ard_3-2-1_089089_2022-06-15_final.stac-item
2022-06-17 09:51:26	ga_ls9c_ard_3-2-1_096070_2022-06-17_final.stac-item
2022-06-19 09:45:54	ga_ls9c_ard_3-2-1_094087_2022-06-19_final.stac-item
2022-06-19 11:23:11	ga_ls9c_ard_3-2-1_110083_2022-06-19_final.stac-item
2022-06-24 09:59:26	ga_ls9c_ard_3-2-1_097074_2022-06-24_final.stac-item
2022-06-30 09:25:09	ga_ls9c_ard_3-2-1_091081_2022-06-29_final.stac-item
2022-07-09 10:52:38	ga_ls9c_ard_3-2-1_106068_2022-07-09_final.stac-item
2022-07-09 10:55:49	ga_ls9c_ard_3-2-1_106076_2022-07-09_final.stac-item
2022-07-12 11:24:42	ga_ls9c_ard_3-2-1_111071_2022-07-12_final.stac-item
2022-07-17 10:09:58	ga_ls9c_ard_3-2-1_098085_2022-07-17_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-08-02 10:07:25	ga_ls9c_ard_3-2-1_098078_2022-08-02_final.stac-item
2022-08-25 10:13:21	ga_ls9c_ard_3-2-1_099077_2022-08-25_final.stac-item
2022-08-30 10:28:18	ga_ls9c_ard_3-2-1_102068_2022-08-30_final.stac-item
2022-09-24 10:26:14	ga_ls9c_ard_3-2-1_101078_2022-09-24_final.stac-item
2022-09-27 09:21:03	ga_ls9c_ard_3-2-1_090085_2022-09-26_final.stac-item
2022-10-14 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-10-14_final.stac-item
2022-10-17 10:29:19	ga_ls9c_ard_3-2-1_102070_2022-10-17_final.stac-item
2022-10-18 09:38:53	ga_ls9c_ard_3-2-1_093083_2022-10-18_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-28 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-10-28_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-03 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-11-03_final.stac-item
2022-11-11 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-11-11_final.stac-item
2022-11-20 10:18:34	ga_ls9c_ard_3-2-1_100074_2022-11-20_final.stac-item
2022-11-22 10:03:25	ga_ls9c_ard_3-2-1_098067_2022-11-22_final.stac-item
2022-11-23 09:16:58	ga_ls9c_ard_3-2-1_089090_2022-11-22_final.stac-item
2022-11-28 09:33:53	ga_ls9c_ard_3-2-1_092086_2022-11-28_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 09:16:33	ga_ls9c_ard_3-2-1_089089_2022-12-08_final.stac-item
2022-12-09 10:47:03	ga_ls9c_ard_3-2-1_105068_2022-12-09_final.stac-item
2022-12-18 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-12-18_final.stac-item
2022-12-26 09:52:12	ga_ls9c_ard_3-2-1_096070_2022-12-26_final.stac-item
2023-01-19 10:41:32	ga_ls9c_ard_3-2-1_104070_2023-01-19_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-02-01 10:16:47	ga_ls9c_ard_3-2-1_099085_2023-02-01_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-02-14 11:19:35	ga_ls9c_ard_3-2-1_110072_2023-02-14_final.stac-item
2023-03-09 11:23:50	ga_ls9c_ard_3-2-1_111068_2023-03-09_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-13 09:23:02	ga_ls9c_ard_3-2-1_091075_2023-03-12_final.stac-item
2023-03-18 09:39:58	ga_ls9c_ard_3-2-1_094071_2023-03-18_final.stac-item
2023-03-21 10:13:38	ga_ls9c_ard_3-2-1_099078_2023-03-21_final.stac-item
2023-03-26 10:28:30	ga_ls9c_ard_3-2-1_102069_2023-03-26_final.stac-item
2023-04-03 11:20:16	ga_ls9c_ard_3-2-1_110075_2023-04-03_final.stac-item
2023-04-14 09:28:43	ga_ls9c_ard_3-2-1_091090_2023-04-13_final.stac-item
2023-04-23 09:21:43	ga_ls9c_ard_3-2-1_090088_2023-04-22_final.stac-item
2023-05-02 09:11:01	ga_ls9c_ard_3-2-1_089077_2023-05-01_final.stac-item
2023-05-11 10:45:40	ga_ls9c_ard_3-2-1_104082_2023-05-11_final.stac-item
2023-05-12 11:25:43	ga_ls9c_ard_3-2-1_111074_2023-05-12_final.stac-item
2023-05-16 09:24:29	ga_ls9c_ard_3-2-1_091080_2023-05-15_final.stac-item
2023-05-19 09:56:56	ga_ls9c_ard_3-2-1_096084_2023-05-19_final.stac-item
2023-05-20 10:38:35	ga_ls9c_ard_3-2-1_103080_2023-05-20_final.stac-item
2023-05-24 11:51:29	ga_ls9c_ard_3-2-1_115077_2023-05-24_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-06-25 10:10:02	ga_ls9c_ard_3-2-1_099071_2023-06-25_final.stac-item
2023-07-03 09:27:34	ga_ls9c_ard_3-2-1_091088_2023-07-02_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-12 10:55:34	ga_ls9c_ard_3-2-1_106076_2023-07-12_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-12 10:10:54	ga_ls9c_ard_3-2-1_099072_2023-08-12_final.stac-item
2023-08-12 11:52:11	ga_ls9c_ard_3-2-1_115078_2023-08-12_final.stac-item
2023-08-14 09:59:20	ga_ls9c_ard_3-2-1_097074_2023-08-14_final.stac-item
2023-08-18 09:40:11	ga_ls9c_ard_3-2-1_093088_2023-08-18_final.stac-item
2023-09-17 11:25:46	ga_ls9c_ard_3-2-1_111073_2023-09-17_final.stac-item
2023-09-24 09:58:13	ga_ls9c_ard_3-2-1_096086_2023-09-24_final.stac-item
2023-10-09 09:11:51	ga_ls9c_ard_3-2-1_089078_2023-10-08_final.stac-item
2023-10-30 09:32:26	ga_ls9c_ard_3-2-1_092083_2023-10-30_final.stac-item
2023-10-31 10:13:41	ga_ls9c_ard_3-2-1_099078_2023-10-31_final.stac-item
2023-11-16 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-11-16_final.stac-item
2023-11-20 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-11-20_final.stac-item
2023-11-23 11:58:28	ga_ls9c_ard_3-2-1_116077_2023-11-23_final.stac-item
2023-11-26 10:49:43	ga_ls9c_ard_3-2-1_105075_2023-11-26_final.stac-item
2023-12-04 09:58:14	ga_ls9c_ard_3-2-1_097070_2023-12-04_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