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
2021-11-02 10:53:16	ga_ls9c_ard_3-2-1_106074_2021-11-02_final.stac-item
2021-11-07 09:23:03	ga_ls9c_ard_3-2-1_090089_2021-11-06_final.stac-item
2021-11-10 11:16:10	ga_ls9c_ard_3-2-1_110072_2021-11-10_final.stac-item
2021-11-12 09:22:20	ga_ls9c_ard_3-2-1_091081_2021-11-11_final.stac-item
2021-12-04 09:26:53	ga_ls9c_ard_3-2-1_091084_2021-12-03_final.stac-item
2021-12-06 09:15:18	ga_ls9c_ard_3-2-1_089086_2021-12-05_final.stac-item
2021-12-25 11:20:36	ga_ls9c_ard_3-2-1_110075_2021-12-25_final.stac-item
2021-12-26 10:26:10	ga_ls9c_ard_3-2-1_101078_2021-12-26_final.stac-item
2022-01-06 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-06_final.stac-item
2022-01-18 10:30:19	ga_ls9c_ard_3-2-1_102073_2022-01-18_final.stac-item
2022-01-29 11:52:17	ga_ls9c_ard_3-2-1_115077_2022-01-29_final.stac-item
2022-01-29 11:53:05	ga_ls9c_ard_3-2-1_115079_2022-01-29_final.stac-item
2022-02-16 09:58:09	ga_ls9c_ard_3-2-1_097070_2022-02-16_final.stac-item
2022-02-18 09:47:46	ga_ls9c_ard_3-2-1_095075_2022-02-18_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-03-10 11:04:59	ga_ls9c_ard_3-2-1_107083_2022-03-10_final.stac-item
2022-03-27 11:45:46	ga_ls9c_ard_3-2-1_114077_2022-03-27_final.stac-item
2022-03-31 09:39:46	ga_ls9c_ard_3-2-1_094071_2022-03-31_final.stac-item
2022-04-02 09:34:12	ga_ls9c_ard_3-2-1_092088_2022-04-02_final.stac-item
2022-04-03 10:09:04	ga_ls9c_ard_3-2-1_099067_2022-04-03_final.stac-item
2022-04-04 10:52:44	ga_ls9c_ard_3-2-1_106068_2022-04-04_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-04-29 09:13:52	ga_ls9c_ard_3-2-1_089084_2022-04-28_final.stac-item
2022-05-06 09:18:48	ga_ls9c_ard_3-2-1_090081_2022-05-05_final.stac-item
2022-05-30 10:02:52	ga_ls9c_ard_3-2-1_098068_2022-05-30_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-16 09:12:33	ga_ls9c_ard_3-2-1_089081_2022-06-15_final.stac-item
2022-06-21 11:06:07	ga_ls9c_ard_3-2-1_108071_2022-06-21_final.stac-item
2022-06-30 11:01:38	ga_ls9c_ard_3-2-1_107075_2022-06-30_final.stac-item
2022-07-15 10:18:42	ga_ls9c_ard_3-2-1_100076_2022-07-15_final.stac-item
2022-07-18 09:13:34	ga_ls9c_ard_3-2-1_089083_2022-07-17_final.stac-item
2022-07-24 11:51:34	ga_ls9c_ard_3-2-1_115076_2022-07-24_final.stac-item
2022-07-25 09:17:52	ga_ls9c_ard_3-2-1_090078_2022-07-24_final.stac-item
2022-07-28 11:29:41	ga_ls9c_ard_3-2-1_111083_2022-07-28_final.stac-item
2022-08-02 11:45:30	ga_ls9c_ard_3-2-1_114076_2022-08-02_final.stac-item
2022-08-08 09:33:11	ga_ls9c_ard_3-2-1_092085_2022-08-08_final.stac-item
2022-08-14 10:30:15	ga_ls9c_ard_3-2-1_102073_2022-08-14_final.stac-item
2022-08-17 11:01:58	ga_ls9c_ard_3-2-1_107075_2022-08-17_final.stac-item
2022-08-25 10:11:21	ga_ls9c_ard_3-2-1_099072_2022-08-25_final.stac-item
2022-08-28 09:06:58	ga_ls9c_ard_3-2-1_088081_2022-08-27_final.stac-item
2022-08-31 11:17:57	ga_ls9c_ard_3-2-1_109084_2022-08-31_final.stac-item
2022-09-09 11:06:34	ga_ls9c_ard_3-2-1_108071_2022-09-09_final.stac-item
2022-09-12 11:42:18	ga_ls9c_ard_3-2-1_113083_2022-09-12_final.stac-item
2022-09-15 10:30:21	ga_ls9c_ard_3-2-1_102073_2022-09-15_final.stac-item
2022-10-02 09:35:36	ga_ls9c_ard_3-2-1_093075_2022-10-02_final.stac-item
2022-10-16 09:46:27	ga_ls9c_ard_3-2-1_095071_2022-10-16_final.stac-item
2022-10-18 11:12:35	ga_ls9c_ard_3-2-1_109070_2022-10-18_final.stac-item
2022-10-20 09:25:44	ga_ls9c_ard_3-2-1_091081_2022-10-19_final.stac-item
2022-10-20 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-10-19_final.stac-item
2022-10-28 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-10-28_final.stac-item
2022-11-07 09:13:21	ga_ls9c_ard_3-2-1_089081_2022-11-06_final.stac-item
2022-11-21 09:27:44	ga_ls9c_ard_3-2-1_091086_2022-11-20_final.stac-item
2022-11-28 09:32:17	ga_ls9c_ard_3-2-1_092082_2022-11-28_final.stac-item
2022-12-02 10:42:50	ga_ls9c_ard_3-2-1_104073_2022-12-02_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-07 09:25:43	ga_ls9c_ard_3-2-1_091081_2022-12-06_final.stac-item
2022-12-08 10:06:59	ga_ls9c_ard_3-2-1_098076_2022-12-08_final.stac-item
2022-12-12 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-12-12_final.stac-item
2022-12-14 09:34:18	ga_ls9c_ard_3-2-1_092087_2022-12-14_final.stac-item
2022-12-17 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-12-17_final.stac-item
2022-12-24 10:10:07	ga_ls9c_ard_3-2-1_098084_2022-12-24_final.stac-item
2022-12-24 11:47:01	ga_ls9c_ard_3-2-1_114079_2022-12-24_final.stac-item
2022-12-26 11:36:16	ga_ls9c_ard_3-2-1_112083_2022-12-26_final.stac-item
2022-12-30 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-12-29_final.stac-item
2023-01-11 09:56:36	ga_ls9c_ard_3-2-1_096081_2023-01-11_final.stac-item
2023-01-15 11:06:20	ga_ls9c_ard_3-2-1_108070_2023-01-15_final.stac-item
2023-01-24 09:29:13	ga_ls9c_ard_3-2-1_091090_2023-01-23_final.stac-item
2023-01-25 11:45:48	ga_ls9c_ard_3-2-1_114076_2023-01-25_final.stac-item
2023-01-26 09:11:42	ga_ls9c_ard_3-2-1_089077_2023-01-25_final.stac-item
2023-01-30 10:23:32	ga_ls9c_ard_3-2-1_101071_2023-01-30_final.stac-item
2023-01-31 09:31:55	ga_ls9c_ard_3-2-1_092081_2023-01-31_final.stac-item
2023-02-01 11:52:28	ga_ls9c_ard_3-2-1_115077_2023-02-01_final.stac-item
2023-02-05 11:29:47	ga_ls9c_ard_3-2-1_111082_2023-02-05_final.stac-item
2023-02-07 11:18:13	ga_ls9c_ard_3-2-1_109084_2023-02-07_final.stac-item
2023-02-25 09:28:44	ga_ls9c_ard_3-2-1_091089_2023-02-24_final.stac-item
2023-03-30 11:44:58	ga_ls9c_ard_3-2-1_114075_2023-03-30_final.stac-item
2023-03-31 09:12:28	ga_ls9c_ard_3-2-1_089080_2023-03-30_final.stac-item
2023-03-31 10:48:10	ga_ls9c_ard_3-2-1_105072_2023-03-31_final.stac-item
2023-03-31 10:52:09	ga_ls9c_ard_3-2-1_105082_2023-03-31_final.stac-item
2023-04-05 11:08:18	ga_ls9c_ard_3-2-1_108076_2023-04-05_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_final.stac-item
2023-04-10 09:52:18	ga_ls9c_ard_3-2-1_095087_2023-04-10_final.stac-item
2023-04-26 09:46:12	ga_ls9c_ard_3-2-1_095072_2023-04-26_final.stac-item
2023-05-08 11:52:03	ga_ls9c_ard_3-2-1_115078_2023-05-08_final.stac-item
2023-05-09 10:55:14	ga_ls9c_ard_3-2-1_106075_2023-05-09_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-06-03 10:48:28	ga_ls9c_ard_3-2-1_105074_2023-06-03_final.stac-item
2023-06-20 09:51:07	ga_ls9c_ard_3-2-1_096070_2023-06-20_final.stac-item
2023-07-01 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-07-01_final.stac-item
2023-07-23 10:38:14	ga_ls9c_ard_3-2-1_103079_2023-07-23_final.stac-item
2023-07-28 09:17:32	ga_ls9c_ard_3-2-1_090078_2023-07-27_final.stac-item
2023-08-06 10:52:21	ga_ls9c_ard_3-2-1_105083_2023-08-06_final.stac-item
2023-08-14 09:56:56	ga_ls9c_ard_3-2-1_097068_2023-08-14_final.stac-item
2023-10-15 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-10-15_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-10-25 09:12:45	ga_ls9c_ard_3-2-1_089080_2023-10-24_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-11-21 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-11-21_final.stac-item
2023-11-26 10:49:19	ga_ls9c_ard_3-2-1_105074_2023-11-26_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