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
2021-12-15 10:42:43	ga_ls9c_ard_3-2-1_104073_2021-12-15_final.stac-item
2022-01-15 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-01-15_final.stac-item
2022-01-17 09:47:03	ga_ls9c_ard_3-2-1_095073_2022-01-17_final.stac-item
2022-01-21 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-01-20_final.stac-item
2022-02-04 11:13:12	ga_ls9c_ard_3-2-1_109072_2022-02-04_final.stac-item
2022-02-14 11:53:25	ga_ls9c_ard_3-2-1_115080_2022-02-14_final.stac-item
2022-02-15 09:20:53	ga_ls9c_ard_3-2-1_090085_2022-02-14_final.stac-item
2022-02-16 09:58:09	ga_ls9c_ard_3-2-1_097070_2022-02-16_final.stac-item
2022-03-02 10:13:08	ga_ls9c_ard_3-2-1_099077_2022-03-02_final.stac-item
2022-03-03 10:56:00	ga_ls9c_ard_3-2-1_106076_2022-03-03_final.stac-item
2022-03-19 10:58:47	ga_ls9c_ard_3-2-1_106083_2022-03-19_final.stac-item
2022-03-29 11:31:49	ga_ls9c_ard_3-2-1_112073_2022-03-29_final.stac-item
2022-04-13 09:11:59	ga_ls9c_ard_3-2-1_089079_2022-04-12_final.stac-item
2022-04-20 10:52:34	ga_ls9c_ard_3-2-1_106068_2022-04-20_final.stac-item
2022-04-27 09:22:14	ga_ls9c_ard_3-2-1_091074_2022-04-26_final.stac-item
2022-04-29 09:11:52	ga_ls9c_ard_3-2-1_089079_2022-04-28_final.stac-item
2022-05-04 09:31:34	ga_ls9c_ard_3-2-1_092082_2022-05-04_final.stac-item
2022-05-23 09:57:05	ga_ls9c_ard_3-2-1_097069_2022-05-23_final.stac-item
2022-05-25 09:50:42	ga_ls9c_ard_3-2-1_095084_2022-05-25_final.stac-item
2022-06-22 10:16:07	ga_ls9c_ard_3-2-1_099085_2022-06-22_final.stac-item
2022-06-24 11:41:54	ga_ls9c_ard_3-2-1_113083_2022-06-24_final.stac-item
2022-06-30 09:23:33	ga_ls9c_ard_3-2-1_091077_2022-06-29_final.stac-item
2022-06-30 09:25:33	ga_ls9c_ard_3-2-1_091082_2022-06-29_final.stac-item
2022-07-02 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-07-02_final.stac-item
2022-07-02 10:51:40	ga_ls9c_ard_3-2-1_105081_2022-07-02_final.stac-item
2022-08-03 10:52:41	ga_ls9c_ard_3-2-1_105083_2022-08-03_final.stac-item
2022-08-13 09:52:10	ga_ls9c_ard_3-2-1_095086_2022-08-13_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-08-20 11:31:41	ga_ls9c_ard_3-2-1_112072_2022-08-20_final.stac-item
2022-08-24 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-08-24_final.stac-item
2022-08-31 11:13:34	ga_ls9c_ard_3-2-1_109073_2022-08-31_final.stac-item
2022-09-04 09:16:44	ga_ls9c_ard_3-2-1_089090_2022-09-03_final.stac-item
2022-09-07 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-09-07_final.stac-item
2022-09-09 11:08:10	ga_ls9c_ard_3-2-1_108075_2022-09-09_final.stac-item
2022-09-10 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-09-10_final.stac-item
2022-09-11 09:21:44	ga_ls9c_ard_3-2-1_090087_2022-09-10_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-25 09:33:24	ga_ls9c_ard_3-2-1_092085_2022-09-25_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-26 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-10-26_final.stac-item
2022-10-29 09:17:56	ga_ls9c_ard_3-2-1_090077_2022-10-28_final.stac-item
2022-10-29 10:53:14	ga_ls9c_ard_3-2-1_106068_2022-10-29_final.stac-item
2022-10-29 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-10-29_final.stac-item
2022-11-03 09:40:26	ga_ls9c_ard_3-2-1_093087_2022-11-03_final.stac-item
2022-11-06 10:09:45	ga_ls9c_ard_3-2-1_098083_2022-11-06_final.stac-item
2022-11-22 11:45:05	ga_ls9c_ard_3-2-1_114074_2022-11-22_final.stac-item
2022-12-08 10:10:35	ga_ls9c_ard_3-2-1_098085_2022-12-08_final.stac-item
2022-12-09 09:16:57	ga_ls9c_ard_3-2-1_089090_2022-12-08_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2022-12-14 11:08:24	ga_ls9c_ard_3-2-1_108075_2022-12-14_final.stac-item
2022-12-14 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-14_final.stac-item
2022-12-15 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-12-15_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2022-12-24 10:05:20	ga_ls9c_ard_3-2-1_098072_2022-12-24_final.stac-item
2023-01-01 09:20:44	ga_ls9c_ard_3-2-1_090084_2022-12-31_final.stac-item
2023-01-01 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-12-31_final.stac-item
2023-01-03 10:40:53	ga_ls9c_ard_3-2-1_104068_2023-01-03_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-16 11:51:58	ga_ls9c_ard_3-2-1_115076_2023-01-16_final.stac-item
2023-01-18 09:58:18	ga_ls9c_ard_3-2-1_097070_2023-01-18_final.stac-item
2023-01-22 11:17:14	ga_ls9c_ard_3-2-1_109082_2023-01-22_final.stac-item
2023-01-25 10:03:19	ga_ls9c_ard_3-2-1_098067_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
2023-02-08 11:59:06	ga_ls9c_ard_3-2-1_116078_2023-02-08_final.stac-item
2023-02-25 09:29:08	ga_ls9c_ard_3-2-1_091090_2023-02-24_final.stac-item
2023-02-26 10:08:24	ga_ls9c_ard_3-2-1_098080_2023-02-26_final.stac-item
2023-02-27 09:13:59	ga_ls9c_ard_3-2-1_089083_2023-02-26_final.stac-item
2023-02-27 10:47:41	ga_ls9c_ard_3-2-1_105070_2023-02-27_final.stac-item
2023-03-07 11:42:13	ga_ls9c_ard_3-2-1_113083_2023-03-07_final.stac-item
2023-03-09 11:24:38	ga_ls9c_ard_3-2-1_111070_2023-03-09_final.stac-item
2023-03-17 10:39:59	ga_ls9c_ard_3-2-1_103082_2023-03-17_final.stac-item
2023-03-23 09:58:51	ga_ls9c_ard_3-2-1_097072_2023-03-23_final.stac-item
2023-03-27 11:16:56	ga_ls9c_ard_3-2-1_109082_2023-03-27_final.stac-item
2023-04-03 09:40:35	ga_ls9c_ard_3-2-1_094073_2023-04-03_final.stac-item
2023-04-07 10:58:43	ga_ls9c_ard_3-2-1_106083_2023-04-07_final.stac-item
2023-04-11 10:28:46	ga_ls9c_ard_3-2-1_102070_2023-04-11_final.stac-item
2023-04-13 11:58:27	ga_ls9c_ard_3-2-1_116078_2023-04-13_final.stac-item
2023-04-26 11:29:05	ga_ls9c_ard_3-2-1_111082_2023-04-26_final.stac-item
2023-05-24 11:51:53	ga_ls9c_ard_3-2-1_115078_2023-05-24_final.stac-item
2023-05-25 09:20:34	ga_ls9c_ard_3-2-1_090086_2023-05-24_final.stac-item
2023-05-26 09:57:26	ga_ls9c_ard_3-2-1_097070_2023-05-26_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-05-28 09:50:40	ga_ls9c_ard_3-2-1_095084_2023-05-28_final.stac-item
2023-06-04 11:34:55	ga_ls9c_ard_3-2-1_112082_2023-06-04_final.stac-item
2023-06-06 11:19:21	ga_ls9c_ard_3-2-1_110074_2023-06-06_final.stac-item
2023-06-08 09:31:40	ga_ls9c_ard_3-2-1_092083_2023-06-08_final.stac-item
2023-07-20 10:07:20	ga_ls9c_ard_3-2-1_098079_2023-07-20_final.stac-item
2023-07-21 09:16:06	ga_ls9c_ard_3-2-1_089090_2023-07-20_final.stac-item
2023-07-30 09:06:48	ga_ls9c_ard_3-2-1_088082_2023-07-29_final.stac-item
2023-09-17 11:29:46	ga_ls9c_ard_3-2-1_111083_2023-09-17_final.stac-item
2023-09-22 10:03:01	ga_ls9c_ard_3-2-1_098067_2023-09-22_final.stac-item
2023-09-28 11:07:08	ga_ls9c_ard_3-2-1_108073_2023-09-28_final.stac-item
2023-10-02 09:06:24	ga_ls9c_ard_3-2-1_088080_2023-10-01_final.stac-item
2023-10-14 09:34:28	ga_ls9c_ard_3-2-1_092088_2023-10-14_final.stac-item
2023-10-22 10:19:09	ga_ls9c_ard_3-2-1_100076_2023-10-22_final.stac-item
2023-10-23 09:28:43	ga_ls9c_ard_3-2-1_091089_2023-10-22_final.stac-item
2023-11-09 10:03:55	ga_ls9c_ard_3-2-1_098069_2023-11-09_final.stac-item
2023-11-24 09:22:46	ga_ls9c_ard_3-2-1_091074_2023-11-23_final.stac-item
2023-12-13 11:32:33	ga_ls9c_ard_3-2-1_112074_2023-12-13_final.stac-item
2023-12-26 11:02:30	ga_ls9c_ard_3-2-1_107076_2023-12-26_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