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
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2021-12-10 10:28:13	ga_ls9c_ard_3-2-1_101083_2021-12-10_final.stac-item
2021-12-16 11:30:21	ga_ls9c_ard_3-2-1_111084_2021-12-16_final.stac-item
2021-12-25 11:19:00	ga_ls9c_ard_3-2-1_110071_2021-12-25_final.stac-item
2022-01-02 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-01-02_final.stac-item
2022-01-12 11:11:22	ga_ls9c_ard_3-2-1_108083_2022-01-12_final.stac-item
2022-01-17 09:51:50	ga_ls9c_ard_3-2-1_095085_2022-01-17_final.stac-item
2022-01-26 11:21:23	ga_ls9c_ard_3-2-1_110077_2022-01-26_final.stac-item
2022-02-06 09:25:08	ga_ls9c_ard_3-2-1_091080_2022-02-05_final.stac-item
2022-02-07 10:10:23	ga_ls9c_ard_3-2-1_098085_2022-02-07_final.stac-item
2022-02-08 10:52:51	ga_ls9c_ard_3-2-1_105083_2022-02-08_final.stac-item
2022-02-22 11:05:29	ga_ls9c_ard_3-2-1_107084_2022-02-22_final.stac-item
2022-02-26 10:39:54	ga_ls9c_ard_3-2-1_103082_2022-02-26_final.stac-item
2022-03-31 09:45:45	ga_ls9c_ard_3-2-1_094086_2022-03-31_final.stac-item
2022-05-04 09:31:34	ga_ls9c_ard_3-2-1_092082_2022-05-04_final.stac-item
2022-05-11 11:16:58	ga_ls9c_ard_3-2-1_109083_2022-05-11_final.stac-item
2022-05-16 09:51:22	ga_ls9c_ard_3-2-1_096070_2022-05-16_final.stac-item
2022-05-21 10:12:14	ga_ls9c_ard_3-2-1_099076_2022-05-21_final.stac-item
2022-05-29 09:22:48	ga_ls9c_ard_3-2-1_091076_2022-05-28_final.stac-item
2022-06-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2022-06-23_final.stac-item
2022-06-24 09:59:02	ga_ls9c_ard_3-2-1_097073_2022-06-24_final.stac-item
2022-06-26 09:51:05	ga_ls9c_ard_3-2-1_095084_2022-06-26_final.stac-item
2022-07-05 09:45:16	ga_ls9c_ard_3-2-1_094085_2022-07-05_final.stac-item
2022-07-10 11:41:28	ga_ls9c_ard_3-2-1_113082_2022-07-10_final.stac-item
2022-07-16 09:23:06	ga_ls9c_ard_3-2-1_091076_2022-07-15_final.stac-item
2022-07-18 10:46:52	ga_ls9c_ard_3-2-1_105069_2022-07-18_final.stac-item
2022-08-03 09:16:12	ga_ls9c_ard_3-2-1_089089_2022-08-02_final.stac-item
2022-08-15 09:35:26	ga_ls9c_ard_3-2-1_093075_2022-08-15_final.stac-item
2022-08-18 10:05:09	ga_ls9c_ard_3-2-1_098072_2022-08-18_final.stac-item
2022-09-09 09:30:29	ga_ls9c_ard_3-2-1_092078_2022-09-09_final.stac-item
2022-09-10 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-09-10_final.stac-item
2022-09-12 10:03:49	ga_ls9c_ard_3-2-1_097084_2022-09-12_final.stac-item
2022-09-18 09:24:47	ga_ls9c_ard_3-2-1_091079_2022-09-17_final.stac-item
2022-10-02 09:34:00	ga_ls9c_ard_3-2-1_093071_2022-10-02_final.stac-item
2022-10-04 11:02:31	ga_ls9c_ard_3-2-1_107076_2022-10-04_final.stac-item
2022-10-05 10:07:17	ga_ls9c_ard_3-2-1_098077_2022-10-05_final.stac-item
2022-10-05 11:44:59	ga_ls9c_ard_3-2-1_114074_2022-10-05_final.stac-item
2022-10-06 10:52:56	ga_ls9c_ard_3-2-1_105083_2022-10-06_final.stac-item
2022-10-11 09:35:27	ga_ls9c_ard_3-2-1_092090_2022-10-11_final.stac-item
2022-10-19 10:22:09	ga_ls9c_ard_3-2-1_100083_2022-10-19_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-10 09:43:52	ga_ls9c_ard_3-2-1_094080_2022-11-10_final.stac-item
2022-11-18 10:30:32	ga_ls9c_ard_3-2-1_102073_2022-11-18_final.stac-item
2022-11-30 09:20:42	ga_ls9c_ard_3-2-1_090084_2022-11-29_final.stac-item
2022-12-05 11:17:21	ga_ls9c_ard_3-2-1_109082_2022-12-05_final.stac-item
2022-12-09 10:46:40	ga_ls9c_ard_3-2-1_105067_2022-12-09_final.stac-item
2022-12-10 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-12-10_final.stac-item
2022-12-14 09:32:42	ga_ls9c_ard_3-2-1_092083_2022-12-14_final.stac-item
2022-12-19 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-12-19_final.stac-item
2022-12-19 09:48:50	ga_ls9c_ard_3-2-1_095077_2022-12-19_final.stac-item
2022-12-28 11:21:32	ga_ls9c_ard_3-2-1_110077_2022-12-28_final.stac-item
2023-01-01 09:19:33	ga_ls9c_ard_3-2-1_090081_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
2023-01-01 10:56:50	ga_ls9c_ard_3-2-1_106077_2023-01-01_final.stac-item
2023-01-04 09:46:28	ga_ls9c_ard_3-2-1_095071_2023-01-04_final.stac-item
2023-01-04 09:49:39	ga_ls9c_ard_3-2-1_095079_2023-01-04_final.stac-item
2023-01-06 11:17:22	ga_ls9c_ard_3-2-1_109082_2023-01-06_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-22 11:12:50	ga_ls9c_ard_3-2-1_109071_2023-01-22_final.stac-item
2023-01-26 09:14:06	ga_ls9c_ard_3-2-1_089083_2023-01-25_final.stac-item
2023-01-26 09:15:18	ga_ls9c_ard_3-2-1_089086_2023-01-25_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-02-12 09:57:28	ga_ls9c_ard_3-2-1_096083_2023-02-12_final.stac-item
2023-02-12 11:36:21	ga_ls9c_ard_3-2-1_112083_2023-02-12_final.stac-item
2023-03-18 09:44:21	ga_ls9c_ard_3-2-1_094082_2023-03-18_final.stac-item
2023-03-18 11:19:39	ga_ls9c_ard_3-2-1_110073_2023-03-18_final.stac-item
2023-03-21 11:51:43	ga_ls9c_ard_3-2-1_115076_2023-03-21_final.stac-item
2023-04-19 09:43:16	ga_ls9c_ard_3-2-1_094080_2023-04-19_final.stac-item
2023-04-19 11:18:58	ga_ls9c_ard_3-2-1_110072_2023-04-19_final.stac-item
2023-04-26 09:51:00	ga_ls9c_ard_3-2-1_095084_2023-04-26_final.stac-item
2023-05-05 09:40:16	ga_ls9c_ard_3-2-1_094073_2023-05-05_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-14 09:34:28	ga_ls9c_ard_3-2-1_093074_2023-05-14_final.stac-item
2023-05-16 09:26:05	ga_ls9c_ard_3-2-1_091084_2023-05-15_final.stac-item
2023-05-21 11:22:38	ga_ls9c_ard_3-2-1_110082_2023-05-21_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-05-31 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-05-31_final.stac-item
2023-06-18 10:07:28	ga_ls9c_ard_3-2-1_098080_2023-06-18_final.stac-item
2023-06-19 10:45:56	ga_ls9c_ard_3-2-1_105068_2023-06-19_final.stac-item
2023-06-20 11:35:11	ga_ls9c_ard_3-2-1_112083_2023-06-20_final.stac-item
2023-06-26 09:16:49	ga_ls9c_ard_3-2-1_090077_2023-06-25_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-07-01 09:37:06	ga_ls9c_ard_3-2-1_093081_2023-07-01_final.stac-item
2023-07-03 09:25:34	ga_ls9c_ard_3-2-1_091083_2023-07-02_final.stac-item
2023-07-06 09:54:55	ga_ls9c_ard_3-2-1_096079_2023-07-06_final.stac-item
2023-07-08 09:43:46	ga_ls9c_ard_3-2-1_094082_2023-07-08_final.stac-item
2023-07-08 09:44:34	ga_ls9c_ard_3-2-1_094084_2023-07-08_final.stac-item
2023-07-10 09:30:38	ga_ls9c_ard_3-2-1_092080_2023-07-10_final.stac-item
2023-07-10 11:10:43	ga_ls9c_ard_3-2-1_108083_2023-07-10_final.stac-item
2023-09-05 09:26:51	ga_ls9c_ard_3-2-1_091085_2023-09-04_final.stac-item
2023-09-12 11:06:25	ga_ls9c_ard_3-2-1_108071_2023-09-12_final.stac-item
2023-09-12 11:11:12	ga_ls9c_ard_3-2-1_108083_2023-09-12_final.stac-item
2023-09-14 10:54:04	ga_ls9c_ard_3-2-1_106071_2023-09-14_final.stac-item
2023-09-16 10:40:31	ga_ls9c_ard_3-2-1_104068_2023-09-16_final.stac-item
2023-09-28 09:29:27	ga_ls9c_ard_3-2-1_092076_2023-09-27_final.stac-item
2023-09-30 10:54:49	ga_ls9c_ard_3-2-1_106073_2023-09-30_final.stac-item
2023-10-08 10:07:04	ga_ls9c_ard_3-2-1_098077_2023-10-08_final.stac-item
2023-10-09 10:48:21	ga_ls9c_ard_3-2-1_105072_2023-10-09_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