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
2021-12-13 09:21:48	ga_ls9c_ard_3-2-1_090087_2021-12-12_final.stac-item
2022-01-25 10:38:07	ga_ls9c_ard_3-2-1_103077_2022-01-25_final.stac-item
2022-01-30 09:22:34	ga_ls9c_ard_3-2-1_090089_2022-01-29_final.stac-item
2022-01-30 10:56:39	ga_ls9c_ard_3-2-1_106077_2022-01-30_final.stac-item
2022-02-06 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-02-05_final.stac-item
2022-04-03 10:09:04	ga_ls9c_ard_3-2-1_099067_2022-04-03_final.stac-item
2022-05-20 11:09:51	ga_ls9c_ard_3-2-1_108081_2022-05-20_final.stac-item
2022-05-21 10:08:38	ga_ls9c_ard_3-2-1_099067_2022-05-21_final.stac-item
2022-06-05 11:09:52	ga_ls9c_ard_3-2-1_108081_2022-06-05_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-07-10 09:57:48	ga_ls9c_ard_3-2-1_097070_2022-07-10_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-03 10:52:41	ga_ls9c_ard_3-2-1_105083_2022-08-03_final.stac-item
2022-08-17 11:01:34	ga_ls9c_ard_3-2-1_107074_2022-08-17_final.stac-item
2022-08-31 09:37:04	ga_ls9c_ard_3-2-1_093079_2022-08-31_final.stac-item
2022-10-04 11:04:31	ga_ls9c_ard_3-2-1_107081_2022-10-04_final.stac-item
2022-10-18 09:35:17	ga_ls9c_ard_3-2-1_093074_2022-10-18_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-10-29 09:19:56	ga_ls9c_ard_3-2-1_090082_2022-10-28_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-11-26 11:19:09	ga_ls9c_ard_3-2-1_110071_2022-11-26_final.stac-item
2022-12-07 11:04:36	ga_ls9c_ard_3-2-1_107081_2022-12-07_final.stac-item
2022-12-10 09:58:13	ga_ls9c_ard_3-2-1_096085_2022-12-10_final.stac-item
2022-12-17 09:59:36	ga_ls9c_ard_3-2-1_097073_2022-12-17_final.stac-item
2022-12-20 10:34:05	ga_ls9c_ard_3-2-1_102082_2022-12-20_final.stac-item
2022-12-23 09:28:52	ga_ls9c_ard_3-2-1_091089_2022-12-22_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-11 09:56:36	ga_ls9c_ard_3-2-1_096081_2023-01-11_final.stac-item
2023-01-12 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-12_final.stac-item
2023-01-13 09:45:49	ga_ls9c_ard_3-2-1_094085_2023-01-13_final.stac-item
2023-01-15 09:28:15	ga_ls9c_ard_3-2-1_092072_2023-01-14_final.stac-item
2023-01-17 10:57:32	ga_ls9c_ard_3-2-1_106079_2023-01-17_final.stac-item
2023-01-19 10:43:56	ga_ls9c_ard_3-2-1_104076_2023-01-19_final.stac-item
2023-01-22 09:40:20	ga_ls9c_ard_3-2-1_093087_2023-01-22_final.stac-item
2023-01-24 09:25:37	ga_ls9c_ard_3-2-1_091081_2023-01-23_final.stac-item
2023-01-31 11:06:48	ga_ls9c_ard_3-2-1_108071_2023-01-31_final.stac-item
2023-02-02 10:58:03	ga_ls9c_ard_3-2-1_106080_2023-02-02_final.stac-item
2023-02-04 10:44:55	ga_ls9c_ard_3-2-1_104078_2023-02-04_final.stac-item
2023-02-05 11:26:59	ga_ls9c_ard_3-2-1_111075_2023-02-05_final.stac-item
2023-02-07 09:39:44	ga_ls9c_ard_3-2-1_093085_2023-02-07_final.stac-item
2023-04-21 11:10:59	ga_ls9c_ard_3-2-1_108083_2023-04-21_final.stac-item
2023-04-23 10:53:49	ga_ls9c_ard_3-2-1_106071_2023-04-23_final.stac-item
2023-04-28 09:38:12	ga_ls9c_ard_3-2-1_093083_2023-04-28_final.stac-item
2023-04-29 10:20:15	ga_ls9c_ard_3-2-1_100080_2023-04-29_final.stac-item
2023-04-29 10:21:03	ga_ls9c_ard_3-2-1_100082_2023-04-29_final.stac-item
2023-05-28 09:50:16	ga_ls9c_ard_3-2-1_095083_2023-05-28_final.stac-item
2023-07-17 11:12:32	ga_ls9c_ard_3-2-1_109072_2023-07-17_final.stac-item
2023-07-18 10:17:19	ga_ls9c_ard_3-2-1_100073_2023-07-18_final.stac-item
2023-07-19 09:25:17	ga_ls9c_ard_3-2-1_091082_2023-07-18_final.stac-item
2023-07-19 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-07-19_final.stac-item
2023-07-20 11:44:14	ga_ls9c_ard_3-2-1_114074_2023-07-20_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-07-24 09:40:12	ga_ls9c_ard_3-2-1_094073_2023-07-24_final.stac-item
2023-07-26 09:29:03	ga_ls9c_ard_3-2-1_092076_2023-07-25_final.stac-item
2023-07-26 11:05:09	ga_ls9c_ard_3-2-1_108069_2023-07-26_final.stac-item
2023-07-26 11:05:57	ga_ls9c_ard_3-2-1_108071_2023-07-26_final.stac-item
2023-07-26 11:06:21	ga_ls9c_ard_3-2-1_108072_2023-07-26_final.stac-item
2023-07-28 10:54:49	ga_ls9c_ard_3-2-1_106074_2023-07-28_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-04 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-08-04_final.stac-item
2023-08-04 11:05:05	ga_ls9c_ard_3-2-1_107084_2023-08-04_final.stac-item
2023-08-06 09:14:16	ga_ls9c_ard_3-2-1_089085_2023-08-05_final.stac-item
2023-10-14 11:07:46	ga_ls9c_ard_3-2-1_108074_2023-10-14_final.stac-item
2023-10-15 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-10-15_final.stac-item
2023-10-16 10:57:49	ga_ls9c_ard_3-2-1_106080_2023-10-16_final.stac-item
2023-10-17 10:01:48	ga_ls9c_ard_3-2-1_097079_2023-10-17_final.stac-item
2023-10-17 10:04:12	ga_ls9c_ard_3-2-1_097085_2023-10-17_final.stac-item
2023-10-19 09:52:38	ga_ls9c_ard_3-2-1_095087_2023-10-19_final.stac-item
2023-10-21 09:35:53	ga_ls9c_ard_3-2-1_093076_2023-10-21_final.stac-item
2023-10-21 11:17:34	ga_ls9c_ard_3-2-1_109083_2023-10-21_final.stac-item
2023-10-22 11:58:02	ga_ls9c_ard_3-2-1_116076_2023-10-22_final.stac-item
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-10-27 10:38:03	ga_ls9c_ard_3-2-1_103077_2023-10-27_final.stac-item
2023-10-29 10:24:05	ga_ls9c_ard_3-2-1_101073_2023-10-29_final.stac-item
2023-10-29 10:25:40	ga_ls9c_ard_3-2-1_101077_2023-10-29_final.stac-item
2023-10-29 10:28:04	ga_ls9c_ard_3-2-1_101083_2023-10-29_final.stac-item
2023-10-30 09:30:02	ga_ls9c_ard_3-2-1_092077_2023-10-30_final.stac-item
2023-11-01 09:22:50	ga_ls9c_ard_3-2-1_090090_2023-10-31_final.stac-item
2023-11-01 10:57:43	ga_ls9c_ard_3-2-1_106080_2023-11-01_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-02 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final.stac-item
2023-11-02 10:01:41	ga_ls9c_ard_3-2-1_097079_2023-11-02_final.stac-item
2023-11-04 11:25:25	ga_ls9c_ard_3-2-1_111072_2023-11-04_final.stac-item
2023-11-04 11:27:01	ga_ls9c_ard_3-2-1_111076_2023-11-04_final.stac-item
2023-11-04 11:29:01	ga_ls9c_ard_3-2-1_111081_2023-11-04_final.stac-item
2023-11-14 10:28:03	ga_ls9c_ard_3-2-1_101083_2023-11-14_final.stac-item
2023-11-15 09:32:49	ga_ls9c_ard_3-2-1_092084_2023-11-15_final.stac-item
2023-11-15 09:33:13	ga_ls9c_ard_3-2-1_092085_2023-11-15_final.stac-item
2023-11-15 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-15 11:05:43	ga_ls9c_ard_3-2-1_108069_2023-11-15_final.stac-item
2023-11-15 11:08:31	ga_ls9c_ard_3-2-1_108076_2023-11-15_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-17 10:56:34	ga_ls9c_ard_3-2-1_106077_2023-11-17_final.stac-item
2023-11-19 10:43:51	ga_ls9c_ard_3-2-1_104076_2023-11-19_final.stac-item
2023-11-21 10:31:31	ga_ls9c_ard_3-2-1_102076_2023-11-21_final.stac-item
2023-11-22 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-11-22_final.stac-item
2023-11-23 10:17:59	ga_ls9c_ard_3-2-1_100073_2023-11-23_final.stac-item
2023-11-25 10:06:27	ga_ls9c_ard_3-2-1_098075_2023-11-25_final.stac-item
2023-11-25 11:47:19	ga_ls9c_ard_3-2-1_114080_2023-11-25_final.stac-item
2023-11-29 11:23:25	ga_ls9c_ard_3-2-1_110082_2023-11-29_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