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
2021-11-03 09:57:21	ga_ls9c_ard_3-2-1_096081_2021-11-03_final.stac-item
2021-12-12 11:51:08	ga_ls9c_ard_3-2-1_115074_2021-12-12_final.stac-item
2021-12-20 09:27:09	ga_ls9c_ard_3-2-1_091085_2021-12-19_final.stac-item
2021-12-22 10:52:05	ga_ls9c_ard_3-2-1_105081_2021-12-22_final.stac-item
2021-12-24 10:35:44	ga_ls9c_ard_3-2-1_103071_2021-12-24_final.stac-item
2022-01-02 10:28:21	ga_ls9c_ard_3-2-1_102068_2022-01-02_final.stac-item
2022-01-10 11:19:21	ga_ls9c_ard_3-2-1_110072_2022-01-10_final.stac-item
2022-01-12 11:06:11	ga_ls9c_ard_3-2-1_108070_2022-01-12_final.stac-item
2022-01-17 11:25:08	ga_ls9c_ard_3-2-1_111071_2022-01-17_final.stac-item
2022-01-28 11:07:01	ga_ls9c_ard_3-2-1_108072_2022-01-28_final.stac-item
2022-02-01 10:46:17	ga_ls9c_ard_3-2-1_104082_2022-02-01_final.stac-item
2022-02-06 09:25:56	ga_ls9c_ard_3-2-1_091082_2022-02-05_final.stac-item
2022-02-07 11:47:17	ga_ls9c_ard_3-2-1_114080_2022-02-07_final.stac-item
2022-02-11 11:19:20	ga_ls9c_ard_3-2-1_110072_2022-02-11_final.stac-item
2022-04-18 11:09:21	ga_ls9c_ard_3-2-1_108079_2022-04-18_final.stac-item
2022-05-08 10:45:42	ga_ls9c_ard_3-2-1_104082_2022-05-08_final.stac-item
2022-05-11 11:16:10	ga_ls9c_ard_3-2-1_109081_2022-05-11_final.stac-item
2022-05-13 11:04:59	ga_ls9c_ard_3-2-1_107084_2022-05-13_final.stac-item
2022-05-27 11:16:01	ga_ls9c_ard_3-2-1_109081_2022-05-27_final.stac-item
2022-05-31 09:12:02	ga_ls9c_ard_3-2-1_089080_2022-05-30_final.stac-item
2022-06-10 11:26:26	ga_ls9c_ard_3-2-1_111076_2022-06-10_final.stac-item
2022-06-14 11:04:58	ga_ls9c_ard_3-2-1_107084_2022-06-14_final.stac-item
2022-07-10 10:01:23	ga_ls9c_ard_3-2-1_097079_2022-07-10_final.stac-item
2022-07-15 10:17:06	ga_ls9c_ard_3-2-1_100072_2022-07-15_final.stac-item
2022-08-10 10:53:45	ga_ls9c_ard_3-2-1_106070_2022-08-10_final.stac-item
2022-08-10 10:54:09	ga_ls9c_ard_3-2-1_106071_2022-08-10_final.stac-item
2022-08-22 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-08-22_final.stac-item
2022-08-30 10:28:42	ga_ls9c_ard_3-2-1_102069_2022-08-30_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-11 10:58:37	ga_ls9c_ard_3-2-1_106082_2022-09-11_final.stac-item
2022-09-14 09:47:29	ga_ls9c_ard_3-2-1_095074_2022-09-14_final.stac-item
2022-09-20 09:14:02	ga_ls9c_ard_3-2-1_089083_2022-09-19_final.stac-item
2022-09-21 11:35:24	ga_ls9c_ard_3-2-1_112081_2022-09-21_final.stac-item
2022-09-30 09:47:34	ga_ls9c_ard_3-2-1_095074_2022-09-30_final.stac-item
2022-10-01 10:29:14	ga_ls9c_ard_3-2-1_102070_2022-10-01_final.stac-item
2022-10-09 09:44:35	ga_ls9c_ard_3-2-1_094082_2022-10-09_final.stac-item
2022-10-30 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-30_final.stac-item
2022-11-07 09:16:56	ga_ls9c_ard_3-2-1_089090_2022-11-06_final.stac-item
2022-11-19 11:13:24	ga_ls9c_ard_3-2-1_109072_2022-11-19_final.stac-item
2022-11-21 09:22:09	ga_ls9c_ard_3-2-1_091072_2022-11-20_final.stac-item
2022-11-21 11:03:50	ga_ls9c_ard_3-2-1_107079_2022-11-21_final.stac-item
2022-11-23 10:47:52	ga_ls9c_ard_3-2-1_105070_2022-11-23_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 09:14:10	ga_ls9c_ard_3-2-1_089083_2022-12-08_final.stac-item
2022-12-19 09:52:49	ga_ls9c_ard_3-2-1_095087_2022-12-19_final.stac-item
2022-12-21 09:38:51	ga_ls9c_ard_3-2-1_093083_2022-12-21_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 09:36:30	ga_ls9c_ard_3-2-1_093077_2023-01-06_final.stac-item
2023-01-13 09:40:14	ga_ls9c_ard_3-2-1_094071_2023-01-13_final.stac-item
2023-01-13 11:19:07	ga_ls9c_ard_3-2-1_110071_2023-01-13_final.stac-item
2023-02-15 10:24:21	ga_ls9c_ard_3-2-1_101073_2023-02-15_final.stac-item
2023-02-19 10:04:20	ga_ls9c_ard_3-2-1_097085_2023-02-19_final.stac-item
2023-03-04 11:11:46	ga_ls9c_ard_3-2-1_108084_2023-03-04_final.stac-item
2023-03-11 09:39:46	ga_ls9c_ard_3-2-1_093086_2023-03-11_final.stac-item
2023-04-03 09:45:22	ga_ls9c_ard_3-2-1_094085_2023-04-03_final.stac-item
2023-04-10 11:26:00	ga_ls9c_ard_3-2-1_111074_2023-04-10_final.stac-item
2023-04-19 09:44:04	ga_ls9c_ard_3-2-1_094082_2023-04-19_final.stac-item
2023-04-25 10:40:39	ga_ls9c_ard_3-2-1_104069_2023-04-25_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-16 09:26:28	ga_ls9c_ard_3-2-1_091085_2023-05-15_final.stac-item
2023-05-18 10:45:47	ga_ls9c_ard_3-2-1_105067_2023-05-18_final.stac-item
2023-05-19 09:51:45	ga_ls9c_ard_3-2-1_096071_2023-05-19_final.stac-item
2023-05-21 09:39:22	ga_ls9c_ard_3-2-1_094071_2023-05-21_final.stac-item
2023-05-23 09:27:22	ga_ls9c_ard_3-2-1_092072_2023-05-22_final.stac-item
2023-05-27 09:06:13	ga_ls9c_ard_3-2-1_088081_2023-05-26_final.stac-item
2023-06-01 09:24:45	ga_ls9c_ard_3-2-1_091081_2023-05-31_final.stac-item
2023-06-02 11:46:29	ga_ls9c_ard_3-2-1_114080_2023-06-02_final.stac-item
2023-06-11 11:40:37	ga_ls9c_ard_3-2-1_113081_2023-06-11_final.stac-item
2023-06-13 11:28:38	ga_ls9c_ard_3-2-1_111082_2023-06-13_final.stac-item
2023-06-14 10:30:12	ga_ls9c_ard_3-2-1_102075_2023-06-14_final.stac-item
2023-07-04 11:44:08	ga_ls9c_ard_3-2-1_114074_2023-07-04_final.stac-item
2023-07-05 10:46:08	ga_ls9c_ard_3-2-1_105068_2023-07-05_final.stac-item
2023-07-17 09:38:50	ga_ls9c_ard_3-2-1_093085_2023-07-17_final.stac-item
2023-07-21 09:12:55	ga_ls9c_ard_3-2-1_089082_2023-07-20_final.stac-item
2023-08-09 09:43:59	ga_ls9c_ard_3-2-1_094082_2023-08-09_final.stac-item
2023-08-09 11:19:40	ga_ls9c_ard_3-2-1_110074_2023-08-09_final.stac-item
2023-08-13 10:55:45	ga_ls9c_ard_3-2-1_106076_2023-08-13_final.stac-item
2023-08-17 10:28:14	ga_ls9c_ard_3-2-1_102069_2023-08-17_final.stac-item
2023-08-18 09:37:48	ga_ls9c_ard_3-2-1_093082_2023-08-18_final.stac-item
2023-08-20 09:22:17	ga_ls9c_ard_3-2-1_091074_2023-08-19_final.stac-item
2023-08-20 09:24:40	ga_ls9c_ard_3-2-1_091080_2023-08-19_final.stac-item
2023-08-25 09:44:05	ga_ls9c_ard_3-2-1_094082_2023-08-25_final.stac-item
2023-09-10 09:44:16	ga_ls9c_ard_3-2-1_094082_2023-09-10_final.stac-item
2023-09-12 11:06:25	ga_ls9c_ard_3-2-1_108071_2023-09-12_final.stac-item
2023-09-19 11:12:36	ga_ls9c_ard_3-2-1_109071_2023-09-19_final.stac-item
2023-09-21 11:05:01	ga_ls9c_ard_3-2-1_107083_2023-09-21_final.stac-item
2023-09-23 09:11:22	ga_ls9c_ard_3-2-1_089077_2023-09-22_final.stac-item
2023-10-05 11:13:26	ga_ls9c_ard_3-2-1_109073_2023-10-05_final.stac-item
2023-10-16 09:20:32	ga_ls9c_ard_3-2-1_090084_2023-10-15_final.stac-item
2023-11-06 09:38:35	ga_ls9c_ard_3-2-1_093083_2023-11-06_final.stac-item
2023-11-06 09:39:23	ga_ls9c_ard_3-2-1_093085_2023-11-06_final.stac-item
2023-11-06 11:11:53	ga_ls9c_ard_3-2-1_109069_2023-11-06_final.stac-item
2023-11-30 10:23:48	ga_ls9c_ard_3-2-1_101072_2023-11-30_final.stac-item
2023-12-02 11:51:06	ga_ls9c_ard_3-2-1_115074_2023-12-02_final.stac-item
2023-12-03 09:19:47	ga_ls9c_ard_3-2-1_090082_2023-12-02_final.stac-item
2023-12-03 10:58:40	ga_ls9c_ard_3-2-1_106082_2023-12-03_final.stac-item
2023-12-28 10:47:20	ga_ls9c_ard_3-2-1_105069_2023-12-28_final.stac-item
2023-12-28 10:49:44	ga_ls9c_ard_3-2-1_105075_2023-12-28_final.stac-item
2023-12-29 09:53:42	ga_ls9c_ard_3-2-1_096074_2023-12-29_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