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
2021-11-07 09:23:03	ga_ls9c_ard_3-2-1_090089_2021-11-06_final.stac-item
2021-12-08 10:35:49	ga_ls9c_ard_3-2-1_103071_2021-12-08_final.stac-item
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-18 09:35:07	ga_ls9c_ard_3-2-1_093074_2021-12-18_final.stac-item
2021-12-20 09:23:57	ga_ls9c_ard_3-2-1_091077_2021-12-19_final.stac-item
2021-12-29 10:56:16	ga_ls9c_ard_3-2-1_106076_2021-12-29_final.stac-item
2022-01-22 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-22_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-11 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-02-11_final.stac-item
2022-02-20 09:36:59	ga_ls9c_ard_3-2-1_093079_2022-02-20_final.stac-item
2022-03-08 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-03-08_final.stac-item
2022-03-11 11:46:39	ga_ls9c_ard_3-2-1_114079_2022-03-11_final.stac-item
2022-03-12 10:52:13	ga_ls9c_ard_3-2-1_105082_2022-03-12_final.stac-item
2022-04-17 10:25:42	ga_ls9c_ard_3-2-1_101078_2022-04-17_final.stac-item
2022-05-09 09:48:04	ga_ls9c_ard_3-2-1_095077_2022-05-09_final.stac-item
2022-05-09 11:26:33	ga_ls9c_ard_3-2-1_111076_2022-05-09_final.stac-item
2022-06-21 11:10:06	ga_ls9c_ard_3-2-1_108081_2022-06-21_final.stac-item
2022-06-25 09:06:37	ga_ls9c_ard_3-2-1_088081_2022-06-24_final.stac-item
2022-07-02 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-07-01_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-27 09:06:20	ga_ls9c_ard_3-2-1_088080_2022-07-26_final.stac-item
2022-07-27 10:40:26	ga_ls9c_ard_3-2-1_104068_2022-07-27_final.stac-item
2022-08-03 09:13:00	ga_ls9c_ard_3-2-1_089081_2022-08-02_final.stac-item
2022-08-10 10:53:45	ga_ls9c_ard_3-2-1_106070_2022-08-10_final.stac-item
2022-08-28 09:07:22	ga_ls9c_ard_3-2-1_088082_2022-08-27_final.stac-item
2022-09-09 09:30:05	ga_ls9c_ard_3-2-1_092077_2022-09-09_final.stac-item
2022-09-25 09:33:48	ga_ls9c_ard_3-2-1_092086_2022-09-25_final.stac-item
2022-09-26 10:10:41	ga_ls9c_ard_3-2-1_099070_2022-09-26_final.stac-item
2022-09-29 10:42:47	ga_ls9c_ard_3-2-1_104073_2022-09-29_final.stac-item
2022-10-04 09:27:37	ga_ls9c_ard_3-2-1_091086_2022-10-03_final.stac-item
2022-10-05 11:44:59	ga_ls9c_ard_3-2-1_114074_2022-10-05_final.stac-item
2022-10-12 10:10:20	ga_ls9c_ard_3-2-1_099069_2022-10-12_final.stac-item
2022-10-29 10:54:02	ga_ls9c_ard_3-2-1_106070_2022-10-29_final.stac-item
2022-11-01 09:47:37	ga_ls9c_ard_3-2-1_095074_2022-11-01_final.stac-item
2022-11-01 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-11-01_final.stac-item
2022-11-09 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-09_final.stac-item
2022-11-09 10:37:06	ga_ls9c_ard_3-2-1_103074_2022-11-09_final.stac-item
2022-11-13 11:51:17	ga_ls9c_ard_3-2-1_115074_2022-11-13_final.stac-item
2022-11-15 11:40:07	ga_ls9c_ard_3-2-1_113077_2022-11-15_final.stac-item
2022-11-27 10:24:43	ga_ls9c_ard_3-2-1_101074_2022-11-27_final.stac-item
2022-11-28 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-11-28_final.stac-item
2022-12-03 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-12-03_final.stac-item
2022-12-03 11:27:42	ga_ls9c_ard_3-2-1_111077_2022-12-03_final.stac-item
2022-12-05 11:14:33	ga_ls9c_ard_3-2-1_109075_2022-12-05_final.stac-item
2022-12-21 09:40:27	ga_ls9c_ard_3-2-1_093087_2022-12-21_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-25 10:52:36	ga_ls9c_ard_3-2-1_105082_2022-12-25_final.stac-item
2022-12-29 10:26:19	ga_ls9c_ard_3-2-1_101078_2022-12-29_final.stac-item
2022-12-30 09:35:29	ga_ls9c_ard_3-2-1_092090_2022-12-30_final.stac-item
2023-01-01 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-12-31_final.stac-item
2023-01-05 10:32:07	ga_ls9c_ard_3-2-1_102077_2023-01-05_final.stac-item
2023-01-10 10:50:38	ga_ls9c_ard_3-2-1_105077_2023-01-10_final.stac-item
2023-01-12 10:37:52	ga_ls9c_ard_3-2-1_103076_2023-01-12_final.stac-item
2023-01-19 09:07:03	ga_ls9c_ard_3-2-1_088081_2023-01-18_final.stac-item
2023-01-20 11:27:10	ga_ls9c_ard_3-2-1_111076_2023-01-20_final.stac-item
2023-01-24 11:01:43	ga_ls9c_ard_3-2-1_107074_2023-01-24_final.stac-item
2023-01-25 11:46:36	ga_ls9c_ard_3-2-1_114078_2023-01-25_final.stac-item
2023-01-26 10:52:35	ga_ls9c_ard_3-2-1_105082_2023-01-26_final.stac-item
2023-02-04 10:43:19	ga_ls9c_ard_3-2-1_104074_2023-02-04_final.stac-item
2023-02-06 10:30:34	ga_ls9c_ard_3-2-1_102073_2023-02-06_final.stac-item
2023-02-08 10:19:25	ga_ls9c_ard_3-2-1_100076_2023-02-08_final.stac-item
2023-03-05 10:14:08	ga_ls9c_ard_3-2-1_099079_2023-03-05_final.stac-item
2023-03-27 09:36:51	ga_ls9c_ard_3-2-1_093079_2023-03-27_final.stac-item
2023-04-23 09:19:44	ga_ls9c_ard_3-2-1_090083_2023-04-22_final.stac-item
2023-04-26 11:28:17	ga_ls9c_ard_3-2-1_111080_2023-04-26_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-04-30 09:23:49	ga_ls9c_ard_3-2-1_091078_2023-04-29_final.stac-item
2023-05-05 11:20:45	ga_ls9c_ard_3-2-1_110077_2023-05-05_final.stac-item
2023-05-07 11:09:35	ga_ls9c_ard_3-2-1_108080_2023-05-07_final.stac-item
2023-05-10 10:02:00	ga_ls9c_ard_3-2-1_097081_2023-05-10_final.stac-item
2023-05-10 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-05-10_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-05-15 10:18:55	ga_ls9c_ard_3-2-1_100077_2023-05-15_final.stac-item
2023-06-02 10:04:01	ga_ls9c_ard_3-2-1_098071_2023-06-02_final.stac-item
2023-06-22 11:20:02	ga_ls9c_ard_3-2-1_110076_2023-06-22_final.stac-item
2023-06-22 11:20:26	ga_ls9c_ard_3-2-1_110077_2023-06-22_final.stac-item
2023-06-24 11:04:52	ga_ls9c_ard_3-2-1_108069_2023-06-24_final.stac-item
2023-06-25 11:51:19	ga_ls9c_ard_3-2-1_115077_2023-06-25_final.stac-item
2023-06-26 10:52:55	ga_ls9c_ard_3-2-1_106070_2023-06-26_final.stac-item
2023-07-15 11:28:05	ga_ls9c_ard_3-2-1_111080_2023-07-15_final.stac-item
2023-07-19 09:28:28	ga_ls9c_ard_3-2-1_091090_2023-07-18_final.stac-item
2023-07-20 11:44:14	ga_ls9c_ard_3-2-1_114074_2023-07-20_final.stac-item
2023-07-24 11:20:41	ga_ls9c_ard_3-2-1_110077_2023-07-24_final.stac-item
2023-07-27 11:52:25	ga_ls9c_ard_3-2-1_115079_2023-07-27_final.stac-item
2023-07-28 09:22:19	ga_ls9c_ard_3-2-1_090090_2023-07-27_final.stac-item
2023-07-31 11:25:22	ga_ls9c_ard_3-2-1_111073_2023-07-31_final.stac-item
2023-08-02 11:14:14	ga_ls9c_ard_3-2-1_109076_2023-08-02_final.stac-item
2023-08-05 10:09:29	ga_ls9c_ard_3-2-1_098084_2023-08-05_final.stac-item
2023-08-05 11:46:46	ga_ls9c_ard_3-2-1_114080_2023-08-05_final.stac-item
2023-08-10 10:27:39	ga_ls9c_ard_3-2-1_101083_2023-08-10_final.stac-item
2023-08-13 09:22:04	ga_ls9c_ard_3-2-1_090089_2023-08-12_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-16 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-11-16_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final.stac-item
2023-11-24 11:00:28	ga_ls9c_ard_3-2-1_107071_2023-11-24_final.stac-item
2023-11-25 10:07:14	ga_ls9c_ard_3-2-1_098077_2023-11-25_final.stac-item
2023-11-25 11:44:56	ga_ls9c_ard_3-2-1_114074_2023-11-25_final.stac-item
2023-11-25 11:46:31	ga_ls9c_ard_3-2-1_114078_2023-11-25_final.stac-item
2023-11-26 09:13:37	ga_ls9c_ard_3-2-1_089082_2023-11-25_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