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
2021-11-16 10:22:42	ga_ls9c_ard_3-2-1_100079_2021-11-16_final.stac-item
2021-11-17 09:23:40	ga_ls9c_ard_3-2-1_091078_2021-11-16_final.stac-item
2021-12-11 09:30:59	ga_ls9c_ard_3-2-1_092079_2021-12-11_final.stac-item
2021-12-11 11:11:04	ga_ls9c_ard_3-2-1_108082_2021-12-11_final.stac-item
2021-12-16 11:25:10	ga_ls9c_ard_3-2-1_111071_2021-12-16_final.stac-item
2021-12-27 09:34:56	ga_ls9c_ard_3-2-1_092089_2021-12-27_final.stac-item
2021-12-27 11:11:02	ga_ls9c_ard_3-2-1_108082_2021-12-27_final.stac-item
2022-01-04 10:20:22	ga_ls9c_ard_3-2-1_100079_2022-01-04_final.stac-item
2022-01-08 11:35:19	ga_ls9c_ard_3-2-1_112081_2022-01-08_final.stac-item
2022-01-19 11:15:35	ga_ls9c_ard_3-2-1_109078_2022-01-19_final.stac-item
2022-01-30 09:18:58	ga_ls9c_ard_3-2-1_090080_2022-01-29_final.stac-item
2022-02-25 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-02-25_final.stac-item
2022-03-03 09:18:43	ga_ls9c_ard_3-2-1_090080_2022-03-02_final.stac-item
2022-03-31 09:42:10	ga_ls9c_ard_3-2-1_094077_2022-03-31_final.stac-item
2022-04-04 10:54:20	ga_ls9c_ard_3-2-1_106072_2022-04-04_final.stac-item
2022-05-11 11:15:46	ga_ls9c_ard_3-2-1_109080_2022-05-11_final.stac-item
2022-05-21 10:15:49	ga_ls9c_ard_3-2-1_099085_2022-05-21_final.stac-item
2022-05-29 09:26:23	ga_ls9c_ard_3-2-1_091085_2022-05-28_final.stac-item
2022-06-08 09:58:18	ga_ls9c_ard_3-2-1_097072_2022-06-08_final.stac-item
2022-06-19 09:43:06	ga_ls9c_ard_3-2-1_094080_2022-06-19_final.stac-item
2022-06-30 11:00:51	ga_ls9c_ard_3-2-1_107073_2022-06-30_final.stac-item
2022-07-02 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-07-02_final.stac-item
2022-07-06 10:23:20	ga_ls9c_ard_3-2-1_101072_2022-07-06_final.stac-item
2022-07-07 11:06:36	ga_ls9c_ard_3-2-1_108072_2022-07-07_final.stac-item
2022-07-09 09:18:32	ga_ls9c_ard_3-2-1_090080_2022-07-08_final.stac-item
2022-07-15 10:20:41	ga_ls9c_ard_3-2-1_100081_2022-07-15_final.stac-item
2022-07-16 11:00:47	ga_ls9c_ard_3-2-1_107073_2022-07-16_final.stac-item
2022-07-18 10:48:04	ga_ls9c_ard_3-2-1_105072_2022-07-18_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-01 09:26:08	ga_ls9c_ard_3-2-1_091083_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
2022-08-06 09:44:44	ga_ls9c_ard_3-2-1_094083_2022-08-06_final.stac-item
2022-08-18 10:08:45	ga_ls9c_ard_3-2-1_098081_2022-08-18_final.stac-item
2022-08-19 10:47:37	ga_ls9c_ard_3-2-1_105070_2022-08-19_final.stac-item
2022-08-31 09:37:28	ga_ls9c_ard_3-2-1_093080_2022-08-31_final.stac-item
2022-09-16 11:17:37	ga_ls9c_ard_3-2-1_109083_2022-09-16_final.stac-item
2022-09-19 11:45:45	ga_ls9c_ard_3-2-1_114076_2022-09-19_final.stac-item
2022-09-21 09:52:55	ga_ls9c_ard_3-2-1_096072_2022-09-21_final.stac-item
2022-09-25 11:07:06	ga_ls9c_ard_3-2-1_108072_2022-09-25_final.stac-item
2022-10-09 09:44:59	ga_ls9c_ard_3-2-1_094083_2022-10-09_final.stac-item
2022-10-14 09:59:59	ga_ls9c_ard_3-2-1_097074_2022-10-14_final.stac-item
2022-10-17 10:33:42	ga_ls9c_ard_3-2-1_102081_2022-10-17_final.stac-item
2022-10-18 11:12:35	ga_ls9c_ard_3-2-1_109070_2022-10-18_final.stac-item
2022-10-21 11:47:29	ga_ls9c_ard_3-2-1_114080_2022-10-21_final.stac-item
2022-10-23 11:34:43	ga_ls9c_ard_3-2-1_112079_2022-10-23_final.stac-item
2022-10-24 10:40:18	ga_ls9c_ard_3-2-1_103082_2022-10-24_final.stac-item
2022-11-03 11:13:20	ga_ls9c_ard_3-2-1_109072_2022-11-03_final.stac-item
2022-11-12 09:32:43	ga_ls9c_ard_3-2-1_092083_2022-11-12_final.stac-item
2022-11-15 10:00:50	ga_ls9c_ard_3-2-1_097076_2022-11-15_final.stac-item
2022-11-19 11:16:11	ga_ls9c_ard_3-2-1_109079_2022-11-19_final.stac-item
2022-11-20 11:58:15	ga_ls9c_ard_3-2-1_116076_2022-11-20_final.stac-item
2022-11-22 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-11-22_final.stac-item
2022-11-24 09:56:38	ga_ls9c_ard_3-2-1_096081_2022-11-24_final.stac-item
2022-12-03 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-03_final.stac-item
2022-12-04 10:31:17	ga_ls9c_ard_3-2-1_102075_2022-12-04_final.stac-item
2022-12-05 09:37:16	ga_ls9c_ard_3-2-1_093079_2022-12-05_final.stac-item
2023-01-01 10:57:38	ga_ls9c_ard_3-2-1_106079_2023-01-01_final.stac-item
2023-01-04 11:27:20	ga_ls9c_ard_3-2-1_111076_2023-01-04_final.stac-item
2023-01-09 10:06:11	ga_ls9c_ard_3-2-1_098074_2023-01-09_final.stac-item
2023-01-12 10:38:40	ga_ls9c_ard_3-2-1_103078_2023-01-12_final.stac-item
2023-01-13 09:46:37	ga_ls9c_ard_3-2-1_094087_2023-01-13_final.stac-item
2023-01-17 09:19:03	ga_ls9c_ard_3-2-1_090080_2023-01-16_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 09:39:08	ga_ls9c_ard_3-2-1_093084_2023-01-22_final.stac-item
2023-02-03 11:40:08	ga_ls9c_ard_3-2-1_113077_2023-02-03_final.stac-item
2023-02-04 10:44:55	ga_ls9c_ard_3-2-1_104078_2023-02-04_final.stac-item
2023-02-06 10:31:46	ga_ls9c_ard_3-2-1_102076_2023-02-06_final.stac-item
2023-02-23 09:35:31	ga_ls9c_ard_3-2-1_093075_2023-02-23_final.stac-item
2023-02-23 09:37:07	ga_ls9c_ard_3-2-1_093079_2023-02-23_final.stac-item
2023-02-27 10:50:28	ga_ls9c_ard_3-2-1_105077_2023-02-27_final.stac-item
2023-03-03 10:23:44	ga_ls9c_ard_3-2-1_101072_2023-03-03_final.stac-item
2023-03-06 09:18:06	ga_ls9c_ard_3-2-1_090078_2023-03-05_final.stac-item
2023-03-11 09:35:47	ga_ls9c_ard_3-2-1_093076_2023-03-11_final.stac-item
2023-03-11 09:37:46	ga_ls9c_ard_3-2-1_093081_2023-03-11_final.stac-item
2023-03-27 09:33:39	ga_ls9c_ard_3-2-1_093071_2023-03-27_final.stac-item
2023-04-05 09:33:24	ga_ls9c_ard_3-2-1_092086_2023-04-05_final.stac-item
2023-04-05 11:10:41	ga_ls9c_ard_3-2-1_108082_2023-04-05_final.stac-item
2023-04-08 09:59:30	ga_ls9c_ard_3-2-1_097074_2023-04-08_final.stac-item
2023-04-12 11:15:12	ga_ls9c_ard_3-2-1_109078_2023-04-12_final.stac-item
2023-04-23 09:18:08	ga_ls9c_ard_3-2-1_090079_2023-04-22_final.stac-item
2023-05-05 11:20:21	ga_ls9c_ard_3-2-1_110076_2023-05-05_final.stac-item
2023-05-07 11:11:11	ga_ls9c_ard_3-2-1_108084_2023-05-07_final.stac-item
2023-05-12 09:48:02	ga_ls9c_ard_3-2-1_095077_2023-05-12_final.stac-item
2023-05-12 11:27:19	ga_ls9c_ard_3-2-1_111078_2023-05-12_final.stac-item
2023-05-19 09:52:57	ga_ls9c_ard_3-2-1_096074_2023-05-19_final.stac-item
2023-05-21 11:23:02	ga_ls9c_ard_3-2-1_110083_2023-05-21_final.stac-item
2023-05-30 09:36:43	ga_ls9c_ard_3-2-1_093080_2023-05-30_final.stac-item
2023-06-19 10:46:44	ga_ls9c_ard_3-2-1_105070_2023-06-19_final.stac-item
2023-07-07 10:34:12	ga_ls9c_ard_3-2-1_103069_2023-07-07_final.stac-item
2023-07-16 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-31 09:46:53	ga_ls9c_ard_3-2-1_095074_2023-07-31_final.stac-item
2023-08-15 10:41:00	ga_ls9c_ard_3-2-1_104070_2023-08-15_final.stac-item
2023-08-16 11:26:15	ga_ls9c_ard_3-2-1_111075_2023-08-16_final.stac-item
2023-10-14 09:31:40	ga_ls9c_ard_3-2-1_092081_2023-10-14_final.stac-item
2023-10-14 09:32:28	ga_ls9c_ard_3-2-1_092083_2023-10-14_final.stac-item
2023-10-22 10:17:57	ga_ls9c_ard_3-2-1_100073_2023-10-22_final.stac-item
2023-10-30 11:09:43	ga_ls9c_ard_3-2-1_108079_2023-10-30_final.stac-item
2023-11-02 11:38:58	ga_ls9c_ard_3-2-1_113075_2023-11-02_final.stac-item
2023-11-14 10:26:51	ga_ls9c_ard_3-2-1_101080_2023-11-14_final.stac-item
2023-11-15 09:30:49	ga_ls9c_ard_3-2-1_092079_2023-11-15_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