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
2022-01-02 10:32:44	ga_ls9c_ard_3-2-1_102079_2022-01-02_final.stac-item
2022-01-28 09:34:07	ga_ls9c_ard_3-2-1_092087_2022-01-28_final.stac-item
2022-02-23 10:08:15	ga_ls9c_ard_3-2-1_098080_2022-02-23_final.stac-item
2022-04-04 10:54:43	ga_ls9c_ard_3-2-1_106073_2022-04-04_final.stac-item
2022-04-25 11:11:29	ga_ls9c_ard_3-2-1_109069_2022-04-25_final.stac-item
2022-05-02 09:40:45	ga_ls9c_ard_3-2-1_094074_2022-05-02_final.stac-item
2022-05-18 09:43:21	ga_ls9c_ard_3-2-1_094081_2022-05-18_final.stac-item
2022-05-30 10:04:52	ga_ls9c_ard_3-2-1_098073_2022-05-30_final.stac-item
2022-07-22 10:26:12	ga_ls9c_ard_3-2-1_101079_2022-07-22_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-08-11 09:59:44	ga_ls9c_ard_3-2-1_097074_2022-08-11_final.stac-item
2022-08-26 09:20:08	ga_ls9c_ard_3-2-1_090083_2022-08-25_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-08-27 09:59:48	ga_ls9c_ard_3-2-1_097074_2022-08-27_final.stac-item
2022-08-31 09:40:16	ga_ls9c_ard_3-2-1_093087_2022-08-31_final.stac-item
2022-09-13 10:43:53	ga_ls9c_ard_3-2-1_104076_2022-09-13_final.stac-item
2022-09-17 10:18:24	ga_ls9c_ard_3-2-1_100074_2022-09-17_final.stac-item
2022-09-18 11:01:41	ga_ls9c_ard_3-2-1_107074_2022-09-18_final.stac-item
2022-09-30 09:49:57	ga_ls9c_ard_3-2-1_095080_2022-09-30_final.stac-item
2022-10-02 09:36:00	ga_ls9c_ard_3-2-1_093076_2022-10-02_final.stac-item
2022-10-04 09:24:50	ga_ls9c_ard_3-2-1_091079_2022-10-03_final.stac-item
2022-10-05 11:45:22	ga_ls9c_ard_3-2-1_114075_2022-10-05_final.stac-item
2022-10-10 10:27:52	ga_ls9c_ard_3-2-1_101082_2022-10-10_final.stac-item
2022-10-14 09:59:11	ga_ls9c_ard_3-2-1_097072_2022-10-14_final.stac-item
2022-10-14 11:40:04	ga_ls9c_ard_3-2-1_113077_2022-10-14_final.stac-item
2022-10-26 10:25:32	ga_ls9c_ard_3-2-1_101076_2022-10-26_final.stac-item
2022-10-26 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-10-26_final.stac-item
2022-10-28 10:11:58	ga_ls9c_ard_3-2-1_099073_2022-10-28_final.stac-item
2022-10-30 11:42:04	ga_ls9c_ard_3-2-1_113082_2022-10-30_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-10 11:22:45	ga_ls9c_ard_3-2-1_110080_2022-11-10_final.stac-item
2022-11-15 10:00:02	ga_ls9c_ard_3-2-1_097074_2022-11-15_final.stac-item
2022-11-22 10:04:37	ga_ls9c_ard_3-2-1_098070_2022-11-22_final.stac-item
2022-12-10 09:57:25	ga_ls9c_ard_3-2-1_096083_2022-12-10_final.stac-item
2022-12-14 11:07:36	ga_ls9c_ard_3-2-1_108073_2022-12-14_final.stac-item
2022-12-25 09:15:19	ga_ls9c_ard_3-2-1_089086_2022-12-24_final.stac-item
2022-12-26 09:56:35	ga_ls9c_ard_3-2-1_096081_2022-12-26_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2023-01-03 10:45:16	ga_ls9c_ard_3-2-1_104079_2023-01-03_final.stac-item
2023-01-12 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-12_final.stac-item
2023-01-15 09:32:14	ga_ls9c_ard_3-2-1_092082_2023-01-15_final.stac-item
2023-01-29 09:44:15	ga_ls9c_ard_3-2-1_094081_2023-01-29_final.stac-item
2023-01-29 11:22:44	ga_ls9c_ard_3-2-1_110080_2023-01-29_final.stac-item
2023-02-05 11:28:11	ga_ls9c_ard_3-2-1_111078_2023-02-05_final.stac-item
2023-02-07 11:12:14	ga_ls9c_ard_3-2-1_109069_2023-02-07_final.stac-item
2023-02-07 11:13:50	ga_ls9c_ard_3-2-1_109073_2023-02-07_final.stac-item
2023-02-08 10:21:48	ga_ls9c_ard_3-2-1_100082_2023-02-08_final.stac-item
2023-02-09 09:24:11	ga_ls9c_ard_3-2-1_091077_2023-02-08_final.stac-item
2023-02-09 11:00:41	ga_ls9c_ard_3-2-1_107071_2023-02-09_final.stac-item
2023-02-10 10:09:03	ga_ls9c_ard_3-2-1_098081_2023-02-10_final.stac-item
2023-02-10 11:46:20	ga_ls9c_ard_3-2-1_114077_2023-02-10_final.stac-item
2023-04-22 11:53:03	ga_ls9c_ard_3-2-1_115080_2023-04-22_final.stac-item
2023-04-23 09:19:20	ga_ls9c_ard_3-2-1_090082_2023-04-22_final.stac-item
2023-04-23 10:53:25	ga_ls9c_ard_3-2-1_106070_2023-04-23_final.stac-item
2023-04-25 10:41:27	ga_ls9c_ard_3-2-1_104071_2023-04-25_final.stac-item
2023-04-25 10:41:50	ga_ls9c_ard_3-2-1_104072_2023-04-25_final.stac-item
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final.stac-item
2023-04-28 11:13:06	ga_ls9c_ard_3-2-1_109073_2023-04-28_final.stac-item
2023-05-28 11:28:45	ga_ls9c_ard_3-2-1_111082_2023-05-28_final.stac-item
2023-06-01 09:24:45	ga_ls9c_ard_3-2-1_091081_2023-05-31_final.stac-item
2023-07-16 10:29:16	ga_ls9c_ard_3-2-1_102072_2023-07-16_final.stac-item
2023-07-17 09:35:39	ga_ls9c_ard_3-2-1_093077_2023-07-17_final.stac-item
2023-07-17 11:11:20	ga_ls9c_ard_3-2-1_109069_2023-07-17_final.stac-item
2023-07-20 10:04:57	ga_ls9c_ard_3-2-1_098073_2023-07-20_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 10:47:00	ga_ls9c_ard_3-2-1_105070_2023-07-21_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-22 09:52:35	ga_ls9c_ard_3-2-1_096073_2023-07-22_final.stac-item
2023-07-25 10:23:04	ga_ls9c_ard_3-2-1_101072_2023-07-25_final.stac-item
2023-07-26 09:28:39	ga_ls9c_ard_3-2-1_092075_2023-07-25_final.stac-item
2023-07-28 09:19:08	ga_ls9c_ard_3-2-1_090082_2023-07-27_final.stac-item
2023-07-28 10:53:37	ga_ls9c_ard_3-2-1_106071_2023-07-28_final.stac-item
2023-08-02 09:35:45	ga_ls9c_ard_3-2-1_093077_2023-08-02_final.stac-item
2023-08-03 10:21:25	ga_ls9c_ard_3-2-1_100083_2023-08-03_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_2023-10-13_final.stac-item
2023-10-14 09:32:04	ga_ls9c_ard_3-2-1_092082_2023-10-14_final.stac-item
2023-10-15 10:13:21	ga_ls9c_ard_3-2-1_099077_2023-10-15_final.stac-item
2023-10-15 11:51:02	ga_ls9c_ard_3-2-1_115074_2023-10-15_final.stac-item
2023-10-17 11:38:41	ga_ls9c_ard_3-2-1_113074_2023-10-17_final.stac-item
2023-10-17 11:42:17	ga_ls9c_ard_3-2-1_113083_2023-10-17_final.stac-item
2023-10-19 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-10-19_final.stac-item
2023-10-19 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-10-19_final.stac-item
2023-10-19 09:47:51	ga_ls9c_ard_3-2-1_095075_2023-10-19_final.stac-item
2023-10-20 10:29:31	ga_ls9c_ard_3-2-1_102071_2023-10-20_final.stac-item
2023-10-24 11:45:16	ga_ls9c_ard_3-2-1_114075_2023-10-24_final.stac-item
2023-10-26 09:52:25	ga_ls9c_ard_3-2-1_096071_2023-10-26_final.stac-item
2023-10-28 09:43:37	ga_ls9c_ard_3-2-1_094080_2023-10-28_final.stac-item
2023-10-28 11:19:19	ga_ls9c_ard_3-2-1_110072_2023-10-28_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 10:54:32	ga_ls9c_ard_3-2-1_106072_2023-11-01_final.stac-item
2023-11-02 09:58:53	ga_ls9c_ard_3-2-1_097072_2023-11-02_final.stac-item
2023-11-03 10:44:08	ga_ls9c_ard_3-2-1_104077_2023-11-03_final.stac-item
2023-11-05 10:33:24	ga_ls9c_ard_3-2-1_102081_2023-11-05_final.stac-item
2023-11-14 10:26:27	ga_ls9c_ard_3-2-1_101079_2023-11-14_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 09:34:49	ga_ls9c_ard_3-2-1_092089_2023-11-15_final.stac-item
2023-11-17 10:56:58	ga_ls9c_ard_3-2-1_106078_2023-11-17_final.stac-item
2023-11-18 10:00:34	ga_ls9c_ard_3-2-1_097076_2023-11-18_final.stac-item
2023-11-20 09:51:02	ga_ls9c_ard_3-2-1_095083_2023-11-20_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