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
2021-11-15 09:42:21	ga_ls9c_ard_3-2-1_094078_2021-11-15_final.stac-item
2021-11-20 11:21:53	ga_ls9c_ard_3-2-1_110074_2021-11-20_final.stac-item
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2022-01-28 11:10:13	ga_ls9c_ard_3-2-1_108080_2022-01-28_final.stac-item
2022-02-20 11:15:28	ga_ls9c_ard_3-2-1_109078_2022-02-20_final.stac-item
2022-03-22 09:49:35	ga_ls9c_ard_3-2-1_095080_2022-03-22_final.stac-item
2022-03-28 09:13:15	ga_ls9c_ard_3-2-1_089082_2022-03-27_final.stac-item
2022-04-02 11:08:41	ga_ls9c_ard_3-2-1_108077_2022-04-02_final.stac-item
2022-10-27 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-10-27_final.stac-item
2022-10-31 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-31_final.stac-item
2022-11-03 11:16:31	ga_ls9c_ard_3-2-1_109080_2022-11-03_final.stac-item
2022-11-08 09:56:13	ga_ls9c_ard_3-2-1_096080_2022-11-08_final.stac-item
2022-11-12 11:09:36	ga_ls9c_ard_3-2-1_108078_2022-11-12_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-11-19 11:16:35	ga_ls9c_ard_3-2-1_109080_2022-11-19_final.stac-item
2022-11-20 10:17:46	ga_ls9c_ard_3-2-1_100072_2022-11-20_final.stac-item
2022-11-21 11:04:13	ga_ls9c_ard_3-2-1_107080_2022-11-21_final.stac-item
2022-11-26 09:43:04	ga_ls9c_ard_3-2-1_094078_2022-11-26_final.stac-item
2022-11-28 11:09:34	ga_ls9c_ard_3-2-1_108078_2022-11-28_final.stac-item
2022-11-29 11:51:14	ga_ls9c_ard_3-2-1_115074_2022-11-29_final.stac-item
2022-12-03 11:28:30	ga_ls9c_ard_3-2-1_111079_2022-12-03_final.stac-item
2022-12-12 11:20:45	ga_ls9c_ard_3-2-1_110075_2022-12-12_final.stac-item
2022-12-19 11:28:54	ga_ls9c_ard_3-2-1_111080_2022-12-19_final.stac-item
2022-12-27 10:35:04	ga_ls9c_ard_3-2-1_103069_2022-12-27_final.stac-item
2022-12-28 09:43:03	ga_ls9c_ard_3-2-1_094078_2022-12-28_final.stac-item
2022-12-30 09:31:06	ga_ls9c_ard_3-2-1_092079_2022-12-30_final.stac-item
2022-12-31 10:14:22	ga_ls9c_ard_3-2-1_099079_2022-12-31_final.stac-item
2023-01-04 09:49:15	ga_ls9c_ard_3-2-1_095078_2023-01-04_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 10:37:04	ga_ls9c_ard_3-2-1_103074_2023-01-12_final.stac-item
2023-01-12 10:37:28	ga_ls9c_ard_3-2-1_103075_2023-01-12_final.stac-item
2023-01-20 09:49:29	ga_ls9c_ard_3-2-1_095079_2023-01-20_final.stac-item
2023-01-22 11:16:26	ga_ls9c_ard_3-2-1_109080_2023-01-22_final.stac-item
2023-01-23 10:20:50	ga_ls9c_ard_3-2-1_100080_2023-01-23_final.stac-item
2023-01-24 11:04:07	ga_ls9c_ard_3-2-1_107080_2023-01-24_final.stac-item
2023-01-28 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-28_final.stac-item
2023-01-29 11:20:20	ga_ls9c_ard_3-2-1_110074_2023-01-29_final.stac-item
2023-01-29 11:20:44	ga_ls9c_ard_3-2-1_110075_2023-01-29_final.stac-item
2023-01-29 11:22:20	ga_ls9c_ard_3-2-1_110079_2023-01-29_final.stac-item
2023-01-31 11:11:12	ga_ls9c_ard_3-2-1_108082_2023-01-31_final.stac-item
2023-02-05 09:49:18	ga_ls9c_ard_3-2-1_095078_2023-02-05_final.stac-item
2023-02-07 11:15:50	ga_ls9c_ard_3-2-1_109078_2023-02-07_final.stac-item
2023-02-08 10:18:13	ga_ls9c_ard_3-2-1_100073_2023-02-08_final.stac-item
2023-02-09 11:02:16	ga_ls9c_ard_3-2-1_107075_2023-02-09_final.stac-item
2023-04-23 10:53:01	ga_ls9c_ard_3-2-1_106069_2023-04-23_final.stac-item
2023-04-24 10:02:11	ga_ls9c_ard_3-2-1_097081_2023-04-24_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-04-26 09:49:24	ga_ls9c_ard_3-2-1_095080_2023-04-26_final.stac-item
2023-04-28 11:15:53	ga_ls9c_ard_3-2-1_109080_2023-04-28_final.stac-item
2023-05-28 09:47:52	ga_ls9c_ard_3-2-1_095077_2023-05-28_final.stac-item
2023-05-28 11:26:46	ga_ls9c_ard_3-2-1_111077_2023-05-28_final.stac-item
2023-07-05 10:50:32	ga_ls9c_ard_3-2-1_105079_2023-07-05_final.stac-item
2023-07-15 11:26:29	ga_ls9c_ard_3-2-1_111076_2023-07-15_final.stac-item
2023-07-15 11:27:17	ga_ls9c_ard_3-2-1_111078_2023-07-15_final.stac-item
2023-07-16 10:30:04	ga_ls9c_ard_3-2-1_102074_2023-07-16_final.stac-item
2023-07-16 10:33:16	ga_ls9c_ard_3-2-1_102082_2023-07-16_final.stac-item
2023-07-18 10:18:06	ga_ls9c_ard_3-2-1_100075_2023-07-18_final.stac-item
2023-07-19 11:03:22	ga_ls9c_ard_3-2-1_107080_2023-07-19_final.stac-item
2023-07-21 10:49:48	ga_ls9c_ard_3-2-1_105077_2023-07-21_final.stac-item
2023-07-21 10:50:36	ga_ls9c_ard_3-2-1_105079_2023-07-21_final.stac-item
2023-07-22 09:54:10	ga_ls9c_ard_3-2-1_096077_2023-07-22_final.stac-item
2023-07-22 09:55:22	ga_ls9c_ard_3-2-1_096080_2023-07-22_final.stac-item
2023-07-22 11:34:15	ga_ls9c_ard_3-2-1_112080_2023-07-22_final.stac-item
2023-07-23 10:36:14	ga_ls9c_ard_3-2-1_103074_2023-07-23_final.stac-item
2023-07-23 10:37:50	ga_ls9c_ard_3-2-1_103078_2023-07-23_final.stac-item
2023-07-25 10:24:15	ga_ls9c_ard_3-2-1_101075_2023-07-25_final.stac-item
2023-07-26 11:09:32	ga_ls9c_ard_3-2-1_108080_2023-07-26_final.stac-item
2023-07-26 11:10:20	ga_ls9c_ard_3-2-1_108082_2023-07-26_final.stac-item
2023-07-28 10:58:01	ga_ls9c_ard_3-2-1_106082_2023-07-28_final.stac-item
2023-08-02 09:36:33	ga_ls9c_ard_3-2-1_093079_2023-08-02_final.stac-item
2023-10-17 10:02:12	ga_ls9c_ard_3-2-1_097080_2023-10-17_final.stac-item
2023-10-18 10:43:04	ga_ls9c_ard_3-2-1_104074_2023-10-18_final.stac-item
2023-10-18 10:45:52	ga_ls9c_ard_3-2-1_104081_2023-10-18_final.stac-item
2023-10-19 11:25:56	ga_ls9c_ard_3-2-1_111073_2023-10-19_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-10-26 11:33:17	ga_ls9c_ard_3-2-1_112076_2023-10-26_final.stac-item
2023-10-26 11:34:29	ga_ls9c_ard_3-2-1_112079_2023-10-26_final.stac-item
2023-10-26 11:34:53	ga_ls9c_ard_3-2-1_112080_2023-10-26_final.stac-item
2023-10-27 10:39:15	ga_ls9c_ard_3-2-1_103080_2023-10-27_final.stac-item
2023-10-28 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-28_final.stac-item
2023-10-30 09:34:02	ga_ls9c_ard_3-2-1_092087_2023-10-30_final.stac-item
2023-10-30 11:10:07	ga_ls9c_ard_3-2-1_108080_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
2023-11-04 09:46:32	ga_ls9c_ard_3-2-1_095072_2023-11-04_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_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
2023-11-15 11:09:18	ga_ls9c_ard_3-2-1_108078_2023-11-15_final.stac-item
2023-11-16 10:14:53	ga_ls9c_ard_3-2-1_099081_2023-11-16_final.stac-item
2023-11-19 10:40:39	ga_ls9c_ard_3-2-1_104068_2023-11-19_final.stac-item
2023-11-19 10:41:03	ga_ls9c_ard_3-2-1_104069_2023-11-19_final.stac-item
2023-11-20 09:51:26	ga_ls9c_ard_3-2-1_095084_2023-11-20_final.stac-item
2023-11-22 09:37:30	ga_ls9c_ard_3-2-1_093080_2023-11-22_final.stac-item
2023-11-22 11:15:59	ga_ls9c_ard_3-2-1_109079_2023-11-22_final.stac-item
2023-11-22 11:16:23	ga_ls9c_ard_3-2-1_109080_2023-11-22_final.stac-item
2023-11-24 09:28:22	ga_ls9c_ard_3-2-1_091088_2023-11-23_final.stac-item
2023-11-24 11:04:03	ga_ls9c_ard_3-2-1_107080_2023-11-24_final.stac-item
2023-11-26 10:50:31	ga_ls9c_ard_3-2-1_105077_2023-11-26_final.stac-item
2023-11-27 11:34:34	ga_ls9c_ard_3-2-1_112079_2023-11-27_final.stac-item
2024-02-18 10:27:40	ga_ls9c_ard_3-2-1_101082_2024-02-18_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