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
2021-12-13 09:21:48	ga_ls9c_ard_3-2-1_090087_2021-12-12_final.stac-item
2022-01-19 09:35:06	ga_ls9c_ard_3-2-1_093074_2022-01-19_final.stac-item
2022-01-20 10:17:34	ga_ls9c_ard_3-2-1_100072_2022-01-20_final.stac-item
2022-02-19 10:30:13	ga_ls9c_ard_3-2-1_102073_2022-02-19_final.stac-item
2022-03-07 10:30:06	ga_ls9c_ard_3-2-1_102073_2022-03-07_final.stac-item
2022-03-09 10:17:20	ga_ls9c_ard_3-2-1_100072_2022-03-09_final.stac-item
2022-03-12 10:52:13	ga_ls9c_ard_3-2-1_105082_2022-03-12_final.stac-item
2022-04-09 09:37:33	ga_ls9c_ard_3-2-1_093081_2022-04-09_final.stac-item
2022-04-16 09:40:27	ga_ls9c_ard_3-2-1_094073_2022-04-16_final.stac-item
2022-05-10 10:33:19	ga_ls9c_ard_3-2-1_102082_2022-05-10_final.stac-item
2022-06-07 10:54:19	ga_ls9c_ard_3-2-1_106073_2022-06-07_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-06-30 09:23:33	ga_ls9c_ard_3-2-1_091077_2022-06-29_final.stac-item
2022-07-16 09:24:41	ga_ls9c_ard_3-2-1_091080_2022-07-15_final.stac-item
2022-07-23 09:29:00	ga_ls9c_ard_3-2-1_092075_2022-07-22_final.stac-item
2022-07-25 10:54:45	ga_ls9c_ard_3-2-1_106073_2022-07-25_final.stac-item
2022-08-03 09:13:48	ga_ls9c_ard_3-2-1_089083_2022-08-02_final.stac-item
2022-08-05 10:39:33	ga_ls9c_ard_3-2-1_103081_2022-08-05_final.stac-item
2022-08-16 10:21:54	ga_ls9c_ard_3-2-1_100083_2022-08-16_final.stac-item
2022-08-17 11:01:34	ga_ls9c_ard_3-2-1_107074_2022-08-17_final.stac-item
2022-09-06 10:34:52	ga_ls9c_ard_3-2-1_103069_2022-09-06_final.stac-item
2022-09-27 10:54:21	ga_ls9c_ard_3-2-1_106071_2022-09-27_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_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 10:09:56	ga_ls9c_ard_3-2-1_099068_2022-10-12_final.stac-item
2022-10-21 10:07:48	ga_ls9c_ard_3-2-1_098078_2022-10-21_final.stac-item
2022-10-21 11:47:53	ga_ls9c_ard_3-2-1_114081_2022-10-21_final.stac-item
2022-11-17 09:50:52	ga_ls9c_ard_3-2-1_095082_2022-11-17_final.stac-item
2022-11-24 09:57:50	ga_ls9c_ard_3-2-1_096084_2022-11-24_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-10 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-12-10_final.stac-item
2022-12-10 09:58:37	ga_ls9c_ard_3-2-1_096086_2022-12-10_final.stac-item
2022-12-10 11:35:54	ga_ls9c_ard_3-2-1_112082_2022-12-10_final.stac-item
2022-12-14 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-14_final.stac-item
2022-12-23 11:04:33	ga_ls9c_ard_3-2-1_107081_2022-12-23_final.stac-item
2022-12-31 10:13:58	ga_ls9c_ard_3-2-1_099078_2022-12-31_final.stac-item
2023-01-09 10:05:23	ga_ls9c_ard_3-2-1_098072_2023-01-09_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-12 10:36:40	ga_ls9c_ard_3-2-1_103073_2023-01-12_final.stac-item
2023-01-15 11:05:56	ga_ls9c_ard_3-2-1_108069_2023-01-15_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_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 11:30:22	ga_ls9c_ard_3-2-1_111084_2023-01-20_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-04 09:07:14	ga_ls9c_ard_3-2-1_088081_2023-02-03_final.stac-item
2023-02-09 09:29:23	ga_ls9c_ard_3-2-1_091090_2023-02-08_final.stac-item
2023-04-24 10:03:23	ga_ls9c_ard_3-2-1_097084_2023-04-24_final.stac-item
2023-04-26 11:28:41	ga_ls9c_ard_3-2-1_111081_2023-04-26_final.stac-item
2023-04-27 10:29:51	ga_ls9c_ard_3-2-1_102073_2023-04-27_final.stac-item
2023-04-30 09:25:49	ga_ls9c_ard_3-2-1_091083_2023-04-29_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-18 10:18:30	ga_ls9c_ard_3-2-1_100076_2023-07-18_final.stac-item
2023-07-19 11:04:34	ga_ls9c_ard_3-2-1_107083_2023-07-19_final.stac-item
2023-07-20 10:04:09	ga_ls9c_ard_3-2-1_098071_2023-07-20_final.stac-item
2023-07-21 09:10:55	ga_ls9c_ard_3-2-1_089077_2023-07-20_final.stac-item
2023-07-22 09:57:22	ga_ls9c_ard_3-2-1_096085_2023-07-22_final.stac-item
2023-07-24 11:18:41	ga_ls9c_ard_3-2-1_110072_2023-07-24_final.stac-item
2023-07-24 11:20:17	ga_ls9c_ard_3-2-1_110076_2023-07-24_final.stac-item
2023-07-26 09:28:39	ga_ls9c_ard_3-2-1_092075_2023-07-25_final.stac-item
2023-07-26 09:32:39	ga_ls9c_ard_3-2-1_092085_2023-07-26_final.stac-item
2023-07-28 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-07-27_final.stac-item
2023-07-28 10:57:13	ga_ls9c_ard_3-2-1_106080_2023-07-28_final.stac-item
2023-07-29 11:40:54	ga_ls9c_ard_3-2-1_113081_2023-07-29_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-04 11:04:41	ga_ls9c_ard_3-2-1_107083_2023-08-04_final.stac-item
2023-08-05 10:04:17	ga_ls9c_ard_3-2-1_098071_2023-08-05_final.stac-item
2023-10-14 11:06:34	ga_ls9c_ard_3-2-1_108071_2023-10-14_final.stac-item
2023-10-14 11:07:22	ga_ls9c_ard_3-2-1_108073_2023-10-14_final.stac-item
2023-10-15 10:15:45	ga_ls9c_ard_3-2-1_099083_2023-10-15_final.stac-item
2023-10-16 09:20:56	ga_ls9c_ard_3-2-1_090085_2023-10-15_final.stac-item
2023-10-16 10:55:01	ga_ls9c_ard_3-2-1_106073_2023-10-16_final.stac-item
2023-10-20 10:28:43	ga_ls9c_ard_3-2-1_102069_2023-10-20_final.stac-item
2023-10-22 10:21:56	ga_ls9c_ard_3-2-1_100083_2023-10-22_final.stac-item
2023-10-23 11:04:48	ga_ls9c_ard_3-2-1_107082_2023-10-23_final.stac-item
2023-10-25 10:48:50	ga_ls9c_ard_3-2-1_105073_2023-10-25_final.stac-item
2023-10-27 10:34:28	ga_ls9c_ard_3-2-1_103068_2023-10-27_final.stac-item
2023-10-30 09:33:38	ga_ls9c_ard_3-2-1_092086_2023-10-30_final.stac-item
2023-10-30 11:07:19	ga_ls9c_ard_3-2-1_108073_2023-10-30_final.stac-item
2023-10-31 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-10-31_final.stac-item
2023-11-01 10:54:08	ga_ls9c_ard_3-2-1_106071_2023-11-01_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-04 09:46:56	ga_ls9c_ard_3-2-1_095073_2023-11-04_final.stac-item
2023-11-15 09:31:13	ga_ls9c_ard_3-2-1_092080_2023-11-15_final.stac-item
2023-11-15 11:06:31	ga_ls9c_ard_3-2-1_108071_2023-11-15_final.stac-item
2023-11-16 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-11-16_final.stac-item
2023-11-16 10:15:41	ga_ls9c_ard_3-2-1_099083_2023-11-16_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-16 11:52:34	ga_ls9c_ard_3-2-1_115078_2023-11-16_final.stac-item
2023-11-17 09:22:29	ga_ls9c_ard_3-2-1_090089_2023-11-16_final.stac-item
2023-11-17 10:53:23	ga_ls9c_ard_3-2-1_106069_2023-11-17_final.stac-item
2023-11-17 10:53:47	ga_ls9c_ard_3-2-1_106070_2023-11-17_final.stac-item
2023-11-18 09:57:46	ga_ls9c_ard_3-2-1_097069_2023-11-18_final.stac-item
2023-11-19 09:06:57	ga_ls9c_ard_3-2-1_088081_2023-11-18_final.stac-item
2023-11-20 09:46:39	ga_ls9c_ard_3-2-1_095072_2023-11-20_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_final.stac-item
2023-11-25 10:03:39	ga_ls9c_ard_3-2-1_098068_2023-11-25_final.stac-item
2023-11-25 10:04:27	ga_ls9c_ard_3-2-1_098070_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