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 10:59:20	ga_ls9c_ard_3-2-1_106083_2021-11-07_final.stac-item
2021-11-19 10:39:32	ga_ls9c_ard_3-2-1_104068_2021-11-19_final.stac-item
2021-12-29 09:22:59	ga_ls9c_ard_3-2-1_090090_2021-12-28_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-01-22 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-22_final.stac-item
2022-02-03 10:29:32	ga_ls9c_ard_3-2-1_102071_2022-02-03_final.stac-item
2022-02-07 11:44:53	ga_ls9c_ard_3-2-1_114074_2022-02-07_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-03-03 10:58:48	ga_ls9c_ard_3-2-1_106083_2022-03-03_final.stac-item
2022-03-12 09:12:33	ga_ls9c_ard_3-2-1_089080_2022-03-11_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-04-19 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-04-19_final.stac-item
2022-04-30 09:51:32	ga_ls9c_ard_3-2-1_096070_2022-04-30_final.stac-item
2022-05-15 10:46:12	ga_ls9c_ard_3-2-1_105068_2022-05-15_final.stac-item
2022-05-18 09:39:22	ga_ls9c_ard_3-2-1_094071_2022-05-18_final.stac-item
2022-05-31 10:46:08	ga_ls9c_ard_3-2-1_105068_2022-05-31_final.stac-item
2022-07-11 09:06:09	ga_ls9c_ard_3-2-1_088080_2022-07-10_final.stac-item
2022-07-11 10:42:15	ga_ls9c_ard_3-2-1_104073_2022-07-11_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-07-21 09:45:43	ga_ls9c_ard_3-2-1_094086_2022-07-21_final.stac-item
2022-07-27 09:06:20	ga_ls9c_ard_3-2-1_088080_2022-07-26_final.stac-item
2022-08-01 10:59:50	ga_ls9c_ard_3-2-1_107070_2022-08-01_final.stac-item
2022-08-08 11:11:41	ga_ls9c_ard_3-2-1_108084_2022-08-08_final.stac-item
2022-08-09 11:51:21	ga_ls9c_ard_3-2-1_115075_2022-08-09_final.stac-item
2022-08-15 09:39:02	ga_ls9c_ard_3-2-1_093084_2022-08-15_final.stac-item
2022-08-17 09:22:17	ga_ls9c_ard_3-2-1_091073_2022-08-16_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-09-02 09:22:19	ga_ls9c_ard_3-2-1_091073_2022-09-01_final.stac-item
2022-09-26 10:09:29	ga_ls9c_ard_3-2-1_099067_2022-09-26_final.stac-item
2022-09-26 10:11:05	ga_ls9c_ard_3-2-1_099071_2022-09-26_final.stac-item
2022-10-01 10:28:26	ga_ls9c_ard_3-2-1_102068_2022-10-01_final.stac-item
2022-10-05 10:03:42	ga_ls9c_ard_3-2-1_098068_2022-10-05_final.stac-item
2022-10-05 10:04:54	ga_ls9c_ard_3-2-1_098071_2022-10-05_final.stac-item
2022-10-11 09:33:27	ga_ls9c_ard_3-2-1_092085_2022-10-11_final.stac-item
2022-10-12 10:09:56	ga_ls9c_ard_3-2-1_099068_2022-10-12_final.stac-item
2022-10-12 10:11:32	ga_ls9c_ard_3-2-1_099072_2022-10-12_final.stac-item
2022-10-24 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-10-24_final.stac-item
2022-10-29 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-10-29_final.stac-item
2022-11-05 09:29:17	ga_ls9c_ard_3-2-1_091090_2022-11-04_final.stac-item
2022-11-06 10:07:46	ga_ls9c_ard_3-2-1_098078_2022-11-06_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_final.stac-item
2022-12-06 10:19:20	ga_ls9c_ard_3-2-1_100076_2022-12-06_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-10 09:52:38	ga_ls9c_ard_3-2-1_096071_2022-12-10_final.stac-item
2022-12-19 11:26:31	ga_ls9c_ard_3-2-1_111074_2022-12-19_final.stac-item
2022-12-23 09:27:16	ga_ls9c_ard_3-2-1_091085_2022-12-22_final.stac-item
2022-12-26 11:32:41	ga_ls9c_ard_3-2-1_112074_2022-12-26_final.stac-item
2023-01-08 11:01:01	ga_ls9c_ard_3-2-1_107072_2023-01-08_final.stac-item
2023-01-09 10:05:23	ga_ls9c_ard_3-2-1_098072_2023-01-09_final.stac-item
2023-01-09 10:10:35	ga_ls9c_ard_3-2-1_098085_2023-01-09_final.stac-item
2023-01-10 10:50:14	ga_ls9c_ard_3-2-1_105076_2023-01-10_final.stac-item
2023-01-22 09:38:44	ga_ls9c_ard_3-2-1_093083_2023-01-22_final.stac-item
2023-01-23 10:17:14	ga_ls9c_ard_3-2-1_100071_2023-01-23_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-02-01 10:16:47	ga_ls9c_ard_3-2-1_099085_2023-02-01_final.stac-item
2023-02-02 09:21:10	ga_ls9c_ard_3-2-1_090085_2023-02-01_final.stac-item
2023-02-03 09:58:03	ga_ls9c_ard_3-2-1_097069_2023-02-03_final.stac-item
2023-02-03 09:58:27	ga_ls9c_ard_3-2-1_097070_2023-02-03_final.stac-item
2023-02-12 11:32:46	ga_ls9c_ard_3-2-1_112074_2023-02-12_final.stac-item
2023-02-14 09:41:30	ga_ls9c_ard_3-2-1_094074_2023-02-14_final.stac-item
2023-02-18 10:54:24	ga_ls9c_ard_3-2-1_106071_2023-02-18_final.stac-item
2023-03-15 10:47:34	ga_ls9c_ard_3-2-1_105070_2023-03-15_final.stac-item
2023-03-21 11:53:19	ga_ls9c_ard_3-2-1_115080_2023-03-21_final.stac-item
2023-03-22 10:53:17	ga_ls9c_ard_3-2-1_106069_2023-03-22_final.stac-item
2023-04-08 09:57:54	ga_ls9c_ard_3-2-1_097070_2023-04-08_final.stac-item
2023-04-09 09:07:27	ga_ls9c_ard_3-2-1_088083_2023-04-08_final.stac-item
2023-04-12 11:12:01	ga_ls9c_ard_3-2-1_109070_2023-04-12_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 09:20:56	ga_ls9c_ard_3-2-1_090086_2023-04-22_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-05-11 09:06:23	ga_ls9c_ard_3-2-1_088081_2023-05-10_final.stac-item
2023-05-18 09:11:18	ga_ls9c_ard_3-2-1_089078_2023-05-17_final.stac-item
2023-05-23 09:27:22	ga_ls9c_ard_3-2-1_092072_2023-05-22_final.stac-item
2023-05-23 09:32:57	ga_ls9c_ard_3-2-1_092086_2023-05-23_final.stac-item
2023-05-25 09:16:34	ga_ls9c_ard_3-2-1_090076_2023-05-24_final.stac-item
2023-05-25 10:55:27	ga_ls9c_ard_3-2-1_106076_2023-05-25_final.stac-item
2023-05-26 09:57:26	ga_ls9c_ard_3-2-1_097070_2023-05-26_final.stac-item
2023-05-27 09:06:13	ga_ls9c_ard_3-2-1_088081_2023-05-26_final.stac-item
2023-06-19 09:10:39	ga_ls9c_ard_3-2-1_089077_2023-06-18_final.stac-item
2023-06-30 10:27:31	ga_ls9c_ard_3-2-1_102068_2023-06-30_final.stac-item
2023-07-01 11:13:36	ga_ls9c_ard_3-2-1_109075_2023-07-01_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-05 09:12:02	ga_ls9c_ard_3-2-1_089080_2023-07-04_final.stac-item
2023-07-05 09:14:26	ga_ls9c_ard_3-2-1_089086_2023-07-04_final.stac-item
2023-07-08 09:45:22	ga_ls9c_ard_3-2-1_094086_2023-07-08_final.stac-item
2023-07-08 11:22:39	ga_ls9c_ard_3-2-1_110082_2023-07-08_final.stac-item
2023-07-10 09:28:14	ga_ls9c_ard_3-2-1_092074_2023-07-09_final.stac-item
2023-09-04 10:16:52	ga_ls9c_ard_3-2-1_100071_2023-09-04_final.stac-item
2023-09-19 09:34:07	ga_ls9c_ard_3-2-1_093072_2023-09-19_final.stac-item
2023-09-21 09:26:32	ga_ls9c_ard_3-2-1_091084_2023-09-20_final.stac-item
2023-09-22 10:07:24	ga_ls9c_ard_3-2-1_098078_2023-09-22_final.stac-item
2023-09-23 10:46:16	ga_ls9c_ard_3-2-1_105067_2023-09-23_final.stac-item
2023-09-23 10:49:51	ga_ls9c_ard_3-2-1_105076_2023-09-23_final.stac-item
2023-09-27 10:25:29	ga_ls9c_ard_3-2-1_101077_2023-09-27_final.stac-item
2023-10-07 09:26:36	ga_ls9c_ard_3-2-1_091084_2023-10-06_final.stac-item
2023-10-11 10:39:37	ga_ls9c_ard_3-2-1_103081_2023-10-11_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years