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
2021-11-10 09:37:06	ga_ls9c_ard_3-2-1_094071_2021-11-10_final.stac-item
2021-11-12 10:57:01	ga_ls9c_ard_3-2-1_106071_2021-11-12_final.stac-item
2021-11-20 11:23:05	ga_ls9c_ard_3-2-1_110077_2021-11-20_final.stac-item
2021-12-22 09:11:36	ga_ls9c_ard_3-2-1_089077_2021-12-21_final.stac-item
2021-12-24 10:39:44	ga_ls9c_ard_3-2-1_103081_2021-12-24_final.stac-item
2022-01-06 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-06_final.stac-item
2022-01-08 09:58:02	ga_ls9c_ard_3-2-1_096085_2022-01-08_final.stac-item
2022-01-15 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-01-15_final.stac-item
2022-01-17 11:26:20	ga_ls9c_ard_3-2-1_111074_2022-01-17_final.stac-item
2022-01-28 11:06:13	ga_ls9c_ard_3-2-1_108070_2022-01-28_final.stac-item
2022-02-04 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-02-04_final.stac-item
2022-02-14 10:14:32	ga_ls9c_ard_3-2-1_099080_2022-02-14_final.stac-item
2022-02-20 09:39:23	ga_ls9c_ard_3-2-1_093085_2022-02-20_final.stac-item
2022-03-27 11:46:58	ga_ls9c_ard_3-2-1_114080_2022-03-27_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-11 09:21:58	ga_ls9c_ard_3-2-1_091073_2022-04-10_final.stac-item
2022-04-18 11:07:45	ga_ls9c_ard_3-2-1_108075_2022-04-18_final.stac-item
2022-04-27 09:28:13	ga_ls9c_ard_3-2-1_091089_2022-04-26_final.stac-item
2022-04-29 09:15:51	ga_ls9c_ard_3-2-1_089089_2022-04-28_final.stac-item
2022-04-30 09:51:32	ga_ls9c_ard_3-2-1_096070_2022-04-30_final.stac-item
2022-05-20 11:07:03	ga_ls9c_ard_3-2-1_108074_2022-05-20_final.stac-item
2022-06-08 09:57:30	ga_ls9c_ard_3-2-1_097070_2022-06-08_final.stac-item
2022-06-09 09:06:40	ga_ls9c_ard_3-2-1_088082_2022-06-08_final.stac-item
2022-06-19 11:23:11	ga_ls9c_ard_3-2-1_110083_2022-06-19_final.stac-item
2022-06-25 09:06:13	ga_ls9c_ard_3-2-1_088080_2022-06-24_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-07-25 10:55:57	ga_ls9c_ard_3-2-1_106076_2022-07-25_final.stac-item
2022-08-11 09:57:44	ga_ls9c_ard_3-2-1_097069_2022-08-11_final.stac-item
2022-08-20 11:32:29	ga_ls9c_ard_3-2-1_112074_2022-08-20_final.stac-item
2022-08-21 10:34:28	ga_ls9c_ard_3-2-1_103068_2022-08-21_final.stac-item
2022-09-02 11:00:00	ga_ls9c_ard_3-2-1_107070_2022-09-02_final.stac-item
2022-09-10 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-09-10_final.stac-item
2022-09-13 09:07:24	ga_ls9c_ard_3-2-1_088082_2022-09-12_final.stac-item
2022-09-28 10:04:19	ga_ls9c_ard_3-2-1_097085_2022-09-28_final.stac-item
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_final.stac-item
2022-10-04 09:22:26	ga_ls9c_ard_3-2-1_091073_2022-10-03_final.stac-item
2022-10-05 10:03:42	ga_ls9c_ard_3-2-1_098068_2022-10-05_final.stac-item
2022-10-06 10:49:45	ga_ls9c_ard_3-2-1_105075_2022-10-06_final.stac-item
2022-10-19 10:17:45	ga_ls9c_ard_3-2-1_100072_2022-10-19_final.stac-item
2022-10-21 10:04:36	ga_ls9c_ard_3-2-1_098070_2022-10-21_final.stac-item
2022-10-21 10:07:48	ga_ls9c_ard_3-2-1_098078_2022-10-21_final.stac-item
2022-11-13 10:16:23	ga_ls9c_ard_3-2-1_099084_2022-11-13_final.stac-item
2022-11-18 10:29:20	ga_ls9c_ard_3-2-1_102070_2022-11-18_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-11-23 10:49:04	ga_ls9c_ard_3-2-1_105073_2022-11-23_final.stac-item
2022-11-24 11:36:19	ga_ls9c_ard_3-2-1_112083_2022-11-24_final.stac-item
2023-01-13 11:19:31	ga_ls9c_ard_3-2-1_110072_2023-01-13_final.stac-item
2023-01-19 09:07:27	ga_ls9c_ard_3-2-1_088082_2023-01-18_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-02-03 11:38:56	ga_ls9c_ard_3-2-1_113074_2023-02-03_final.stac-item
2023-02-09 11:00:41	ga_ls9c_ard_3-2-1_107071_2023-02-09_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-02-23 09:39:31	ga_ls9c_ard_3-2-1_093085_2023-02-23_final.stac-item
2023-03-02 11:23:21	ga_ls9c_ard_3-2-1_110082_2023-03-02_final.stac-item
2023-03-05 10:14:32	ga_ls9c_ard_3-2-1_099080_2023-03-05_final.stac-item
2023-03-06 09:22:30	ga_ls9c_ard_3-2-1_090089_2023-03-05_final.stac-item
2023-03-13 09:23:26	ga_ls9c_ard_3-2-1_091076_2023-03-12_final.stac-item
2023-03-21 10:15:38	ga_ls9c_ard_3-2-1_099083_2023-03-21_final.stac-item
2023-03-21 11:53:19	ga_ls9c_ard_3-2-1_115080_2023-03-21_final.stac-item
2023-04-05 09:34:12	ga_ls9c_ard_3-2-1_092088_2023-04-05_final.stac-item
2023-04-07 10:58:43	ga_ls9c_ard_3-2-1_106083_2023-04-07_final.stac-item
2023-04-15 10:06:47	ga_ls9c_ard_3-2-1_098077_2023-04-15_final.stac-item
2023-04-16 09:10:22	ga_ls9c_ard_3-2-1_089075_2023-04-15_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-04-26 09:51:48	ga_ls9c_ard_3-2-1_095086_2023-04-26_final.stac-item
2023-06-13 09:51:45	ga_ls9c_ard_3-2-1_095087_2023-06-13_final.stac-item
2023-06-18 10:02:40	ga_ls9c_ard_3-2-1_098068_2023-06-18_final.stac-item
2023-06-29 11:25:06	ga_ls9c_ard_3-2-1_111073_2023-06-29_final.stac-item
2023-07-04 10:04:04	ga_ls9c_ard_3-2-1_098071_2023-07-04_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-07-08 11:23:27	ga_ls9c_ard_3-2-1_110084_2023-07-08_final.stac-item
2023-07-13 11:38:03	ga_ls9c_ard_3-2-1_113074_2023-07-13_final.stac-item
2023-07-15 09:46:24	ga_ls9c_ard_3-2-1_095073_2023-07-15_final.stac-item
2023-07-28 09:17:08	ga_ls9c_ard_3-2-1_090077_2023-07-27_final.stac-item
2023-08-18 09:40:11	ga_ls9c_ard_3-2-1_093088_2023-08-18_final.stac-item
2023-09-01 09:46:21	ga_ls9c_ard_3-2-1_095072_2023-09-01_final.stac-item
2023-09-06 10:06:56	ga_ls9c_ard_3-2-1_098077_2023-09-06_final.stac-item
2023-09-26 11:19:07	ga_ls9c_ard_3-2-1_110072_2023-09-26_final.stac-item
2023-10-18 10:42:40	ga_ls9c_ard_3-2-1_104073_2023-10-18_final.stac-item
2023-10-26 11:32:29	ga_ls9c_ard_3-2-1_112074_2023-10-26_final.stac-item
2023-10-31 10:09:18	ga_ls9c_ard_3-2-1_099067_2023-10-31_final.stac-item
2023-11-02 09:57:42	ga_ls9c_ard_3-2-1_097069_2023-11-02_final.stac-item
2023-11-13 11:20:29	ga_ls9c_ard_3-2-1_110075_2023-11-13_final.stac-item
2023-11-14 10:25:39	ga_ls9c_ard_3-2-1_101077_2023-11-14_final.stac-item
2023-11-16 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-11-16_final.stac-item
2023-11-26 10:46:55	ga_ls9c_ard_3-2-1_105068_2023-11-26_final.stac-item
2023-11-26 10:50:31	ga_ls9c_ard_3-2-1_105077_2023-11-26_final.stac-item
2023-12-04 09:58:14	ga_ls9c_ard_3-2-1_097070_2023-12-04_final.stac-item
2023-12-10 09:23:56	ga_ls9c_ard_3-2-1_091077_2023-12-09_final.stac-item
2023-12-15 11:20:13	ga_ls9c_ard_3-2-1_110074_2023-12-15_final.stac-item
2023-12-17 09:34:10	ga_ls9c_ard_3-2-1_092087_2023-12-17_final.stac-item
2023-12-18 11:51:32	ga_ls9c_ard_3-2-1_115075_2023-12-18_final.stac-item
2023-12-19 10:57:55	ga_ls9c_ard_3-2-1_106080_2023-12-19_final.stac-item
2023-12-28 09:16:50	ga_ls9c_ard_3-2-1_089090_2023-12-27_final.stac-item
2024-01-11 11:02:26	ga_ls9c_ard_3-2-1_107076_2024-01-11_final.stac-item
2024-01-13 09:12:48	ga_ls9c_ard_3-2-1_089080_2024-01-12_final.stac-item
2024-01-19 10:14:11	ga_ls9c_ard_3-2-1_099079_2024-01-19_final.stac-item
2024-02-04 11:53:07	ga_ls9c_ard_3-2-1_115079_2024-02-04_final.stac-item
2024-02-05 10:55:30	ga_ls9c_ard_3-2-1_106074_2024-02-05_final.stac-item
2024-02-15 09:58:25	ga_ls9c_ard_3-2-1_096086_2024-02-15_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