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
2021-11-18 11:40:38	ga_ls9c_ard_3-2-1_113074_2021-11-18_final.stac-item
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-20 09:23:10	ga_ls9c_ard_3-2-1_091075_2021-12-19_final.stac-item
2021-12-25 11:21:00	ga_ls9c_ard_3-2-1_110076_2021-12-25_final.stac-item
2021-12-29 09:18:11	ga_ls9c_ard_3-2-1_090078_2021-12-28_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-17 09:46:39	ga_ls9c_ard_3-2-1_095072_2022-01-17_final.stac-item
2022-01-29 10:14:36	ga_ls9c_ard_3-2-1_099080_2022-01-29_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-05 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-02-05_final.stac-item
2022-02-08 10:52:27	ga_ls9c_ard_3-2-1_105082_2022-02-08_final.stac-item
2022-02-10 10:34:29	ga_ls9c_ard_3-2-1_103068_2022-02-10_final.stac-item
2022-02-10 10:39:41	ga_ls9c_ard_3-2-1_103081_2022-02-10_final.stac-item
2022-02-17 09:07:19	ga_ls9c_ard_3-2-1_088082_2022-02-16_final.stac-item
2022-03-12 10:47:02	ga_ls9c_ard_3-2-1_105069_2022-03-12_final.stac-item
2022-04-03 10:09:52	ga_ls9c_ard_3-2-1_099069_2022-04-03_final.stac-item
2022-04-05 09:57:06	ga_ls9c_ard_3-2-1_097068_2022-04-05_final.stac-item
2022-04-07 11:25:37	ga_ls9c_ard_3-2-1_111073_2022-04-07_final.stac-item
2022-04-15 10:35:42	ga_ls9c_ard_3-2-1_103072_2022-04-15_final.stac-item
2022-04-29 09:11:52	ga_ls9c_ard_3-2-1_089079_2022-04-28_final.stac-item
2022-05-01 10:35:35	ga_ls9c_ard_3-2-1_103072_2022-05-01_final.stac-item
2022-05-04 09:32:22	ga_ls9c_ard_3-2-1_092084_2022-05-04_final.stac-item
2022-05-06 09:20:24	ga_ls9c_ard_3-2-1_090085_2022-05-05_final.stac-item
2022-05-07 11:38:08	ga_ls9c_ard_3-2-1_113074_2022-05-07_final.stac-item
2022-05-08 09:07:13	ga_ls9c_ard_3-2-1_088083_2022-05-07_final.stac-item
2022-05-11 11:17:22	ga_ls9c_ard_3-2-1_109084_2022-05-11_final.stac-item
2022-05-29 09:22:24	ga_ls9c_ard_3-2-1_091075_2022-05-28_final.stac-item
2022-05-29 09:27:11	ga_ls9c_ard_3-2-1_091087_2022-05-28_final.stac-item
2022-06-05 09:28:12	ga_ls9c_ard_3-2-1_092074_2022-06-04_final.stac-item
2022-06-06 10:15:27	ga_ls9c_ard_3-2-1_099084_2022-06-06_final.stac-item
2022-06-10 11:25:38	ga_ls9c_ard_3-2-1_111074_2022-06-10_final.stac-item
2022-06-14 10:59:22	ga_ls9c_ard_3-2-1_107070_2022-06-14_final.stac-item
2022-06-23 10:52:37	ga_ls9c_ard_3-2-1_106068_2022-06-23_final.stac-item
2022-07-08 11:51:27	ga_ls9c_ard_3-2-1_115076_2022-07-08_final.stac-item
2022-07-12 11:23:54	ga_ls9c_ard_3-2-1_111069_2022-07-12_final.stac-item
2022-07-12 11:25:54	ga_ls9c_ard_3-2-1_111074_2022-07-12_final.stac-item
2022-07-19 09:57:39	ga_ls9c_ard_3-2-1_096085_2022-07-19_final.stac-item
2022-07-21 09:46:07	ga_ls9c_ard_3-2-1_094087_2022-07-21_final.stac-item
2022-07-30 09:35:17	ga_ls9c_ard_3-2-1_093075_2022-07-30_final.stac-item
2022-07-30 09:39:16	ga_ls9c_ard_3-2-1_093085_2022-07-30_final.stac-item
2022-08-06 11:20:25	ga_ls9c_ard_3-2-1_110075_2022-08-06_final.stac-item
2022-08-18 10:04:45	ga_ls9c_ard_3-2-1_098071_2022-08-18_final.stac-item
2022-08-25 10:10:33	ga_ls9c_ard_3-2-1_099070_2022-08-25_final.stac-item
2022-09-02 09:27:30	ga_ls9c_ard_3-2-1_091086_2022-09-01_final.stac-item
2022-09-07 11:20:08	ga_ls9c_ard_3-2-1_110074_2022-09-07_final.stac-item
2022-09-10 10:10:57	ga_ls9c_ard_3-2-1_099071_2022-09-10_final.stac-item
2022-09-11 10:53:02	ga_ls9c_ard_3-2-1_106068_2022-09-11_final.stac-item
2022-09-25 09:29:25	ga_ls9c_ard_3-2-1_092075_2022-09-24_final.stac-item
2022-09-25 11:07:54	ga_ls9c_ard_3-2-1_108074_2022-09-25_final.stac-item
2022-10-11 11:11:32	ga_ls9c_ard_3-2-1_108083_2022-10-11_final.stac-item
2022-10-22 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-10-22_final.stac-item
2022-10-28 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-10-28_final.stac-item
2022-10-30 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-30_final.stac-item
2022-11-04 10:17:18	ga_ls9c_ard_3-2-1_100071_2022-11-04_final.stac-item
2022-11-22 10:07:00	ga_ls9c_ard_3-2-1_098076_2022-11-22_final.stac-item
2022-11-26 09:40:16	ga_ls9c_ard_3-2-1_094071_2022-11-26_final.stac-item
2022-12-03 11:26:06	ga_ls9c_ard_3-2-1_111073_2022-12-03_final.stac-item
2022-12-05 11:14:09	ga_ls9c_ard_3-2-1_109074_2022-12-05_final.stac-item
2022-12-07 09:28:07	ga_ls9c_ard_3-2-1_091087_2022-12-06_final.stac-item
2022-12-15 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-12-15_final.stac-item
2022-12-28 09:41:27	ga_ls9c_ard_3-2-1_094074_2022-12-28_final.stac-item
2023-01-01 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-12-31_final.stac-item
2023-01-05 10:29:19	ga_ls9c_ard_3-2-1_102070_2023-01-05_final.stac-item
2023-01-11 11:36:41	ga_ls9c_ard_3-2-1_112084_2023-01-11_final.stac-item
2023-01-25 10:03:43	ga_ls9c_ard_3-2-1_098068_2023-01-25_final.stac-item
2023-01-25 10:04:07	ga_ls9c_ard_3-2-1_098069_2023-01-25_final.stac-item
2023-01-31 09:29:55	ga_ls9c_ard_3-2-1_092076_2023-01-30_final.stac-item
2023-01-31 09:30:19	ga_ls9c_ard_3-2-1_092077_2023-01-31_final.stac-item
2023-02-12 11:32:46	ga_ls9c_ard_3-2-1_112074_2023-02-12_final.stac-item
2023-02-16 09:29:30	ga_ls9c_ard_3-2-1_092075_2023-02-15_final.stac-item
2023-02-19 09:57:09	ga_ls9c_ard_3-2-1_097067_2023-02-19_final.stac-item
2023-02-20 10:41:11	ga_ls9c_ard_3-2-1_104069_2023-02-20_final.stac-item
2023-02-20 10:46:23	ga_ls9c_ard_3-2-1_104082_2023-02-20_final.stac-item
2023-03-01 10:37:42	ga_ls9c_ard_3-2-1_103076_2023-03-01_final.stac-item
2023-03-04 11:07:47	ga_ls9c_ard_3-2-1_108074_2023-03-04_final.stac-item
2023-03-05 10:14:08	ga_ls9c_ard_3-2-1_099079_2023-03-05_final.stac-item
2023-03-17 10:35:12	ga_ls9c_ard_3-2-1_103070_2023-03-17_final.stac-item
2023-03-27 11:12:32	ga_ls9c_ard_3-2-1_109071_2023-03-27_final.stac-item
2023-04-05 11:07:30	ga_ls9c_ard_3-2-1_108074_2023-04-05_final.stac-item
2023-04-14 11:03:37	ga_ls9c_ard_3-2-1_107080_2023-04-14_final.stac-item
2023-04-25 10:45:50	ga_ls9c_ard_3-2-1_104082_2023-04-25_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-05-08 10:09:59	ga_ls9c_ard_3-2-1_099070_2023-05-08_final.stac-item
2023-06-10 09:21:41	ga_ls9c_ard_3-2-1_090089_2023-06-09_final.stac-item
2023-06-27 11:41:24	ga_ls9c_ard_3-2-1_113083_2023-06-27_final.stac-item
2023-07-08 09:39:23	ga_ls9c_ard_3-2-1_094071_2023-07-08_final.stac-item
2023-07-19 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-07-18_final.stac-item
2023-07-22 11:31:52	ga_ls9c_ard_3-2-1_112074_2023-07-22_final.stac-item
2023-07-26 11:06:45	ga_ls9c_ard_3-2-1_108073_2023-07-26_final.stac-item
2023-07-31 11:23:47	ga_ls9c_ard_3-2-1_111069_2023-07-31_final.stac-item
2023-08-18 09:33:48	ga_ls9c_ard_3-2-1_093072_2023-08-18_final.stac-item
2023-08-18 09:34:12	ga_ls9c_ard_3-2-1_093073_2023-08-18_final.stac-item
2023-10-14 09:33:40	ga_ls9c_ard_3-2-1_092086_2023-10-14_final.stac-item
2023-10-17 09:57:01	ga_ls9c_ard_3-2-1_097067_2023-10-17_final.stac-item
2023-10-23 09:28:19	ga_ls9c_ard_3-2-1_091088_2023-10-22_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-28 09:40:50	ga_ls9c_ard_3-2-1_094073_2023-10-28_final.stac-item
2023-11-20 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-11-20_final.stac-item
2023-11-22 11:14:48	ga_ls9c_ard_3-2-1_109076_2023-11-22_final.stac-item
2023-11-26 09:12:25	ga_ls9c_ard_3-2-1_089079_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