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
2021-10-31 11:10:24	ga_ls9c_ard_3-2-1_109070_2021-10-31_final.stac-item
2021-12-13 09:21:24	ga_ls9c_ard_3-2-1_090086_2021-12-12_final.stac-item
2021-12-20 09:26:45	ga_ls9c_ard_3-2-1_091084_2021-12-19_final.stac-item
2021-12-25 09:40:55	ga_ls9c_ard_3-2-1_094073_2021-12-25_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-26 09:42:53	ga_ls9c_ard_3-2-1_094078_2022-01-26_final.stac-item
2022-02-27 09:40:41	ga_ls9c_ard_3-2-1_094073_2022-02-27_final.stac-item
2022-03-10 09:24:54	ga_ls9c_ard_3-2-1_091080_2022-03-09_final.stac-item
2022-03-31 09:40:10	ga_ls9c_ard_3-2-1_094072_2022-03-31_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-05 09:28:36	ga_ls9c_ard_3-2-1_092075_2022-06-04_final.stac-item
2022-06-14 09:24:29	ga_ls9c_ard_3-2-1_091080_2022-06-13_final.stac-item
2022-07-07 11:05:48	ga_ls9c_ard_3-2-1_108070_2022-07-07_final.stac-item
2022-07-09 09:18:56	ga_ls9c_ard_3-2-1_090081_2022-07-08_final.stac-item
2022-08-14 10:30:15	ga_ls9c_ard_3-2-1_102073_2022-08-14_final.stac-item
2022-08-24 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-08-24_final.stac-item
2022-09-04 09:11:57	ga_ls9c_ard_3-2-1_089078_2022-09-03_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-10-02 11:14:29	ga_ls9c_ard_3-2-1_109075_2022-10-02_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_2022-10-03_final.stac-item
2022-10-09 09:41:24	ga_ls9c_ard_3-2-1_094074_2022-10-09_final.stac-item
2022-10-15 09:07:34	ga_ls9c_ard_3-2-1_088082_2022-10-14_final.stac-item
2022-10-18 09:38:53	ga_ls9c_ard_3-2-1_093083_2022-10-18_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-24 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-10-24_final.stac-item
2022-10-24 10:39:54	ga_ls9c_ard_3-2-1_103081_2022-10-24_final.stac-item
2022-10-27 11:08:00	ga_ls9c_ard_3-2-1_108074_2022-10-27_final.stac-item
2022-10-28 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-10-28_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-11 10:25:56	ga_ls9c_ard_3-2-1_101077_2022-11-11_final.stac-item
2022-11-12 09:35:07	ga_ls9c_ard_3-2-1_092089_2022-11-12_final.stac-item
2022-11-12 11:11:36	ga_ls9c_ard_3-2-1_108083_2022-11-12_final.stac-item
2022-11-18 10:30:08	ga_ls9c_ard_3-2-1_102072_2022-11-18_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-21 09:27:44	ga_ls9c_ard_3-2-1_091086_2022-11-20_final.stac-item
2022-11-28 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-11-28_final.stac-item
2022-11-28 11:06:47	ga_ls9c_ard_3-2-1_108071_2022-11-28_final.stac-item
2022-11-29 10:14:44	ga_ls9c_ard_3-2-1_099080_2022-11-29_final.stac-item
2022-11-29 11:52:02	ga_ls9c_ard_3-2-1_115076_2022-11-29_final.stac-item
2022-12-15 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-15_final.stac-item
2022-12-16 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-12-15_final.stac-item
2022-12-17 11:38:53	ga_ls9c_ard_3-2-1_113074_2022-12-17_final.stac-item
2022-12-27 10:37:52	ga_ls9c_ard_3-2-1_103076_2022-12-27_final.stac-item
2023-01-04 09:46:28	ga_ls9c_ard_3-2-1_095071_2023-01-04_final.stac-item
2023-01-08 09:29:19	ga_ls9c_ard_3-2-1_091090_2023-01-07_final.stac-item
2023-01-13 11:19:07	ga_ls9c_ard_3-2-1_110071_2023-01-13_final.stac-item
2023-01-17 09:21:03	ga_ls9c_ard_3-2-1_090085_2023-01-16_final.stac-item
2023-01-17 09:22:14	ga_ls9c_ard_3-2-1_090088_2023-01-16_final.stac-item
2023-01-17 09:22:38	ga_ls9c_ard_3-2-1_090089_2023-01-16_final.stac-item
2023-01-23 10:18:02	ga_ls9c_ard_3-2-1_100073_2023-01-23_final.stac-item
2023-01-28 10:38:15	ga_ls9c_ard_3-2-1_103077_2023-01-28_final.stac-item
2023-02-03 11:38:56	ga_ls9c_ard_3-2-1_113074_2023-02-03_final.stac-item
2023-02-07 11:14:38	ga_ls9c_ard_3-2-1_109075_2023-02-07_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-04-21 11:05:24	ga_ls9c_ard_3-2-1_108069_2023-04-21_final.stac-item
2023-04-22 11:51:51	ga_ls9c_ard_3-2-1_115077_2023-04-22_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-04-23 10:52:38	ga_ls9c_ard_3-2-1_106068_2023-04-23_final.stac-item
2023-04-24 09:58:36	ga_ls9c_ard_3-2-1_097072_2023-04-24_final.stac-item
2023-04-28 09:39:48	ga_ls9c_ard_3-2-1_093087_2023-04-28_final.stac-item
2023-05-01 10:07:27	ga_ls9c_ard_3-2-1_098079_2023-05-01_final.stac-item
2023-05-02 10:51:54	ga_ls9c_ard_3-2-1_105082_2023-05-02_final.stac-item
2023-05-05 09:45:27	ga_ls9c_ard_3-2-1_094086_2023-05-05_final.stac-item
2023-05-07 11:05:36	ga_ls9c_ard_3-2-1_108070_2023-05-07_final.stac-item
2023-05-08 10:15:10	ga_ls9c_ard_3-2-1_099083_2023-05-08_final.stac-item
2023-05-09 09:20:44	ga_ls9c_ard_3-2-1_090086_2023-05-08_final.stac-item
2023-05-28 11:24:46	ga_ls9c_ard_3-2-1_111072_2023-05-28_final.stac-item
2023-06-01 09:24:45	ga_ls9c_ard_3-2-1_091081_2023-05-31_final.stac-item
2023-06-01 09:25:57	ga_ls9c_ard_3-2-1_091084_2023-05-31_final.stac-item
2023-06-24 11:10:27	ga_ls9c_ard_3-2-1_108083_2023-06-24_final.stac-item
2023-06-25 11:51:19	ga_ls9c_ard_3-2-1_115077_2023-06-25_final.stac-item
2023-06-29 11:25:06	ga_ls9c_ard_3-2-1_111073_2023-06-29_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-07-21 09:12:07	ga_ls9c_ard_3-2-1_089080_2023-07-20_final.stac-item
2023-07-21 10:48:36	ga_ls9c_ard_3-2-1_105074_2023-07-21_final.stac-item
2023-07-28 10:55:37	ga_ls9c_ard_3-2-1_106076_2023-07-28_final.stac-item
2023-08-02 09:39:21	ga_ls9c_ard_3-2-1_093086_2023-08-02_final.stac-item
2023-08-08 10:35:36	ga_ls9c_ard_3-2-1_103072_2023-08-08_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-15 10:09:45	ga_ls9c_ard_3-2-1_099068_2023-10-15_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-16 09:22:07	ga_ls9c_ard_3-2-1_090088_2023-10-15_final.stac-item
2023-10-16 09:22:31	ga_ls9c_ard_3-2-1_090089_2023-10-15_final.stac-item
2023-10-17 11:38:41	ga_ls9c_ard_3-2-1_113074_2023-10-17_final.stac-item
2023-10-17 11:42:17	ga_ls9c_ard_3-2-1_113083_2023-10-17_final.stac-item
2023-10-22 10:17:09	ga_ls9c_ard_3-2-1_100071_2023-10-22_final.stac-item
2023-10-24 10:09:34	ga_ls9c_ard_3-2-1_098083_2023-10-24_final.stac-item
2023-10-25 09:13:09	ga_ls9c_ard_3-2-1_089081_2023-10-24_final.stac-item
2023-10-25 10:50:02	ga_ls9c_ard_3-2-1_105076_2023-10-25_final.stac-item
2023-10-28 09:45:37	ga_ls9c_ard_3-2-1_094085_2023-10-28_final.stac-item
2023-10-28 11:18:55	ga_ls9c_ard_3-2-1_110071_2023-10-28_final.stac-item
2023-10-31 11:51:22	ga_ls9c_ard_3-2-1_115075_2023-10-31_final.stac-item
2023-10-31 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-10-31_final.stac-item
2023-11-16 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-11-16_final.stac-item
2023-11-19 10:43:03	ga_ls9c_ard_3-2-1_104074_2023-11-19_final.stac-item
2023-11-23 10:21:59	ga_ls9c_ard_3-2-1_100083_2023-11-23_final.stac-item
2023-11-24 09:25:10	ga_ls9c_ard_3-2-1_091080_2023-11-23_final.stac-item
2023-11-24 11:00:28	ga_ls9c_ard_3-2-1_107071_2023-11-24_final.stac-item
2023-11-25 11:46:08	ga_ls9c_ard_3-2-1_114077_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