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
2021-11-09 10:37:00	ga_ls9c_ard_3-2-1_103074_2021-11-09_final.stac-item
2021-11-09 10:39:23	ga_ls9c_ard_3-2-1_103080_2021-11-09_final.stac-item
2021-11-13 09:57:31	ga_ls9c_ard_3-2-1_097069_2021-11-13_final.stac-item
2021-11-23 10:01:38	ga_ls9c_ard_3-2-1_098067_2021-11-23_final.stac-item
2021-12-05 10:03:21	ga_ls9c_ard_3-2-1_098067_2021-12-05_final.stac-item
2021-12-05 10:05:21	ga_ls9c_ard_3-2-1_098072_2021-12-05_final.stac-item
2021-12-13 09:21:24	ga_ls9c_ard_3-2-1_090086_2021-12-12_final.stac-item
2021-12-19 10:17:35	ga_ls9c_ard_3-2-1_100072_2021-12-19_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2022-01-03 11:12:48	ga_ls9c_ard_3-2-1_109071_2022-01-03_final.stac-item
2022-01-04 10:17:35	ga_ls9c_ard_3-2-1_100072_2022-01-04_final.stac-item
2022-01-05 09:26:45	ga_ls9c_ard_3-2-1_091084_2022-01-04_final.stac-item
2022-01-14 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-01-13_final.stac-item
2022-01-22 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-01-22_final.stac-item
2022-02-18 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-02-18_final.stac-item
2022-03-03 09:22:42	ga_ls9c_ard_3-2-1_090090_2022-03-02_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-06-06 10:09:04	ga_ls9c_ard_3-2-1_099068_2022-06-06_final.stac-item
2022-07-05 09:45:40	ga_ls9c_ard_3-2-1_094086_2022-07-05_final.stac-item
2022-07-10 11:41:04	ga_ls9c_ard_3-2-1_113081_2022-07-10_final.stac-item
2022-07-12 11:23:30	ga_ls9c_ard_3-2-1_111068_2022-07-12_final.stac-item
2022-07-25 09:21:28	ga_ls9c_ard_3-2-1_090087_2022-07-24_final.stac-item
2022-07-30 11:13:22	ga_ls9c_ard_3-2-1_109073_2022-07-30_final.stac-item
2022-08-02 10:07:01	ga_ls9c_ard_3-2-1_098077_2022-08-02_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-09-03 10:10:22	ga_ls9c_ard_3-2-1_098085_2022-09-03_final.stac-item
2022-10-02 09:34:48	ga_ls9c_ard_3-2-1_093073_2022-10-02_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_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
2022-10-19 10:20:33	ga_ls9c_ard_3-2-1_100079_2022-10-19_final.stac-item
2022-10-25 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-10-25_final.stac-item
2022-10-26 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-10-26_final.stac-item
2022-10-27 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-10-26_final.stac-item
2022-10-28 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-10-28_final.stac-item
2022-10-29 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-10-28_final.stac-item
2022-10-31 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-10-30_final.stac-item
2022-11-10 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-11-10_final.stac-item
2022-11-14 09:21:34	ga_ls9c_ard_3-2-1_090086_2022-11-13_final.stac-item
2022-11-14 10:54:27	ga_ls9c_ard_3-2-1_106071_2022-11-14_final.stac-item
2022-11-14 10:59:15	ga_ls9c_ard_3-2-1_106083_2022-11-14_final.stac-item
2022-11-26 11:23:56	ga_ls9c_ard_3-2-1_110083_2022-11-26_final.stac-item
2022-11-29 10:13:57	ga_ls9c_ard_3-2-1_099078_2022-11-29_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-07 11:02:36	ga_ls9c_ard_3-2-1_107076_2022-12-07_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-15 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-12-15_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_2022-12-28_final.stac-item
2023-01-01 09:23:08	ga_ls9c_ard_3-2-1_090090_2022-12-31_final.stac-item
2023-01-06 09:40:29	ga_ls9c_ard_3-2-1_093087_2023-01-06_final.stac-item
2023-01-09 10:03:48	ga_ls9c_ard_3-2-1_098068_2023-01-09_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-01-19 09:07:27	ga_ls9c_ard_3-2-1_088082_2023-01-18_final.stac-item
2023-01-28 10:37:04	ga_ls9c_ard_3-2-1_103074_2023-01-28_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-01 10:14:23	ga_ls9c_ard_3-2-1_099079_2023-02-01_final.stac-item
2023-02-04 10:42:55	ga_ls9c_ard_3-2-1_104073_2023-02-04_final.stac-item
2023-02-11 09:12:37	ga_ls9c_ard_3-2-1_089079_2023-02-10_final.stac-item
2023-03-01 10:34:55	ga_ls9c_ard_3-2-1_103069_2023-03-01_final.stac-item
2023-03-11 09:36:34	ga_ls9c_ard_3-2-1_093078_2023-03-11_final.stac-item
2023-03-13 09:22:38	ga_ls9c_ard_3-2-1_091074_2023-03-12_final.stac-item
2023-03-31 10:46:58	ga_ls9c_ard_3-2-1_105069_2023-03-31_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-05-01 10:03:04	ga_ls9c_ard_3-2-1_098068_2023-05-01_final.stac-item
2023-05-02 09:11:01	ga_ls9c_ard_3-2-1_089077_2023-05-01_final.stac-item
2023-05-19 09:56:56	ga_ls9c_ard_3-2-1_096084_2023-05-19_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-06-20 11:35:35	ga_ls9c_ard_3-2-1_112084_2023-06-20_final.stac-item
2023-06-23 10:26:48	ga_ls9c_ard_3-2-1_101082_2023-06-23_final.stac-item
2023-06-24 09:32:22	ga_ls9c_ard_3-2-1_092085_2023-06-24_final.stac-item
2023-06-25 10:13:14	ga_ls9c_ard_3-2-1_099079_2023-06-25_final.stac-item
2023-06-28 10:45:24	ga_ls9c_ard_3-2-1_104082_2023-06-28_final.stac-item
2023-07-01 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-07-01_final.stac-item
2023-07-03 09:25:58	ga_ls9c_ard_3-2-1_091084_2023-07-02_final.stac-item
2023-07-19 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-07-18_final.stac-item
2023-07-22 09:57:46	ga_ls9c_ard_3-2-1_096086_2023-07-22_final.stac-item
2023-07-22 11:31:04	ga_ls9c_ard_3-2-1_112072_2023-07-22_final.stac-item
2023-07-24 09:44:59	ga_ls9c_ard_3-2-1_094085_2023-07-24_final.stac-item
2023-07-28 09:22:19	ga_ls9c_ard_3-2-1_090090_2023-07-27_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 09:22:55	ga_ls9c_ard_3-2-1_090090_2023-10-15_final.stac-item
2023-10-19 11:24:20	ga_ls9c_ard_3-2-1_111069_2023-10-19_final.stac-item
2023-10-19 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-10-19_final.stac-item
2023-10-23 09:26:43	ga_ls9c_ard_3-2-1_091084_2023-10-22_final.stac-item
2023-10-25 09:10:21	ga_ls9c_ard_3-2-1_089074_2023-10-24_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 11:06:08	ga_ls9c_ard_3-2-1_108070_2023-10-30_final.stac-item
2023-11-01 10:53:20	ga_ls9c_ard_3-2-1_106069_2023-11-01_final.stac-item
2023-11-02 09:58:06	ga_ls9c_ard_3-2-1_097070_2023-11-02_final.stac-item
2023-11-02 09:59:41	ga_ls9c_ard_3-2-1_097074_2023-11-02_final.stac-item
2023-11-02 10:03:41	ga_ls9c_ard_3-2-1_097084_2023-11-02_final.stac-item
2023-11-02 11:38:34	ga_ls9c_ard_3-2-1_113074_2023-11-02_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 10:10:06	ga_ls9c_ard_3-2-1_099069_2023-11-16_final.stac-item
2023-11-17 09:20:53	ga_ls9c_ard_3-2-1_090085_2023-11-16_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_2023-11-23_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