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
2021-11-03 09:52:58	ga_ls9c_ard_3-2-1_096070_2021-11-03_final.stac-item
2021-11-07 09:21:28	ga_ls9c_ard_3-2-1_090085_2021-11-06_final.stac-item
2021-11-13 10:03:29	ga_ls9c_ard_3-2-1_097084_2021-11-13_final.stac-item
2021-11-20 09:42:01	ga_ls9c_ard_3-2-1_094071_2021-11-20_final.stac-item
2021-11-20 09:42:25	ga_ls9c_ard_3-2-1_094072_2021-11-20_final.stac-item
2021-11-23 10:01:38	ga_ls9c_ard_3-2-1_098067_2021-11-23_final.stac-item
2021-12-13 10:59:05	ga_ls9c_ard_3-2-1_106083_2021-12-13_final.stac-item
2021-12-23 11:31:45	ga_ls9c_ard_3-2-1_112072_2021-12-23_final.stac-item
2022-01-09 10:34:30	ga_ls9c_ard_3-2-1_103068_2022-01-09_final.stac-item
2022-01-14 09:20:55	ga_ls9c_ard_3-2-1_090085_2022-01-13_final.stac-item
2022-01-19 11:11:59	ga_ls9c_ard_3-2-1_109069_2022-01-19_final.stac-item
2022-01-23 10:46:53	ga_ls9c_ard_3-2-1_105068_2022-01-23_final.stac-item
2022-01-27 10:28:09	ga_ls9c_ard_3-2-1_101083_2022-01-27_final.stac-item
2022-02-02 11:24:22	ga_ls9c_ard_3-2-1_111069_2022-02-02_final.stac-item
2022-02-04 11:12:24	ga_ls9c_ard_3-2-1_109070_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
2022-02-16 10:01:21	ga_ls9c_ard_3-2-1_097078_2022-02-16_final.stac-item
2022-02-21 10:20:14	ga_ls9c_ard_3-2-1_100079_2022-02-21_final.stac-item
2022-03-05 09:06:45	ga_ls9c_ard_3-2-1_088081_2022-03-04_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-27 10:09:40	ga_ls9c_ard_3-2-1_098084_2022-03-27_final.stac-item
2022-03-28 09:11:39	ga_ls9c_ard_3-2-1_089078_2022-03-27_final.stac-item
2022-03-28 10:48:57	ga_ls9c_ard_3-2-1_105074_2022-03-28_final.stac-item
2022-04-25 11:13:05	ga_ls9c_ard_3-2-1_109073_2022-04-25_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
2022-05-06 10:58:29	ga_ls9c_ard_3-2-1_106083_2022-05-06_final.stac-item
2022-05-13 09:22:54	ga_ls9c_ard_3-2-1_091076_2022-05-12_final.stac-item
2022-05-20 11:05:27	ga_ls9c_ard_3-2-1_108070_2022-05-20_final.stac-item
2022-06-15 10:03:46	ga_ls9c_ard_3-2-1_098070_2022-06-15_final.stac-item
2022-07-07 09:33:18	ga_ls9c_ard_3-2-1_092086_2022-07-07_final.stac-item
2022-07-18 10:49:15	ga_ls9c_ard_3-2-1_105075_2022-07-18_final.stac-item
2022-07-21 09:46:07	ga_ls9c_ard_3-2-1_094087_2022-07-21_final.stac-item
2022-07-29 10:28:06	ga_ls9c_ard_3-2-1_102068_2022-07-29_final.stac-item
2022-08-03 10:46:42	ga_ls9c_ard_3-2-1_105068_2022-08-03_final.stac-item
2022-08-10 09:17:15	ga_ls9c_ard_3-2-1_090076_2022-08-09_final.stac-item
2022-08-28 09:06:58	ga_ls9c_ard_3-2-1_088081_2022-08-27_final.stac-item
2022-08-29 11:25:55	ga_ls9c_ard_3-2-1_111073_2022-08-29_final.stac-item
2022-09-05 11:31:42	ga_ls9c_ard_3-2-1_112072_2022-09-05_final.stac-item
2022-09-09 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-09-08_final.stac-item
2022-09-09 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-09-09_final.stac-item
2022-09-20 09:16:26	ga_ls9c_ard_3-2-1_089089_2022-09-19_final.stac-item
2022-09-20 10:52:31	ga_ls9c_ard_3-2-1_105082_2022-09-20_final.stac-item
2022-09-23 09:45:21	ga_ls9c_ard_3-2-1_094084_2022-09-23_final.stac-item
2022-09-27 09:18:39	ga_ls9c_ard_3-2-1_090079_2022-09-26_final.stac-item
2022-10-14 09:57:36	ga_ls9c_ard_3-2-1_097068_2022-10-14_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-10-29 09:17:56	ga_ls9c_ard_3-2-1_090077_2022-10-28_final.stac-item
2022-10-29 10:54:02	ga_ls9c_ard_3-2-1_106070_2022-10-29_final.stac-item
2022-11-01 09:52:49	ga_ls9c_ard_3-2-1_095087_2022-11-01_final.stac-item
2022-11-07 09:16:32	ga_ls9c_ard_3-2-1_089089_2022-11-06_final.stac-item
2022-11-12 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-11-11_final.stac-item
2022-11-23 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-11-22_final.stac-item
2022-11-26 09:41:04	ga_ls9c_ard_3-2-1_094073_2022-11-26_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 10:17:20	ga_ls9c_ard_3-2-1_100071_2022-12-06_final.stac-item
2022-12-13 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-12-13_final.stac-item
2022-12-14 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-12-13_final.stac-item
2022-12-15 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-12-15_final.stac-item
2022-12-16 09:17:09	ga_ls9c_ard_3-2-1_090075_2022-12-15_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
2022-12-24 10:05:20	ga_ls9c_ard_3-2-1_098072_2022-12-24_final.stac-item
2022-12-26 11:32:41	ga_ls9c_ard_3-2-1_112074_2022-12-26_final.stac-item
2023-01-01 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-12-31_final.stac-item
2023-01-03 10:44:05	ga_ls9c_ard_3-2-1_104076_2023-01-03_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-13 11:24:18	ga_ls9c_ard_3-2-1_110084_2023-01-13_final.stac-item
2023-01-19 09:07:03	ga_ls9c_ard_3-2-1_088081_2023-01-18_final.stac-item
2023-01-21 10:33:33	ga_ls9c_ard_3-2-1_102081_2023-01-21_final.stac-item
2023-01-24 09:24:02	ga_ls9c_ard_3-2-1_091077_2023-01-23_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-01-25 10:10:06	ga_ls9c_ard_3-2-1_098084_2023-01-25_final.stac-item
2023-02-03 09:57:39	ga_ls9c_ard_3-2-1_097068_2023-02-03_final.stac-item
2023-02-18 10:54:24	ga_ls9c_ard_3-2-1_106071_2023-02-18_final.stac-item
2023-04-16 09:13:10	ga_ls9c_ard_3-2-1_089082_2023-04-15_final.stac-item
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final.stac-item
2023-04-28 11:11:30	ga_ls9c_ard_3-2-1_109069_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 09:14:37	ga_ls9c_ard_3-2-1_089086_2023-05-01_final.stac-item
2023-05-08 10:10:23	ga_ls9c_ard_3-2-1_099071_2023-05-08_final.stac-item
2023-05-14 09:40:03	ga_ls9c_ard_3-2-1_093088_2023-05-14_final.stac-item
2023-05-17 10:03:20	ga_ls9c_ard_3-2-1_098069_2023-05-17_final.stac-item
2023-05-24 11:51:05	ga_ls9c_ard_3-2-1_115076_2023-05-24_final.stac-item
2023-06-02 10:06:24	ga_ls9c_ard_3-2-1_098077_2023-06-02_final.stac-item
2023-06-04 09:56:50	ga_ls9c_ard_3-2-1_096084_2023-06-04_final.stac-item
2023-06-10 10:55:23	ga_ls9c_ard_3-2-1_106076_2023-06-10_final.stac-item
2023-06-12 09:06:30	ga_ls9c_ard_3-2-1_088082_2023-06-11_final.stac-item
2023-06-20 09:56:42	ga_ls9c_ard_3-2-1_096084_2023-06-20_final.stac-item
2023-06-22 11:23:13	ga_ls9c_ard_3-2-1_110084_2023-06-22_final.stac-item
2023-06-24 09:27:59	ga_ls9c_ard_3-2-1_092074_2023-06-23_final.stac-item
2023-06-25 10:08:51	ga_ls9c_ard_3-2-1_099068_2023-06-25_final.stac-item
2023-06-26 10:52:07	ga_ls9c_ard_3-2-1_106068_2023-06-26_final.stac-item
2023-07-02 10:21:11	ga_ls9c_ard_3-2-1_100083_2023-07-02_final.stac-item
2023-07-10 11:07:31	ga_ls9c_ard_3-2-1_108075_2023-07-10_final.stac-item
2023-09-06 10:03:21	ga_ls9c_ard_3-2-1_098068_2023-09-06_final.stac-item
2023-09-13 10:09:12	ga_ls9c_ard_3-2-1_099067_2023-09-13_final.stac-item
2023-09-30 09:21:07	ga_ls9c_ard_3-2-1_090086_2023-09-29_final.stac-item
2023-10-08 10:07:28	ga_ls9c_ard_3-2-1_098078_2023-10-08_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