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
2021-11-02 10:55:39	ga_ls9c_ard_3-2-1_106080_2021-11-02_final.stac-item
2021-11-03 09:52:58	ga_ls9c_ard_3-2-1_096070_2021-11-03_final.stac-item
2021-11-10 11:17:45	ga_ls9c_ard_3-2-1_110076_2021-11-10_final.stac-item
2021-12-22 10:49:41	ga_ls9c_ard_3-2-1_105075_2021-12-22_final.stac-item
2021-12-23 11:32:33	ga_ls9c_ard_3-2-1_112074_2021-12-23_final.stac-item
2021-12-27 09:34:08	ga_ls9c_ard_3-2-1_092087_2021-12-27_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2022-01-05 09:22:21	ga_ls9c_ard_3-2-1_091073_2022-01-04_final.stac-item
2022-01-21 09:23:08	ga_ls9c_ard_3-2-1_091075_2022-01-20_final.stac-item
2022-02-08 10:49:15	ga_ls9c_ard_3-2-1_105074_2022-02-08_final.stac-item
2022-02-22 09:22:36	ga_ls9c_ard_3-2-1_091074_2022-02-21_final.stac-item
2022-03-03 10:53:36	ga_ls9c_ard_3-2-1_106070_2022-03-03_final.stac-item
2022-03-03 10:56:00	ga_ls9c_ard_3-2-1_106076_2022-03-03_final.stac-item
2022-03-21 10:46:00	ga_ls9c_ard_3-2-1_104082_2022-03-21_final.stac-item
2022-03-24 11:14:29	ga_ls9c_ard_3-2-1_109076_2022-03-24_final.stac-item
2022-04-26 10:20:39	ga_ls9c_ard_3-2-1_100081_2022-04-26_final.stac-item
2022-05-21 11:50:19	ga_ls9c_ard_3-2-1_115074_2022-05-21_final.stac-item
2022-05-27 09:39:56	ga_ls9c_ard_3-2-1_093088_2022-05-27_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-03 11:18:38	ga_ls9c_ard_3-2-1_110072_2022-06-03_final.stac-item
2022-06-19 11:17:36	ga_ls9c_ard_3-2-1_110069_2022-06-19_final.stac-item
2022-07-17 10:06:46	ga_ls9c_ard_3-2-1_098077_2022-07-17_final.stac-item
2022-07-28 09:52:00	ga_ls9c_ard_3-2-1_095086_2022-07-28_final.stac-item
2022-07-28 11:26:06	ga_ls9c_ard_3-2-1_111074_2022-07-28_final.stac-item
2022-08-01 09:23:44	ga_ls9c_ard_3-2-1_091077_2022-07-31_final.stac-item
2022-08-01 09:28:08	ga_ls9c_ard_3-2-1_091088_2022-07-31_final.stac-item
2022-08-09 10:13:16	ga_ls9c_ard_3-2-1_099077_2022-08-09_final.stac-item
2022-08-10 09:16:51	ga_ls9c_ard_3-2-1_090075_2022-08-09_final.stac-item
2022-08-15 09:33:50	ga_ls9c_ard_3-2-1_093071_2022-08-15_final.stac-item
2022-08-20 11:32:29	ga_ls9c_ard_3-2-1_112074_2022-08-20_final.stac-item
2022-08-26 09:17:20	ga_ls9c_ard_3-2-1_090076_2022-08-25_final.stac-item
2022-09-07 09:40:51	ga_ls9c_ard_3-2-1_094073_2022-09-07_final.stac-item
2022-09-09 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-09-08_final.stac-item
2022-10-05 10:03:42	ga_ls9c_ard_3-2-1_098068_2022-10-05_final.stac-item
2022-10-07 11:36:12	ga_ls9c_ard_3-2-1_112083_2022-10-07_final.stac-item
2022-10-13 10:53:13	ga_ls9c_ard_3-2-1_106068_2022-10-13_final.stac-item
2022-11-01 09:52:25	ga_ls9c_ard_3-2-1_095086_2022-11-01_final.stac-item
2022-11-06 10:09:45	ga_ls9c_ard_3-2-1_098083_2022-11-06_final.stac-item
2022-11-15 10:01:14	ga_ls9c_ard_3-2-1_097077_2022-11-15_final.stac-item
2022-11-19 11:18:11	ga_ls9c_ard_3-2-1_109084_2022-11-19_final.stac-item
2022-11-21 09:22:09	ga_ls9c_ard_3-2-1_091072_2022-11-20_final.stac-item
2022-11-25 10:36:18	ga_ls9c_ard_3-2-1_103072_2022-11-25_final.stac-item
2022-11-30 10:56:24	ga_ls9c_ard_3-2-1_106076_2022-11-30_final.stac-item
2022-12-06 10:17:20	ga_ls9c_ard_3-2-1_100071_2022-12-06_final.stac-item
2022-12-07 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-12-06_final.stac-item
2022-12-14 09:29:07	ga_ls9c_ard_3-2-1_092074_2022-12-13_final.stac-item
2022-12-24 10:04:56	ga_ls9c_ard_3-2-1_098071_2022-12-24_final.stac-item
2022-12-28 11:19:56	ga_ls9c_ard_3-2-1_110073_2022-12-28_final.stac-item
2022-12-28 11:21:08	ga_ls9c_ard_3-2-1_110076_2022-12-28_final.stac-item
2022-12-30 11:07:35	ga_ls9c_ard_3-2-1_108073_2022-12-30_final.stac-item
2023-01-08 11:01:49	ga_ls9c_ard_3-2-1_107074_2023-01-08_final.stac-item
2023-01-15 09:34:14	ga_ls9c_ard_3-2-1_092087_2023-01-15_final.stac-item
2023-01-15 11:06:20	ga_ls9c_ard_3-2-1_108070_2023-01-15_final.stac-item
2023-01-15 11:07:56	ga_ls9c_ard_3-2-1_108074_2023-01-15_final.stac-item
2023-01-27 09:52:59	ga_ls9c_ard_3-2-1_096072_2023-01-27_final.stac-item
2023-01-27 11:32:40	ga_ls9c_ard_3-2-1_112074_2023-01-27_final.stac-item
2023-02-11 10:50:18	ga_ls9c_ard_3-2-1_105076_2023-02-11_final.stac-item
2023-02-14 11:20:23	ga_ls9c_ard_3-2-1_110074_2023-02-14_final.stac-item
2023-02-21 11:24:02	ga_ls9c_ard_3-2-1_111068_2023-02-21_final.stac-item
2023-03-10 10:28:12	ga_ls9c_ard_3-2-1_102068_2023-03-10_final.stac-item
2023-03-10 10:29:00	ga_ls9c_ard_3-2-1_102070_2023-03-10_final.stac-item
2023-03-14 10:03:30	ga_ls9c_ard_3-2-1_098068_2023-03-14_final.stac-item
2023-03-17 10:34:24	ga_ls9c_ard_3-2-1_103068_2023-03-17_final.stac-item
2023-03-27 11:16:56	ga_ls9c_ard_3-2-1_109082_2023-03-27_final.stac-item
2023-03-30 11:44:58	ga_ls9c_ard_3-2-1_114075_2023-03-30_final.stac-item
2023-04-01 11:31:25	ga_ls9c_ard_3-2-1_112072_2023-04-01_final.stac-item
2023-04-01 11:35:49	ga_ls9c_ard_3-2-1_112083_2023-04-01_final.stac-item
2023-04-03 11:23:03	ga_ls9c_ard_3-2-1_110082_2023-04-03_final.stac-item
2023-04-13 10:21:34	ga_ls9c_ard_3-2-1_100083_2023-04-13_final.stac-item
2023-04-26 09:46:36	ga_ls9c_ard_3-2-1_095073_2023-04-26_final.stac-item
2023-04-26 11:24:18	ga_ls9c_ard_3-2-1_111070_2023-04-26_final.stac-item
2023-05-06 10:27:07	ga_ls9c_ard_3-2-1_101082_2023-05-06_final.stac-item
2023-05-08 10:08:47	ga_ls9c_ard_3-2-1_099067_2023-05-08_final.stac-item
2023-05-08 10:09:35	ga_ls9c_ard_3-2-1_099069_2023-05-08_final.stac-item
2023-05-09 09:21:56	ga_ls9c_ard_3-2-1_090089_2023-05-08_final.stac-item
2023-05-18 10:48:59	ga_ls9c_ard_3-2-1_105075_2023-05-18_final.stac-item
2023-06-01 09:21:57	ga_ls9c_ard_3-2-1_091074_2023-05-31_final.stac-item
2023-06-18 10:08:39	ga_ls9c_ard_3-2-1_098083_2023-06-18_final.stac-item
2023-06-29 11:25:30	ga_ls9c_ard_3-2-1_111074_2023-06-29_final.stac-item
2023-07-01 09:39:30	ga_ls9c_ard_3-2-1_093087_2023-07-01_final.stac-item
2023-07-03 09:28:22	ga_ls9c_ard_3-2-1_091090_2023-07-02_final.stac-item
2023-07-04 10:07:15	ga_ls9c_ard_3-2-1_098079_2023-07-04_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-15 11:24:06	ga_ls9c_ard_3-2-1_111070_2023-07-15_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-08-04 10:59:30	ga_ls9c_ard_3-2-1_107070_2023-08-04_final.stac-item
2023-08-11 11:07:19	ga_ls9c_ard_3-2-1_108074_2023-08-11_final.stac-item
2023-08-16 09:51:45	ga_ls9c_ard_3-2-1_095086_2023-08-16_final.stac-item
2023-08-17 10:29:50	ga_ls9c_ard_3-2-1_102073_2023-08-17_final.stac-item
2023-10-17 09:57:49	ga_ls9c_ard_3-2-1_097069_2023-10-17_final.stac-item
2023-10-18 10:42:40	ga_ls9c_ard_3-2-1_104073_2023-10-18_final.stac-item
2023-10-23 11:02:00	ga_ls9c_ard_3-2-1_107075_2023-10-23_final.stac-item
2023-10-28 11:19:43	ga_ls9c_ard_3-2-1_110073_2023-10-28_final.stac-item
2023-10-31 10:14:29	ga_ls9c_ard_3-2-1_099080_2023-10-31_final.stac-item
2023-11-03 09:07:15	ga_ls9c_ard_3-2-1_088082_2023-11-02_final.stac-item
2023-11-16 10:16:05	ga_ls9c_ard_3-2-1_099084_2023-11-16_final.stac-item
2023-11-17 09:22:29	ga_ls9c_ard_3-2-1_090089_2023-11-16_final.stac-item
2023-11-17 10:55:46	ga_ls9c_ard_3-2-1_106075_2023-11-17_final.stac-item
2023-11-20 11:24:44	ga_ls9c_ard_3-2-1_111070_2023-11-20_final.stac-item
2023-11-24 09:22:22	ga_ls9c_ard_3-2-1_091073_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