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
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2021-12-21 10:10:25	ga_ls9c_ard_3-2-1_098085_2021-12-21_final.stac-item
2021-12-27 09:31:21	ga_ls9c_ard_3-2-1_092080_2021-12-27_final.stac-item
2021-12-28 11:51:54	ga_ls9c_ard_3-2-1_115076_2021-12-28_final.stac-item
2021-12-29 09:21:23	ga_ls9c_ard_3-2-1_090086_2021-12-28_final.stac-item
2021-12-29 10:53:29	ga_ls9c_ard_3-2-1_106069_2021-12-29_final.stac-item
2022-01-05 09:29:08	ga_ls9c_ard_3-2-1_091090_2022-01-04_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-14 09:21:19	ga_ls9c_ard_3-2-1_090086_2022-01-13_final.stac-item
2022-02-02 09:50:16	ga_ls9c_ard_3-2-1_095081_2022-02-02_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-20 09:39:23	ga_ls9c_ard_3-2-1_093085_2022-02-20_final.stac-item
2022-03-02 11:52:25	ga_ls9c_ard_3-2-1_115078_2022-03-02_final.stac-item
2022-03-03 09:22:18	ga_ls9c_ard_3-2-1_090089_2022-03-02_final.stac-item
2022-03-06 09:50:49	ga_ls9c_ard_3-2-1_095083_2022-03-06_final.stac-item
2022-03-20 09:57:10	ga_ls9c_ard_3-2-1_097068_2022-03-20_final.stac-item
2022-03-24 09:35:12	ga_ls9c_ard_3-2-1_093075_2022-03-24_final.stac-item
2022-03-28 10:46:33	ga_ls9c_ard_3-2-1_105068_2022-03-28_final.stac-item
2022-04-09 09:33:33	ga_ls9c_ard_3-2-1_093071_2022-04-09_final.stac-item
2022-04-26 10:17:04	ga_ls9c_ard_3-2-1_100072_2022-04-26_final.stac-item
2022-05-25 11:28:23	ga_ls9c_ard_3-2-1_111081_2022-05-25_final.stac-item
2022-05-27 09:39:56	ga_ls9c_ard_3-2-1_093088_2022-05-27_final.stac-item
2022-06-10 11:29:13	ga_ls9c_ard_3-2-1_111083_2022-06-10_final.stac-item
2022-06-16 09:16:08	ga_ls9c_ard_3-2-1_089090_2022-06-15_final.stac-item
2022-07-19 09:58:03	ga_ls9c_ard_3-2-1_096086_2022-07-19_final.stac-item
2022-07-24 10:09:29	ga_ls9c_ard_3-2-1_099068_2022-07-24_final.stac-item
2022-09-02 09:27:30	ga_ls9c_ard_3-2-1_091086_2022-09-01_final.stac-item
2022-09-04 09:14:21	ga_ls9c_ard_3-2-1_089084_2022-09-03_final.stac-item
2022-09-25 09:33:48	ga_ls9c_ard_3-2-1_092086_2022-09-25_final.stac-item
2022-10-05 10:04:54	ga_ls9c_ard_3-2-1_098071_2022-10-05_final.stac-item
2022-10-09 09:46:35	ga_ls9c_ard_3-2-1_094087_2022-10-09_final.stac-item
2022-10-12 10:09:56	ga_ls9c_ard_3-2-1_099068_2022-10-12_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-29 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-10-28_final.stac-item
2022-11-01 09:51:37	ga_ls9c_ard_3-2-1_095084_2022-11-01_final.stac-item
2022-11-01 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-11-01_final.stac-item
2022-11-02 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-11-02_final.stac-item
2022-11-07 10:47:27	ga_ls9c_ard_3-2-1_105069_2022-11-07_final.stac-item
2022-11-13 10:10:00	ga_ls9c_ard_3-2-1_099068_2022-11-13_final.stac-item
2022-11-13 11:51:40	ga_ls9c_ard_3-2-1_115075_2022-11-13_final.stac-item
2022-11-19 09:36:07	ga_ls9c_ard_3-2-1_093076_2022-11-19_final.stac-item
2022-11-20 10:22:10	ga_ls9c_ard_3-2-1_100083_2022-11-20_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-14 11:11:11	ga_ls9c_ard_3-2-1_108082_2022-12-14_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 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-12-17_final.stac-item
2022-12-21 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-12-21_final.stac-item
2022-12-21 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-12-21_final.stac-item
2022-12-24 10:09:43	ga_ls9c_ard_3-2-1_098083_2022-12-24_final.stac-item
2022-12-25 09:14:55	ga_ls9c_ard_3-2-1_089085_2022-12-24_final.stac-item
2023-01-04 09:52:27	ga_ls9c_ard_3-2-1_095086_2023-01-04_final.stac-item
2023-01-07 11:58:14	ga_ls9c_ard_3-2-1_116076_2023-01-07_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-10 09:13:21	ga_ls9c_ard_3-2-1_089081_2023-01-09_final.stac-item
2023-01-10 10:47:03	ga_ls9c_ard_3-2-1_105068_2023-01-10_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 11:02:07	ga_ls9c_ard_3-2-1_107075_2023-01-24_final.stac-item
2023-02-07 11:18:13	ga_ls9c_ard_3-2-1_109084_2023-02-07_final.stac-item
2023-02-08 11:58:42	ga_ls9c_ard_3-2-1_116077_2023-02-08_final.stac-item
2023-02-09 09:24:11	ga_ls9c_ard_3-2-1_091077_2023-02-08_final.stac-item
2023-02-11 09:15:01	ga_ls9c_ard_3-2-1_089085_2023-02-10_final.stac-item
2023-02-25 09:29:08	ga_ls9c_ard_3-2-1_091090_2023-02-24_final.stac-item
2023-03-01 10:39:42	ga_ls9c_ard_3-2-1_103081_2023-03-01_final.stac-item
2023-03-02 11:23:21	ga_ls9c_ard_3-2-1_110082_2023-03-02_final.stac-item
2023-03-04 11:08:11	ga_ls9c_ard_3-2-1_108075_2023-03-04_final.stac-item
2023-03-13 09:29:01	ga_ls9c_ard_3-2-1_091090_2023-03-12_final.stac-item
2023-03-17 10:35:59	ga_ls9c_ard_3-2-1_103072_2023-03-17_final.stac-item
2023-03-29 09:25:14	ga_ls9c_ard_3-2-1_091081_2023-03-28_final.stac-item
2023-04-22 10:15:21	ga_ls9c_ard_3-2-1_099083_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
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-05-02 09:16:12	ga_ls9c_ard_3-2-1_089090_2023-05-01_final.stac-item
2023-05-18 10:48:35	ga_ls9c_ard_3-2-1_105074_2023-05-18_final.stac-item
2023-05-28 09:45:29	ga_ls9c_ard_3-2-1_095071_2023-05-28_final.stac-item
2023-06-01 09:21:09	ga_ls9c_ard_3-2-1_091072_2023-05-31_final.stac-item
2023-06-03 10:46:04	ga_ls9c_ard_3-2-1_105068_2023-06-03_final.stac-item
2023-07-02 10:20:47	ga_ls9c_ard_3-2-1_100082_2023-07-02_final.stac-item
2023-07-06 09:54:31	ga_ls9c_ard_3-2-1_096078_2023-07-06_final.stac-item
2023-07-15 11:25:17	ga_ls9c_ard_3-2-1_111073_2023-07-15_final.stac-item
2023-07-17 09:34:27	ga_ls9c_ard_3-2-1_093074_2023-07-17_final.stac-item
2023-07-20 10:02:57	ga_ls9c_ard_3-2-1_098068_2023-07-20_final.stac-item
2023-07-20 10:03:45	ga_ls9c_ard_3-2-1_098070_2023-07-20_final.stac-item
2023-07-21 09:15:42	ga_ls9c_ard_3-2-1_089089_2023-07-20_final.stac-item
2023-07-21 10:49:00	ga_ls9c_ard_3-2-1_105075_2023-07-21_final.stac-item
2023-07-27 10:13:08	ga_ls9c_ard_3-2-1_099078_2023-07-27_final.stac-item
2023-08-04 11:01:30	ga_ls9c_ard_3-2-1_107075_2023-08-04_final.stac-item
2023-08-08 10:39:12	ga_ls9c_ard_3-2-1_103081_2023-08-08_final.stac-item
2023-08-12 11:50:59	ga_ls9c_ard_3-2-1_115075_2023-08-12_final.stac-item
2023-10-14 09:33:40	ga_ls9c_ard_3-2-1_092086_2023-10-14_final.stac-item
2023-10-30 11:06:08	ga_ls9c_ard_3-2-1_108070_2023-10-30_final.stac-item
2023-10-31 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-10-31_final.stac-item
2023-11-05 10:29:01	ga_ls9c_ard_3-2-1_102070_2023-11-05_final.stac-item
2023-11-17 09:21:17	ga_ls9c_ard_3-2-1_090086_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

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