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

100 results

Time (local)	Label
2021-11-10 11:15:22	ga_ls9c_ard_3-2-1_110070_2021-11-10_final.stac-item
2021-11-22 09:28:27	ga_ls9c_ard_3-2-1_091084_2021-11-21_final.stac-item
2021-11-22 11:01:32	ga_ls9c_ard_3-2-1_107070_2021-11-22_final.stac-item
2021-11-22 11:06:43	ga_ls9c_ard_3-2-1_107083_2021-11-22_final.stac-item
2021-12-04 11:00:35	ga_ls9c_ard_3-2-1_107071_2021-12-04_final.stac-item
2021-12-06 10:50:11	ga_ls9c_ard_3-2-1_105076_2021-12-06_final.stac-item
2021-12-19 10:17:35	ga_ls9c_ard_3-2-1_100072_2021-12-19_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-02-15 09:22:53	ga_ls9c_ard_3-2-1_090090_2022-02-14_final.stac-item
2022-02-22 11:05:05	ga_ls9c_ard_3-2-1_107083_2022-02-22_final.stac-item
2022-02-26 10:39:30	ga_ls9c_ard_3-2-1_103081_2022-02-26_final.stac-item
2022-03-03 09:21:06	ga_ls9c_ard_3-2-1_090086_2022-03-02_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-12 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-04-12_final.stac-item
2022-05-11 09:40:05	ga_ls9c_ard_3-2-1_093088_2022-05-11_final.stac-item
2022-06-20 10:27:36	ga_ls9c_ard_3-2-1_101083_2022-06-20_final.stac-item
2022-06-30 11:05:14	ga_ls9c_ard_3-2-1_107084_2022-06-30_final.stac-item
2022-07-28 11:28:06	ga_ls9c_ard_3-2-1_111079_2022-07-28_final.stac-item
2022-08-03 10:46:42	ga_ls9c_ard_3-2-1_105068_2022-08-03_final.stac-item
2022-08-06 11:23:37	ga_ls9c_ard_3-2-1_110083_2022-08-06_final.stac-item
2022-08-09 10:10:29	ga_ls9c_ard_3-2-1_099070_2022-08-09_final.stac-item
2022-08-13 09:46:35	ga_ls9c_ard_3-2-1_095072_2022-08-13_final.stac-item
2022-08-17 09:28:40	ga_ls9c_ard_3-2-1_091089_2022-08-16_final.stac-item
2022-08-30 10:29:30	ga_ls9c_ard_3-2-1_102071_2022-08-30_final.stac-item
2022-09-11 10:53:02	ga_ls9c_ard_3-2-1_106068_2022-09-11_final.stac-item
2022-09-16 09:40:44	ga_ls9c_ard_3-2-1_093088_2022-09-16_final.stac-item
2022-10-06 10:47:21	ga_ls9c_ard_3-2-1_105069_2022-10-06_final.stac-item
2022-10-18 09:36:53	ga_ls9c_ard_3-2-1_093078_2022-10-18_final.stac-item
2022-10-21 10:04:12	ga_ls9c_ard_3-2-1_098069_2022-10-21_final.stac-item
2022-11-03 09:40:26	ga_ls9c_ard_3-2-1_093087_2022-11-03_final.stac-item
2022-11-05 11:05:22	ga_ls9c_ard_3-2-1_107083_2022-11-05_final.stac-item
2022-12-07 09:22:55	ga_ls9c_ard_3-2-1_091074_2022-12-06_final.stac-item
2022-12-14 09:29:54	ga_ls9c_ard_3-2-1_092076_2022-12-13_final.stac-item
2023-01-02 10:04:24	ga_ls9c_ard_3-2-1_097085_2023-01-02_final.stac-item
2023-01-10 09:14:09	ga_ls9c_ard_3-2-1_089083_2023-01-09_final.stac-item
2023-01-22 09:39:32	ga_ls9c_ard_3-2-1_093085_2023-01-22_final.stac-item
2023-01-25 10:07:42	ga_ls9c_ard_3-2-1_098078_2023-01-25_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-15 10:23:33	ga_ls9c_ard_3-2-1_101071_2023-02-15_final.stac-item
2023-03-05 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-03-05_final.stac-item
2023-03-07 10:00:57	ga_ls9c_ard_3-2-1_097077_2023-03-07_final.stac-item
2023-03-14 10:07:29	ga_ls9c_ard_3-2-1_098078_2023-03-14_final.stac-item
2023-03-20 09:34:22	ga_ls9c_ard_3-2-1_092088_2023-03-20_final.stac-item
2023-03-21 11:52:31	ga_ls9c_ard_3-2-1_115078_2023-03-21_final.stac-item
2023-03-30 10:02:54	ga_ls9c_ard_3-2-1_098067_2023-03-30_final.stac-item
2023-04-11 10:28:46	ga_ls9c_ard_3-2-1_102070_2023-04-11_final.stac-item
2023-04-14 09:28:19	ga_ls9c_ard_3-2-1_091089_2023-04-13_final.stac-item
2023-04-14 11:05:12	ga_ls9c_ard_3-2-1_107084_2023-04-14_final.stac-item
2023-04-18 10:34:06	ga_ls9c_ard_3-2-1_103068_2023-04-18_final.stac-item
2023-04-20 10:25:20	ga_ls9c_ard_3-2-1_101077_2023-04-20_final.stac-item
2023-04-22 10:10:58	ga_ls9c_ard_3-2-1_099072_2023-04-22_final.stac-item
2023-04-28 09:39:00	ga_ls9c_ard_3-2-1_093085_2023-04-28_final.stac-item
2023-04-30 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-04-29_final.stac-item
2023-05-14 09:40:03	ga_ls9c_ard_3-2-1_093088_2023-05-14_final.stac-item
2023-05-26 11:37:55	ga_ls9c_ard_3-2-1_113074_2023-05-26_final.stac-item
2023-06-01 09:27:56	ga_ls9c_ard_3-2-1_091089_2023-05-31_final.stac-item
2023-06-10 10:52:11	ga_ls9c_ard_3-2-1_106068_2023-06-10_final.stac-item
2023-06-14 10:27:24	ga_ls9c_ard_3-2-1_102068_2023-06-14_final.stac-item
2023-06-21 10:35:10	ga_ls9c_ard_3-2-1_103072_2023-06-21_final.stac-item
2023-06-23 10:24:48	ga_ls9c_ard_3-2-1_101077_2023-06-23_final.stac-item
2023-07-10 09:34:13	ga_ls9c_ard_3-2-1_092089_2023-07-10_final.stac-item
2023-07-12 09:16:41	ga_ls9c_ard_3-2-1_090076_2023-07-11_final.stac-item
2023-07-12 10:52:23	ga_ls9c_ard_3-2-1_106068_2023-07-12_final.stac-item
2023-07-17 09:39:14	ga_ls9c_ard_3-2-1_093086_2023-07-17_final.stac-item
2023-07-20 10:07:20	ga_ls9c_ard_3-2-1_098079_2023-07-20_final.stac-item
2023-07-27 10:10:44	ga_ls9c_ard_3-2-1_099072_2023-07-27_final.stac-item
2023-08-05 10:03:05	ga_ls9c_ard_3-2-1_098068_2023-08-05_final.stac-item
2023-08-11 09:28:26	ga_ls9c_ard_3-2-1_092074_2023-08-10_final.stac-item
2023-08-18 09:34:12	ga_ls9c_ard_3-2-1_093073_2023-08-18_final.stac-item
2023-09-07 09:13:43	ga_ls9c_ard_3-2-1_089083_2023-09-06_final.stac-item
2023-09-14 10:53:40	ga_ls9c_ard_3-2-1_106070_2023-09-14_final.stac-item
2023-09-16 09:06:49	ga_ls9c_ard_3-2-1_088081_2023-09-15_final.stac-item
2023-09-19 11:17:48	ga_ls9c_ard_3-2-1_109084_2023-09-19_final.stac-item
2023-10-02 09:06:48	ga_ls9c_ard_3-2-1_088081_2023-10-01_final.stac-item
2023-10-16 10:53:02	ga_ls9c_ard_3-2-1_106068_2023-10-16_final.stac-item
2023-10-28 09:40:50	ga_ls9c_ard_3-2-1_094073_2023-10-28_final.stac-item
2023-11-02 09:57:42	ga_ls9c_ard_3-2-1_097069_2023-11-02_final.stac-item
2023-11-03 09:06:27	ga_ls9c_ard_3-2-1_088080_2023-11-02_final.stac-item
2023-11-04 11:25:01	ga_ls9c_ard_3-2-1_111071_2023-11-04_final.stac-item
2023-11-18 09:58:10	ga_ls9c_ard_3-2-1_097070_2023-11-18_final.stac-item
2023-11-20 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-11-20_final.stac-item
2023-11-26 10:52:54	ga_ls9c_ard_3-2-1_105083_2023-11-26_final.stac-item
2023-12-04 11:38:43	ga_ls9c_ard_3-2-1_113074_2023-12-04_final.stac-item
2023-12-04 11:41:31	ga_ls9c_ard_3-2-1_113081_2023-12-04_final.stac-item
2023-12-07 10:30:17	ga_ls9c_ard_3-2-1_102073_2023-12-07_final.stac-item
2023-12-10 09:23:32	ga_ls9c_ard_3-2-1_091076_2023-12-09_final.stac-item
2023-12-22 09:46:45	ga_ls9c_ard_3-2-1_095072_2023-12-22_final.stac-item
2023-12-24 09:35:35	ga_ls9c_ard_3-2-1_093075_2023-12-24_final.stac-item
2023-12-24 09:40:23	ga_ls9c_ard_3-2-1_093087_2023-12-24_final.stac-item
2024-01-06 10:43:03	ga_ls9c_ard_3-2-1_104074_2024-01-06_final.stac-item
2024-01-12 10:07:13	ga_ls9c_ard_3-2-1_098077_2024-01-12_final.stac-item
2024-01-15 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-15_final.stac-item
2024-02-04 11:52:43	ga_ls9c_ard_3-2-1_115078_2024-02-04_final.stac-item
2024-02-28 11:00:18	ga_ls9c_ard_3-2-1_107071_2024-02-28_final.stac-item
2024-04-05 11:23:54	ga_ls9c_ard_3-2-1_110084_2024-04-05_final.stac-item
2024-04-08 10:11:06	ga_ls9c_ard_3-2-1_099072_2024-04-08_final.stac-item
2024-04-26 09:57:12	ga_ls9c_ard_3-2-1_097069_2024-04-26_final.stac-item
2024-05-07 11:19:31	ga_ls9c_ard_3-2-1_110074_2024-05-07_nrt.stac-item
2024-05-11 09:16:42	ga_ls9c_ard_3-2-1_090076_2024-05-10_nrt.stac-item
2024-05-11 10:52:23	ga_ls9c_ard_3-2-1_106068_2024-05-11_nrt.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