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
2021-12-21 10:03:38	ga_ls9c_ard_3-2-1_098068_2021-12-21_final.stac-item
2021-12-25 09:45:18	ga_ls9c_ard_3-2-1_094084_2021-12-25_final.stac-item
2022-01-12 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-01-12_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-02-15 09:19:42	ga_ls9c_ard_3-2-1_090082_2022-02-14_final.stac-item
2022-02-25 09:57:51	ga_ls9c_ard_3-2-1_096085_2022-02-25_final.stac-item
2022-02-27 11:20:46	ga_ls9c_ard_3-2-1_110076_2022-02-27_final.stac-item
2022-03-06 11:29:42	ga_ls9c_ard_3-2-1_111083_2022-03-06_final.stac-item
2022-03-11 11:45:03	ga_ls9c_ard_3-2-1_114075_2022-03-11_final.stac-item
2022-03-24 11:13:18	ga_ls9c_ard_3-2-1_109073_2022-03-24_final.stac-item
2022-03-26 11:04:54	ga_ls9c_ard_3-2-1_107083_2022-03-26_final.stac-item
2022-04-06 09:07:28	ga_ls9c_ard_3-2-1_088083_2022-04-05_final.stac-item
2022-04-11 10:59:40	ga_ls9c_ard_3-2-1_107070_2022-04-11_final.stac-item
2022-04-14 11:36:07	ga_ls9c_ard_3-2-1_112084_2022-04-14_final.stac-item
2022-04-16 09:44:03	ga_ls9c_ard_3-2-1_094082_2022-04-16_final.stac-item
2022-04-18 11:09:21	ga_ls9c_ard_3-2-1_108079_2022-04-18_final.stac-item
2022-04-18 11:11:20	ga_ls9c_ard_3-2-1_108084_2022-04-18_final.stac-item
2022-04-25 11:12:41	ga_ls9c_ard_3-2-1_109072_2022-04-25_final.stac-item
2022-05-02 09:43:09	ga_ls9c_ard_3-2-1_094080_2022-05-02_final.stac-item
2022-05-09 11:26:09	ga_ls9c_ard_3-2-1_111075_2022-05-09_final.stac-item
2022-05-27 11:16:01	ga_ls9c_ard_3-2-1_109081_2022-05-27_final.stac-item
2022-06-03 09:40:09	ga_ls9c_ard_3-2-1_094073_2022-06-03_final.stac-item
2022-06-09 09:07:04	ga_ls9c_ard_3-2-1_088083_2022-06-08_final.stac-item
2022-06-11 10:30:01	ga_ls9c_ard_3-2-1_102074_2022-06-11_final.stac-item
2022-06-23 10:54:37	ga_ls9c_ard_3-2-1_106073_2022-06-23_final.stac-item
2022-06-28 11:13:12	ga_ls9c_ard_3-2-1_109073_2022-06-28_final.stac-item
2022-07-08 10:09:22	ga_ls9c_ard_3-2-1_099068_2022-07-08_final.stac-item
2022-07-08 10:12:34	ga_ls9c_ard_3-2-1_099076_2022-07-08_final.stac-item
2022-07-13 10:30:40	ga_ls9c_ard_3-2-1_102075_2022-07-13_final.stac-item
2022-08-01 11:05:01	ga_ls9c_ard_3-2-1_107083_2022-08-01_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-14 10:31:51	ga_ls9c_ard_3-2-1_102077_2022-08-14_final.stac-item
2022-09-03 11:46:03	ga_ls9c_ard_3-2-1_114077_2022-09-03_final.stac-item
2022-09-09 09:32:04	ga_ls9c_ard_3-2-1_092082_2022-09-09_final.stac-item
2022-09-10 10:14:57	ga_ls9c_ard_3-2-1_099081_2022-09-10_final.stac-item
2022-09-11 10:54:14	ga_ls9c_ard_3-2-1_106071_2022-09-11_final.stac-item
2022-09-16 09:33:56	ga_ls9c_ard_3-2-1_093071_2022-09-16_final.stac-item
2022-09-16 09:37:32	ga_ls9c_ard_3-2-1_093080_2022-09-16_final.stac-item
2022-09-25 09:29:01	ga_ls9c_ard_3-2-1_092074_2022-09-24_final.stac-item
2022-10-11 09:30:15	ga_ls9c_ard_3-2-1_092077_2022-10-11_final.stac-item
2022-10-27 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-10-27_final.stac-item
2022-11-01 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-11-01_final.stac-item
2022-11-05 09:27:17	ga_ls9c_ard_3-2-1_091085_2022-11-04_final.stac-item
2022-11-10 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-10_final.stac-item
2022-11-12 11:07:37	ga_ls9c_ard_3-2-1_108073_2022-11-12_final.stac-item
2022-11-13 10:12:47	ga_ls9c_ard_3-2-1_099075_2022-11-13_final.stac-item
2022-11-26 09:44:16	ga_ls9c_ard_3-2-1_094081_2022-11-26_final.stac-item
2022-11-30 09:20:42	ga_ls9c_ard_3-2-1_090084_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
2022-12-16 10:55:14	ga_ls9c_ard_3-2-1_106073_2022-12-16_final.stac-item
2022-12-23 09:22:05	ga_ls9c_ard_3-2-1_091072_2022-12-22_final.stac-item
2022-12-31 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-12-31_final.stac-item
2023-01-04 11:29:44	ga_ls9c_ard_3-2-1_111082_2023-01-04_final.stac-item
2023-01-11 09:53:25	ga_ls9c_ard_3-2-1_096073_2023-01-11_final.stac-item
2023-01-15 11:11:07	ga_ls9c_ard_3-2-1_108082_2023-01-15_final.stac-item
2023-01-22 11:12:50	ga_ls9c_ard_3-2-1_109071_2023-01-22_final.stac-item
2023-01-24 09:28:25	ga_ls9c_ard_3-2-1_091088_2023-01-23_final.stac-item
2023-02-01 10:12:23	ga_ls9c_ard_3-2-1_099074_2023-02-01_final.stac-item
2023-02-17 10:09:33	ga_ls9c_ard_3-2-1_099067_2023-02-17_final.stac-item
2023-02-19 10:04:20	ga_ls9c_ard_3-2-1_097085_2023-02-19_final.stac-item
2023-03-05 10:15:20	ga_ls9c_ard_3-2-1_099082_2023-03-05_final.stac-item
2023-03-15 09:16:16	ga_ls9c_ard_3-2-1_089089_2023-03-14_final.stac-item
2023-03-18 11:18:27	ga_ls9c_ard_3-2-1_110070_2023-03-18_final.stac-item
2023-03-30 10:02:54	ga_ls9c_ard_3-2-1_098067_2023-03-30_final.stac-item
2023-04-04 10:25:50	ga_ls9c_ard_3-2-1_101078_2023-04-04_final.stac-item
2023-04-12 09:34:44	ga_ls9c_ard_3-2-1_093074_2023-04-12_final.stac-item
2023-04-16 09:12:22	ga_ls9c_ard_3-2-1_089080_2023-04-15_final.stac-item
2023-04-18 10:36:30	ga_ls9c_ard_3-2-1_103074_2023-04-18_final.stac-item
2023-04-19 09:43:40	ga_ls9c_ard_3-2-1_094081_2023-04-19_final.stac-item
2023-05-02 10:51:30	ga_ls9c_ard_3-2-1_105081_2023-05-02_final.stac-item
2023-05-05 11:23:32	ga_ls9c_ard_3-2-1_110084_2023-05-05_final.stac-item
2023-05-07 11:09:59	ga_ls9c_ard_3-2-1_108081_2023-05-07_final.stac-item
2023-05-11 10:40:04	ga_ls9c_ard_3-2-1_104068_2023-05-11_final.stac-item
2023-05-14 09:34:28	ga_ls9c_ard_3-2-1_093074_2023-05-14_final.stac-item
2023-05-15 10:17:19	ga_ls9c_ard_3-2-1_100073_2023-05-15_final.stac-item
2023-05-16 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-05-15_final.stac-item
2023-05-16 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-05-16_final.stac-item
2023-05-20 10:35:48	ga_ls9c_ard_3-2-1_103073_2023-05-20_final.stac-item
2023-05-23 09:32:33	ga_ls9c_ard_3-2-1_092085_2023-05-23_final.stac-item
2023-05-26 09:57:50	ga_ls9c_ard_3-2-1_097071_2023-05-26_final.stac-item
2023-06-05 10:36:06	ga_ls9c_ard_3-2-1_103074_2023-06-05_final.stac-item
2023-06-15 11:16:38	ga_ls9c_ard_3-2-1_109083_2023-06-15_final.stac-item
2023-06-20 09:51:07	ga_ls9c_ard_3-2-1_096070_2023-06-20_final.stac-item
2023-06-27 11:40:12	ga_ls9c_ard_3-2-1_113080_2023-06-27_final.stac-item
2023-06-28 10:44:36	ga_ls9c_ard_3-2-1_104080_2023-06-28_final.stac-item
2023-07-01 11:16:47	ga_ls9c_ard_3-2-1_109083_2023-07-01_final.stac-item
2023-07-03 09:25:34	ga_ls9c_ard_3-2-1_091083_2023-07-02_final.stac-item
2023-07-04 11:46:08	ga_ls9c_ard_3-2-1_114079_2023-07-04_final.stac-item
2023-07-10 09:29:02	ga_ls9c_ard_3-2-1_092076_2023-07-09_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-07-13 09:59:57	ga_ls9c_ard_3-2-1_097076_2023-07-13_final.stac-item
2023-07-17 11:12:56	ga_ls9c_ard_3-2-1_109073_2023-07-17_final.stac-item
2023-08-10 10:24:27	ga_ls9c_ard_3-2-1_101075_2023-08-10_final.stac-item
2023-10-26 11:35:41	ga_ls9c_ard_3-2-1_112082_2023-10-26_final.stac-item
2023-10-27 10:34:52	ga_ls9c_ard_3-2-1_103069_2023-10-27_final.stac-item
2023-10-30 11:05:44	ga_ls9c_ard_3-2-1_108069_2023-10-30_final.stac-item
2023-11-15 11:06:31	ga_ls9c_ard_3-2-1_108071_2023-11-15_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-28 10:38:33	ga_ls9c_ard_3-2-1_103078_2023-11-28_final.stac-item
2023-11-29 11:23:01	ga_ls9c_ard_3-2-1_110081_2023-11-29_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