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
2021-11-05 09:37:25	ga_ls9c_ard_3-2-1_093078_2021-11-05_final.stac-item
2021-11-16 10:19:55	ga_ls9c_ard_3-2-1_100072_2021-11-16_final.stac-item
2021-11-18 10:00:46	ga_ls9c_ard_3-2-1_097071_2021-11-18_final.stac-item
2022-01-19 09:35:06	ga_ls9c_ard_3-2-1_093074_2022-01-19_final.stac-item
2022-02-25 09:52:40	ga_ls9c_ard_3-2-1_096072_2022-02-25_final.stac-item
2022-03-26 09:23:38	ga_ls9c_ard_3-2-1_091077_2022-03-25_final.stac-item
2022-05-04 11:05:16	ga_ls9c_ard_3-2-1_108069_2022-05-04_final.stac-item
2022-05-06 09:20:47	ga_ls9c_ard_3-2-1_090086_2022-05-05_final.stac-item
2022-05-13 09:26:06	ga_ls9c_ard_3-2-1_091084_2022-05-12_final.stac-item
2022-06-07 09:20:38	ga_ls9c_ard_3-2-1_090086_2022-06-06_final.stac-item
2022-06-29 10:21:34	ga_ls9c_ard_3-2-1_100083_2022-06-29_final.stac-item
2022-07-12 09:52:12	ga_ls9c_ard_3-2-1_095087_2022-07-12_final.stac-item
2022-07-18 09:13:34	ga_ls9c_ard_3-2-1_089083_2022-07-17_final.stac-item
2022-07-23 09:33:47	ga_ls9c_ard_3-2-1_092087_2022-07-23_final.stac-item
2022-08-01 09:24:56	ga_ls9c_ard_3-2-1_091080_2022-07-31_final.stac-item
2022-08-10 09:19:15	ga_ls9c_ard_3-2-1_090081_2022-08-09_final.stac-item
2022-08-17 09:25:05	ga_ls9c_ard_3-2-1_091080_2022-08-16_final.stac-item
2022-08-31 11:12:22	ga_ls9c_ard_3-2-1_109070_2022-08-31_final.stac-item
2022-09-28 09:58:20	ga_ls9c_ard_3-2-1_097070_2022-09-28_final.stac-item
2022-10-11 11:08:21	ga_ls9c_ard_3-2-1_108075_2022-10-11_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_2022-10-12_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-14_final.stac-item
2022-10-26 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-10-26_final.stac-item
2022-10-27 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-10-26_final.stac-item
2022-10-27 11:06:48	ga_ls9c_ard_3-2-1_108071_2022-10-27_final.stac-item
2022-11-01 09:46:50	ga_ls9c_ard_3-2-1_095072_2022-11-01_final.stac-item
2022-11-03 11:12:32	ga_ls9c_ard_3-2-1_109070_2022-11-03_final.stac-item
2022-11-10 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-11-10_final.stac-item
2022-11-19 09:34:07	ga_ls9c_ard_3-2-1_093071_2022-11-19_final.stac-item
2022-11-19 11:13:48	ga_ls9c_ard_3-2-1_109073_2022-11-19_final.stac-item
2022-11-22 11:45:53	ga_ls9c_ard_3-2-1_114076_2022-11-22_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-12-01 09:59:34	ga_ls9c_ard_3-2-1_097073_2022-12-01_final.stac-item
2022-12-02 10:44:02	ga_ls9c_ard_3-2-1_104076_2022-12-02_final.stac-item
2022-12-02 10:44:49	ga_ls9c_ard_3-2-1_104078_2022-12-02_final.stac-item
2022-12-03 09:46:49	ga_ls9c_ard_3-2-1_095072_2022-12-03_final.stac-item
2022-12-10 11:35:54	ga_ls9c_ard_3-2-1_112082_2022-12-10_final.stac-item
2022-12-12 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-12-12_final.stac-item
2022-12-14 09:29:31	ga_ls9c_ard_3-2-1_092075_2022-12-13_final.stac-item
2022-12-17 09:57:13	ga_ls9c_ard_3-2-1_097067_2022-12-17_final.stac-item
2022-12-21 09:40:51	ga_ls9c_ard_3-2-1_093088_2022-12-21_final.stac-item
2022-12-23 09:24:04	ga_ls9c_ard_3-2-1_091077_2022-12-22_final.stac-item
2022-12-23 09:28:28	ga_ls9c_ard_3-2-1_091088_2022-12-22_final.stac-item
2022-12-23 11:05:21	ga_ls9c_ard_3-2-1_107083_2022-12-23_final.stac-item
2022-12-25 10:52:36	ga_ls9c_ard_3-2-1_105082_2022-12-25_final.stac-item
2022-12-26 11:33:05	ga_ls9c_ard_3-2-1_112075_2022-12-26_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_2022-12-28_final.stac-item
2023-01-06 09:40:53	ga_ls9c_ard_3-2-1_093088_2023-01-06_final.stac-item
2023-01-08 09:25:19	ga_ls9c_ard_3-2-1_091080_2023-01-07_final.stac-item
2023-01-11 09:57:24	ga_ls9c_ard_3-2-1_096083_2023-01-11_final.stac-item
2023-01-22 11:13:38	ga_ls9c_ard_3-2-1_109073_2023-01-22_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-24 09:27:37	ga_ls9c_ard_3-2-1_091086_2023-01-23_final.stac-item
2023-01-26 09:15:18	ga_ls9c_ard_3-2-1_089086_2023-01-25_final.stac-item
2023-01-27 11:36:16	ga_ls9c_ard_3-2-1_112083_2023-01-27_final.stac-item
2023-01-29 09:41:03	ga_ls9c_ard_3-2-1_094073_2023-01-29_final.stac-item
2023-01-31 09:31:55	ga_ls9c_ard_3-2-1_092081_2023-01-31_final.stac-item
2023-01-31 11:06:00	ga_ls9c_ard_3-2-1_108069_2023-01-31_final.stac-item
2023-01-31 11:06:24	ga_ls9c_ard_3-2-1_108070_2023-01-31_final.stac-item
2023-02-02 10:54:52	ga_ls9c_ard_3-2-1_106072_2023-02-02_final.stac-item
2023-02-06 10:29:22	ga_ls9c_ard_3-2-1_102070_2023-02-06_final.stac-item
2023-02-07 11:12:38	ga_ls9c_ard_3-2-1_109070_2023-02-07_final.stac-item
2023-02-10 10:03:51	ga_ls9c_ard_3-2-1_098068_2023-02-10_final.stac-item
2023-04-25 09:06:33	ga_ls9c_ard_3-2-1_088081_2023-04-24_final.stac-item
2023-05-01 11:44:45	ga_ls9c_ard_3-2-1_114075_2023-05-01_final.stac-item
2023-07-05 10:51:43	ga_ls9c_ard_3-2-1_105082_2023-07-05_final.stac-item
2023-07-17 11:14:08	ga_ls9c_ard_3-2-1_109076_2023-07-17_final.stac-item
2023-07-22 09:57:22	ga_ls9c_ard_3-2-1_096085_2023-07-22_final.stac-item
2023-07-24 11:18:17	ga_ls9c_ard_3-2-1_110071_2023-07-24_final.stac-item
2023-07-27 11:51:37	ga_ls9c_ard_3-2-1_115077_2023-07-27_final.stac-item
2023-07-27 11:52:25	ga_ls9c_ard_3-2-1_115079_2023-07-27_final.stac-item
2023-07-29 10:01:13	ga_ls9c_ard_3-2-1_097079_2023-07-29_final.stac-item
2023-08-04 11:01:30	ga_ls9c_ard_3-2-1_107075_2023-08-04_final.stac-item
2023-08-06 09:14:40	ga_ls9c_ard_3-2-1_089086_2023-08-05_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-10-21 11:12:47	ga_ls9c_ard_3-2-1_109071_2023-10-21_final.stac-item
2023-10-22 11:58:26	ga_ls9c_ard_3-2-1_116077_2023-10-22_final.stac-item
2023-10-23 09:23:31	ga_ls9c_ard_3-2-1_091076_2023-10-22_final.stac-item
2023-10-23 11:00:49	ga_ls9c_ard_3-2-1_107072_2023-10-23_final.stac-item
2023-10-24 10:05:11	ga_ls9c_ard_3-2-1_098072_2023-10-24_final.stac-item
2023-10-29 10:27:40	ga_ls9c_ard_3-2-1_101082_2023-10-29_final.stac-item
2023-10-30 09:34:02	ga_ls9c_ard_3-2-1_092087_2023-10-30_final.stac-item
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final.stac-item
2023-11-01 09:20:50	ga_ls9c_ard_3-2-1_090085_2023-10-31_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-01 10:55:20	ga_ls9c_ard_3-2-1_106074_2023-11-01_final.stac-item
2023-11-01 10:58:55	ga_ls9c_ard_3-2-1_106083_2023-11-01_final.stac-item
2023-11-02 09:59:41	ga_ls9c_ard_3-2-1_097074_2023-11-02_final.stac-item
2023-11-17 10:53:47	ga_ls9c_ard_3-2-1_106070_2023-11-17_final.stac-item
2023-11-17 10:54:11	ga_ls9c_ard_3-2-1_106071_2023-11-17_final.stac-item
2023-11-18 10:03:46	ga_ls9c_ard_3-2-1_097084_2023-11-18_final.stac-item
2023-11-20 09:47:03	ga_ls9c_ard_3-2-1_095073_2023-11-20_final.stac-item
2023-11-21 10:33:31	ga_ls9c_ard_3-2-1_102081_2023-11-21_final.stac-item
2023-11-22 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-11-22_final.stac-item
2023-11-22 11:13:36	ga_ls9c_ard_3-2-1_109073_2023-11-22_final.stac-item
2023-11-22 11:17:59	ga_ls9c_ard_3-2-1_109084_2023-11-22_final.stac-item
2023-11-25 10:07:14	ga_ls9c_ard_3-2-1_098077_2023-11-25_final.stac-item
2023-11-25 10:08:02	ga_ls9c_ard_3-2-1_098079_2023-11-25_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