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
2021-11-08 11:36:06	ga_ls9c_ard_3-2-1_113075_2021-11-08_final.stac-item
2021-11-13 11:40:57	ga_ls9c_ard_3-2-1_113081_2021-11-13_final.stac-item
2021-11-22 11:02:44	ga_ls9c_ard_3-2-1_107073_2021-11-22_final.stac-item
2021-12-11 09:31:23	ga_ls9c_ard_3-2-1_092080_2021-12-11_final.stac-item
2021-12-16 11:29:33	ga_ls9c_ard_3-2-1_111082_2021-12-16_final.stac-item
2021-12-18 11:15:36	ga_ls9c_ard_3-2-1_109078_2021-12-18_final.stac-item
2021-12-25 09:45:42	ga_ls9c_ard_3-2-1_094085_2021-12-25_final.stac-item
2021-12-27 11:10:38	ga_ls9c_ard_3-2-1_108081_2021-12-27_final.stac-item
2021-12-29 09:21:47	ga_ls9c_ard_3-2-1_090087_2021-12-28_final.stac-item
2022-01-12 11:10:35	ga_ls9c_ard_3-2-1_108081_2022-01-12_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-01-29 10:15:23	ga_ls9c_ard_3-2-1_099082_2022-01-29_final.stac-item
2022-01-30 09:18:58	ga_ls9c_ard_3-2-1_090080_2022-01-29_final.stac-item
2022-02-13 09:33:40	ga_ls9c_ard_3-2-1_092086_2022-02-13_final.stac-item
2022-02-13 11:08:34	ga_ls9c_ard_3-2-1_108076_2022-02-13_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-02-21 10:21:02	ga_ls9c_ard_3-2-1_100081_2022-02-21_final.stac-item
2022-02-24 10:47:30	ga_ls9c_ard_3-2-1_105070_2022-02-24_final.stac-item
2022-03-31 09:45:21	ga_ls9c_ard_3-2-1_094085_2022-03-31_final.stac-item
2022-04-10 10:20:48	ga_ls9c_ard_3-2-1_100081_2022-04-10_final.stac-item
2022-04-15 10:36:05	ga_ls9c_ard_3-2-1_103073_2022-04-15_final.stac-item
2022-04-25 09:38:35	ga_ls9c_ard_3-2-1_093084_2022-04-25_final.stac-item
2022-05-03 10:24:01	ga_ls9c_ard_3-2-1_101074_2022-05-03_final.stac-item
2022-05-06 10:54:29	ga_ls9c_ard_3-2-1_106073_2022-05-06_final.stac-item
2022-05-07 09:58:03	ga_ls9c_ard_3-2-1_097071_2022-05-07_final.stac-item
2022-05-22 10:53:54	ga_ls9c_ard_3-2-1_106072_2022-05-22_final.stac-item
2022-06-13 10:17:18	ga_ls9c_ard_3-2-1_100073_2022-06-13_final.stac-item
2022-06-14 11:03:46	ga_ls9c_ard_3-2-1_107081_2022-06-14_final.stac-item
2022-07-08 10:11:46	ga_ls9c_ard_3-2-1_099074_2022-07-08_final.stac-item
2022-07-14 11:11:56	ga_ls9c_ard_3-2-1_109070_2022-07-14_final.stac-item
2022-07-23 09:31:24	ga_ls9c_ard_3-2-1_092081_2022-07-23_final.stac-item
2022-08-03 09:16:12	ga_ls9c_ard_3-2-1_089089_2022-08-02_final.stac-item
2022-08-12 10:43:24	ga_ls9c_ard_3-2-1_104075_2022-08-12_final.stac-item
2022-08-21 10:34:52	ga_ls9c_ard_3-2-1_103069_2022-08-21_final.stac-item
2022-08-25 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-08-25_final.stac-item
2022-09-27 09:18:39	ga_ls9c_ard_3-2-1_090079_2022-09-26_final.stac-item
2022-10-02 11:14:05	ga_ls9c_ard_3-2-1_109074_2022-10-02_final.stac-item
2022-10-13 10:58:00	ga_ls9c_ard_3-2-1_106080_2022-10-13_final.stac-item
2022-10-19 10:21:45	ga_ls9c_ard_3-2-1_100082_2022-10-19_final.stac-item
2022-11-01 09:46:26	ga_ls9c_ard_3-2-1_095071_2022-11-01_final.stac-item
2022-11-06 11:45:51	ga_ls9c_ard_3-2-1_114076_2022-11-06_final.stac-item
2022-11-09 10:37:30	ga_ls9c_ard_3-2-1_103075_2022-11-09_final.stac-item
2022-11-10 11:18:46	ga_ls9c_ard_3-2-1_110070_2022-11-10_final.stac-item
2022-11-23 10:47:28	ga_ls9c_ard_3-2-1_105069_2022-11-23_final.stac-item
2022-11-25 10:36:42	ga_ls9c_ard_3-2-1_103073_2022-11-25_final.stac-item
2022-11-26 09:43:28	ga_ls9c_ard_3-2-1_094079_2022-11-26_final.stac-item
2022-12-03 09:48:25	ga_ls9c_ard_3-2-1_095076_2022-12-03_final.stac-item
2022-12-03 11:27:18	ga_ls9c_ard_3-2-1_111076_2022-12-03_final.stac-item
2022-12-10 09:53:26	ga_ls9c_ard_3-2-1_096073_2022-12-10_final.stac-item
2022-12-12 09:42:16	ga_ls9c_ard_3-2-1_094076_2022-12-12_final.stac-item
2022-12-19 09:48:02	ga_ls9c_ard_3-2-1_095075_2022-12-19_final.stac-item
2022-12-27 10:39:27	ga_ls9c_ard_3-2-1_103080_2022-12-27_final.stac-item
2022-12-29 10:26:43	ga_ls9c_ard_3-2-1_101079_2022-12-29_final.stac-item
2022-12-30 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-12-30_final.stac-item
2023-01-02 11:42:29	ga_ls9c_ard_3-2-1_113083_2023-01-02_final.stac-item
2023-01-06 09:38:05	ga_ls9c_ard_3-2-1_093081_2023-01-06_final.stac-item
2023-01-12 10:35:52	ga_ls9c_ard_3-2-1_103071_2023-01-12_final.stac-item
2023-01-13 11:24:42	ga_ls9c_ard_3-2-1_110085_2023-01-13_final.stac-item
2023-01-19 10:43:56	ga_ls9c_ard_3-2-1_104076_2023-01-19_final.stac-item
2023-01-20 11:29:34	ga_ls9c_ard_3-2-1_111082_2023-01-20_final.stac-item
2023-01-22 11:16:02	ga_ls9c_ard_3-2-1_109079_2023-01-22_final.stac-item
2023-01-27 09:53:47	ga_ls9c_ard_3-2-1_096074_2023-01-27_final.stac-item
2023-02-04 10:44:55	ga_ls9c_ard_3-2-1_104078_2023-02-04_final.stac-item
2023-02-06 10:31:46	ga_ls9c_ard_3-2-1_102076_2023-02-06_final.stac-item
2023-02-24 10:21:10	ga_ls9c_ard_3-2-1_100081_2023-02-24_final.stac-item
2023-03-02 11:20:09	ga_ls9c_ard_3-2-1_110074_2023-03-02_final.stac-item
2023-03-13 09:27:25	ga_ls9c_ard_3-2-1_091086_2023-03-12_final.stac-item
2023-04-05 11:09:53	ga_ls9c_ard_3-2-1_108080_2023-04-05_final.stac-item
2023-04-06 10:12:16	ga_ls9c_ard_3-2-1_099075_2023-04-06_final.stac-item
2023-04-07 10:57:31	ga_ls9c_ard_3-2-1_106080_2023-04-07_final.stac-item
2023-04-09 10:45:08	ga_ls9c_ard_3-2-1_104080_2023-04-09_final.stac-item
2023-04-12 09:36:19	ga_ls9c_ard_3-2-1_093078_2023-04-12_final.stac-item
2023-04-12 09:37:31	ga_ls9c_ard_3-2-1_093081_2023-04-12_final.stac-item
2023-04-24 10:00:59	ga_ls9c_ard_3-2-1_097078_2023-04-24_final.stac-item
2023-04-28 11:12:42	ga_ls9c_ard_3-2-1_109072_2023-04-28_final.stac-item
2023-04-30 11:02:42	ga_ls9c_ard_3-2-1_107078_2023-04-30_final.stac-item
2023-05-01 11:46:44	ga_ls9c_ard_3-2-1_114080_2023-05-01_final.stac-item
2023-05-15 10:21:42	ga_ls9c_ard_3-2-1_100084_2023-05-15_final.stac-item
2023-05-16 10:59:22	ga_ls9c_ard_3-2-1_107070_2023-05-16_final.stac-item
2023-05-22 10:24:12	ga_ls9c_ard_3-2-1_101075_2023-05-22_final.stac-item
2023-06-22 09:44:20	ga_ls9c_ard_3-2-1_094084_2023-06-22_final.stac-item
2023-06-23 10:26:24	ga_ls9c_ard_3-2-1_101081_2023-06-23_final.stac-item
2023-06-24 09:28:47	ga_ls9c_ard_3-2-1_092076_2023-06-23_final.stac-item
2023-06-29 09:46:37	ga_ls9c_ard_3-2-1_095074_2023-06-29_final.stac-item
2023-06-29 09:51:01	ga_ls9c_ard_3-2-1_095085_2023-06-29_final.stac-item
2023-06-29 11:26:18	ga_ls9c_ard_3-2-1_111076_2023-06-29_final.stac-item
2023-06-29 11:28:18	ga_ls9c_ard_3-2-1_111081_2023-06-29_final.stac-item
2023-07-01 11:16:23	ga_ls9c_ard_3-2-1_109082_2023-07-01_final.stac-item
2023-07-30 10:45:41	ga_ls9c_ard_3-2-1_104082_2023-07-30_final.stac-item
2023-08-14 11:40:37	ga_ls9c_ard_3-2-1_113080_2023-08-14_final.stac-item
2023-08-17 10:30:37	ga_ls9c_ard_3-2-1_102075_2023-08-17_final.stac-item
2023-10-14 11:07:46	ga_ls9c_ard_3-2-1_108074_2023-10-14_final.stac-item
2023-10-16 10:57:49	ga_ls9c_ard_3-2-1_106080_2023-10-16_final.stac-item
2023-10-20 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-10-20_final.stac-item
2023-10-25 09:15:09	ga_ls9c_ard_3-2-1_089086_2023-10-24_final.stac-item
2023-10-26 09:54:48	ga_ls9c_ard_3-2-1_096077_2023-10-26_final.stac-item
2023-10-30 11:11:43	ga_ls9c_ard_3-2-1_108084_2023-10-30_final.stac-item
2023-11-02 11:38:58	ga_ls9c_ard_3-2-1_113075_2023-11-02_final.stac-item
2023-11-02 11:41:46	ga_ls9c_ard_3-2-1_113082_2023-11-02_final.stac-item
2023-11-15 09:31:37	ga_ls9c_ard_3-2-1_092081_2023-11-15_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