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

82 results

Time (local)	Label
2021-11-16 10:24:18	ga_ls9c_ard_3-2-1_100083_2021-11-16_final.stac-item
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-04 11:05:46	ga_ls9c_ard_3-2-1_107084_2021-12-04_final.stac-item
2021-12-05 11:47:25	ga_ls9c_ard_3-2-1_114080_2021-12-05_final.stac-item
2021-12-14 09:58:16	ga_ls9c_ard_3-2-1_097070_2021-12-14_final.stac-item
2021-12-16 09:50:40	ga_ls9c_ard_3-2-1_095082_2021-12-16_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2021-12-22 09:11:36	ga_ls9c_ard_3-2-1_089077_2021-12-21_final.stac-item
2021-12-29 09:22:59	ga_ls9c_ard_3-2-1_090090_2021-12-28_final.stac-item
2022-01-01 11:27:10	ga_ls9c_ard_3-2-1_111076_2022-01-01_final.stac-item
2022-01-05 09:25:09	ga_ls9c_ard_3-2-1_091080_2022-01-04_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-13 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-01-13_final.stac-item
2022-02-22 09:26:12	ga_ls9c_ard_3-2-1_091083_2022-02-21_final.stac-item
2022-03-21 09:07:07	ga_ls9c_ard_3-2-1_088082_2022-03-20_final.stac-item
2022-03-29 09:52:56	ga_ls9c_ard_3-2-1_096073_2022-03-29_final.stac-item
2022-03-31 11:19:51	ga_ls9c_ard_3-2-1_110074_2022-03-31_final.stac-item
2022-04-06 10:40:22	ga_ls9c_ard_3-2-1_104068_2022-04-06_final.stac-item
2022-04-19 10:16:06	ga_ls9c_ard_3-2-1_099085_2022-04-19_final.stac-item
2022-05-12 10:18:08	ga_ls9c_ard_3-2-1_100075_2022-05-12_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-06-01 11:35:47	ga_ls9c_ard_3-2-1_112084_2022-06-01_final.stac-item
2022-06-09 09:06:40	ga_ls9c_ard_3-2-1_088082_2022-06-08_final.stac-item
2022-06-24 11:41:06	ga_ls9c_ard_3-2-1_113081_2022-06-24_final.stac-item
2022-07-05 09:46:04	ga_ls9c_ard_3-2-1_094087_2022-07-05_final.stac-item
2022-07-14 11:12:43	ga_ls9c_ard_3-2-1_109072_2022-07-14_final.stac-item
2022-07-17 10:04:23	ga_ls9c_ard_3-2-1_098071_2022-07-17_final.stac-item
2022-07-25 10:58:21	ga_ls9c_ard_3-2-1_106082_2022-07-25_final.stac-item
2022-07-28 09:51:12	ga_ls9c_ard_3-2-1_095084_2022-07-28_final.stac-item
2022-08-09 10:09:41	ga_ls9c_ard_3-2-1_099068_2022-08-09_final.stac-item
2022-08-13 11:25:52	ga_ls9c_ard_3-2-1_111073_2022-08-13_final.stac-item
2022-08-28 09:07:22	ga_ls9c_ard_3-2-1_088082_2022-08-27_final.stac-item
2022-09-07 09:45:38	ga_ls9c_ard_3-2-1_094085_2022-09-07_final.stac-item
2022-09-25 11:07:54	ga_ls9c_ard_3-2-1_108074_2022-09-25_final.stac-item
2022-10-05 11:46:34	ga_ls9c_ard_3-2-1_114078_2022-10-05_final.stac-item
2022-10-16 11:25:44	ga_ls9c_ard_3-2-1_111072_2022-10-16_final.stac-item
2022-10-23 09:52:39	ga_ls9c_ard_3-2-1_096071_2022-10-23_final.stac-item
2022-10-26 10:23:32	ga_ls9c_ard_3-2-1_101071_2022-10-26_final.stac-item
2022-11-11 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-11-11_final.stac-item
2022-11-27 10:26:19	ga_ls9c_ard_3-2-1_101078_2022-11-27_final.stac-item
2022-12-05 09:35:40	ga_ls9c_ard_3-2-1_093075_2022-12-05_final.stac-item
2023-01-01 09:18:21	ga_ls9c_ard_3-2-1_090078_2022-12-31_final.stac-item
2023-01-03 10:45:16	ga_ls9c_ard_3-2-1_104079_2023-01-03_final.stac-item
2023-02-10 10:09:51	ga_ls9c_ard_3-2-1_098083_2023-02-10_final.stac-item
2023-02-25 09:27:56	ga_ls9c_ard_3-2-1_091087_2023-02-24_final.stac-item
2023-02-27 10:49:40	ga_ls9c_ard_3-2-1_105075_2023-02-27_final.stac-item
2023-03-02 09:41:16	ga_ls9c_ard_3-2-1_094074_2023-03-02_final.stac-item
2023-04-09 09:06:39	ga_ls9c_ard_3-2-1_088081_2023-04-08_final.stac-item
2023-04-14 11:00:25	ga_ls9c_ard_3-2-1_107072_2023-04-14_final.stac-item
2023-04-15 10:09:58	ga_ls9c_ard_3-2-1_098085_2023-04-15_final.stac-item
2023-04-30 09:28:36	ga_ls9c_ard_3-2-1_091090_2023-04-29_final.stac-item
2023-05-01 11:44:21	ga_ls9c_ard_3-2-1_114074_2023-05-01_final.stac-item
2023-05-16 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-05-16_final.stac-item
2023-05-21 11:19:02	ga_ls9c_ard_3-2-1_110073_2023-05-21_final.stac-item
2023-06-25 11:52:07	ga_ls9c_ard_3-2-1_115079_2023-06-25_final.stac-item
2023-07-12 10:54:22	ga_ls9c_ard_3-2-1_106073_2023-07-12_final.stac-item
2023-07-25 10:25:03	ga_ls9c_ard_3-2-1_101077_2023-07-25_final.stac-item
2023-07-25 10:26:39	ga_ls9c_ard_3-2-1_101081_2023-07-25_final.stac-item
2023-07-27 10:13:56	ga_ls9c_ard_3-2-1_099080_2023-07-27_final.stac-item
2023-07-28 09:22:19	ga_ls9c_ard_3-2-1_090090_2023-07-27_final.stac-item
2023-08-04 09:26:12	ga_ls9c_ard_3-2-1_091084_2023-08-03_final.stac-item
2023-08-13 09:20:28	ga_ls9c_ard_3-2-1_090085_2023-08-12_final.stac-item
2023-09-20 10:21:46	ga_ls9c_ard_3-2-1_100083_2023-09-20_final.stac-item
2023-09-23 09:12:34	ga_ls9c_ard_3-2-1_089080_2023-09-22_final.stac-item
2023-10-20 10:31:55	ga_ls9c_ard_3-2-1_102077_2023-10-20_final.stac-item
2023-10-26 09:53:12	ga_ls9c_ard_3-2-1_096073_2023-10-26_final.stac-item
2023-11-09 10:03:55	ga_ls9c_ard_3-2-1_098069_2023-11-09_final.stac-item
2023-11-20 09:51:50	ga_ls9c_ard_3-2-1_095085_2023-11-20_final.stac-item
2023-12-02 10:09:49	ga_ls9c_ard_3-2-1_099068_2023-12-02_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-12 09:13:35	ga_ls9c_ard_3-2-1_089082_2023-12-11_final.stac-item
2023-12-20 11:38:47	ga_ls9c_ard_3-2-1_113074_2023-12-20_final.stac-item
2023-12-29 09:52:54	ga_ls9c_ard_3-2-1_096072_2023-12-29_final.stac-item
2024-01-15 10:37:43	ga_ls9c_ard_3-2-1_103076_2024-01-15_final.stac-item
2024-01-27 09:25:07	ga_ls9c_ard_3-2-1_091080_2024-01-26_final.stac-item
2024-02-26 09:33:45	ga_ls9c_ard_3-2-1_093071_2024-02-26_final.stac-item
2024-03-04 09:41:12	ga_ls9c_ard_3-2-1_094074_2024-03-04_final.stac-item
2024-03-04 11:18:05	ga_ls9c_ard_3-2-1_110069_2024-03-04_final.stac-item
2024-03-14 10:21:27	ga_ls9c_ard_3-2-1_100082_2024-03-14_final.stac-item
2024-03-25 11:42:08	ga_ls9c_ard_3-2-1_113083_2024-03-25_final.stac-item
2024-04-22 10:24:46	ga_ls9c_ard_3-2-1_101076_2024-04-22_final.stac-item
2024-04-24 10:10:44	ga_ls9c_ard_3-2-1_099072_2024-04-24_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