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

95 results

Time (local)	Label
2021-11-02 10:54:51	ga_ls9c_ard_3-2-1_106078_2021-11-02_final.stac-item
2021-11-17 09:21:17	ga_ls9c_ard_3-2-1_091072_2021-11-16_final.stac-item
2021-11-20 11:21:29	ga_ls9c_ard_3-2-1_110073_2021-11-20_final.stac-item
2021-12-04 09:26:29	ga_ls9c_ard_3-2-1_091083_2021-12-03_final.stac-item
2021-12-13 09:22:36	ga_ls9c_ard_3-2-1_090089_2021-12-12_final.stac-item
2021-12-15 10:43:31	ga_ls9c_ard_3-2-1_104075_2021-12-15_final.stac-item
2021-12-16 09:52:16	ga_ls9c_ard_3-2-1_095086_2021-12-16_final.stac-item
2021-12-22 09:14:48	ga_ls9c_ard_3-2-1_089085_2021-12-21_final.stac-item
2021-12-27 09:32:57	ga_ls9c_ard_3-2-1_092084_2021-12-27_final.stac-item
2021-12-28 11:51:06	ga_ls9c_ard_3-2-1_115074_2021-12-28_final.stac-item
2021-12-29 09:22:59	ga_ls9c_ard_3-2-1_090090_2021-12-28_final.stac-item
2021-12-31 10:41:07	ga_ls9c_ard_3-2-1_104069_2021-12-31_final.stac-item
2022-01-11 10:27:19	ga_ls9c_ard_3-2-1_101081_2022-01-11_final.stac-item
2022-01-13 10:14:57	ga_ls9c_ard_3-2-1_099081_2022-01-13_final.stac-item
2022-01-14 10:53:49	ga_ls9c_ard_3-2-1_106070_2022-01-14_final.stac-item
2022-01-24 09:52:03	ga_ls9c_ard_3-2-1_096070_2022-01-24_final.stac-item
2022-02-01 10:40:42	ga_ls9c_ard_3-2-1_104068_2022-02-01_final.stac-item
2022-02-25 09:52:16	ga_ls9c_ard_3-2-1_096071_2022-02-25_final.stac-item
2022-03-12 09:14:32	ga_ls9c_ard_3-2-1_089085_2022-03-11_final.stac-item
2022-04-02 11:05:54	ga_ls9c_ard_3-2-1_108070_2022-04-02_final.stac-item
2022-04-10 10:21:36	ga_ls9c_ard_3-2-1_100083_2022-04-10_final.stac-item
2022-05-02 11:20:26	ga_ls9c_ard_3-2-1_110076_2022-05-02_final.stac-item
2022-05-31 10:46:32	ga_ls9c_ard_3-2-1_105069_2022-05-31_final.stac-item
2022-06-06 10:13:51	ga_ls9c_ard_3-2-1_099080_2022-06-06_final.stac-item
2022-06-09 09:05:52	ga_ls9c_ard_3-2-1_088080_2022-06-08_final.stac-item
2022-06-16 09:12:09	ga_ls9c_ard_3-2-1_089080_2022-06-15_final.stac-item
2022-06-27 10:28:21	ga_ls9c_ard_3-2-1_102069_2022-06-27_final.stac-item
2022-07-05 09:44:04	ga_ls9c_ard_3-2-1_094082_2022-07-05_final.stac-item
2022-07-07 11:07:00	ga_ls9c_ard_3-2-1_108073_2022-07-07_final.stac-item
2022-07-10 10:03:47	ga_ls9c_ard_3-2-1_097085_2022-07-10_final.stac-item
2022-07-18 10:50:03	ga_ls9c_ard_3-2-1_105077_2022-07-18_final.stac-item
2022-08-27 10:03:23	ga_ls9c_ard_3-2-1_097083_2022-08-27_final.stac-item
2022-09-12 10:02:13	ga_ls9c_ard_3-2-1_097080_2022-09-12_final.stac-item
2022-09-16 09:39:08	ga_ls9c_ard_3-2-1_093084_2022-09-16_final.stac-item
2022-09-20 09:16:50	ga_ls9c_ard_3-2-1_089090_2022-09-19_final.stac-item
2022-09-27 10:55:09	ga_ls9c_ard_3-2-1_106073_2022-09-27_final.stac-item
2022-09-27 10:58:44	ga_ls9c_ard_3-2-1_106082_2022-09-27_final.stac-item
2022-09-30 09:46:22	ga_ls9c_ard_3-2-1_095071_2022-09-30_final.stac-item
2022-10-04 11:04:07	ga_ls9c_ard_3-2-1_107080_2022-10-04_final.stac-item
2022-10-07 11:35:48	ga_ls9c_ard_3-2-1_112082_2022-10-07_final.stac-item
2022-10-16 11:25:20	ga_ls9c_ard_3-2-1_111071_2022-10-16_final.stac-item
2022-10-24 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-10-24_final.stac-item
2022-11-03 09:34:51	ga_ls9c_ard_3-2-1_093073_2022-11-03_final.stac-item
2022-11-03 11:14:08	ga_ls9c_ard_3-2-1_109074_2022-11-03_final.stac-item
2022-11-12 09:28:20	ga_ls9c_ard_3-2-1_092072_2022-11-11_final.stac-item
2022-11-15 09:59:38	ga_ls9c_ard_3-2-1_097073_2022-11-15_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_2022-11-26_final.stac-item
2022-12-02 10:41:14	ga_ls9c_ard_3-2-1_104069_2022-12-02_final.stac-item
2022-12-09 10:49:03	ga_ls9c_ard_3-2-1_105073_2022-12-09_final.stac-item
2022-12-11 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-12-11_final.stac-item
2022-12-19 09:50:49	ga_ls9c_ard_3-2-1_095082_2022-12-19_final.stac-item
2022-12-30 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-30_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-29 11:20:20	ga_ls9c_ard_3-2-1_110074_2023-01-29_final.stac-item
2023-03-15 09:14:16	ga_ls9c_ard_3-2-1_089084_2023-03-14_final.stac-item
2023-03-15 09:14:40	ga_ls9c_ard_3-2-1_089085_2023-03-14_final.stac-item
2023-04-14 09:27:55	ga_ls9c_ard_3-2-1_091088_2023-04-13_final.stac-item
2023-04-23 09:22:31	ga_ls9c_ard_3-2-1_090090_2023-04-22_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-05-13 10:28:54	ga_ls9c_ard_3-2-1_102071_2023-05-13_final.stac-item
2023-05-14 09:34:28	ga_ls9c_ard_3-2-1_093074_2023-05-14_final.stac-item
2023-05-16 10:59:46	ga_ls9c_ard_3-2-1_107071_2023-05-16_final.stac-item
2023-06-01 11:03:14	ga_ls9c_ard_3-2-1_107080_2023-06-01_final.stac-item
2023-06-04 09:57:38	ga_ls9c_ard_3-2-1_096086_2023-06-04_final.stac-item
2023-06-26 09:16:49	ga_ls9c_ard_3-2-1_090077_2023-06-25_final.stac-item
2023-07-21 09:13:43	ga_ls9c_ard_3-2-1_089084_2023-07-20_final.stac-item
2023-07-31 11:29:22	ga_ls9c_ard_3-2-1_111083_2023-07-31_final.stac-item
2023-08-11 09:28:50	ga_ls9c_ard_3-2-1_092075_2023-08-10_final.stac-item
2023-08-22 09:13:09	ga_ls9c_ard_3-2-1_089082_2023-08-21_final.stac-item
2023-08-30 09:57:30	ga_ls9c_ard_3-2-1_097069_2023-08-30_final.stac-item
2023-09-05 09:24:51	ga_ls9c_ard_3-2-1_091080_2023-09-04_final.stac-item
2023-09-06 10:03:45	ga_ls9c_ard_3-2-1_098069_2023-09-06_final.stac-item
2023-09-07 10:47:01	ga_ls9c_ard_3-2-1_105069_2023-09-07_final.stac-item
2023-09-08 09:52:36	ga_ls9c_ard_3-2-1_096072_2023-09-08_final.stac-item
2023-09-25 10:39:52	ga_ls9c_ard_3-2-1_103082_2023-09-25_final.stac-item
2023-10-01 11:37:42	ga_ls9c_ard_3-2-1_113072_2023-10-01_final.stac-item
2023-10-31 10:11:41	ga_ls9c_ard_3-2-1_099073_2023-10-31_final.stac-item
2023-11-27 11:36:10	ga_ls9c_ard_3-2-1_112083_2023-11-27_final.stac-item
2023-12-04 09:58:38	ga_ls9c_ard_3-2-1_097071_2023-12-04_final.stac-item
2023-12-10 11:04:00	ga_ls9c_ard_3-2-1_107080_2023-12-10_final.stac-item
2023-12-16 10:23:24	ga_ls9c_ard_3-2-1_101071_2023-12-16_final.stac-item
2023-12-22 09:52:20	ga_ls9c_ard_3-2-1_095086_2023-12-22_final.stac-item
2023-12-23 10:28:25	ga_ls9c_ard_3-2-1_102068_2023-12-23_final.stac-item
2023-12-28 10:48:32	ga_ls9c_ard_3-2-1_105072_2023-12-28_final.stac-item
2024-01-25 11:15:32	ga_ls9c_ard_3-2-1_109078_2024-01-25_final.stac-item
2024-02-24 11:23:46	ga_ls9c_ard_3-2-1_111068_2024-02-24_final.stac-item
2024-02-27 10:22:13	ga_ls9c_ard_3-2-1_100084_2024-02-27_final.stac-item
2024-02-29 10:08:17	ga_ls9c_ard_3-2-1_098080_2024-02-29_final.stac-item
2024-03-11 09:51:22	ga_ls9c_ard_3-2-1_095084_2024-03-11_final.stac-item
2024-03-29 11:14:56	ga_ls9c_ard_3-2-1_109077_2024-03-29_final.stac-item
2024-03-30 10:21:18	ga_ls9c_ard_3-2-1_100082_2024-03-30_final.stac-item
2024-04-16 09:25:09	ga_ls9c_ard_3-2-1_091081_2024-04-15_final.stac-item
2024-05-09 11:07:09	ga_ls9c_ard_3-2-1_108074_2024-05-09_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