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
2021-11-13 10:02:18	ga_ls9c_ard_3-2-1_097081_2021-11-13_final.stac-item
2021-12-06 10:52:35	ga_ls9c_ard_3-2-1_105082_2021-12-06_final.stac-item
2021-12-22 09:13:36	ga_ls9c_ard_3-2-1_089082_2021-12-21_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2021-12-28 11:51:30	ga_ls9c_ard_3-2-1_115075_2021-12-28_final.stac-item
2021-12-29 10:54:17	ga_ls9c_ard_3-2-1_106071_2021-12-29_final.stac-item
2022-01-03 11:13:36	ga_ls9c_ard_3-2-1_109073_2022-01-03_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-13 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-01-13_final.stac-item
2022-01-15 09:57:24	ga_ls9c_ard_3-2-1_097068_2022-01-15_final.stac-item
2022-01-17 11:25:32	ga_ls9c_ard_3-2-1_111072_2022-01-17_final.stac-item
2022-01-22 11:44:54	ga_ls9c_ard_3-2-1_114074_2022-01-22_final.stac-item
2022-02-16 11:37:50	ga_ls9c_ard_3-2-1_113072_2022-02-16_final.stac-item
2022-02-17 10:40:37	ga_ls9c_ard_3-2-1_104068_2022-02-17_final.stac-item
2022-03-11 10:03:23	ga_ls9c_ard_3-2-1_098068_2022-03-11_final.stac-item
2022-04-16 11:18:56	ga_ls9c_ard_3-2-1_110072_2022-04-16_final.stac-item
2022-05-04 09:32:46	ga_ls9c_ard_3-2-1_092085_2022-05-04_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-05-30 10:02:28	ga_ls9c_ard_3-2-1_098067_2022-05-30_final.stac-item
2022-06-18 10:33:54	ga_ls9c_ard_3-2-1_103068_2022-06-18_final.stac-item
2022-07-03 09:57:14	ga_ls9c_ard_3-2-1_096084_2022-07-03_final.stac-item
2022-07-05 11:19:46	ga_ls9c_ard_3-2-1_110074_2022-07-05_final.stac-item
2022-07-12 09:46:37	ga_ls9c_ard_3-2-1_095073_2022-07-12_final.stac-item
2022-07-12 11:25:30	ga_ls9c_ard_3-2-1_111073_2022-07-12_final.stac-item
2022-08-08 09:34:47	ga_ls9c_ard_3-2-1_092089_2022-08-08_final.stac-item
2022-08-13 09:46:59	ga_ls9c_ard_3-2-1_095073_2022-08-13_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-08-26 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-08-25_final.stac-item
2022-08-26 09:22:07	ga_ls9c_ard_3-2-1_090088_2022-08-25_final.stac-item
2022-08-27 11:41:52	ga_ls9c_ard_3-2-1_113082_2022-08-27_final.stac-item
2022-09-16 09:39:56	ga_ls9c_ard_3-2-1_093086_2022-09-16_final.stac-item
2022-09-30 09:46:46	ga_ls9c_ard_3-2-1_095072_2022-09-30_final.stac-item
2022-10-09 09:41:24	ga_ls9c_ard_3-2-1_094074_2022-10-09_final.stac-item
2022-10-11 09:32:39	ga_ls9c_ard_3-2-1_092083_2022-10-11_final.stac-item
2022-10-14 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-10-14_final.stac-item
2022-10-16 09:47:15	ga_ls9c_ard_3-2-1_095073_2022-10-16_final.stac-item
2022-10-18 09:38:53	ga_ls9c_ard_3-2-1_093083_2022-10-18_final.stac-item
2022-10-24 10:35:54	ga_ls9c_ard_3-2-1_103071_2022-10-24_final.stac-item
2022-10-29 10:54:26	ga_ls9c_ard_3-2-1_106071_2022-10-29_final.stac-item
2022-11-02 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-11-02_final.stac-item
2022-11-09 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-09_final.stac-item
2022-11-14 10:54:04	ga_ls9c_ard_3-2-1_106070_2022-11-14_final.stac-item
2022-11-21 09:27:20	ga_ls9c_ard_3-2-1_091085_2022-11-20_final.stac-item
2022-11-23 09:12:35	ga_ls9c_ard_3-2-1_089079_2022-11-22_final.stac-item
2022-11-23 09:12:58	ga_ls9c_ard_3-2-1_089080_2022-11-22_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-12-14 11:06:24	ga_ls9c_ard_3-2-1_108070_2022-12-14_final.stac-item
2022-12-16 10:59:13	ga_ls9c_ard_3-2-1_106083_2022-12-16_final.stac-item
2022-12-28 11:20:20	ga_ls9c_ard_3-2-1_110074_2022-12-28_final.stac-item
2023-01-01 09:22:20	ga_ls9c_ard_3-2-1_090088_2022-12-31_final.stac-item
2023-01-09 11:47:28	ga_ls9c_ard_3-2-1_114080_2023-01-09_final.stac-item
2023-01-25 10:04:55	ga_ls9c_ard_3-2-1_098071_2023-01-25_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-01-30 10:23:32	ga_ls9c_ard_3-2-1_101071_2023-01-30_final.stac-item
2023-02-01 11:52:52	ga_ls9c_ard_3-2-1_115078_2023-02-01_final.stac-item
2023-03-06 09:22:06	ga_ls9c_ard_3-2-1_090088_2023-03-05_final.stac-item
2023-03-13 09:23:50	ga_ls9c_ard_3-2-1_091077_2023-03-12_final.stac-item
2023-04-14 09:27:31	ga_ls9c_ard_3-2-1_091087_2023-04-13_final.stac-item
2023-04-15 10:02:47	ga_ls9c_ard_3-2-1_098067_2023-04-15_final.stac-item
2023-04-15 10:03:11	ga_ls9c_ard_3-2-1_098068_2023-04-15_final.stac-item
2023-04-22 10:16:09	ga_ls9c_ard_3-2-1_099085_2023-04-22_final.stac-item
2023-06-06 11:22:56	ga_ls9c_ard_3-2-1_110083_2023-06-06_final.stac-item
2023-06-22 11:19:14	ga_ls9c_ard_3-2-1_110074_2023-06-22_final.stac-item
2023-06-26 09:16:01	ga_ls9c_ard_3-2-1_090075_2023-06-25_final.stac-item
2023-07-12 09:17:05	ga_ls9c_ard_3-2-1_090077_2023-07-11_final.stac-item
2023-07-13 11:41:14	ga_ls9c_ard_3-2-1_113082_2023-07-13_final.stac-item
2023-07-17 11:12:08	ga_ls9c_ard_3-2-1_109071_2023-07-17_final.stac-item
2023-07-31 09:46:05	ga_ls9c_ard_3-2-1_095072_2023-07-31_final.stac-item
2023-08-12 11:51:23	ga_ls9c_ard_3-2-1_115076_2023-08-12_final.stac-item
2023-09-03 11:16:52	ga_ls9c_ard_3-2-1_109082_2023-09-03_final.stac-item
2023-09-10 09:39:52	ga_ls9c_ard_3-2-1_094071_2023-09-10_final.stac-item
2023-10-03 11:24:58	ga_ls9c_ard_3-2-1_111071_2023-10-03_final.stac-item
2023-10-04 10:28:10	ga_ls9c_ard_3-2-1_102068_2023-10-04_final.stac-item
2023-10-08 10:07:28	ga_ls9c_ard_3-2-1_098078_2023-10-08_final.stac-item
2023-10-12 11:20:30	ga_ls9c_ard_3-2-1_110075_2023-10-12_final.stac-item
2023-10-14 11:08:10	ga_ls9c_ard_3-2-1_108075_2023-10-14_final.stac-item
2023-10-15 10:10:57	ga_ls9c_ard_3-2-1_099071_2023-10-15_final.stac-item
2023-10-19 11:29:56	ga_ls9c_ard_3-2-1_111083_2023-10-19_final.stac-item
2023-10-21 09:33:54	ga_ls9c_ard_3-2-1_093071_2023-10-21_final.stac-item
2023-11-26 09:14:49	ga_ls9c_ard_3-2-1_089085_2023-11-25_final.stac-item
2023-12-05 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-12-05_final.stac-item
2023-12-09 11:58:01	ga_ls9c_ard_3-2-1_116076_2023-12-09_final.stac-item
2023-12-12 09:13:35	ga_ls9c_ard_3-2-1_089082_2023-12-11_final.stac-item
2023-12-15 11:24:36	ga_ls9c_ard_3-2-1_110085_2023-12-15_final.stac-item
2023-12-19 10:56:19	ga_ls9c_ard_3-2-1_106076_2023-12-19_final.stac-item
2023-12-28 09:13:39	ga_ls9c_ard_3-2-1_089082_2023-12-27_final.stac-item
2023-12-29 09:52:30	ga_ls9c_ard_3-2-1_096071_2023-12-29_final.stac-item
2023-12-31 11:19:24	ga_ls9c_ard_3-2-1_110072_2023-12-31_final.stac-item
2024-01-09 11:11:59	ga_ls9c_ard_3-2-1_109069_2024-01-09_final.stac-item
2024-01-11 09:23:57	ga_ls9c_ard_3-2-1_091077_2024-01-10_final.stac-item
2024-01-14 09:58:27	ga_ls9c_ard_3-2-1_096086_2024-01-14_final.stac-item
2024-01-14 11:36:32	ga_ls9c_ard_3-2-1_112084_2024-01-14_final.stac-item
2024-01-25 11:17:56	ga_ls9c_ard_3-2-1_109084_2024-01-25_final.stac-item
2024-01-29 09:13:35	ga_ls9c_ard_3-2-1_089082_2024-01-28_final.stac-item
2024-01-30 09:52:28	ga_ls9c_ard_3-2-1_096071_2024-01-30_final.stac-item
2024-02-05 10:54:42	ga_ls9c_ard_3-2-1_106072_2024-02-05_final.stac-item
2024-02-09 10:30:22	ga_ls9c_ard_3-2-1_102073_2024-02-09_final.stac-item
2024-02-11 10:19:12	ga_ls9c_ard_3-2-1_100076_2024-02-11_final.stac-item
2024-02-19 11:07:19	ga_ls9c_ard_3-2-1_108073_2024-02-19_final.stac-item
2024-02-19 11:11:42	ga_ls9c_ard_3-2-1_108084_2024-02-19_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