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
2021-11-03 11:36:25	ga_ls9c_ard_3-2-1_112082_2021-11-03_final.stac-item
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-07 09:20:16	ga_ls9c_ard_3-2-1_090082_2021-11-06_final.stac-item
2021-11-13 10:01:06	ga_ls9c_ard_3-2-1_097078_2021-11-13_final.stac-item
2021-11-24 10:45:34	ga_ls9c_ard_3-2-1_104077_2021-11-24_final.stac-item
2021-12-09 11:19:52	ga_ls9c_ard_3-2-1_110073_2021-12-09_final.stac-item
2021-12-11 11:07:29	ga_ls9c_ard_3-2-1_108073_2021-12-11_final.stac-item
2021-12-14 09:58:40	ga_ls9c_ard_3-2-1_097071_2021-12-14_final.stac-item
2021-12-16 11:29:57	ga_ls9c_ard_3-2-1_111083_2021-12-16_final.stac-item
2022-01-01 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-01-01_final.stac-item
2022-01-28 09:30:32	ga_ls9c_ard_3-2-1_092078_2022-01-28_final.stac-item
2022-02-05 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-02-05_final.stac-item
2022-02-09 09:57:13	ga_ls9c_ard_3-2-1_096083_2022-02-09_final.stac-item
2022-02-11 11:22:56	ga_ls9c_ard_3-2-1_110081_2022-02-11_final.stac-item
2022-02-13 11:11:21	ga_ls9c_ard_3-2-1_108083_2022-02-13_final.stac-item
2022-02-15 10:54:35	ga_ls9c_ard_3-2-1_106072_2022-02-15_final.stac-item
2022-02-22 09:27:00	ga_ls9c_ard_3-2-1_091085_2022-02-21_final.stac-item
2022-03-01 11:09:58	ga_ls9c_ard_3-2-1_108080_2022-03-01_final.stac-item
2022-03-25 10:21:39	ga_ls9c_ard_3-2-1_100083_2022-03-25_final.stac-item
2022-03-31 09:40:10	ga_ls9c_ard_3-2-1_094072_2022-03-31_final.stac-item
2022-03-31 09:44:57	ga_ls9c_ard_3-2-1_094084_2022-03-31_final.stac-item
2022-04-13 10:52:28	ga_ls9c_ard_3-2-1_105083_2022-04-13_final.stac-item
2022-04-21 09:59:19	ga_ls9c_ard_3-2-1_097074_2022-04-21_final.stac-item
2022-05-29 09:24:23	ga_ls9c_ard_3-2-1_091080_2022-05-28_final.stac-item
2022-06-07 10:54:43	ga_ls9c_ard_3-2-1_106074_2022-06-07_final.stac-item
2022-06-12 09:34:25	ga_ls9c_ard_3-2-1_093074_2022-06-12_final.stac-item
2022-06-21 11:10:54	ga_ls9c_ard_3-2-1_108083_2022-06-21_final.stac-item
2022-06-30 11:01:38	ga_ls9c_ard_3-2-1_107075_2022-06-30_final.stac-item
2022-07-12 09:50:36	ga_ls9c_ard_3-2-1_095083_2022-07-12_final.stac-item
2022-07-16 09:23:06	ga_ls9c_ard_3-2-1_091076_2022-07-15_final.stac-item
2022-07-19 11:35:20	ga_ls9c_ard_3-2-1_112082_2022-07-19_final.stac-item
2022-07-23 09:27:48	ga_ls9c_ard_3-2-1_092072_2022-07-22_final.stac-item
2022-07-23 09:29:00	ga_ls9c_ard_3-2-1_092075_2022-07-22_final.stac-item
2022-07-24 11:51:34	ga_ls9c_ard_3-2-1_115076_2022-07-24_final.stac-item
2022-07-26 11:40:50	ga_ls9c_ard_3-2-1_113080_2022-07-26_final.stac-item
2022-07-29 10:30:29	ga_ls9c_ard_3-2-1_102074_2022-07-29_final.stac-item
2022-07-30 09:38:52	ga_ls9c_ard_3-2-1_093084_2022-07-30_final.stac-item
2022-08-01 11:01:26	ga_ls9c_ard_3-2-1_107074_2022-08-01_final.stac-item
2022-08-11 11:40:37	ga_ls9c_ard_3-2-1_113079_2022-08-11_final.stac-item
2022-08-15 09:37:50	ga_ls9c_ard_3-2-1_093081_2022-08-15_final.stac-item
2022-09-02 11:04:24	ga_ls9c_ard_3-2-1_107081_2022-09-02_final.stac-item
2022-09-05 09:57:12	ga_ls9c_ard_3-2-1_096083_2022-09-05_final.stac-item
2022-09-07 09:42:02	ga_ls9c_ard_3-2-1_094076_2022-09-07_final.stac-item
2022-09-12 11:41:06	ga_ls9c_ard_3-2-1_113080_2022-09-12_final.stac-item
2022-09-23 11:23:03	ga_ls9c_ard_3-2-1_110081_2022-09-23_final.stac-item
2022-10-16 09:51:14	ga_ls9c_ard_3-2-1_095083_2022-10-16_final.stac-item
2022-10-28 11:52:03	ga_ls9c_ard_3-2-1_115076_2022-10-28_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-12 09:32:19	ga_ls9c_ard_3-2-1_092082_2022-11-12_final.stac-item
2022-11-28 09:31:53	ga_ls9c_ard_3-2-1_092081_2022-11-28_final.stac-item
2022-11-28 11:08:46	ga_ls9c_ard_3-2-1_108076_2022-11-28_final.stac-item
2022-11-29 11:51:14	ga_ls9c_ard_3-2-1_115074_2022-11-29_final.stac-item
2022-11-30 10:59:11	ga_ls9c_ard_3-2-1_106083_2022-11-30_final.stac-item
2022-12-03 11:25:42	ga_ls9c_ard_3-2-1_111072_2022-12-03_final.stac-item
2022-12-14 11:06:00	ga_ls9c_ard_3-2-1_108069_2022-12-14_final.stac-item
2022-12-31 11:52:27	ga_ls9c_ard_3-2-1_115077_2022-12-31_final.stac-item
2023-01-13 09:45:49	ga_ls9c_ard_3-2-1_094085_2023-01-13_final.stac-item
2023-01-14 10:25:05	ga_ls9c_ard_3-2-1_101075_2023-01-14_final.stac-item
2023-01-20 09:46:17	ga_ls9c_ard_3-2-1_095071_2023-01-20_final.stac-item
2023-01-23 10:18:02	ga_ls9c_ard_3-2-1_100073_2023-01-23_final.stac-item
2023-02-10 10:06:39	ga_ls9c_ard_3-2-1_098075_2023-02-10_final.stac-item
2023-02-25 11:01:14	ga_ls9c_ard_3-2-1_107073_2023-02-25_final.stac-item
2023-03-04 09:34:29	ga_ls9c_ard_3-2-1_092088_2023-03-04_final.stac-item
2023-03-09 09:49:20	ga_ls9c_ard_3-2-1_095079_2023-03-09_final.stac-item
2023-03-18 09:45:09	ga_ls9c_ard_3-2-1_094084_2023-03-18_final.stac-item
2023-03-18 11:24:02	ga_ls9c_ard_3-2-1_110084_2023-03-18_final.stac-item
2023-03-20 09:34:46	ga_ls9c_ard_3-2-1_092089_2023-03-20_final.stac-item
2023-03-20 11:09:40	ga_ls9c_ard_3-2-1_108079_2023-03-20_final.stac-item
2023-03-25 09:46:04	ga_ls9c_ard_3-2-1_095071_2023-03-25_final.stac-item
2023-03-25 11:26:56	ga_ls9c_ard_3-2-1_111076_2023-03-25_final.stac-item
2023-04-06 11:53:09	ga_ls9c_ard_3-2-1_115080_2023-04-06_final.stac-item
2023-04-26 09:47:00	ga_ls9c_ard_3-2-1_095074_2023-04-26_final.stac-item
2023-05-08 10:12:22	ga_ls9c_ard_3-2-1_099076_2023-05-08_final.stac-item
2023-05-08 11:50:27	ga_ls9c_ard_3-2-1_115074_2023-05-08_final.stac-item
2023-05-14 11:12:33	ga_ls9c_ard_3-2-1_109072_2023-05-14_final.stac-item
2023-05-14 11:15:21	ga_ls9c_ard_3-2-1_109079_2023-05-14_final.stac-item
2023-05-16 11:01:22	ga_ls9c_ard_3-2-1_107075_2023-05-16_final.stac-item
2023-06-01 09:21:09	ga_ls9c_ard_3-2-1_091072_2023-05-31_final.stac-item
2023-07-09 10:22:15	ga_ls9c_ard_3-2-1_101070_2023-07-09_final.stac-item
2023-07-15 09:46:48	ga_ls9c_ard_3-2-1_095074_2023-07-15_final.stac-item
2023-07-17 09:34:51	ga_ls9c_ard_3-2-1_093075_2023-07-17_final.stac-item
2023-07-23 10:34:14	ga_ls9c_ard_3-2-1_103069_2023-07-23_final.stac-item
2023-07-28 10:54:49	ga_ls9c_ard_3-2-1_106074_2023-07-28_final.stac-item
2023-07-31 11:29:46	ga_ls9c_ard_3-2-1_111084_2023-07-31_final.stac-item
2023-08-01 10:28:58	ga_ls9c_ard_3-2-1_102071_2023-08-01_final.stac-item
2023-08-06 10:49:09	ga_ls9c_ard_3-2-1_105075_2023-08-06_final.stac-item
2023-08-10 10:24:51	ga_ls9c_ard_3-2-1_101076_2023-08-10_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-13 10:14:23	ga_ls9c_ard_3-2-1_099080_2023-09-13_final.stac-item
2023-09-26 11:23:07	ga_ls9c_ard_3-2-1_110082_2023-09-26_final.stac-item
2023-10-07 11:00:41	ga_ls9c_ard_3-2-1_107072_2023-10-07_final.stac-item
2023-10-07 11:02:17	ga_ls9c_ard_3-2-1_107076_2023-10-07_final.stac-item
2023-10-10 11:34:01	ga_ls9c_ard_3-2-1_112078_2023-10-10_final.stac-item
2023-10-15 10:09:21	ga_ls9c_ard_3-2-1_099067_2023-10-15_final.stac-item
2023-11-04 11:28:13	ga_ls9c_ard_3-2-1_111079_2023-11-04_final.stac-item
2023-11-07 11:57:57	ga_ls9c_ard_3-2-1_116076_2023-11-07_final.stac-item
2023-12-11 11:47:17	ga_ls9c_ard_3-2-1_114080_2023-12-11_final.stac-item
2023-12-24 09:35:11	ga_ls9c_ard_3-2-1_093074_2023-12-24_final.stac-item
2023-12-26 11:01:18	ga_ls9c_ard_3-2-1_107073_2023-12-26_final.stac-item
2024-01-04 09:19:44	ga_ls9c_ard_3-2-1_090082_2024-01-03_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