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
2021-11-10 11:17:45	ga_ls9c_ard_3-2-1_110076_2021-11-10_final.stac-item
2021-12-16 09:52:16	ga_ls9c_ard_3-2-1_095086_2021-12-16_final.stac-item
2022-01-10 11:20:33	ga_ls9c_ard_3-2-1_110075_2022-01-10_final.stac-item
2022-01-13 11:52:38	ga_ls9c_ard_3-2-1_115078_2022-01-13_final.stac-item
2022-01-21 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-01-20_final.stac-item
2022-01-25 10:37:19	ga_ls9c_ard_3-2-1_103075_2022-01-25_final.stac-item
2022-02-07 10:04:00	ga_ls9c_ard_3-2-1_098069_2022-02-07_final.stac-item
2022-02-15 10:53:23	ga_ls9c_ard_3-2-1_106069_2022-02-15_final.stac-item
2022-03-06 11:24:55	ga_ls9c_ard_3-2-1_111071_2022-03-06_final.stac-item
2022-03-26 09:23:14	ga_ls9c_ard_3-2-1_091076_2022-03-25_final.stac-item
2022-03-29 11:34:12	ga_ls9c_ard_3-2-1_112079_2022-03-29_final.stac-item
2022-04-09 11:13:38	ga_ls9c_ard_3-2-1_109074_2022-04-09_final.stac-item
2022-04-12 10:07:13	ga_ls9c_ard_3-2-1_098078_2022-04-12_final.stac-item
2022-04-13 10:46:53	ga_ls9c_ard_3-2-1_105069_2022-04-13_final.stac-item
2022-04-18 09:28:52	ga_ls9c_ard_3-2-1_092075_2022-04-17_final.stac-item
2022-05-14 10:04:09	ga_ls9c_ard_3-2-1_098071_2022-05-14_final.stac-item
2022-05-16 09:51:46	ga_ls9c_ard_3-2-1_096071_2022-05-16_final.stac-item
2022-05-25 11:24:24	ga_ls9c_ard_3-2-1_111071_2022-05-25_final.stac-item
2022-05-30 10:02:28	ga_ls9c_ard_3-2-1_098067_2022-05-30_final.stac-item
2022-06-06 10:15:27	ga_ls9c_ard_3-2-1_099084_2022-06-06_final.stac-item
2022-07-02 10:46:53	ga_ls9c_ard_3-2-1_105069_2022-07-02_final.stac-item
2022-07-16 11:01:35	ga_ls9c_ard_3-2-1_107075_2022-07-16_final.stac-item
2022-07-27 09:07:08	ga_ls9c_ard_3-2-1_088082_2022-07-26_final.stac-item
2022-07-31 11:57:50	ga_ls9c_ard_3-2-1_116076_2022-07-31_final.stac-item
2022-08-07 10:28:00	ga_ls9c_ard_3-2-1_101083_2022-08-07_final.stac-item
2022-08-08 09:33:35	ga_ls9c_ard_3-2-1_092086_2022-08-08_final.stac-item
2022-08-09 10:10:29	ga_ls9c_ard_3-2-1_099070_2022-08-09_final.stac-item
2022-08-18 11:46:02	ga_ls9c_ard_3-2-1_114077_2022-08-18_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-09-13 09:06:36	ga_ls9c_ard_3-2-1_088080_2022-09-12_final.stac-item
2022-09-16 09:40:20	ga_ls9c_ard_3-2-1_093087_2022-09-16_final.stac-item
2022-09-17 10:21:36	ga_ls9c_ard_3-2-1_100082_2022-09-17_final.stac-item
2022-09-26 10:09:29	ga_ls9c_ard_3-2-1_099067_2022-09-26_final.stac-item
2022-09-30 09:52:21	ga_ls9c_ard_3-2-1_095086_2022-09-30_final.stac-item
2022-10-06 10:46:33	ga_ls9c_ard_3-2-1_105067_2022-10-06_final.stac-item
2022-10-12 10:13:56	ga_ls9c_ard_3-2-1_099078_2022-10-12_final.stac-item
2022-10-17 10:29:43	ga_ls9c_ard_3-2-1_102071_2022-10-17_final.stac-item
2022-11-12 09:33:55	ga_ls9c_ard_3-2-1_092086_2022-11-12_final.stac-item
2022-11-13 11:51:40	ga_ls9c_ard_3-2-1_115075_2022-11-13_final.stac-item
2022-11-18 10:29:20	ga_ls9c_ard_3-2-1_102070_2022-11-18_final.stac-item
2022-11-28 09:29:53	ga_ls9c_ard_3-2-1_092076_2022-11-27_final.stac-item
2022-12-04 10:28:29	ga_ls9c_ard_3-2-1_102068_2022-12-04_final.stac-item
2022-12-23 09:29:16	ga_ls9c_ard_3-2-1_091090_2022-12-22_final.stac-item
2022-12-28 09:44:38	ga_ls9c_ard_3-2-1_094082_2022-12-28_final.stac-item
2023-01-08 09:28:31	ga_ls9c_ard_3-2-1_091088_2023-01-07_final.stac-item
2023-01-15 09:33:26	ga_ls9c_ard_3-2-1_092085_2023-01-15_final.stac-item
2023-01-21 10:29:33	ga_ls9c_ard_3-2-1_102071_2023-01-21_final.stac-item
2023-01-25 10:09:42	ga_ls9c_ard_3-2-1_098083_2023-01-25_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-02-27 10:50:04	ga_ls9c_ard_3-2-1_105076_2023-02-27_final.stac-item
2023-03-18 11:18:27	ga_ls9c_ard_3-2-1_110070_2023-03-18_final.stac-item
2023-04-06 10:14:16	ga_ls9c_ard_3-2-1_099080_2023-04-06_final.stac-item
2023-04-09 09:06:15	ga_ls9c_ard_3-2-1_088080_2023-04-08_final.stac-item
2023-04-11 10:27:58	ga_ls9c_ard_3-2-1_102068_2023-04-11_final.stac-item
2023-04-13 10:21:34	ga_ls9c_ard_3-2-1_100083_2023-04-13_final.stac-item
2023-04-16 10:49:39	ga_ls9c_ard_3-2-1_105076_2023-04-16_final.stac-item
2023-04-24 09:58:36	ga_ls9c_ard_3-2-1_097072_2023-04-24_final.stac-item
2023-04-26 09:52:12	ga_ls9c_ard_3-2-1_095087_2023-04-26_final.stac-item
2023-04-30 11:05:06	ga_ls9c_ard_3-2-1_107084_2023-04-30_final.stac-item
2023-05-01 10:04:16	ga_ls9c_ard_3-2-1_098071_2023-05-01_final.stac-item
2023-05-18 09:11:42	ga_ls9c_ard_3-2-1_089079_2023-05-17_final.stac-item
2023-05-19 09:57:20	ga_ls9c_ard_3-2-1_096085_2023-05-19_final.stac-item
2023-05-26 10:01:02	ga_ls9c_ard_3-2-1_097079_2023-05-26_final.stac-item
2023-05-29 10:29:32	ga_ls9c_ard_3-2-1_102073_2023-05-29_final.stac-item
2023-05-31 10:21:10	ga_ls9c_ard_3-2-1_100083_2023-05-31_final.stac-item
2023-06-03 09:12:46	ga_ls9c_ard_3-2-1_089082_2023-06-02_final.stac-item
2023-06-06 09:40:04	ga_ls9c_ard_3-2-1_094073_2023-06-06_final.stac-item
2023-06-09 10:10:32	ga_ls9c_ard_3-2-1_099072_2023-06-09_final.stac-item
2023-06-15 11:17:02	ga_ls9c_ard_3-2-1_109084_2023-06-15_final.stac-item
2023-06-22 09:39:57	ga_ls9c_ard_3-2-1_094073_2023-06-22_final.stac-item
2023-06-22 11:18:02	ga_ls9c_ard_3-2-1_110071_2023-06-22_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-24 09:44:59	ga_ls9c_ard_3-2-1_094085_2023-07-24_final.stac-item
2023-08-14 09:59:20	ga_ls9c_ard_3-2-1_097074_2023-08-14_final.stac-item
2023-08-16 09:45:46	ga_ls9c_ard_3-2-1_095071_2023-08-16_final.stac-item
2023-09-01 09:46:21	ga_ls9c_ard_3-2-1_095072_2023-09-01_final.stac-item
2023-09-10 09:40:40	ga_ls9c_ard_3-2-1_094073_2023-09-10_final.stac-item
2023-09-12 09:32:43	ga_ls9c_ard_3-2-1_092084_2023-09-12_final.stac-item
2023-09-12 09:33:55	ga_ls9c_ard_3-2-1_092087_2023-09-12_final.stac-item
2023-09-13 11:52:28	ga_ls9c_ard_3-2-1_115078_2023-09-13_final.stac-item
2023-09-21 09:27:20	ga_ls9c_ard_3-2-1_091086_2023-09-20_final.stac-item
2023-09-23 09:16:34	ga_ls9c_ard_3-2-1_089090_2023-09-22_final.stac-item
2023-11-06 09:40:35	ga_ls9c_ard_3-2-1_093088_2023-11-06_final.stac-item
2023-11-17 09:21:17	ga_ls9c_ard_3-2-1_090086_2023-11-16_final.stac-item
2023-11-25 10:03:15	ga_ls9c_ard_3-2-1_098067_2023-11-25_final.stac-item
2023-12-03 10:55:52	ga_ls9c_ard_3-2-1_106075_2023-12-03_final.stac-item
2023-12-19 10:55:31	ga_ls9c_ard_3-2-1_106074_2023-12-19_final.stac-item
2023-12-23 10:28:25	ga_ls9c_ard_3-2-1_102068_2023-12-23_final.stac-item
2023-12-23 10:33:12	ga_ls9c_ard_3-2-1_102080_2023-12-23_final.stac-item
2023-12-30 10:34:34	ga_ls9c_ard_3-2-1_103068_2023-12-30_final.stac-item
2024-01-02 09:34:32	ga_ls9c_ard_3-2-1_092088_2024-01-02_final.stac-item
2024-01-02 11:07:25	ga_ls9c_ard_3-2-1_108073_2024-01-02_final.stac-item
2024-01-13 09:13:36	ga_ls9c_ard_3-2-1_089082_2024-01-12_final.stac-item
2024-01-18 09:30:56	ga_ls9c_ard_3-2-1_092079_2024-01-18_final.stac-item
2024-01-23 09:46:37	ga_ls9c_ard_3-2-1_095072_2024-01-23_final.stac-item
2024-01-23 11:30:18	ga_ls9c_ard_3-2-1_111084_2024-01-23_final.stac-item
2024-02-04 11:51:31	ga_ls9c_ard_3-2-1_115075_2024-02-04_final.stac-item
2024-02-05 09:18:36	ga_ls9c_ard_3-2-1_090079_2024-02-04_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