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
2021-12-13 10:55:30	ga_ls9c_ard_3-2-1_106074_2021-12-13_final.stac-item
2021-12-18 09:35:07	ga_ls9c_ard_3-2-1_093074_2021-12-18_final.stac-item
2021-12-29 10:54:17	ga_ls9c_ard_3-2-1_106071_2021-12-29_final.stac-item
2022-01-04 10:21:58	ga_ls9c_ard_3-2-1_100083_2022-01-04_final.stac-item
2022-01-05 09:26:45	ga_ls9c_ard_3-2-1_091084_2022-01-04_final.stac-item
2022-01-20 10:18:46	ga_ls9c_ard_3-2-1_100075_2022-01-20_final.stac-item
2022-01-20 10:22:21	ga_ls9c_ard_3-2-1_100084_2022-01-20_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-02-05 10:21:58	ga_ls9c_ard_3-2-1_100083_2022-02-05_final.stac-item
2022-02-14 10:15:19	ga_ls9c_ard_3-2-1_099082_2022-02-14_final.stac-item
2022-02-15 10:53:23	ga_ls9c_ard_3-2-1_106069_2022-02-15_final.stac-item
2022-02-19 10:29:02	ga_ls9c_ard_3-2-1_102070_2022-02-19_final.stac-item
2022-02-27 09:41:05	ga_ls9c_ard_3-2-1_094074_2022-02-27_final.stac-item
2022-03-02 10:13:56	ga_ls9c_ard_3-2-1_099079_2022-03-02_final.stac-item
2022-03-24 09:39:12	ga_ls9c_ard_3-2-1_093085_2022-03-24_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-04-19 10:16:06	ga_ls9c_ard_3-2-1_099085_2022-04-19_final.stac-item
2022-04-25 09:36:59	ga_ls9c_ard_3-2-1_093080_2022-04-25_final.stac-item
2022-04-28 10:02:42	ga_ls9c_ard_3-2-1_098067_2022-04-28_final.stac-item
2022-05-20 11:06:39	ga_ls9c_ard_3-2-1_108073_2022-05-20_final.stac-item
2022-05-21 11:51:55	ga_ls9c_ard_3-2-1_115078_2022-05-21_final.stac-item
2022-05-29 09:21:12	ga_ls9c_ard_3-2-1_091072_2022-05-28_final.stac-item
2022-06-07 10:57:07	ga_ls9c_ard_3-2-1_106080_2022-06-07_final.stac-item
2022-06-11 10:28:02	ga_ls9c_ard_3-2-1_102069_2022-06-11_final.stac-item
2022-06-11 10:29:37	ga_ls9c_ard_3-2-1_102073_2022-06-11_final.stac-item
2022-06-19 11:20:00	ga_ls9c_ard_3-2-1_110075_2022-06-19_final.stac-item
2022-06-20 10:25:13	ga_ls9c_ard_3-2-1_101077_2022-06-20_final.stac-item
2022-06-23 10:57:25	ga_ls9c_ard_3-2-1_106080_2022-06-23_final.stac-item
2022-08-08 09:28:48	ga_ls9c_ard_3-2-1_092074_2022-08-07_final.stac-item
2022-09-13 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-09-12_final.stac-item
2022-09-14 09:52:16	ga_ls9c_ard_3-2-1_095086_2022-09-14_final.stac-item
2022-10-05 10:07:41	ga_ls9c_ard_3-2-1_098078_2022-10-05_final.stac-item
2022-10-12 10:09:56	ga_ls9c_ard_3-2-1_099068_2022-10-12_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-18 09:40:29	ga_ls9c_ard_3-2-1_093087_2022-10-18_final.stac-item
2022-10-27 11:11:35	ga_ls9c_ard_3-2-1_108083_2022-10-27_final.stac-item
2022-10-27 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-10-27_final.stac-item
2022-10-29 10:55:14	ga_ls9c_ard_3-2-1_106073_2022-10-29_final.stac-item
2022-10-31 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-31_final.stac-item
2022-11-11 10:23:57	ga_ls9c_ard_3-2-1_101072_2022-11-11_final.stac-item
2022-11-15 11:38:55	ga_ls9c_ard_3-2-1_113074_2022-11-15_final.stac-item
2022-11-21 09:22:33	ga_ls9c_ard_3-2-1_091073_2022-11-20_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_2022-11-26_final.stac-item
2022-11-27 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-11-27_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-04_final.stac-item
2022-12-07 11:00:12	ga_ls9c_ard_3-2-1_107070_2022-12-07_final.stac-item
2022-12-07 11:00:36	ga_ls9c_ard_3-2-1_107071_2022-12-07_final.stac-item
2022-12-08 10:09:47	ga_ls9c_ard_3-2-1_098083_2022-12-08_final.stac-item
2022-12-08 11:47:28	ga_ls9c_ard_3-2-1_114080_2022-12-08_final.stac-item
2022-12-14 11:07:36	ga_ls9c_ard_3-2-1_108073_2022-12-14_final.stac-item
2022-12-16 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-12-16_final.stac-item
2022-12-21 09:34:27	ga_ls9c_ard_3-2-1_093072_2022-12-21_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-23 09:24:52	ga_ls9c_ard_3-2-1_091079_2022-12-22_final.stac-item
2022-12-23 11:02:09	ga_ls9c_ard_3-2-1_107075_2022-12-23_final.stac-item
2022-12-31 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-12-31_final.stac-item
2023-01-02 11:39:18	ga_ls9c_ard_3-2-1_113075_2023-01-02_final.stac-item
2023-01-06 09:40:29	ga_ls9c_ard_3-2-1_093087_2023-01-06_final.stac-item
2023-01-08 11:02:37	ga_ls9c_ard_3-2-1_107076_2023-01-08_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-01-10 09:14:09	ga_ls9c_ard_3-2-1_089083_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
2023-02-11 10:52:42	ga_ls9c_ard_3-2-1_105082_2023-02-11_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-02-24 11:58:03	ga_ls9c_ard_3-2-1_116076_2023-02-24_final.stac-item
2023-02-25 11:02:02	ga_ls9c_ard_3-2-1_107075_2023-02-25_final.stac-item
2023-03-02 09:40:05	ga_ls9c_ard_3-2-1_094071_2023-03-02_final.stac-item
2023-03-06 10:56:11	ga_ls9c_ard_3-2-1_106076_2023-03-06_final.stac-item
2023-03-06 10:58:35	ga_ls9c_ard_3-2-1_106082_2023-03-06_final.stac-item
2023-04-07 10:58:19	ga_ls9c_ard_3-2-1_106082_2023-04-07_final.stac-item
2023-04-08 09:58:42	ga_ls9c_ard_3-2-1_097072_2023-04-08_final.stac-item
2023-04-25 10:42:14	ga_ls9c_ard_3-2-1_104073_2023-04-25_final.stac-item
2023-05-07 11:05:12	ga_ls9c_ard_3-2-1_108069_2023-05-07_final.stac-item
2023-05-08 11:52:03	ga_ls9c_ard_3-2-1_115078_2023-05-08_final.stac-item
2023-05-11 09:06:47	ga_ls9c_ard_3-2-1_088082_2023-05-10_final.stac-item
2023-05-14 09:39:15	ga_ls9c_ard_3-2-1_093086_2023-05-14_final.stac-item
2023-05-19 09:56:56	ga_ls9c_ard_3-2-1_096084_2023-05-19_final.stac-item
2023-05-19 09:57:20	ga_ls9c_ard_3-2-1_096085_2023-05-19_final.stac-item
2023-05-21 11:23:26	ga_ls9c_ard_3-2-1_110084_2023-05-21_final.stac-item
2023-05-22 10:25:00	ga_ls9c_ard_3-2-1_101077_2023-05-22_final.stac-item
2023-06-01 11:01:14	ga_ls9c_ard_3-2-1_107075_2023-06-01_final.stac-item
2023-06-20 11:35:35	ga_ls9c_ard_3-2-1_112084_2023-06-20_final.stac-item
2023-06-21 10:38:22	ga_ls9c_ard_3-2-1_103080_2023-06-21_final.stac-item
2023-06-29 09:49:01	ga_ls9c_ard_3-2-1_095080_2023-06-29_final.stac-item
2023-07-01 09:38:42	ga_ls9c_ard_3-2-1_093085_2023-07-01_final.stac-item
2023-07-19 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-07-18_final.stac-item
2023-07-20 11:46:13	ga_ls9c_ard_3-2-1_114079_2023-07-20_final.stac-item
2023-07-24 11:18:41	ga_ls9c_ard_3-2-1_110072_2023-07-24_final.stac-item
2023-07-27 10:10:44	ga_ls9c_ard_3-2-1_099072_2023-07-27_final.stac-item
2023-07-31 11:29:22	ga_ls9c_ard_3-2-1_111083_2023-07-31_final.stac-item
2023-08-03 10:17:02	ga_ls9c_ard_3-2-1_100072_2023-08-03_final.stac-item
2023-08-11 09:33:13	ga_ls9c_ard_3-2-1_092086_2023-08-11_final.stac-item
2023-08-12 11:51:23	ga_ls9c_ard_3-2-1_115076_2023-08-12_final.stac-item
2023-10-14 09:33:40	ga_ls9c_ard_3-2-1_092086_2023-10-14_final.stac-item
2023-10-16 10:54:37	ga_ls9c_ard_3-2-1_106072_2023-10-16_final.stac-item
2023-10-16 10:59:01	ga_ls9c_ard_3-2-1_106083_2023-10-16_final.stac-item
2023-10-26 09:58:24	ga_ls9c_ard_3-2-1_096086_2023-10-26_final.stac-item
2023-10-28 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-28_final.stac-item
2023-11-14 10:23:16	ga_ls9c_ard_3-2-1_101071_2023-11-14_final.stac-item
2023-11-22 09:40:42	ga_ls9c_ard_3-2-1_093088_2023-11-22_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