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
2022-09-18 09:22:00	ga_ls9c_ard_3-2-1_091072_2022-09-17_final.stac-item
2023-10-14 09:27:41	ga_ls9c_ard_3-2-1_092071_2023-10-13_final.stac-item
2023-10-14 09:28:05	ga_ls9c_ard_3-2-1_092072_2023-10-13_final.stac-item
2023-10-14 09:28:29	ga_ls9c_ard_3-2-1_092073_2023-10-13_final.stac-item
2023-10-14 09:28:53	ga_ls9c_ard_3-2-1_092074_2023-10-13_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-16 09:16:32	ga_ls9c_ard_3-2-1_090074_2023-10-15_final.stac-item
2023-10-16 09:16:56	ga_ls9c_ard_3-2-1_090075_2023-10-15_final.stac-item
2023-10-16 09:17:20	ga_ls9c_ard_3-2-1_090076_2023-10-15_final.stac-item
2023-10-16 09:17:44	ga_ls9c_ard_3-2-1_090077_2023-10-15_final.stac-item
2023-10-16 09:18:08	ga_ls9c_ard_3-2-1_090078_2023-10-15_final.stac-item
2023-10-16 09:18:32	ga_ls9c_ard_3-2-1_090079_2023-10-15_final.stac-item
2023-10-16 09:18:56	ga_ls9c_ard_3-2-1_090080_2023-10-15_final.stac-item
2023-10-16 09:19:20	ga_ls9c_ard_3-2-1_090081_2023-10-15_final.stac-item
2023-10-16 09:19:44	ga_ls9c_ard_3-2-1_090082_2023-10-15_final.stac-item
2023-10-16 09:20:08	ga_ls9c_ard_3-2-1_090083_2023-10-15_final.stac-item
2023-10-18 09:06:35	ga_ls9c_ard_3-2-1_088080_2023-10-17_final.stac-item
2023-10-18 09:06:59	ga_ls9c_ard_3-2-1_088081_2023-10-17_final.stac-item
2023-10-18 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-10-17_final.stac-item
2023-10-18 09:07:47	ga_ls9c_ard_3-2-1_088083_2023-10-17_final.stac-item
2023-10-23 09:21:56	ga_ls9c_ard_3-2-1_091072_2023-10-22_final.stac-item
2023-10-23 09:22:19	ga_ls9c_ard_3-2-1_091073_2023-10-22_final.stac-item
2023-10-23 09:22:43	ga_ls9c_ard_3-2-1_091074_2023-10-22_final.stac-item
2023-10-23 09:23:07	ga_ls9c_ard_3-2-1_091075_2023-10-22_final.stac-item
2023-10-23 09:23:31	ga_ls9c_ard_3-2-1_091076_2023-10-22_final.stac-item
2023-10-23 09:23:55	ga_ls9c_ard_3-2-1_091077_2023-10-22_final.stac-item
2023-10-23 09:24:19	ga_ls9c_ard_3-2-1_091078_2023-10-22_final.stac-item
2023-10-23 09:24:43	ga_ls9c_ard_3-2-1_091079_2023-10-22_final.stac-item
2023-10-25 09:10:21	ga_ls9c_ard_3-2-1_089074_2023-10-24_final.stac-item
2023-10-25 09:10:45	ga_ls9c_ard_3-2-1_089075_2023-10-24_final.stac-item
2023-10-25 09:11:09	ga_ls9c_ard_3-2-1_089076_2023-10-24_final.stac-item
2023-10-25 09:11:33	ga_ls9c_ard_3-2-1_089077_2023-10-24_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-10-25 09:12:45	ga_ls9c_ard_3-2-1_089080_2023-10-24_final.stac-item
2023-10-25 09:13:09	ga_ls9c_ard_3-2-1_089081_2023-10-24_final.stac-item
2023-10-25 09:13:33	ga_ls9c_ard_3-2-1_089082_2023-10-24_final.stac-item
2023-10-25 09:13:57	ga_ls9c_ard_3-2-1_089083_2023-10-24_final.stac-item
2023-10-25 09:14:21	ga_ls9c_ard_3-2-1_089084_2023-10-24_final.stac-item
2023-10-25 09:14:45	ga_ls9c_ard_3-2-1_089085_2023-10-24_final.stac-item
2023-10-25 09:15:09	ga_ls9c_ard_3-2-1_089086_2023-10-24_final.stac-item
2023-10-30 09:27:39	ga_ls9c_ard_3-2-1_092071_2023-10-29_final.stac-item
2023-10-30 09:28:03	ga_ls9c_ard_3-2-1_092072_2023-10-29_final.stac-item
2023-10-30 09:28:26	ga_ls9c_ard_3-2-1_092073_2023-10-29_final.stac-item
2023-10-30 09:28:50	ga_ls9c_ard_3-2-1_092074_2023-10-29_final.stac-item
2023-10-30 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-10-29_final.stac-item
2023-11-01 09:16:27	ga_ls9c_ard_3-2-1_090074_2023-10-31_final.stac-item
2023-11-01 09:16:51	ga_ls9c_ard_3-2-1_090075_2023-10-31_final.stac-item
2023-11-01 09:17:15	ga_ls9c_ard_3-2-1_090076_2023-10-31_final.stac-item
2023-11-01 09:17:39	ga_ls9c_ard_3-2-1_090077_2023-10-31_final.stac-item
2023-11-01 09:18:03	ga_ls9c_ard_3-2-1_090078_2023-10-31_final.stac-item
2023-11-01 09:18:27	ga_ls9c_ard_3-2-1_090079_2023-10-31_final.stac-item
2023-11-01 09:18:50	ga_ls9c_ard_3-2-1_090080_2023-10-31_final.stac-item
2023-11-01 09:19:14	ga_ls9c_ard_3-2-1_090081_2023-10-31_final.stac-item
2023-11-01 09:19:38	ga_ls9c_ard_3-2-1_090082_2023-10-31_final.stac-item
2023-11-01 09:20:02	ga_ls9c_ard_3-2-1_090083_2023-10-31_final.stac-item
2023-11-03 09:06:27	ga_ls9c_ard_3-2-1_088080_2023-11-02_final.stac-item
2023-11-03 09:06:51	ga_ls9c_ard_3-2-1_088081_2023-11-02_final.stac-item
2023-11-03 09:07:15	ga_ls9c_ard_3-2-1_088082_2023-11-02_final.stac-item
2023-11-03 09:07:39	ga_ls9c_ard_3-2-1_088083_2023-11-02_final.stac-item
2023-11-15 09:27:38	ga_ls9c_ard_3-2-1_092071_2023-11-14_final.stac-item
2023-11-15 09:28:02	ga_ls9c_ard_3-2-1_092072_2023-11-14_final.stac-item
2023-11-15 09:28:26	ga_ls9c_ard_3-2-1_092073_2023-11-14_final.stac-item
2023-11-15 09:28:50	ga_ls9c_ard_3-2-1_092074_2023-11-14_final.stac-item
2023-11-15 09:29:14	ga_ls9c_ard_3-2-1_092075_2023-11-14_final.stac-item
2023-11-17 09:16:29	ga_ls9c_ard_3-2-1_090074_2023-11-16_final.stac-item
2023-11-17 09:16:53	ga_ls9c_ard_3-2-1_090075_2023-11-16_final.stac-item
2023-11-17 09:17:17	ga_ls9c_ard_3-2-1_090076_2023-11-16_final.stac-item
2023-11-17 09:17:41	ga_ls9c_ard_3-2-1_090077_2023-11-16_final.stac-item
2023-11-17 09:18:05	ga_ls9c_ard_3-2-1_090078_2023-11-16_final.stac-item
2023-11-17 09:18:29	ga_ls9c_ard_3-2-1_090079_2023-11-16_final.stac-item
2023-11-17 09:18:53	ga_ls9c_ard_3-2-1_090080_2023-11-16_final.stac-item
2023-11-17 09:19:17	ga_ls9c_ard_3-2-1_090081_2023-11-16_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-11-17 09:20:05	ga_ls9c_ard_3-2-1_090083_2023-11-16_final.stac-item
2023-11-19 09:06:33	ga_ls9c_ard_3-2-1_088080_2023-11-18_final.stac-item
2023-11-19 09:06:57	ga_ls9c_ard_3-2-1_088081_2023-11-18_final.stac-item
2023-11-19 09:07:21	ga_ls9c_ard_3-2-1_088082_2023-11-18_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-24 09:21:59	ga_ls9c_ard_3-2-1_091072_2023-11-23_final.stac-item
2023-11-24 09:22:22	ga_ls9c_ard_3-2-1_091073_2023-11-23_final.stac-item
2023-11-24 09:22:46	ga_ls9c_ard_3-2-1_091074_2023-11-23_final.stac-item
2023-11-24 09:23:10	ga_ls9c_ard_3-2-1_091075_2023-11-23_final.stac-item
2023-11-24 09:23:34	ga_ls9c_ard_3-2-1_091076_2023-11-23_final.stac-item
2023-11-24 09:23:58	ga_ls9c_ard_3-2-1_091077_2023-11-23_final.stac-item
2023-11-24 09:24:22	ga_ls9c_ard_3-2-1_091078_2023-11-23_final.stac-item
2023-11-24 09:24:46	ga_ls9c_ard_3-2-1_091079_2023-11-23_final.stac-item
2023-11-26 09:10:26	ga_ls9c_ard_3-2-1_089074_2023-11-25_final.stac-item
2023-11-26 09:10:50	ga_ls9c_ard_3-2-1_089075_2023-11-25_final.stac-item
2023-11-26 09:11:14	ga_ls9c_ard_3-2-1_089076_2023-11-25_final.stac-item
2023-11-26 09:11:38	ga_ls9c_ard_3-2-1_089077_2023-11-25_final.stac-item
2023-11-26 09:12:01	ga_ls9c_ard_3-2-1_089078_2023-11-25_final.stac-item
2023-11-26 09:12:25	ga_ls9c_ard_3-2-1_089079_2023-11-25_final.stac-item
2023-11-26 09:12:49	ga_ls9c_ard_3-2-1_089080_2023-11-25_final.stac-item
2023-11-26 09:13:13	ga_ls9c_ard_3-2-1_089081_2023-11-25_final.stac-item
2023-11-26 09:13:37	ga_ls9c_ard_3-2-1_089082_2023-11-25_final.stac-item
2023-11-26 09:14:01	ga_ls9c_ard_3-2-1_089083_2023-11-25_final.stac-item
2023-11-26 09:14:25	ga_ls9c_ard_3-2-1_089084_2023-11-25_final.stac-item
2023-11-26 09:14:49	ga_ls9c_ard_3-2-1_089085_2023-11-25_final.stac-item
2023-11-26 09:15:13	ga_ls9c_ard_3-2-1_089086_2023-11-25_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