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

73 results

Time (local)	Label
2021-11-03 11:34:49	ga_ls9c_ard_3-2-1_112078_2021-11-03_final.stac-item
2021-12-10 10:27:25	ga_ls9c_ard_3-2-1_101081_2021-12-10_final.stac-item
2021-12-12 11:53:07	ga_ls9c_ard_3-2-1_115079_2021-12-12_final.stac-item
2021-12-16 09:47:52	ga_ls9c_ard_3-2-1_095075_2021-12-16_final.stac-item
2022-01-03 09:35:55	ga_ls9c_ard_3-2-1_093076_2022-01-03_final.stac-item
2022-01-13 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-01-13_final.stac-item
2022-02-01 09:06:37	ga_ls9c_ard_3-2-1_088080_2022-01-31_final.stac-item
2022-02-22 09:26:36	ga_ls9c_ard_3-2-1_091084_2022-02-21_final.stac-item
2022-02-23 10:09:27	ga_ls9c_ard_3-2-1_098083_2022-02-23_final.stac-item
2022-03-06 09:46:50	ga_ls9c_ard_3-2-1_095073_2022-03-06_final.stac-item
2022-04-08 10:31:35	ga_ls9c_ard_3-2-1_102077_2022-04-08_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-07 09:57:39	ga_ls9c_ard_3-2-1_097070_2022-05-07_final.stac-item
2022-05-12 10:18:56	ga_ls9c_ard_3-2-1_100077_2022-05-12_final.stac-item
2022-07-30 09:34:05	ga_ls9c_ard_3-2-1_093072_2022-07-30_final.stac-item
2022-08-24 09:28:53	ga_ls9c_ard_3-2-1_092074_2022-08-23_final.stac-item
2022-09-14 09:51:52	ga_ls9c_ard_3-2-1_095085_2022-09-14_final.stac-item
2022-09-23 09:44:10	ga_ls9c_ard_3-2-1_094081_2022-09-23_final.stac-item
2022-10-04 09:26:02	ga_ls9c_ard_3-2-1_091082_2022-10-03_final.stac-item
2022-10-09 11:20:41	ga_ls9c_ard_3-2-1_110075_2022-10-09_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-21 09:28:32	ga_ls9c_ard_3-2-1_091088_2022-11-20_final.stac-item
2022-11-22 10:08:36	ga_ls9c_ard_3-2-1_098080_2022-11-22_final.stac-item
2022-11-26 09:41:04	ga_ls9c_ard_3-2-1_094073_2022-11-26_final.stac-item
2022-12-14 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-14_final.stac-item
2022-12-19 11:24:07	ga_ls9c_ard_3-2-1_111068_2022-12-19_final.stac-item
2022-12-25 09:12:55	ga_ls9c_ard_3-2-1_089080_2022-12-24_final.stac-item
2022-12-29 10:24:19	ga_ls9c_ard_3-2-1_101073_2022-12-29_final.stac-item
2023-01-17 10:54:44	ga_ls9c_ard_3-2-1_106072_2023-01-17_final.stac-item
2023-01-30 10:23:32	ga_ls9c_ard_3-2-1_101071_2023-01-30_final.stac-item
2023-02-03 11:38:56	ga_ls9c_ard_3-2-1_113074_2023-02-03_final.stac-item
2023-02-13 10:38:44	ga_ls9c_ard_3-2-1_103078_2023-02-13_final.stac-item
2023-02-16 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-02-16_final.stac-item
2023-03-15 09:12:16	ga_ls9c_ard_3-2-1_089079_2023-03-14_final.stac-item
2023-03-22 09:18:24	ga_ls9c_ard_3-2-1_090079_2023-03-21_final.stac-item
2023-04-02 10:36:36	ga_ls9c_ard_3-2-1_103074_2023-04-02_final.stac-item
2023-04-06 10:14:16	ga_ls9c_ard_3-2-1_099080_2023-04-06_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-05-09 10:58:02	ga_ls9c_ard_3-2-1_106082_2023-05-09_final.stac-item
2023-05-14 11:16:32	ga_ls9c_ard_3-2-1_109082_2023-05-14_final.stac-item
2023-05-17 10:09:19	ga_ls9c_ard_3-2-1_098084_2023-05-17_final.stac-item
2023-05-30 11:14:24	ga_ls9c_ard_3-2-1_109077_2023-05-30_final.stac-item
2023-06-09 10:08:32	ga_ls9c_ard_3-2-1_099067_2023-06-09_final.stac-item
2023-06-19 09:12:38	ga_ls9c_ard_3-2-1_089082_2023-06-18_final.stac-item
2023-07-04 10:04:27	ga_ls9c_ard_3-2-1_098072_2023-07-04_final.stac-item
2023-07-08 11:19:04	ga_ls9c_ard_3-2-1_110073_2023-07-08_final.stac-item
2023-07-14 09:06:20	ga_ls9c_ard_3-2-1_088081_2023-07-13_final.stac-item
2023-07-20 10:03:45	ga_ls9c_ard_3-2-1_098070_2023-07-20_final.stac-item
2023-07-21 10:48:36	ga_ls9c_ard_3-2-1_105074_2023-07-21_final.stac-item
2023-07-27 10:08:45	ga_ls9c_ard_3-2-1_099067_2023-07-27_final.stac-item
2023-07-29 11:40:30	ga_ls9c_ard_3-2-1_113080_2023-07-29_final.stac-item
2023-08-11 09:28:50	ga_ls9c_ard_3-2-1_092075_2023-08-10_final.stac-item
2023-08-27 09:28:34	ga_ls9c_ard_3-2-1_092074_2023-08-26_final.stac-item
2023-09-01 11:24:26	ga_ls9c_ard_3-2-1_111070_2023-09-01_final.stac-item
2023-09-07 09:13:19	ga_ls9c_ard_3-2-1_089082_2023-09-06_final.stac-item
2023-09-29 11:52:01	ga_ls9c_ard_3-2-1_115077_2023-09-29_final.stac-item
2023-10-19 09:52:14	ga_ls9c_ard_3-2-1_095086_2023-10-19_final.stac-item
2023-10-21 11:14:46	ga_ls9c_ard_3-2-1_109076_2023-10-21_final.stac-item
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-10-31 10:11:41	ga_ls9c_ard_3-2-1_099073_2023-10-31_final.stac-item
2023-11-08 09:27:27	ga_ls9c_ard_3-2-1_091086_2023-11-07_final.stac-item
2023-11-22 09:40:42	ga_ls9c_ard_3-2-1_093088_2023-11-22_final.stac-item
2023-12-16 10:28:12	ga_ls9c_ard_3-2-1_101083_2023-12-16_final.stac-item
2023-12-22 09:47:09	ga_ls9c_ard_3-2-1_095073_2023-12-22_final.stac-item
2024-01-26 10:18:20	ga_ls9c_ard_3-2-1_100074_2024-01-26_final.stac-item
2024-02-05 10:56:18	ga_ls9c_ard_3-2-1_106076_2024-02-05_final.stac-item
2024-02-13 10:03:14	ga_ls9c_ard_3-2-1_098067_2024-02-13_final.stac-item
2024-02-19 11:11:18	ga_ls9c_ard_3-2-1_108083_2024-02-19_final.stac-item
2024-02-22 09:59:39	ga_ls9c_ard_3-2-1_097074_2024-02-22_final.stac-item
2024-02-26 09:39:45	ga_ls9c_ard_3-2-1_093086_2024-02-26_final.stac-item
2024-03-17 10:49:10	ga_ls9c_ard_3-2-1_105074_2024-03-17_final.stac-item
2024-04-10 10:03:07	ga_ls9c_ard_3-2-1_097083_2024-04-10_final.stac-item
2024-05-07 11:20:19	ga_ls9c_ard_3-2-1_110076_2024-05-07_nrt.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