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

58 results

Time (local)	Label
2021-11-07 09:20:16	ga_ls9c_ard_3-2-1_090082_2021-11-06_final.stac-item
2021-11-08 09:59:50	ga_ls9c_ard_3-2-1_097081_2021-11-08_final.stac-item
2021-12-06 10:49:00	ga_ls9c_ard_3-2-1_105073_2021-12-06_final.stac-item
2022-01-31 11:41:07	ga_ls9c_ard_3-2-1_113080_2022-01-31_final.stac-item
2022-02-03 10:29:32	ga_ls9c_ard_3-2-1_102071_2022-02-03_final.stac-item
2022-02-22 09:28:36	ga_ls9c_ard_3-2-1_091089_2022-02-21_final.stac-item
2022-04-02 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-04-02_final.stac-item
2022-04-08 10:32:46	ga_ls9c_ard_3-2-1_102080_2022-04-08_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-11 09:23:10	ga_ls9c_ard_3-2-1_091076_2022-04-10_final.stac-item
2022-04-27 11:01:07	ga_ls9c_ard_3-2-1_107074_2022-04-27_final.stac-item
2022-06-08 10:00:42	ga_ls9c_ard_3-2-1_097078_2022-06-08_final.stac-item
2022-06-08 11:37:59	ga_ls9c_ard_3-2-1_113074_2022-06-08_final.stac-item
2022-06-14 11:03:46	ga_ls9c_ard_3-2-1_107081_2022-06-14_final.stac-item
2022-06-16 10:46:14	ga_ls9c_ard_3-2-1_105068_2022-06-16_final.stac-item
2022-06-19 09:44:18	ga_ls9c_ard_3-2-1_094083_2022-06-19_final.stac-item
2022-06-30 11:03:14	ga_ls9c_ard_3-2-1_107079_2022-06-30_final.stac-item
2022-07-07 09:28:31	ga_ls9c_ard_3-2-1_092074_2022-07-06_final.stac-item
2022-07-13 10:28:40	ga_ls9c_ard_3-2-1_102070_2022-07-13_final.stac-item
2022-07-19 11:36:08	ga_ls9c_ard_3-2-1_112084_2022-07-19_final.stac-item
2022-07-28 09:50:48	ga_ls9c_ard_3-2-1_095083_2022-07-28_final.stac-item
2022-09-13 09:07:00	ga_ls9c_ard_3-2-1_088081_2022-09-12_final.stac-item
2022-09-17 10:21:12	ga_ls9c_ard_3-2-1_100081_2022-09-17_final.stac-item
2022-09-18 09:25:35	ga_ls9c_ard_3-2-1_091081_2022-09-17_final.stac-item
2022-09-25 09:34:36	ga_ls9c_ard_3-2-1_092088_2022-09-25_final.stac-item
2022-10-28 10:15:34	ga_ls9c_ard_3-2-1_099082_2022-10-28_final.stac-item
2022-10-29 09:21:08	ga_ls9c_ard_3-2-1_090085_2022-10-28_final.stac-item
2022-11-22 10:08:36	ga_ls9c_ard_3-2-1_098080_2022-11-22_final.stac-item
2022-11-27 10:26:43	ga_ls9c_ard_3-2-1_101079_2022-11-27_final.stac-item
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final.stac-item
2022-12-03 09:52:24	ga_ls9c_ard_3-2-1_095086_2022-12-03_final.stac-item
2022-12-23 11:05:45	ga_ls9c_ard_3-2-1_107084_2022-12-23_final.stac-item
2022-12-26 09:57:47	ga_ls9c_ard_3-2-1_096084_2022-12-26_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-17 09:21:50	ga_ls9c_ard_3-2-1_090087_2023-01-16_final.stac-item
2023-01-22 09:40:44	ga_ls9c_ard_3-2-1_093088_2023-01-22_final.stac-item
2023-03-11 11:17:51	ga_ls9c_ard_3-2-1_109084_2023-03-11_final.stac-item
2023-03-24 10:45:17	ga_ls9c_ard_3-2-1_104080_2023-03-24_final.stac-item
2023-04-02 10:37:48	ga_ls9c_ard_3-2-1_103077_2023-04-02_final.stac-item
2023-06-01 09:23:09	ga_ls9c_ard_3-2-1_091077_2023-05-31_final.stac-item
2023-06-01 11:01:14	ga_ls9c_ard_3-2-1_107075_2023-06-01_final.stac-item
2023-06-06 09:40:28	ga_ls9c_ard_3-2-1_094074_2023-06-06_final.stac-item
2023-06-25 10:08:27	ga_ls9c_ard_3-2-1_099067_2023-06-25_final.stac-item
2023-07-11 10:09:55	ga_ls9c_ard_3-2-1_099070_2023-07-11_final.stac-item
2023-07-13 11:37:15	ga_ls9c_ard_3-2-1_113072_2023-07-13_final.stac-item
2023-07-24 11:18:41	ga_ls9c_ard_3-2-1_110072_2023-07-24_final.stac-item
2023-09-03 09:39:59	ga_ls9c_ard_3-2-1_093087_2023-09-03_final.stac-item
2023-09-05 11:00:33	ga_ls9c_ard_3-2-1_107072_2023-09-05_final.stac-item
2023-10-08 11:45:09	ga_ls9c_ard_3-2-1_114075_2023-10-08_final.stac-item
2023-10-30 11:06:32	ga_ls9c_ard_3-2-1_108071_2023-10-30_final.stac-item
2023-10-30 11:08:07	ga_ls9c_ard_3-2-1_108075_2023-10-30_final.stac-item
2023-12-29 11:35:23	ga_ls9c_ard_3-2-1_112081_2023-12-29_final.stac-item
2024-01-17 10:25:45	ga_ls9c_ard_3-2-1_101077_2024-01-17_final.stac-item
2024-01-21 10:04:12	ga_ls9c_ard_3-2-1_097085_2024-01-21_final.stac-item
2024-02-28 09:27:24	ga_ls9c_ard_3-2-1_091086_2024-02-27_final.stac-item
2024-02-29 10:09:29	ga_ls9c_ard_3-2-1_098083_2024-02-29_final.stac-item
2024-03-11 09:51:22	ga_ls9c_ard_3-2-1_095084_2024-03-11_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