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
2021-11-05 11:13:41	ga_ls9c_ard_3-2-1_109072_2021-11-05_final.stac-item
2021-11-17 09:26:04	ga_ls9c_ard_3-2-1_091084_2021-11-16_final.stac-item
2021-12-14 09:58:40	ga_ls9c_ard_3-2-1_097071_2021-12-14_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2021-12-21 10:05:38	ga_ls9c_ard_3-2-1_098073_2021-12-21_final.stac-item
2022-02-20 09:39:23	ga_ls9c_ard_3-2-1_093085_2022-02-20_final.stac-item
2022-03-10 11:04:59	ga_ls9c_ard_3-2-1_107083_2022-03-10_final.stac-item
2022-03-12 09:14:32	ga_ls9c_ard_3-2-1_089085_2022-03-11_final.stac-item
2022-03-20 09:56:46	ga_ls9c_ard_3-2-1_097067_2022-03-20_final.stac-item
2022-04-02 09:34:12	ga_ls9c_ard_3-2-1_092088_2022-04-02_final.stac-item
2022-04-23 09:52:08	ga_ls9c_ard_3-2-1_095087_2022-04-23_final.stac-item
2022-04-28 10:05:06	ga_ls9c_ard_3-2-1_098073_2022-04-28_final.stac-item
2022-05-06 09:18:48	ga_ls9c_ard_3-2-1_090081_2022-05-05_final.stac-item
2022-05-27 09:34:21	ga_ls9c_ard_3-2-1_093074_2022-05-27_final.stac-item
2022-06-03 09:40:09	ga_ls9c_ard_3-2-1_094073_2022-06-03_final.stac-item
2022-06-19 09:44:18	ga_ls9c_ard_3-2-1_094083_2022-06-19_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-06-21 09:33:37	ga_ls9c_ard_3-2-1_092087_2022-06-21_final.stac-item
2022-07-07 09:33:42	ga_ls9c_ard_3-2-1_092087_2022-07-07_final.stac-item
2022-07-21 09:40:56	ga_ls9c_ard_3-2-1_094074_2022-07-21_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-09-28 09:58:20	ga_ls9c_ard_3-2-1_097070_2022-09-28_final.stac-item
2022-10-03 10:17:40	ga_ls9c_ard_3-2-1_100072_2022-10-03_final.stac-item
2022-10-04 11:04:31	ga_ls9c_ard_3-2-1_107081_2022-10-04_final.stac-item
2022-10-12 11:51:37	ga_ls9c_ard_3-2-1_115075_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
2022-10-14 09:59:11	ga_ls9c_ard_3-2-1_097072_2022-10-14_final.stac-item
2022-10-30 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-10-30_final.stac-item
2022-10-31 10:44:03	ga_ls9c_ard_3-2-1_104076_2022-10-31_final.stac-item
2022-11-05 09:24:53	ga_ls9c_ard_3-2-1_091079_2022-11-04_final.stac-item
2022-11-05 11:03:46	ga_ls9c_ard_3-2-1_107079_2022-11-05_final.stac-item
2022-11-06 11:45:51	ga_ls9c_ard_3-2-1_114076_2022-11-06_final.stac-item
2022-11-12 11:06:25	ga_ls9c_ard_3-2-1_108070_2022-11-12_final.stac-item
2022-11-21 09:27:44	ga_ls9c_ard_3-2-1_091086_2022-11-20_final.stac-item
2022-11-21 09:28:56	ga_ls9c_ard_3-2-1_091089_2022-11-20_final.stac-item
2022-11-22 11:46:41	ga_ls9c_ard_3-2-1_114078_2022-11-22_final.stac-item
2022-11-23 10:52:39	ga_ls9c_ard_3-2-1_105082_2022-11-23_final.stac-item
2022-11-25 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-25_final.stac-item
2022-11-26 11:23:56	ga_ls9c_ard_3-2-1_110083_2022-11-26_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-03 11:26:30	ga_ls9c_ard_3-2-1_111074_2022-12-03_final.stac-item
2022-12-08 10:05:23	ga_ls9c_ard_3-2-1_098072_2022-12-08_final.stac-item
2022-12-09 10:52:15	ga_ls9c_ard_3-2-1_105081_2022-12-09_final.stac-item
2022-12-15 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-12-15_final.stac-item
2022-12-17 09:59:12	ga_ls9c_ard_3-2-1_097072_2022-12-17_final.stac-item
2022-12-19 09:47:38	ga_ls9c_ard_3-2-1_095074_2022-12-19_final.stac-item
2022-12-28 11:23:08	ga_ls9c_ard_3-2-1_110081_2022-12-28_final.stac-item
2022-12-28 11:24:19	ga_ls9c_ard_3-2-1_110084_2022-12-28_final.stac-item
2023-01-07 10:18:09	ga_ls9c_ard_3-2-1_100073_2023-01-07_final.stac-item
2023-01-10 10:47:51	ga_ls9c_ard_3-2-1_105070_2023-01-10_final.stac-item
2023-01-10 10:50:14	ga_ls9c_ard_3-2-1_105076_2023-01-10_final.stac-item
2023-01-22 09:39:08	ga_ls9c_ard_3-2-1_093084_2023-01-22_final.stac-item
2023-01-30 10:23:32	ga_ls9c_ard_3-2-1_101071_2023-01-30_final.stac-item
2023-01-31 09:29:31	ga_ls9c_ard_3-2-1_092075_2023-01-30_final.stac-item
2023-02-01 10:15:59	ga_ls9c_ard_3-2-1_099083_2023-02-01_final.stac-item
2023-02-02 09:21:58	ga_ls9c_ard_3-2-1_090087_2023-02-01_final.stac-item
2023-02-04 10:40:55	ga_ls9c_ard_3-2-1_104068_2023-02-04_final.stac-item
2023-02-09 11:04:40	ga_ls9c_ard_3-2-1_107081_2023-02-09_final.stac-item
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final.stac-item
2023-02-10 10:07:51	ga_ls9c_ard_3-2-1_098078_2023-02-10_final.stac-item
2023-02-10 11:45:56	ga_ls9c_ard_3-2-1_114076_2023-02-10_final.stac-item
2023-02-11 09:13:01	ga_ls9c_ard_3-2-1_089080_2023-02-10_final.stac-item
2023-04-23 09:18:56	ga_ls9c_ard_3-2-1_090081_2023-04-22_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-04-24 11:38:16	ga_ls9c_ard_3-2-1_113074_2023-04-24_final.stac-item
2023-04-30 09:27:48	ga_ls9c_ard_3-2-1_091088_2023-04-29_final.stac-item
2023-07-16 10:28:04	ga_ls9c_ard_3-2-1_102069_2023-07-16_final.stac-item
2023-07-20 10:04:33	ga_ls9c_ard_3-2-1_098072_2023-07-20_final.stac-item
2023-07-20 11:45:26	ga_ls9c_ard_3-2-1_114077_2023-07-20_final.stac-item
2023-07-22 09:51:47	ga_ls9c_ard_3-2-1_096071_2023-07-22_final.stac-item
2023-07-22 09:56:34	ga_ls9c_ard_3-2-1_096083_2023-07-22_final.stac-item
2023-07-23 10:39:01	ga_ls9c_ard_3-2-1_103081_2023-07-23_final.stac-item
2023-07-24 11:18:17	ga_ls9c_ard_3-2-1_110071_2023-07-24_final.stac-item
2023-07-26 09:28:39	ga_ls9c_ard_3-2-1_092075_2023-07-25_final.stac-item
2023-07-28 09:17:32	ga_ls9c_ard_3-2-1_090078_2023-07-27_final.stac-item
2023-07-28 09:17:56	ga_ls9c_ard_3-2-1_090079_2023-07-27_final.stac-item
2023-07-28 09:20:19	ga_ls9c_ard_3-2-1_090085_2023-07-27_final.stac-item
2023-08-03 11:57:55	ga_ls9c_ard_3-2-1_116077_2023-08-03_final.stac-item
2023-08-06 09:13:04	ga_ls9c_ard_3-2-1_089082_2023-08-05_final.stac-item
2023-10-13 10:27:41	ga_ls9c_ard_3-2-1_101082_2023-10-13_final.stac-item
2023-10-15 11:52:14	ga_ls9c_ard_3-2-1_115077_2023-10-15_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-17 09:59:48	ga_ls9c_ard_3-2-1_097074_2023-10-17_final.stac-item
2023-10-20 10:28:19	ga_ls9c_ard_3-2-1_102068_2023-10-20_final.stac-item
2023-10-21 09:35:29	ga_ls9c_ard_3-2-1_093075_2023-10-21_final.stac-item
2023-10-23 11:02:24	ga_ls9c_ard_3-2-1_107076_2023-10-23_final.stac-item
2023-10-24 11:46:28	ga_ls9c_ard_3-2-1_114078_2023-10-24_final.stac-item
2023-10-25 10:52:26	ga_ls9c_ard_3-2-1_105082_2023-10-25_final.stac-item
2023-10-26 09:58:00	ga_ls9c_ard_3-2-1_096085_2023-10-26_final.stac-item
2023-10-29 10:25:40	ga_ls9c_ard_3-2-1_101077_2023-10-29_final.stac-item
2023-11-01 09:20:50	ga_ls9c_ard_3-2-1_090085_2023-10-31_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-01 09:22:26	ga_ls9c_ard_3-2-1_090089_2023-10-31_final.stac-item
2023-11-15 11:06:07	ga_ls9c_ard_3-2-1_108070_2023-11-15_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-21 10:28:20	ga_ls9c_ard_3-2-1_102068_2023-11-21_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_final.stac-item
2023-11-23 10:19:59	ga_ls9c_ard_3-2-1_100078_2023-11-23_final.stac-item
2023-11-25 10:03:39	ga_ls9c_ard_3-2-1_098068_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