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
2021-11-10 09:37:54	ga_ls9c_ard_3-2-1_094073_2021-11-10_final.stac-item
2021-12-04 09:26:53	ga_ls9c_ard_3-2-1_091084_2021-12-03_final.stac-item
2021-12-08 10:35:01	ga_ls9c_ard_3-2-1_103069_2021-12-08_final.stac-item
2021-12-12 10:14:14	ga_ls9c_ard_3-2-1_099079_2021-12-12_final.stac-item
2021-12-22 09:16:24	ga_ls9c_ard_3-2-1_089089_2021-12-21_final.stac-item
2022-01-04 10:17:59	ga_ls9c_ard_3-2-1_100073_2022-01-04_final.stac-item
2022-01-13 11:51:50	ga_ls9c_ard_3-2-1_115076_2022-01-13_final.stac-item
2022-01-19 11:14:23	ga_ls9c_ard_3-2-1_109075_2022-01-19_final.stac-item
2022-02-02 11:25:34	ga_ls9c_ard_3-2-1_111072_2022-02-02_final.stac-item
2022-02-18 11:25:03	ga_ls9c_ard_3-2-1_111071_2022-02-18_final.stac-item
2022-02-21 10:21:26	ga_ls9c_ard_3-2-1_100082_2022-02-21_final.stac-item
2022-03-06 09:47:14	ga_ls9c_ard_3-2-1_095074_2022-03-06_final.stac-item
2022-03-06 11:24:31	ga_ls9c_ard_3-2-1_111070_2022-03-06_final.stac-item
2022-03-20 09:57:58	ga_ls9c_ard_3-2-1_097070_2022-03-20_final.stac-item
2022-04-03 11:51:33	ga_ls9c_ard_3-2-1_115076_2022-04-03_final.stac-item
2022-04-13 10:49:16	ga_ls9c_ard_3-2-1_105075_2022-04-13_final.stac-item
2022-04-20 09:17:16	ga_ls9c_ard_3-2-1_090077_2022-04-19_final.stac-item
2022-04-28 10:04:18	ga_ls9c_ard_3-2-1_098071_2022-04-28_final.stac-item
2022-05-04 11:09:15	ga_ls9c_ard_3-2-1_108079_2022-05-04_final.stac-item
2022-05-05 10:12:50	ga_ls9c_ard_3-2-1_099077_2022-05-05_final.stac-item
2022-05-10 10:32:55	ga_ls9c_ard_3-2-1_102081_2022-05-10_final.stac-item
2022-05-21 10:08:38	ga_ls9c_ard_3-2-1_099067_2022-05-21_final.stac-item
2022-06-12 09:33:13	ga_ls9c_ard_3-2-1_093071_2022-06-12_final.stac-item
2022-06-22 10:09:20	ga_ls9c_ard_3-2-1_099068_2022-06-22_final.stac-item
2022-06-24 09:57:50	ga_ls9c_ard_3-2-1_097070_2022-06-24_final.stac-item
2022-07-02 10:46:05	ga_ls9c_ard_3-2-1_105067_2022-07-02_final.stac-item
2022-07-11 09:06:33	ga_ls9c_ard_3-2-1_088081_2022-07-10_final.stac-item
2022-07-28 09:46:25	ga_ls9c_ard_3-2-1_095072_2022-07-28_final.stac-item
2022-08-01 09:23:44	ga_ls9c_ard_3-2-1_091077_2022-07-31_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-09-26 10:09:53	ga_ls9c_ard_3-2-1_099068_2022-09-26_final.stac-item
2022-10-02 11:16:29	ga_ls9c_ard_3-2-1_109080_2022-10-02_final.stac-item
2022-10-08 10:36:12	ga_ls9c_ard_3-2-1_103072_2022-10-08_final.stac-item
2022-10-12 10:09:32	ga_ls9c_ard_3-2-1_099067_2022-10-12_final.stac-item
2022-10-15 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-15_final.stac-item
2022-10-16 09:47:15	ga_ls9c_ard_3-2-1_095073_2022-10-16_final.stac-item
2022-10-18 09:35:41	ga_ls9c_ard_3-2-1_093075_2022-10-18_final.stac-item
2022-10-23 11:32:43	ga_ls9c_ard_3-2-1_112074_2022-10-23_final.stac-item
2022-10-25 11:18:22	ga_ls9c_ard_3-2-1_110069_2022-10-25_final.stac-item
2022-10-28 10:09:35	ga_ls9c_ard_3-2-1_099067_2022-10-28_final.stac-item
2022-11-05 11:00:11	ga_ls9c_ard_3-2-1_107070_2022-11-05_final.stac-item
2022-11-14 09:21:10	ga_ls9c_ard_3-2-1_090085_2022-11-13_final.stac-item
2022-11-14 10:56:03	ga_ls9c_ard_3-2-1_106075_2022-11-14_final.stac-item
2022-11-15 09:57:14	ga_ls9c_ard_3-2-1_097067_2022-11-15_final.stac-item
2022-11-15 10:02:02	ga_ls9c_ard_3-2-1_097079_2022-11-15_final.stac-item
2022-11-17 11:25:22	ga_ls9c_ard_3-2-1_111071_2022-11-17_final.stac-item
2022-11-23 09:13:46	ga_ls9c_ard_3-2-1_089082_2022-11-22_final.stac-item
2022-11-23 10:53:03	ga_ls9c_ard_3-2-1_105083_2022-11-23_final.stac-item
2022-12-06 10:20:08	ga_ls9c_ard_3-2-1_100078_2022-12-06_final.stac-item
2022-12-08 11:47:52	ga_ls9c_ard_3-2-1_114081_2022-12-08_final.stac-item
2022-12-19 11:26:07	ga_ls9c_ard_3-2-1_111073_2022-12-19_final.stac-item
2022-12-21 11:14:32	ga_ls9c_ard_3-2-1_109075_2022-12-21_final.stac-item
2022-12-23 11:00:10	ga_ls9c_ard_3-2-1_107070_2022-12-23_final.stac-item
2022-12-31 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-12-31_final.stac-item
2023-01-01 09:21:56	ga_ls9c_ard_3-2-1_090087_2022-12-31_final.stac-item
2023-01-01 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-31_final.stac-item
2023-01-05 10:30:55	ga_ls9c_ard_3-2-1_102074_2023-01-05_final.stac-item
2023-01-08 09:22:56	ga_ls9c_ard_3-2-1_091074_2023-01-07_final.stac-item
2023-01-09 10:08:59	ga_ls9c_ard_3-2-1_098081_2023-01-09_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-10 09:13:45	ga_ls9c_ard_3-2-1_089082_2023-01-09_final.stac-item
2023-01-16 11:52:46	ga_ls9c_ard_3-2-1_115078_2023-01-16_final.stac-item
2023-01-17 09:21:27	ga_ls9c_ard_3-2-1_090086_2023-01-16_final.stac-item
2023-02-02 09:21:58	ga_ls9c_ard_3-2-1_090087_2023-02-01_final.stac-item
2023-02-02 10:55:16	ga_ls9c_ard_3-2-1_106073_2023-02-02_final.stac-item
2023-02-11 09:11:49	ga_ls9c_ard_3-2-1_089077_2023-02-10_final.stac-item
2023-02-12 09:53:29	ga_ls9c_ard_3-2-1_096073_2023-02-12_final.stac-item
2023-03-02 09:40:05	ga_ls9c_ard_3-2-1_094071_2023-03-02_final.stac-item
2023-03-13 09:22:38	ga_ls9c_ard_3-2-1_091074_2023-03-12_final.stac-item
2023-03-30 10:07:17	ga_ls9c_ard_3-2-1_098078_2023-03-30_final.stac-item
2023-03-30 11:45:22	ga_ls9c_ard_3-2-1_114076_2023-03-30_final.stac-item
2023-03-31 09:13:16	ga_ls9c_ard_3-2-1_089082_2023-03-30_final.stac-item
2023-04-21 11:05:48	ga_ls9c_ard_3-2-1_108070_2023-04-21_final.stac-item
2023-04-24 09:57:00	ga_ls9c_ard_3-2-1_097068_2023-04-24_final.stac-item
2023-04-24 11:41:52	ga_ls9c_ard_3-2-1_113083_2023-04-24_final.stac-item
2023-04-28 09:33:49	ga_ls9c_ard_3-2-1_093072_2023-04-28_final.stac-item
2023-04-29 10:16:40	ga_ls9c_ard_3-2-1_100071_2023-04-29_final.stac-item
2023-04-30 11:01:06	ga_ls9c_ard_3-2-1_107074_2023-04-30_final.stac-item
2023-05-18 10:46:11	ga_ls9c_ard_3-2-1_105068_2023-05-18_final.stac-item
2023-05-21 09:39:46	ga_ls9c_ard_3-2-1_094072_2023-05-21_final.stac-item
2023-05-21 09:45:45	ga_ls9c_ard_3-2-1_094087_2023-05-21_final.stac-item
2023-06-02 10:07:12	ga_ls9c_ard_3-2-1_098079_2023-06-02_final.stac-item
2023-06-22 11:23:13	ga_ls9c_ard_3-2-1_110084_2023-06-22_final.stac-item
2023-06-26 09:16:25	ga_ls9c_ard_3-2-1_090076_2023-06-25_final.stac-item
2023-07-20 10:03:45	ga_ls9c_ard_3-2-1_098070_2023-07-20_final.stac-item
2023-07-27 10:09:57	ga_ls9c_ard_3-2-1_099070_2023-07-27_final.stac-item
2023-07-30 09:06:24	ga_ls9c_ard_3-2-1_088081_2023-07-29_final.stac-item
2023-07-30 10:42:06	ga_ls9c_ard_3-2-1_104073_2023-07-30_final.stac-item
2023-08-03 10:16:38	ga_ls9c_ard_3-2-1_100071_2023-08-03_final.stac-item
2023-08-06 09:11:52	ga_ls9c_ard_3-2-1_089079_2023-08-05_final.stac-item
2023-08-12 11:51:47	ga_ls9c_ard_3-2-1_115077_2023-08-12_final.stac-item
2023-10-15 11:51:26	ga_ls9c_ard_3-2-1_115075_2023-10-15_final.stac-item
2023-10-25 09:11:57	ga_ls9c_ard_3-2-1_089078_2023-10-24_final.stac-item
2023-10-31 10:16:05	ga_ls9c_ard_3-2-1_099084_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
2023-11-02 09:57:42	ga_ls9c_ard_3-2-1_097069_2023-11-02_final.stac-item
2023-11-04 09:46:32	ga_ls9c_ard_3-2-1_095072_2023-11-04_final.stac-item
2023-11-14 10:25:39	ga_ls9c_ard_3-2-1_101077_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
2023-11-16 11:52:34	ga_ls9c_ard_3-2-1_115078_2023-11-16_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