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
2021-11-09 10:37:00	ga_ls9c_ard_3-2-1_103074_2021-11-09_final.stac-item
2021-11-22 09:30:26	ga_ls9c_ard_3-2-1_091089_2021-11-22_final.stac-item
2021-12-06 09:12:54	ga_ls9c_ard_3-2-1_089080_2021-12-05_final.stac-item
2021-12-07 09:52:34	ga_ls9c_ard_3-2-1_096071_2021-12-07_final.stac-item
2021-12-20 09:26:45	ga_ls9c_ard_3-2-1_091084_2021-12-19_final.stac-item
2021-12-28 11:53:29	ga_ls9c_ard_3-2-1_115080_2021-12-28_final.stac-item
2022-01-01 09:46:17	ga_ls9c_ard_3-2-1_095071_2022-01-01_final.stac-item
2022-01-06 10:08:00	ga_ls9c_ard_3-2-1_098079_2022-01-06_final.stac-item
2022-01-08 11:36:31	ga_ls9c_ard_3-2-1_112084_2022-01-08_final.stac-item
2022-01-21 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-01-20_final.stac-item
2022-01-26 11:21:23	ga_ls9c_ard_3-2-1_110077_2022-01-26_final.stac-item
2022-02-02 11:26:45	ga_ls9c_ard_3-2-1_111075_2022-02-02_final.stac-item
2022-02-05 10:17:58	ga_ls9c_ard_3-2-1_100073_2022-02-05_final.stac-item
2022-02-08 09:13:34	ga_ls9c_ard_3-2-1_089082_2022-02-07_final.stac-item
2022-02-20 11:17:28	ga_ls9c_ard_3-2-1_109083_2022-02-20_final.stac-item
2022-03-01 11:11:10	ga_ls9c_ard_3-2-1_108083_2022-03-01_final.stac-item
2022-03-04 09:57:59	ga_ls9c_ard_3-2-1_097070_2022-03-04_final.stac-item
2022-03-12 10:52:13	ga_ls9c_ard_3-2-1_105082_2022-03-12_final.stac-item
2022-03-26 09:25:37	ga_ls9c_ard_3-2-1_091082_2022-03-25_final.stac-item
2022-03-30 10:34:12	ga_ls9c_ard_3-2-1_103068_2022-03-30_final.stac-item
2022-04-13 09:13:59	ga_ls9c_ard_3-2-1_089084_2022-04-12_final.stac-item
2022-04-18 11:05:45	ga_ls9c_ard_3-2-1_108070_2022-04-18_final.stac-item
2022-04-27 09:24:14	ga_ls9c_ard_3-2-1_091079_2022-04-26_final.stac-item
2022-04-29 09:13:52	ga_ls9c_ard_3-2-1_089084_2022-04-28_final.stac-item
2022-05-02 11:19:38	ga_ls9c_ard_3-2-1_110074_2022-05-02_final.stac-item
2022-05-13 11:04:59	ga_ls9c_ard_3-2-1_107084_2022-05-13_final.stac-item
2022-05-15 09:12:54	ga_ls9c_ard_3-2-1_089082_2022-05-14_final.stac-item
2022-05-30 10:06:27	ga_ls9c_ard_3-2-1_098077_2022-05-30_final.stac-item
2022-06-15 10:04:10	ga_ls9c_ard_3-2-1_098071_2022-06-15_final.stac-item
2022-06-22 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-06-22_final.stac-item
2022-06-24 11:41:54	ga_ls9c_ard_3-2-1_113083_2022-06-24_final.stac-item
2022-07-02 09:15:59	ga_ls9c_ard_3-2-1_089089_2022-07-01_final.stac-item
2022-07-07 11:05:48	ga_ls9c_ard_3-2-1_108070_2022-07-07_final.stac-item
2022-07-17 10:03:59	ga_ls9c_ard_3-2-1_098070_2022-07-17_final.stac-item
2022-08-03 09:14:36	ga_ls9c_ard_3-2-1_089085_2022-08-02_final.stac-item
2022-08-04 11:35:10	ga_ls9c_ard_3-2-1_112081_2022-08-04_final.stac-item
2022-08-29 11:26:19	ga_ls9c_ard_3-2-1_111074_2022-08-29_final.stac-item
2022-09-07 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-09-07_final.stac-item
2022-09-10 10:14:33	ga_ls9c_ard_3-2-1_099080_2022-09-10_final.stac-item
2022-09-16 11:12:26	ga_ls9c_ard_3-2-1_109070_2022-09-16_final.stac-item
2022-09-20 09:12:03	ga_ls9c_ard_3-2-1_089078_2022-09-19_final.stac-item
2022-09-30 11:30:02	ga_ls9c_ard_3-2-1_111083_2022-09-30_final.stac-item
2022-10-05 11:44:59	ga_ls9c_ard_3-2-1_114074_2022-10-05_final.stac-item
2022-10-19 11:58:14	ga_ls9c_ard_3-2-1_116076_2022-10-19_final.stac-item
2022-10-23 11:35:55	ga_ls9c_ard_3-2-1_112082_2022-10-23_final.stac-item
2022-10-26 10:27:56	ga_ls9c_ard_3-2-1_101082_2022-10-26_final.stac-item
2022-11-01 11:25:43	ga_ls9c_ard_3-2-1_111072_2022-11-01_final.stac-item
2022-11-07 09:16:56	ga_ls9c_ard_3-2-1_089090_2022-11-06_final.stac-item
2022-11-14 10:58:51	ga_ls9c_ard_3-2-1_106082_2022-11-14_final.stac-item
2022-12-08 10:05:23	ga_ls9c_ard_3-2-1_098072_2022-12-08_final.stac-item
2022-12-10 09:57:49	ga_ls9c_ard_3-2-1_096084_2022-12-10_final.stac-item
2022-12-18 10:43:15	ga_ls9c_ard_3-2-1_104074_2022-12-18_final.stac-item
2022-12-19 09:52:49	ga_ls9c_ard_3-2-1_095087_2022-12-19_final.stac-item
2022-12-21 09:35:39	ga_ls9c_ard_3-2-1_093075_2022-12-21_final.stac-item
2022-12-21 09:39:39	ga_ls9c_ard_3-2-1_093085_2022-12-21_final.stac-item
2022-12-22 11:58:59	ga_ls9c_ard_3-2-1_116078_2022-12-22_final.stac-item
2023-01-02 10:02:01	ga_ls9c_ard_3-2-1_097079_2023-01-02_final.stac-item
2023-01-08 11:05:48	ga_ls9c_ard_3-2-1_107084_2023-01-08_final.stac-item
2023-01-24 09:27:37	ga_ls9c_ard_3-2-1_091086_2023-01-23_final.stac-item
2023-01-24 11:02:07	ga_ls9c_ard_3-2-1_107075_2023-01-24_final.stac-item
2023-01-25 10:03:19	ga_ls9c_ard_3-2-1_098067_2023-01-25_final.stac-item
2023-02-03 11:42:31	ga_ls9c_ard_3-2-1_113083_2023-02-03_final.stac-item
2023-02-11 10:52:42	ga_ls9c_ard_3-2-1_105082_2023-02-11_final.stac-item
2023-02-25 09:23:57	ga_ls9c_ard_3-2-1_091077_2023-02-24_final.stac-item
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final.stac-item
2023-03-11 11:14:40	ga_ls9c_ard_3-2-1_109076_2023-03-11_final.stac-item
2023-03-11 11:17:51	ga_ls9c_ard_3-2-1_109084_2023-03-11_final.stac-item
2023-03-13 09:29:01	ga_ls9c_ard_3-2-1_091090_2023-03-12_final.stac-item
2023-03-15 09:12:16	ga_ls9c_ard_3-2-1_089079_2023-03-14_final.stac-item
2023-03-28 10:18:05	ga_ls9c_ard_3-2-1_100074_2023-03-28_final.stac-item
2023-03-29 09:28:50	ga_ls9c_ard_3-2-1_091090_2023-03-28_final.stac-item
2023-04-01 09:51:45	ga_ls9c_ard_3-2-1_096070_2023-04-01_final.stac-item
2023-04-06 10:15:04	ga_ls9c_ard_3-2-1_099082_2023-04-06_final.stac-item
2023-04-14 11:05:12	ga_ls9c_ard_3-2-1_107084_2023-04-14_final.stac-item
2023-04-16 09:11:10	ga_ls9c_ard_3-2-1_089077_2023-04-15_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-04-28 11:11:54	ga_ls9c_ard_3-2-1_109070_2023-04-28_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-05-02 09:14:37	ga_ls9c_ard_3-2-1_089086_2023-05-01_final.stac-item
2023-05-09 10:53:14	ga_ls9c_ard_3-2-1_106070_2023-05-09_final.stac-item
2023-05-17 11:47:01	ga_ls9c_ard_3-2-1_114081_2023-05-17_final.stac-item
2023-05-20 10:39:23	ga_ls9c_ard_3-2-1_103082_2023-05-20_final.stac-item
2023-05-21 09:44:57	ga_ls9c_ard_3-2-1_094085_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 10:06:24	ga_ls9c_ard_3-2-1_098077_2023-06-02_final.stac-item
2023-07-05 10:46:32	ga_ls9c_ard_3-2-1_105069_2023-07-05_final.stac-item
2023-07-21 10:46:12	ga_ls9c_ard_3-2-1_105068_2023-07-21_final.stac-item
2023-07-27 11:51:13	ga_ls9c_ard_3-2-1_115076_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
2023-07-28 10:52:49	ga_ls9c_ard_3-2-1_106069_2023-07-28_final.stac-item
2023-07-30 09:06:24	ga_ls9c_ard_3-2-1_088081_2023-07-29_final.stac-item
2023-08-06 09:14:40	ga_ls9c_ard_3-2-1_089086_2023-08-05_final.stac-item
2023-08-09 11:23:40	ga_ls9c_ard_3-2-1_110084_2023-08-09_final.stac-item
2023-08-11 11:06:07	ga_ls9c_ard_3-2-1_108071_2023-08-11_final.stac-item
2023-08-18 09:39:47	ga_ls9c_ard_3-2-1_093087_2023-08-18_final.stac-item
2023-10-13 10:28:05	ga_ls9c_ard_3-2-1_101083_2023-10-13_final.stac-item
2023-10-15 11:51:50	ga_ls9c_ard_3-2-1_115076_2023-10-15_final.stac-item
2023-10-15 11:52:38	ga_ls9c_ard_3-2-1_115078_2023-10-15_final.stac-item
2023-10-26 09:52:01	ga_ls9c_ard_3-2-1_096070_2023-10-26_final.stac-item
2023-10-26 11:36:05	ga_ls9c_ard_3-2-1_112083_2023-10-26_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