Search ga_ls8c_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
2018-11-18 09:27:36	ga_ls8c_ard_3-1-0_091087_2018-11-17_final
2019-03-22 09:51:10	ga_ls8c_ard_3-1-0_095085_2019-03-22_final
2019-04-11 09:24:46	ga_ls8c_ard_3-1-0_091081_2019-04-10_final
2019-06-14 09:24:42	ga_ls8c_ard_3-1-0_091080_2019-06-13_final
2019-06-26 09:46:41	ga_ls8c_ard_3-1-0_095073_2019-06-26_final
2019-07-12 09:50:44	ga_ls8c_ard_3-1-0_095083_2019-07-12_final
2019-07-28 09:50:49	ga_ls8c_ard_3-1-0_095083_2019-07-28_final
2019-08-29 09:50:35	ga_ls8c_ard_3-1-0_095082_2019-08-29_final
2019-09-02 09:23:29	ga_ls8c_ard_3-1-0_091076_2019-09-01_final
2019-09-14 09:52:39	ga_ls8c_ard_3-1-0_095087_2019-09-14_final
2019-09-18 09:23:58	ga_ls8c_ard_3-1-0_091077_2019-09-17_final
2019-09-30 09:50:45	ga_ls8c_ard_3-1-0_095082_2019-09-30_final
2019-09-30 09:51:33	ga_ls8c_ard_3-1-0_095084_2019-09-30_final
2019-09-30 09:51:56	ga_ls8c_ard_3-1-0_095085_2019-09-30_final
2019-10-04 09:25:14	ga_ls8c_ard_3-1-0_091080_2019-10-03_final
2019-10-20 09:25:16	ga_ls8c_ard_3-1-0_091080_2019-10-19_final
2019-10-20 09:26:28	ga_ls8c_ard_3-1-0_091083_2019-10-19_final
2019-11-05 09:25:15	ga_ls8c_ard_3-1-0_091080_2019-11-04_final
2019-11-17 09:51:08	ga_ls8c_ard_3-1-0_095083_2019-11-17_final
2019-12-07 09:25:35	ga_ls8c_ard_3-1-0_091081_2019-12-06_final
2019-12-07 09:27:35	ga_ls8c_ard_3-1-0_091086_2019-12-06_final
2020-01-08 09:25:04	ga_ls8c_ard_3-1-0_091080_2020-01-07_final
2020-01-08 09:25:28	ga_ls8c_ard_3-1-0_091081_2020-01-07_final
2020-01-08 09:29:04	ga_ls8c_ard_3-1-0_091090_2020-01-07_final
2020-02-05 09:50:51	ga_ls8c_ard_3-1-0_095083_2020-02-05_final
2020-02-09 09:28:31	ga_ls8c_ard_3-1-0_091089_2020-02-08_final
2020-03-08 09:47:31	ga_ls8c_ard_3-1-0_095075_2020-03-08_final
2020-03-12 09:26:21	ga_ls8c_ard_3-1-0_091084_2020-03-11_final
2020-03-12 09:28:21	ga_ls8c_ard_3-1-0_091089_2020-03-11_final
2020-03-24 09:50:34	ga_ls8c_ard_3-1-0_095083_2020-03-24_final
2020-03-28 09:26:13	ga_ls8c_ard_3-1-0_091084_2020-03-27_final
2020-04-13 09:24:29	ga_ls8c_ard_3-1-0_091080_2020-04-12_final
2022-03-30 09:50:32	ga_ls8c_ard_3-2-1_095083_2022-03-30_final
2022-04-01 09:34:58	ga_ls8c_ard_3-2-1_093075_2022-04-01_final
2022-04-01 11:11:52	ga_ls8c_ard_3-2-1_109070_2022-04-01_final
2022-04-02 10:17:02	ga_ls8c_ard_3-2-1_100072_2022-04-02_final
2022-04-02 10:21:02	ga_ls8c_ard_3-2-1_100082_2022-04-02_final
2022-04-03 10:59:54	ga_ls8c_ard_3-2-1_107071_2022-04-03_final
2022-04-09 10:23:41	ga_ls8c_ard_3-2-1_101073_2022-04-09_final
2022-04-09 10:25:17	ga_ls8c_ard_3-2-1_101077_2022-04-09_final
2022-04-10 09:30:52	ga_ls8c_ard_3-2-1_092080_2022-04-10_final
2022-04-10 09:31:16	ga_ls8c_ard_3-2-1_092081_2022-04-10_final
2022-04-10 09:32:52	ga_ls8c_ard_3-2-1_092085_2022-04-10_final
2022-04-10 11:06:57	ga_ls8c_ard_3-2-1_108073_2022-04-10_final
2022-04-13 11:41:28	ga_ls8c_ard_3-2-1_113082_2022-04-13_final
2022-04-14 10:42:16	ga_ls8c_ard_3-2-1_104073_2022-04-14_final
2022-04-15 09:50:38	ga_ls8c_ard_3-2-1_095083_2022-04-15_final
2022-04-15 09:51:02	ga_ls8c_ard_3-2-1_095084_2022-04-15_final
2022-04-18 10:17:56	ga_ls8c_ard_3-2-1_100074_2022-04-18_final
2022-04-19 09:25:06	ga_ls8c_ard_3-2-1_091081_2022-04-18_final
2022-04-19 11:00:00	ga_ls8c_ard_3-2-1_107071_2022-04-19_final
2022-04-21 09:13:56	ga_ls8c_ard_3-2-1_089084_2022-04-20_final
2022-04-24 09:45:36	ga_ls8c_ard_3-2-1_094086_2022-04-24_final
2022-04-26 11:10:07	ga_ls8c_ard_3-2-1_108081_2022-04-26_final
2022-04-26 11:11:19	ga_ls8c_ard_3-2-1_108084_2022-04-26_final
2022-04-27 10:14:53	ga_ls8c_ard_3-2-1_099082_2022-04-27_final
2022-04-27 10:15:17	ga_ls8c_ard_3-2-1_099083_2022-04-27_final
2022-04-28 09:20:27	ga_ls8c_ard_3-2-1_090085_2022-04-27_final
2022-04-28 10:54:33	ga_ls8c_ard_3-2-1_106073_2022-04-28_final
2022-04-29 09:58:31	ga_ls8c_ard_3-2-1_097072_2022-04-29_final
2022-04-30 10:44:59	ga_ls8c_ard_3-2-1_104080_2022-04-30_final
2022-05-01 09:51:23	ga_ls8c_ard_3-2-1_095085_2022-05-01_final
2022-05-02 10:30:16	ga_ls8c_ard_3-2-1_102074_2022-05-02_final
2022-05-03 09:39:03	ga_ls8c_ard_3-2-1_093085_2022-05-03_final
2022-05-03 11:16:44	ga_ls8c_ard_3-2-1_109082_2022-05-03_final
2022-05-04 10:18:20	ga_ls8c_ard_3-2-1_100075_2022-05-04_final
2022-05-04 10:19:55	ga_ls8c_ard_3-2-1_100079_2022-05-04_final
2022-05-05 09:23:31	ga_ls8c_ard_3-2-1_091077_2022-05-04_final
2022-05-05 09:25:55	ga_ls8c_ard_3-2-1_091083_2022-05-04_final
2022-05-06 10:07:59	ga_ls8c_ard_3-2-1_098080_2022-05-06_final
2022-05-10 09:45:18	ga_ls8c_ard_3-2-1_094085_2022-05-10_final
2022-05-11 10:23:47	ga_ls8c_ard_3-2-1_101073_2022-05-11_final
2022-05-13 10:15:26	ga_ls8c_ard_3-2-1_099083_2022-05-13_final
2022-05-14 10:53:31	ga_ls8c_ard_3-2-1_106070_2022-05-14_final
2022-05-14 10:54:42	ga_ls8c_ard_3-2-1_106073_2022-05-14_final
2022-05-14 10:57:54	ga_ls8c_ard_3-2-1_106081_2022-05-14_final
2022-05-16 10:41:10	ga_ls8c_ard_3-2-1_104070_2022-05-16_final
2022-05-17 09:47:08	ga_ls8c_ard_3-2-1_095074_2022-05-17_final
2022-05-18 10:29:12	ga_ls8c_ard_3-2-1_102071_2022-05-18_final
2022-05-19 09:35:35	ga_ls8c_ard_3-2-1_093076_2022-05-19_final
2022-05-20 10:20:02	ga_ls8c_ard_3-2-1_100079_2022-05-20_final
2022-05-25 10:34:35	ga_ls8c_ard_3-2-1_103069_2022-05-25_final
2022-05-30 10:54:45	ga_ls8c_ard_3-2-1_106073_2022-05-30_final
2022-05-30 10:57:56	ga_ls8c_ard_3-2-1_106081_2022-05-30_final
2022-05-31 09:56:45	ga_ls8c_ard_3-2-1_097067_2022-05-31_final
2022-05-31 09:58:44	ga_ls8c_ard_3-2-1_097072_2022-05-31_final
2022-06-01 09:06:43	ga_ls8c_ard_3-2-1_088081_2022-05-31_final
2022-06-02 09:50:48	ga_ls8c_ard_3-2-1_095083_2022-06-02_final
2022-06-02 11:23:42	ga_ls8c_ard_3-2-1_111068_2022-06-02_final
2022-06-04 09:40:28	ga_ls8c_ard_3-2-1_093088_2022-06-04_final
2022-06-07 10:04:13	ga_ls8c_ard_3-2-1_098070_2022-06-07_final
2022-06-07 10:09:25	ga_ls8c_ard_3-2-1_098083_2022-06-07_final
2022-06-08 09:13:24	ga_ls8c_ard_3-2-1_089082_2022-06-07_final
2022-06-13 11:05:42	ga_ls8c_ard_3-2-1_108069_2022-06-13_final
2022-06-13 11:08:30	ga_ls8c_ard_3-2-1_108076_2022-06-13_final
2022-06-16 10:01:44	ga_ls8c_ard_3-2-1_097079_2022-06-16_final
2022-06-17 09:06:31	ga_ls8c_ard_3-2-1_088080_2022-06-16_final
2022-06-17 09:06:55	ga_ls8c_ard_3-2-1_088081_2022-06-16_final
2022-06-18 09:50:35	ga_ls8c_ard_3-2-1_095082_2022-06-18_final
2022-06-18 11:28:41	ga_ls8c_ard_3-2-1_111080_2022-06-18_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 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