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
2021-12-10 10:25:50	ga_ls9c_ard_3-2-1_101077_2021-12-10_final.stac-item
2021-12-11 11:06:41	ga_ls9c_ard_3-2-1_108071_2021-12-11_final.stac-item
2021-12-18 09:35:07	ga_ls9c_ard_3-2-1_093074_2021-12-18_final.stac-item
2021-12-18 11:17:59	ga_ls9c_ard_3-2-1_109084_2021-12-18_final.stac-item
2021-12-23 09:52:28	ga_ls9c_ard_3-2-1_096071_2021-12-23_final.stac-item
2021-12-29 09:21:47	ga_ls9c_ard_3-2-1_090087_2021-12-28_final.stac-item
2021-12-30 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-30_final.stac-item
2022-01-01 11:25:10	ga_ls9c_ard_3-2-1_111071_2022-01-01_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-20 10:19:10	ga_ls9c_ard_3-2-1_100076_2022-01-20_final.stac-item
2022-01-29 11:52:41	ga_ls9c_ard_3-2-1_115078_2022-01-29_final.stac-item
2022-02-05 10:20:46	ga_ls9c_ard_3-2-1_100080_2022-02-05_final.stac-item
2022-02-05 10:21:58	ga_ls9c_ard_3-2-1_100083_2022-02-05_final.stac-item
2022-03-10 09:23:18	ga_ls9c_ard_3-2-1_091076_2022-03-09_final.stac-item
2022-03-12 09:16:32	ga_ls9c_ard_3-2-1_089090_2022-03-11_final.stac-item
2022-03-19 10:53:11	ga_ls9c_ard_3-2-1_106069_2022-03-19_final.stac-item
2022-03-31 09:39:46	ga_ls9c_ard_3-2-1_094071_2022-03-31_final.stac-item
2022-04-04 10:57:31	ga_ls9c_ard_3-2-1_106080_2022-04-04_final.stac-item
2022-04-16 11:23:44	ga_ls9c_ard_3-2-1_110084_2022-04-16_final.stac-item
2022-04-20 10:54:34	ga_ls9c_ard_3-2-1_106073_2022-04-20_final.stac-item
2022-05-07 10:03:15	ga_ls9c_ard_3-2-1_097084_2022-05-07_final.stac-item
2022-05-12 10:21:44	ga_ls9c_ard_3-2-1_100084_2022-05-12_final.stac-item
2022-05-13 11:04:59	ga_ls9c_ard_3-2-1_107084_2022-05-13_final.stac-item
2022-05-14 11:46:14	ga_ls9c_ard_3-2-1_114079_2022-05-14_final.stac-item
2022-05-15 09:12:30	ga_ls9c_ard_3-2-1_089081_2022-05-14_final.stac-item
2022-05-18 11:18:39	ga_ls9c_ard_3-2-1_110072_2022-05-18_final.stac-item
2022-05-25 09:51:06	ga_ls9c_ard_3-2-1_095085_2022-05-25_final.stac-item
2022-06-13 10:21:41	ga_ls9c_ard_3-2-1_100084_2022-06-13_final.stac-item
2022-06-15 10:04:10	ga_ls9c_ard_3-2-1_098071_2022-06-15_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-06-30 11:01:14	ga_ls9c_ard_3-2-1_107074_2022-06-30_final.stac-item
2022-07-10 09:57:24	ga_ls9c_ard_3-2-1_097069_2022-07-10_final.stac-item
2022-07-13 10:29:52	ga_ls9c_ard_3-2-1_102073_2022-07-13_final.stac-item
2022-07-16 09:25:05	ga_ls9c_ard_3-2-1_091081_2022-07-15_final.stac-item
2022-07-23 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-07-23_final.stac-item
2022-07-23 11:11:05	ga_ls9c_ard_3-2-1_108083_2022-07-23_final.stac-item
2022-07-31 10:17:21	ga_ls9c_ard_3-2-1_100072_2022-07-31_final.stac-item
2022-08-18 10:03:57	ga_ls9c_ard_3-2-1_098069_2022-08-18_final.stac-item
2022-08-22 09:45:14	ga_ls9c_ard_3-2-1_094084_2022-08-22_final.stac-item
2022-09-03 10:10:22	ga_ls9c_ard_3-2-1_098085_2022-09-03_final.stac-item
2022-09-07 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-09-07_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-09-12 11:38:42	ga_ls9c_ard_3-2-1_113074_2022-09-12_final.stac-item
2022-09-25 11:07:54	ga_ls9c_ard_3-2-1_108074_2022-09-25_final.stac-item
2022-10-02 11:13:41	ga_ls9c_ard_3-2-1_109073_2022-10-02_final.stac-item
2022-10-04 11:01:19	ga_ls9c_ard_3-2-1_107073_2022-10-04_final.stac-item
2022-10-09 09:44:35	ga_ls9c_ard_3-2-1_094082_2022-10-09_final.stac-item
2022-10-09 11:19:29	ga_ls9c_ard_3-2-1_110072_2022-10-09_final.stac-item
2022-10-12 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-10-12_final.stac-item
2022-10-26 10:26:20	ga_ls9c_ard_3-2-1_101078_2022-10-26_final.stac-item
2022-11-06 10:10:09	ga_ls9c_ard_3-2-1_098084_2022-11-06_final.stac-item
2022-11-10 11:20:46	ga_ls9c_ard_3-2-1_110075_2022-11-10_final.stac-item
2022-11-14 10:55:39	ga_ls9c_ard_3-2-1_106074_2022-11-14_final.stac-item
2022-11-18 10:28:33	ga_ls9c_ard_3-2-1_102068_2022-11-18_final.stac-item
2022-11-23 09:13:22	ga_ls9c_ard_3-2-1_089081_2022-11-22_final.stac-item
2022-11-23 10:52:15	ga_ls9c_ard_3-2-1_105081_2022-11-23_final.stac-item
2022-11-26 11:19:09	ga_ls9c_ard_3-2-1_110071_2022-11-26_final.stac-item
2022-11-30 10:59:11	ga_ls9c_ard_3-2-1_106083_2022-11-30_final.stac-item
2022-12-01 09:59:10	ga_ls9c_ard_3-2-1_097072_2022-12-01_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-03 11:26:54	ga_ls9c_ard_3-2-1_111075_2022-12-03_final.stac-item
2022-12-07 09:24:07	ga_ls9c_ard_3-2-1_091077_2022-12-06_final.stac-item
2022-12-25 09:12:55	ga_ls9c_ard_3-2-1_089080_2022-12-24_final.stac-item
2023-01-06 09:40:29	ga_ls9c_ard_3-2-1_093087_2023-01-06_final.stac-item
2023-01-09 11:47:28	ga_ls9c_ard_3-2-1_114080_2023-01-09_final.stac-item
2023-01-22 09:40:44	ga_ls9c_ard_3-2-1_093088_2023-01-22_final.stac-item
2023-01-24 11:05:42	ga_ls9c_ard_3-2-1_107084_2023-01-24_final.stac-item
2023-02-09 11:01:53	ga_ls9c_ard_3-2-1_107074_2023-02-09_final.stac-item
2023-03-06 10:54:35	ga_ls9c_ard_3-2-1_106072_2023-03-06_final.stac-item
2023-03-07 09:56:57	ga_ls9c_ard_3-2-1_097067_2023-03-07_final.stac-item
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final.stac-item
2023-03-09 11:26:14	ga_ls9c_ard_3-2-1_111074_2023-03-09_final.stac-item
2023-03-16 09:52:20	ga_ls9c_ard_3-2-1_096071_2023-03-16_final.stac-item
2023-04-13 10:17:10	ga_ls9c_ard_3-2-1_100072_2023-04-13_final.stac-item
2023-04-24 11:40:16	ga_ls9c_ard_3-2-1_113079_2023-04-24_final.stac-item
2023-05-09 10:53:14	ga_ls9c_ard_3-2-1_106070_2023-05-09_final.stac-item
2023-05-15 10:18:31	ga_ls9c_ard_3-2-1_100076_2023-05-15_final.stac-item
2023-05-15 11:57:24	ga_ls9c_ard_3-2-1_116076_2023-05-15_final.stac-item
2023-05-18 09:10:54	ga_ls9c_ard_3-2-1_089077_2023-05-17_final.stac-item
2023-05-27 10:41:54	ga_ls9c_ard_3-2-1_104073_2023-05-27_final.stac-item
2023-06-01 11:02:26	ga_ls9c_ard_3-2-1_107078_2023-06-01_final.stac-item
2023-06-02 10:03:13	ga_ls9c_ard_3-2-1_098069_2023-06-02_final.stac-item
2023-06-11 11:40:37	ga_ls9c_ard_3-2-1_113081_2023-06-11_final.stac-item
2023-06-13 11:24:38	ga_ls9c_ard_3-2-1_111072_2023-06-13_final.stac-item
2023-06-17 09:25:47	ga_ls9c_ard_3-2-1_091084_2023-06-16_final.stac-item
2023-06-17 10:59:05	ga_ls9c_ard_3-2-1_107070_2023-06-17_final.stac-item
2023-06-26 09:20:01	ga_ls9c_ard_3-2-1_090085_2023-06-25_final.stac-item
2023-06-27 11:37:48	ga_ls9c_ard_3-2-1_113074_2023-06-27_final.stac-item
2023-07-04 10:02:28	ga_ls9c_ard_3-2-1_098067_2023-07-04_final.stac-item
2023-07-10 11:06:43	ga_ls9c_ard_3-2-1_108073_2023-07-10_final.stac-item
2023-07-12 09:20:17	ga_ls9c_ard_3-2-1_090085_2023-07-11_final.stac-item
2023-09-04 10:21:16	ga_ls9c_ard_3-2-1_100082_2023-09-04_final.stac-item
2023-09-06 10:07:44	ga_ls9c_ard_3-2-1_098079_2023-09-06_final.stac-item
2023-09-12 11:07:13	ga_ls9c_ard_3-2-1_108073_2023-09-12_final.stac-item
2023-09-14 09:17:34	ga_ls9c_ard_3-2-1_090077_2023-09-13_final.stac-item
2023-09-17 11:25:22	ga_ls9c_ard_3-2-1_111072_2023-09-17_final.stac-item
2023-09-20 10:21:46	ga_ls9c_ard_3-2-1_100083_2023-09-20_final.stac-item
2023-10-08 10:03:29	ga_ls9c_ard_3-2-1_098068_2023-10-08_final.stac-item
2023-10-08 10:05:04	ga_ls9c_ard_3-2-1_098072_2023-10-08_final.stac-item
2023-10-08 10:09:28	ga_ls9c_ard_3-2-1_098083_2023-10-08_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years