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
2021-11-25 09:46:52	ga_ls9c_ard_3-2-1_095077_2021-11-25_final.stac-item
2021-12-10 10:27:49	ga_ls9c_ard_3-2-1_101082_2021-12-10_final.stac-item
2021-12-16 09:52:40	ga_ls9c_ard_3-2-1_095087_2021-12-16_final.stac-item
2022-01-02 10:29:09	ga_ls9c_ard_3-2-1_102070_2022-01-02_final.stac-item
2022-01-03 09:40:18	ga_ls9c_ard_3-2-1_093087_2022-01-03_final.stac-item
2022-01-06 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-06_final.stac-item
2022-01-07 10:50:28	ga_ls9c_ard_3-2-1_105077_2022-01-07_final.stac-item
2022-01-12 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-01-12_final.stac-item
2022-01-17 09:47:51	ga_ls9c_ard_3-2-1_095075_2022-01-17_final.stac-item
2022-01-20 10:18:46	ga_ls9c_ard_3-2-1_100075_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
2022-02-11 11:18:56	ga_ls9c_ard_3-2-1_110071_2022-02-11_final.stac-item
2022-03-10 09:24:54	ga_ls9c_ard_3-2-1_091080_2022-03-09_final.stac-item
2022-04-02 11:07:53	ga_ls9c_ard_3-2-1_108075_2022-04-02_final.stac-item
2022-04-09 09:37:33	ga_ls9c_ard_3-2-1_093081_2022-04-09_final.stac-item
2022-04-13 10:52:28	ga_ls9c_ard_3-2-1_105083_2022-04-13_final.stac-item
2022-04-18 11:07:45	ga_ls9c_ard_3-2-1_108075_2022-04-18_final.stac-item
2022-05-16 09:51:46	ga_ls9c_ard_3-2-1_096071_2022-05-16_final.stac-item
2022-05-21 10:12:14	ga_ls9c_ard_3-2-1_099076_2022-05-21_final.stac-item
2022-05-29 11:04:52	ga_ls9c_ard_3-2-1_107084_2022-05-29_final.stac-item
2022-06-03 09:45:21	ga_ls9c_ard_3-2-1_094086_2022-06-03_final.stac-item
2022-06-08 09:57:54	ga_ls9c_ard_3-2-1_097071_2022-06-08_final.stac-item
2022-06-16 09:12:57	ga_ls9c_ard_3-2-1_089082_2022-06-15_final.stac-item
2022-06-21 11:06:55	ga_ls9c_ard_3-2-1_108073_2022-06-21_final.stac-item
2022-06-29 10:21:10	ga_ls9c_ard_3-2-1_100082_2022-06-29_final.stac-item
2022-07-07 11:07:00	ga_ls9c_ard_3-2-1_108073_2022-07-07_final.stac-item
2022-08-10 10:54:57	ga_ls9c_ard_3-2-1_106073_2022-08-10_final.stac-item
2022-08-26 10:56:13	ga_ls9c_ard_3-2-1_106076_2022-08-26_final.stac-item
2022-09-07 11:18:32	ga_ls9c_ard_3-2-1_110070_2022-09-07_final.stac-item
2022-09-16 09:35:08	ga_ls9c_ard_3-2-1_093074_2022-09-16_final.stac-item
2022-09-27 10:58:44	ga_ls9c_ard_3-2-1_106082_2022-09-27_final.stac-item
2022-09-28 09:58:20	ga_ls9c_ard_3-2-1_097070_2022-09-28_final.stac-item
2022-10-02 09:39:59	ga_ls9c_ard_3-2-1_093086_2022-10-02_final.stac-item
2022-10-07 09:52:08	ga_ls9c_ard_3-2-1_096070_2022-10-07_final.stac-item
2022-10-09 11:19:05	ga_ls9c_ard_3-2-1_110071_2022-10-09_final.stac-item
2022-10-18 09:37:17	ga_ls9c_ard_3-2-1_093079_2022-10-18_final.stac-item
2022-10-27 09:29:55	ga_ls9c_ard_3-2-1_092076_2022-10-26_final.stac-item
2022-10-28 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-10-28_final.stac-item
2022-10-30 11:41:17	ga_ls9c_ard_3-2-1_113080_2022-10-30_final.stac-item
2022-11-03 11:12:08	ga_ls9c_ard_3-2-1_109069_2022-11-03_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-26 11:19:09	ga_ls9c_ard_3-2-1_110071_2022-11-26_final.stac-item
2022-12-02 10:43:14	ga_ls9c_ard_3-2-1_104074_2022-12-02_final.stac-item
2022-12-03 09:52:48	ga_ls9c_ard_3-2-1_095087_2022-12-03_final.stac-item
2022-12-05 11:12:09	ga_ls9c_ard_3-2-1_109069_2022-12-05_final.stac-item
2022-12-08 10:05:23	ga_ls9c_ard_3-2-1_098072_2022-12-08_final.stac-item
2022-12-11 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-12-11_final.stac-item
2022-12-12 09:45:04	ga_ls9c_ard_3-2-1_094083_2022-12-12_final.stac-item
2022-12-23 11:00:58	ga_ls9c_ard_3-2-1_107072_2022-12-23_final.stac-item
2022-12-29 10:26:43	ga_ls9c_ard_3-2-1_101079_2022-12-29_final.stac-item
2023-01-02 11:39:18	ga_ls9c_ard_3-2-1_113075_2023-01-02_final.stac-item
2023-01-08 11:00:13	ga_ls9c_ard_3-2-1_107070_2023-01-08_final.stac-item
2023-01-20 09:47:29	ga_ls9c_ard_3-2-1_095074_2023-01-20_final.stac-item
2023-01-20 11:29:10	ga_ls9c_ard_3-2-1_111081_2023-01-20_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-25 10:07:19	ga_ls9c_ard_3-2-1_098077_2023-01-25_final.stac-item
2023-02-09 09:27:23	ga_ls9c_ard_3-2-1_091085_2023-02-08_final.stac-item
2023-02-10 11:46:44	ga_ls9c_ard_3-2-1_114078_2023-02-10_final.stac-item
2023-02-14 11:24:22	ga_ls9c_ard_3-2-1_110084_2023-02-14_final.stac-item
2023-03-01 10:34:55	ga_ls9c_ard_3-2-1_103069_2023-03-01_final.stac-item
2023-03-07 10:01:45	ga_ls9c_ard_3-2-1_097079_2023-03-07_final.stac-item
2023-03-08 10:41:00	ga_ls9c_ard_3-2-1_104069_2023-03-08_final.stac-item
2023-03-08 10:41:24	ga_ls9c_ard_3-2-1_104070_2023-03-08_final.stac-item
2023-03-12 10:18:15	ga_ls9c_ard_3-2-1_100074_2023-03-12_final.stac-item
2023-03-29 09:25:14	ga_ls9c_ard_3-2-1_091081_2023-03-28_final.stac-item
2023-04-01 09:52:08	ga_ls9c_ard_3-2-1_096071_2023-04-01_final.stac-item
2023-04-24 11:39:52	ga_ls9c_ard_3-2-1_113078_2023-04-24_final.stac-item
2023-05-07 09:29:07	ga_ls9c_ard_3-2-1_092076_2023-05-06_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-13 10:28:06	ga_ls9c_ard_3-2-1_102069_2023-05-13_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-18 09:10:54	ga_ls9c_ard_3-2-1_089077_2023-05-17_final.stac-item
2023-05-18 10:45:47	ga_ls9c_ard_3-2-1_105067_2023-05-18_final.stac-item
2023-05-18 10:48:59	ga_ls9c_ard_3-2-1_105075_2023-05-18_final.stac-item
2023-05-21 11:18:39	ga_ls9c_ard_3-2-1_110072_2023-05-21_final.stac-item
2023-05-31 11:57:16	ga_ls9c_ard_3-2-1_116076_2023-05-31_final.stac-item
2023-06-03 10:48:52	ga_ls9c_ard_3-2-1_105075_2023-06-03_final.stac-item
2023-06-04 09:51:38	ga_ls9c_ard_3-2-1_096071_2023-06-04_final.stac-item
2023-06-04 09:52:02	ga_ls9c_ard_3-2-1_096072_2023-06-04_final.stac-item
2023-06-05 10:33:42	ga_ls9c_ard_3-2-1_103068_2023-06-05_final.stac-item
2023-06-24 11:06:28	ga_ls9c_ard_3-2-1_108073_2023-06-24_final.stac-item
2023-06-29 09:46:13	ga_ls9c_ard_3-2-1_095073_2023-06-29_final.stac-item
2023-07-16 10:28:28	ga_ls9c_ard_3-2-1_102070_2023-07-16_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-07-24 09:44:59	ga_ls9c_ard_3-2-1_094085_2023-07-24_final.stac-item
2023-07-26 11:06:21	ga_ls9c_ard_3-2-1_108072_2023-07-26_final.stac-item
2023-07-26 11:07:08	ga_ls9c_ard_3-2-1_108074_2023-07-26_final.stac-item
2023-07-29 10:01:13	ga_ls9c_ard_3-2-1_097079_2023-07-29_final.stac-item
2023-07-31 09:51:17	ga_ls9c_ard_3-2-1_095085_2023-07-31_final.stac-item
2023-08-13 10:53:22	ga_ls9c_ard_3-2-1_106070_2023-08-13_final.stac-item
2023-08-14 11:41:49	ga_ls9c_ard_3-2-1_113083_2023-08-14_final.stac-item
2023-10-18 10:46:16	ga_ls9c_ard_3-2-1_104082_2023-10-18_final.stac-item
2023-10-21 11:13:35	ga_ls9c_ard_3-2-1_109073_2023-10-21_final.stac-item
2023-10-26 09:52:01	ga_ls9c_ard_3-2-1_096070_2023-10-26_final.stac-item
2023-10-28 11:19:19	ga_ls9c_ard_3-2-1_110072_2023-10-28_final.stac-item
2023-10-28 11:20:54	ga_ls9c_ard_3-2-1_110076_2023-10-28_final.stac-item
2023-11-04 09:46:56	ga_ls9c_ard_3-2-1_095073_2023-11-04_final.stac-item
2023-11-16 11:52:10	ga_ls9c_ard_3-2-1_115077_2023-11-16_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_2023-11-23_final.stac-item
2023-11-25 10:09:38	ga_ls9c_ard_3-2-1_098083_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