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
2021-11-13 09:56:43	ga_ls9c_ard_3-2-1_097067_2021-11-13_final.stac-item
2021-12-04 09:26:53	ga_ls9c_ard_3-2-1_091084_2021-12-03_final.stac-item
2021-12-04 11:02:10	ga_ls9c_ard_3-2-1_107075_2021-12-04_final.stac-item
2021-12-07 09:57:45	ga_ls9c_ard_3-2-1_096084_2021-12-07_final.stac-item
2021-12-19 10:17:35	ga_ls9c_ard_3-2-1_100072_2021-12-19_final.stac-item
2022-01-04 10:17:35	ga_ls9c_ard_3-2-1_100072_2022-01-04_final.stac-item
2022-01-10 11:20:09	ga_ls9c_ard_3-2-1_110074_2022-01-10_final.stac-item
2022-01-15 09:57:48	ga_ls9c_ard_3-2-1_097069_2022-01-15_final.stac-item
2022-03-09 10:19:44	ga_ls9c_ard_3-2-1_100078_2022-03-09_final.stac-item
2022-03-12 09:13:44	ga_ls9c_ard_3-2-1_089083_2022-03-11_final.stac-item
2022-05-06 09:20:47	ga_ls9c_ard_3-2-1_090086_2022-05-05_final.stac-item
2022-05-29 10:59:17	ga_ls9c_ard_3-2-1_107070_2022-05-29_final.stac-item
2022-06-05 09:28:36	ga_ls9c_ard_3-2-1_092075_2022-06-04_final.stac-item
2022-06-06 10:09:04	ga_ls9c_ard_3-2-1_099068_2022-06-06_final.stac-item
2022-06-29 10:17:11	ga_ls9c_ard_3-2-1_100072_2022-06-29_final.stac-item
2022-07-12 09:45:49	ga_ls9c_ard_3-2-1_095071_2022-07-12_final.stac-item
2022-07-17 10:06:46	ga_ls9c_ard_3-2-1_098077_2022-07-17_final.stac-item
2022-08-28 09:07:22	ga_ls9c_ard_3-2-1_088082_2022-08-27_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_2022-09-27_final.stac-item
2022-10-02 09:34:00	ga_ls9c_ard_3-2-1_093071_2022-10-02_final.stac-item
2022-10-13 10:53:37	ga_ls9c_ard_3-2-1_106069_2022-10-13_final.stac-item
2022-10-28 10:11:10	ga_ls9c_ard_3-2-1_099071_2022-10-28_final.stac-item
2022-10-28 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-10-28_final.stac-item
2022-10-29 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-10-29_final.stac-item
2022-10-30 10:02:00	ga_ls9c_ard_3-2-1_097079_2022-10-30_final.stac-item
2022-10-31 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-31_final.stac-item
2022-11-05 09:24:05	ga_ls9c_ard_3-2-1_091077_2022-11-04_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_final.stac-item
2022-11-10 09:44:40	ga_ls9c_ard_3-2-1_094082_2022-11-10_final.stac-item
2022-11-13 10:16:23	ga_ls9c_ard_3-2-1_099084_2022-11-13_final.stac-item
2022-11-16 09:07:12	ga_ls9c_ard_3-2-1_088081_2022-11-15_final.stac-item
2022-11-16 10:41:42	ga_ls9c_ard_3-2-1_104070_2022-11-16_final.stac-item
2022-11-17 11:24:10	ga_ls9c_ard_3-2-1_111068_2022-11-17_final.stac-item
2022-11-19 09:35:43	ga_ls9c_ard_3-2-1_093075_2022-11-19_final.stac-item
2022-11-25 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-11-25_final.stac-item
2022-12-10 11:36:18	ga_ls9c_ard_3-2-1_112083_2022-12-10_final.stac-item
2022-12-15 10:11:34	ga_ls9c_ard_3-2-1_099072_2022-12-15_final.stac-item
2022-12-22 10:21:18	ga_ls9c_ard_3-2-1_100081_2022-12-22_final.stac-item
2022-12-23 09:27:16	ga_ls9c_ard_3-2-1_091085_2022-12-22_final.stac-item
2022-12-24 10:05:20	ga_ls9c_ard_3-2-1_098072_2022-12-24_final.stac-item
2022-12-26 09:52:36	ga_ls9c_ard_3-2-1_096071_2022-12-26_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_2022-12-28_final.stac-item
2022-12-30 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-12-29_final.stac-item
2022-12-30 09:34:17	ga_ls9c_ard_3-2-1_092087_2022-12-30_final.stac-item
2023-01-01 09:22:44	ga_ls9c_ard_3-2-1_090089_2022-12-31_final.stac-item
2023-01-04 11:30:32	ga_ls9c_ard_3-2-1_111084_2023-01-04_final.stac-item
2023-01-07 10:19:45	ga_ls9c_ard_3-2-1_100077_2023-01-07_final.stac-item
2023-01-09 10:04:35	ga_ls9c_ard_3-2-1_098070_2023-01-09_final.stac-item
2023-01-12 10:35:04	ga_ls9c_ard_3-2-1_103069_2023-01-12_final.stac-item
2023-01-13 11:19:55	ga_ls9c_ard_3-2-1_110073_2023-01-13_final.stac-item
2023-01-22 09:40:20	ga_ls9c_ard_3-2-1_093087_2023-01-22_final.stac-item
2023-01-23 10:18:26	ga_ls9c_ard_3-2-1_100074_2023-01-23_final.stac-item
2023-02-05 11:30:35	ga_ls9c_ard_3-2-1_111084_2023-02-05_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-08 10:22:36	ga_ls9c_ard_3-2-1_100084_2023-02-08_final.stac-item
2023-02-09 11:00:41	ga_ls9c_ard_3-2-1_107071_2023-02-09_final.stac-item
2023-02-09 11:01:29	ga_ls9c_ard_3-2-1_107073_2023-02-09_final.stac-item
2023-02-10 10:09:51	ga_ls9c_ard_3-2-1_098083_2023-02-10_final.stac-item
2023-02-10 10:10:38	ga_ls9c_ard_3-2-1_098085_2023-02-10_final.stac-item
2023-02-11 09:16:37	ga_ls9c_ard_3-2-1_089089_2023-02-10_final.stac-item
2023-02-11 10:52:42	ga_ls9c_ard_3-2-1_105082_2023-02-11_final.stac-item
2023-04-29 10:17:04	ga_ls9c_ard_3-2-1_100072_2023-04-29_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-04-30 11:01:54	ga_ls9c_ard_3-2-1_107076_2023-04-30_final.stac-item
2023-04-30 11:03:54	ga_ls9c_ard_3-2-1_107081_2023-04-30_final.stac-item
2023-05-01 10:07:03	ga_ls9c_ard_3-2-1_098078_2023-05-01_final.stac-item
2023-05-28 09:45:53	ga_ls9c_ard_3-2-1_095072_2023-05-28_final.stac-item
2023-05-28 09:50:40	ga_ls9c_ard_3-2-1_095084_2023-05-28_final.stac-item
2023-05-28 11:25:10	ga_ls9c_ard_3-2-1_111073_2023-05-28_final.stac-item
2023-07-06 09:51:19	ga_ls9c_ard_3-2-1_096070_2023-07-06_final.stac-item
2023-07-15 11:25:41	ga_ls9c_ard_3-2-1_111074_2023-07-15_final.stac-item
2023-07-16 10:27:40	ga_ls9c_ard_3-2-1_102068_2023-07-16_final.stac-item
2023-07-17 09:39:14	ga_ls9c_ard_3-2-1_093086_2023-07-17_final.stac-item
2023-07-17 09:39:38	ga_ls9c_ard_3-2-1_093087_2023-07-17_final.stac-item
2023-07-20 10:09:44	ga_ls9c_ard_3-2-1_098085_2023-07-20_final.stac-item
2023-07-29 09:57:13	ga_ls9c_ard_3-2-1_097069_2023-07-29_final.stac-item
2023-07-29 10:03:12	ga_ls9c_ard_3-2-1_097084_2023-07-29_final.stac-item
2023-07-30 09:06:00	ga_ls9c_ard_3-2-1_088080_2023-07-29_final.stac-item
2023-08-08 10:35:36	ga_ls9c_ard_3-2-1_103072_2023-08-08_final.stac-item
2023-10-14 11:11:21	ga_ls9c_ard_3-2-1_108083_2023-10-14_final.stac-item
2023-10-14 11:11:45	ga_ls9c_ard_3-2-1_108084_2023-10-14_final.stac-item
2023-10-16 09:22:55	ga_ls9c_ard_3-2-1_090090_2023-10-15_final.stac-item
2023-10-16 10:58:13	ga_ls9c_ard_3-2-1_106081_2023-10-16_final.stac-item
2023-10-16 10:58:37	ga_ls9c_ard_3-2-1_106082_2023-10-16_final.stac-item
2023-10-19 11:26:20	ga_ls9c_ard_3-2-1_111074_2023-10-19_final.stac-item
2023-10-23 11:02:24	ga_ls9c_ard_3-2-1_107076_2023-10-23_final.stac-item
2023-10-24 10:07:35	ga_ls9c_ard_3-2-1_098078_2023-10-24_final.stac-item
2023-10-25 09:12:21	ga_ls9c_ard_3-2-1_089079_2023-10-24_final.stac-item
2023-10-28 09:45:37	ga_ls9c_ard_3-2-1_094085_2023-10-28_final.stac-item
2023-11-01 10:53:20	ga_ls9c_ard_3-2-1_106069_2023-11-01_final.stac-item
2023-11-04 11:26:13	ga_ls9c_ard_3-2-1_111074_2023-11-04_final.stac-item
2023-11-16 10:09:42	ga_ls9c_ard_3-2-1_099068_2023-11-16_final.stac-item
2023-11-17 10:56:10	ga_ls9c_ard_3-2-1_106076_2023-11-17_final.stac-item
2023-11-19 09:07:45	ga_ls9c_ard_3-2-1_088083_2023-11-18_final.stac-item
2023-11-20 11:23:56	ga_ls9c_ard_3-2-1_111068_2023-11-20_final.stac-item
2023-11-24 09:23:58	ga_ls9c_ard_3-2-1_091077_2023-11-23_final.stac-item
2023-11-24 09:28:22	ga_ls9c_ard_3-2-1_091088_2023-11-23_final.stac-item
2023-11-24 11:00:28	ga_ls9c_ard_3-2-1_107071_2023-11-24_final.stac-item
2023-11-26 09:13:13	ga_ls9c_ard_3-2-1_089081_2023-11-25_final.stac-item
2023-11-26 10:48:07	ga_ls9c_ard_3-2-1_105071_2023-11-26_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