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
2021-11-20 09:43:13	ga_ls9c_ard_3-2-1_094074_2021-11-20_final.stac-item
2021-12-16 11:30:21	ga_ls9c_ard_3-2-1_111084_2021-12-16_final.stac-item
2021-12-24 10:37:44	ga_ls9c_ard_3-2-1_103076_2021-12-24_final.stac-item
2022-01-08 09:56:50	ga_ls9c_ard_3-2-1_096082_2022-01-08_final.stac-item
2022-01-14 09:18:08	ga_ls9c_ard_3-2-1_090078_2022-01-13_final.stac-item
2022-01-29 11:53:05	ga_ls9c_ard_3-2-1_115079_2022-01-29_final.stac-item
2022-02-06 11:05:37	ga_ls9c_ard_3-2-1_107084_2022-02-06_final.stac-item
2022-02-08 10:52:03	ga_ls9c_ard_3-2-1_105081_2022-02-08_final.stac-item
2022-02-24 10:52:18	ga_ls9c_ard_3-2-1_105082_2022-02-24_final.stac-item
2022-04-02 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-04-02_final.stac-item
2022-04-04 10:53:32	ga_ls9c_ard_3-2-1_106070_2022-04-04_final.stac-item
2022-04-07 11:25:13	ga_ls9c_ard_3-2-1_111072_2022-04-07_final.stac-item
2022-04-28 10:07:05	ga_ls9c_ard_3-2-1_098078_2022-04-28_final.stac-item
2022-04-28 10:07:29	ga_ls9c_ard_3-2-1_098079_2022-04-28_final.stac-item
2022-05-14 10:09:44	ga_ls9c_ard_3-2-1_098085_2022-05-14_final.stac-item
2022-05-21 11:51:55	ga_ls9c_ard_3-2-1_115078_2022-05-21_final.stac-item
2022-05-22 09:20:36	ga_ls9c_ard_3-2-1_090086_2022-05-21_final.stac-item
2022-06-17 11:35:06	ga_ls9c_ard_3-2-1_112082_2022-06-17_final.stac-item
2022-06-25 09:06:37	ga_ls9c_ard_3-2-1_088081_2022-06-24_final.stac-item
2022-07-13 10:28:16	ga_ls9c_ard_3-2-1_102069_2022-07-13_final.stac-item
2022-07-18 09:11:58	ga_ls9c_ard_3-2-1_089079_2022-07-17_final.stac-item
2022-08-31 09:39:52	ga_ls9c_ard_3-2-1_093086_2022-08-31_final.stac-item
2022-09-16 09:37:08	ga_ls9c_ard_3-2-1_093079_2022-09-16_final.stac-item
2022-09-19 11:44:57	ga_ls9c_ard_3-2-1_114074_2022-09-19_final.stac-item
2022-09-28 10:00:43	ga_ls9c_ard_3-2-1_097076_2022-09-28_final.stac-item
2022-09-30 11:30:26	ga_ls9c_ard_3-2-1_111084_2022-09-30_final.stac-item
2022-10-03 10:19:15	ga_ls9c_ard_3-2-1_100076_2022-10-03_final.stac-item
2022-10-23 09:52:15	ga_ls9c_ard_3-2-1_096070_2022-10-23_final.stac-item
2022-10-26 10:23:56	ga_ls9c_ard_3-2-1_101072_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
2022-10-28 10:15:58	ga_ls9c_ard_3-2-1_099083_2022-10-28_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-11 10:25:56	ga_ls9c_ard_3-2-1_101077_2022-11-11_final.stac-item
2022-11-14 10:58:03	ga_ls9c_ard_3-2-1_106080_2022-11-14_final.stac-item
2022-11-17 09:46:53	ga_ls9c_ard_3-2-1_095072_2022-11-17_final.stac-item
2022-11-20 10:20:10	ga_ls9c_ard_3-2-1_100078_2022-11-20_final.stac-item
2022-11-23 09:14:34	ga_ls9c_ard_3-2-1_089084_2022-11-22_final.stac-item
2022-12-04 10:28:53	ga_ls9c_ard_3-2-1_102069_2022-12-04_final.stac-item
2022-12-07 09:24:07	ga_ls9c_ard_3-2-1_091077_2022-12-06_final.stac-item
2022-12-08 10:04:35	ga_ls9c_ard_3-2-1_098070_2022-12-08_final.stac-item
2022-12-16 10:58:01	ga_ls9c_ard_3-2-1_106080_2022-12-16_final.stac-item
2022-12-30 09:33:05	ga_ls9c_ard_3-2-1_092084_2022-12-30_final.stac-item
2023-01-02 10:00:25	ga_ls9c_ard_3-2-1_097075_2023-01-02_final.stac-item
2023-01-05 10:34:07	ga_ls9c_ard_3-2-1_102082_2023-01-05_final.stac-item
2023-01-10 09:12:09	ga_ls9c_ard_3-2-1_089078_2023-01-09_final.stac-item
2023-01-16 10:11:54	ga_ls9c_ard_3-2-1_099073_2023-01-16_final.stac-item
2023-01-17 09:23:02	ga_ls9c_ard_3-2-1_090090_2023-01-16_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-01-25 10:10:30	ga_ls9c_ard_3-2-1_098085_2023-01-25_final.stac-item
2023-02-02 10:56:04	ga_ls9c_ard_3-2-1_106075_2023-02-02_final.stac-item
2023-02-03 09:59:15	ga_ls9c_ard_3-2-1_097072_2023-02-03_final.stac-item
2023-02-05 11:26:35	ga_ls9c_ard_3-2-1_111074_2023-02-05_final.stac-item
2023-02-06 10:34:10	ga_ls9c_ard_3-2-1_102082_2023-02-06_final.stac-item
2023-02-09 09:27:47	ga_ls9c_ard_3-2-1_091086_2023-02-08_final.stac-item
2023-02-14 11:24:22	ga_ls9c_ard_3-2-1_110084_2023-02-14_final.stac-item
2023-03-02 09:44:28	ga_ls9c_ard_3-2-1_094082_2023-03-02_final.stac-item
2023-03-13 09:24:14	ga_ls9c_ard_3-2-1_091078_2023-03-12_final.stac-item
2023-03-13 09:25:01	ga_ls9c_ard_3-2-1_091080_2023-03-12_final.stac-item
2023-03-29 09:28:02	ga_ls9c_ard_3-2-1_091088_2023-03-28_final.stac-item
2023-04-06 10:15:28	ga_ls9c_ard_3-2-1_099083_2023-04-06_final.stac-item
2023-04-07 10:53:32	ga_ls9c_ard_3-2-1_106070_2023-04-07_final.stac-item
2023-04-09 09:06:39	ga_ls9c_ard_3-2-1_088081_2023-04-08_final.stac-item
2023-04-21 11:10:59	ga_ls9c_ard_3-2-1_108083_2023-04-21_final.stac-item
2023-04-22 11:51:03	ga_ls9c_ard_3-2-1_115075_2023-04-22_final.stac-item
2023-04-27 10:30:39	ga_ls9c_ard_3-2-1_102075_2023-04-27_final.stac-item
2023-04-30 11:03:54	ga_ls9c_ard_3-2-1_107081_2023-04-30_final.stac-item
2023-05-02 10:46:42	ga_ls9c_ard_3-2-1_105069_2023-05-02_final.stac-item
2023-05-02 10:48:18	ga_ls9c_ard_3-2-1_105073_2023-05-02_final.stac-item
2023-05-03 11:35:56	ga_ls9c_ard_3-2-1_112084_2023-05-03_final.stac-item
2023-05-05 09:40:16	ga_ls9c_ard_3-2-1_094073_2023-05-05_final.stac-item
2023-05-05 11:23:32	ga_ls9c_ard_3-2-1_110084_2023-05-05_final.stac-item
2023-05-07 09:34:18	ga_ls9c_ard_3-2-1_092089_2023-05-07_final.stac-item
2023-05-09 09:17:09	ga_ls9c_ard_3-2-1_090077_2023-05-08_final.stac-item
2023-05-09 10:54:50	ga_ls9c_ard_3-2-1_106074_2023-05-09_final.stac-item
2023-05-12 11:26:07	ga_ls9c_ard_3-2-1_111075_2023-05-12_final.stac-item
2023-05-16 09:23:41	ga_ls9c_ard_3-2-1_091078_2023-05-15_final.stac-item
2023-05-16 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-05-15_final.stac-item
2023-05-16 11:01:46	ga_ls9c_ard_3-2-1_107076_2023-05-16_final.stac-item
2023-05-18 10:51:23	ga_ls9c_ard_3-2-1_105081_2023-05-18_final.stac-item
2023-05-23 09:28:34	ga_ls9c_ard_3-2-1_092075_2023-05-22_final.stac-item
2023-06-03 10:46:28	ga_ls9c_ard_3-2-1_105069_2023-06-03_final.stac-item
2023-06-19 09:11:26	ga_ls9c_ard_3-2-1_089079_2023-06-18_final.stac-item
2023-06-27 09:58:55	ga_ls9c_ard_3-2-1_097074_2023-06-27_final.stac-item
2023-07-24 09:43:48	ga_ls9c_ard_3-2-1_094082_2023-07-24_final.stac-item
2023-07-26 09:33:27	ga_ls9c_ard_3-2-1_092087_2023-07-26_final.stac-item
2023-08-03 10:21:25	ga_ls9c_ard_3-2-1_100083_2023-08-03_final.stac-item
2023-08-13 09:20:52	ga_ls9c_ard_3-2-1_090086_2023-08-12_final.stac-item
2023-08-13 09:22:04	ga_ls9c_ard_3-2-1_090089_2023-08-12_final.stac-item
2023-10-16 10:55:25	ga_ls9c_ard_3-2-1_106074_2023-10-16_final.stac-item
2023-10-19 11:29:56	ga_ls9c_ard_3-2-1_111083_2023-10-19_final.stac-item
2023-10-23 11:04:24	ga_ls9c_ard_3-2-1_107081_2023-10-23_final.stac-item
2023-10-25 10:47:14	ga_ls9c_ard_3-2-1_105069_2023-10-25_final.stac-item
2023-10-27 10:34:28	ga_ls9c_ard_3-2-1_103068_2023-10-27_final.stac-item
2023-10-28 09:41:14	ga_ls9c_ard_3-2-1_094074_2023-10-28_final.stac-item
2023-10-28 11:19:19	ga_ls9c_ard_3-2-1_110072_2023-10-28_final.stac-item
2023-11-01 10:54:56	ga_ls9c_ard_3-2-1_106073_2023-11-01_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-04 11:29:24	ga_ls9c_ard_3-2-1_111082_2023-11-04_final.stac-item
2023-11-14 10:24:03	ga_ls9c_ard_3-2-1_101073_2023-11-14_final.stac-item
2023-11-19 09:06:33	ga_ls9c_ard_3-2-1_088080_2023-11-18_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