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 11:21:29	ga_ls9c_ard_3-2-1_110073_2021-11-20_final.stac-item
2021-11-20 11:22:41	ga_ls9c_ard_3-2-1_110076_2021-11-20_final.stac-item
2021-12-04 09:24:29	ga_ls9c_ard_3-2-1_091078_2021-12-03_final.stac-item
2021-12-04 11:02:34	ga_ls9c_ard_3-2-1_107076_2021-12-04_final.stac-item
2021-12-05 11:47:49	ga_ls9c_ard_3-2-1_114081_2021-12-05_final.stac-item
2021-12-18 09:40:18	ga_ls9c_ard_3-2-1_093087_2021-12-18_final.stac-item
2021-12-25 09:41:19	ga_ls9c_ard_3-2-1_094074_2021-12-25_final.stac-item
2021-12-27 11:07:26	ga_ls9c_ard_3-2-1_108073_2021-12-27_final.stac-item
2022-01-15 09:58:12	ga_ls9c_ard_3-2-1_097070_2022-01-15_final.stac-item
2022-01-31 10:03:50	ga_ls9c_ard_3-2-1_097084_2022-01-31_final.stac-item
2022-02-04 09:39:30	ga_ls9c_ard_3-2-1_093085_2022-02-04_final.stac-item
2022-02-10 10:38:05	ga_ls9c_ard_3-2-1_103077_2022-02-10_final.stac-item
2022-04-03 10:14:16	ga_ls9c_ard_3-2-1_099080_2022-04-03_final.stac-item
2022-04-07 11:30:00	ga_ls9c_ard_3-2-1_111084_2022-04-07_final.stac-item
2022-04-11 09:23:10	ga_ls9c_ard_3-2-1_091076_2022-04-10_final.stac-item
2022-04-16 11:20:32	ga_ls9c_ard_3-2-1_110076_2022-04-16_final.stac-item
2022-04-30 09:57:31	ga_ls9c_ard_3-2-1_096085_2022-04-30_final.stac-item
2022-05-04 11:10:03	ga_ls9c_ard_3-2-1_108081_2022-05-04_final.stac-item
2022-05-06 10:58:05	ga_ls9c_ard_3-2-1_106082_2022-05-06_final.stac-item
2022-05-22 09:20:36	ga_ls9c_ard_3-2-1_090086_2022-05-21_final.stac-item
2022-05-30 10:04:04	ga_ls9c_ard_3-2-1_098071_2022-05-30_final.stac-item
2022-06-03 09:40:33	ga_ls9c_ard_3-2-1_094074_2022-06-03_final.stac-item
2022-06-15 10:04:34	ga_ls9c_ard_3-2-1_098072_2022-06-15_final.stac-item
2022-06-23 09:20:07	ga_ls9c_ard_3-2-1_090084_2022-06-22_final.stac-item
2022-07-08 10:09:22	ga_ls9c_ard_3-2-1_099068_2022-07-08_final.stac-item
2022-07-16 11:01:11	ga_ls9c_ard_3-2-1_107074_2022-07-16_final.stac-item
2022-07-18 10:46:52	ga_ls9c_ard_3-2-1_105069_2022-07-18_final.stac-item
2022-07-21 11:20:13	ga_ls9c_ard_3-2-1_110075_2022-07-21_final.stac-item
2022-07-23 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-07-23_final.stac-item
2022-07-27 09:06:44	ga_ls9c_ard_3-2-1_088081_2022-07-26_final.stac-item
2022-08-17 09:25:05	ga_ls9c_ard_3-2-1_091080_2022-08-16_final.stac-item
2022-08-19 09:16:43	ga_ls9c_ard_3-2-1_089090_2022-08-18_final.stac-item
2022-09-09 11:11:21	ga_ls9c_ard_3-2-1_108083_2022-09-09_final.stac-item
2022-10-02 09:35:12	ga_ls9c_ard_3-2-1_093074_2022-10-02_final.stac-item
2022-10-31 10:42:51	ga_ls9c_ard_3-2-1_104073_2022-10-31_final.stac-item
2022-11-07 09:12:57	ga_ls9c_ard_3-2-1_089080_2022-11-06_final.stac-item
2022-11-19 11:14:12	ga_ls9c_ard_3-2-1_109074_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
2022-11-26 11:21:33	ga_ls9c_ard_3-2-1_110077_2022-11-26_final.stac-item
2022-11-29 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-11-29_final.stac-item
2022-12-02 10:41:14	ga_ls9c_ard_3-2-1_104069_2022-12-02_final.stac-item
2022-12-04 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-12-04_final.stac-item
2022-12-06 11:58:13	ga_ls9c_ard_3-2-1_116076_2022-12-06_final.stac-item
2022-12-07 09:25:19	ga_ls9c_ard_3-2-1_091080_2022-12-06_final.stac-item
2022-12-14 11:11:59	ga_ls9c_ard_3-2-1_108084_2022-12-14_final.stac-item
2022-12-18 10:42:04	ga_ls9c_ard_3-2-1_104071_2022-12-18_final.stac-item
2022-12-19 09:51:13	ga_ls9c_ard_3-2-1_095083_2022-12-19_final.stac-item
2022-12-19 11:26:55	ga_ls9c_ard_3-2-1_111075_2022-12-19_final.stac-item
2022-12-25 10:50:36	ga_ls9c_ard_3-2-1_105077_2022-12-25_final.stac-item
2022-12-28 09:45:26	ga_ls9c_ard_3-2-1_094084_2022-12-28_final.stac-item
2022-12-29 10:26:43	ga_ls9c_ard_3-2-1_101079_2022-12-29_final.stac-item
2023-01-01 10:56:50	ga_ls9c_ard_3-2-1_106077_2023-01-01_final.stac-item
2023-01-04 11:30:32	ga_ls9c_ard_3-2-1_111084_2023-01-04_final.stac-item
2023-01-05 10:32:07	ga_ls9c_ard_3-2-1_102077_2023-01-05_final.stac-item
2023-01-08 09:26:31	ga_ls9c_ard_3-2-1_091083_2023-01-07_final.stac-item
2023-01-15 09:33:26	ga_ls9c_ard_3-2-1_092085_2023-01-15_final.stac-item
2023-01-24 11:05:42	ga_ls9c_ard_3-2-1_107084_2023-01-24_final.stac-item
2023-01-25 11:47:47	ga_ls9c_ard_3-2-1_114081_2023-01-25_final.stac-item
2023-01-30 10:27:55	ga_ls9c_ard_3-2-1_101082_2023-01-30_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 09:36:57	ga_ls9c_ard_3-2-1_093078_2023-02-07_final.stac-item
2023-03-11 09:39:22	ga_ls9c_ard_3-2-1_093085_2023-03-11_final.stac-item
2023-03-12 11:57:56	ga_ls9c_ard_3-2-1_116076_2023-03-12_final.stac-item
2023-03-13 11:01:55	ga_ls9c_ard_3-2-1_107075_2023-03-13_final.stac-item
2023-03-14 10:08:17	ga_ls9c_ard_3-2-1_098080_2023-03-14_final.stac-item
2023-03-27 09:37:39	ga_ls9c_ard_3-2-1_093081_2023-03-27_final.stac-item
2023-04-02 10:37:24	ga_ls9c_ard_3-2-1_103076_2023-04-02_final.stac-item
2023-04-22 10:15:45	ga_ls9c_ard_3-2-1_099084_2023-04-22_final.stac-item
2023-04-22 11:51:03	ga_ls9c_ard_3-2-1_115075_2023-04-22_final.stac-item
2023-04-24 10:03:23	ga_ls9c_ard_3-2-1_097084_2023-04-24_final.stac-item
2023-04-24 11:39:52	ga_ls9c_ard_3-2-1_113078_2023-04-24_final.stac-item
2023-05-02 09:11:25	ga_ls9c_ard_3-2-1_089078_2023-05-01_final.stac-item
2023-05-10 11:41:41	ga_ls9c_ard_3-2-1_113083_2023-05-10_final.stac-item
2023-05-18 09:14:29	ga_ls9c_ard_3-2-1_089086_2023-05-17_final.stac-item
2023-05-31 10:18:22	ga_ls9c_ard_3-2-1_100076_2023-05-31_final.stac-item
2023-06-01 09:25:09	ga_ls9c_ard_3-2-1_091082_2023-05-31_final.stac-item
2023-06-18 10:03:28	ga_ls9c_ard_3-2-1_098070_2023-06-18_final.stac-item
2023-06-20 11:35:11	ga_ls9c_ard_3-2-1_112083_2023-06-20_final.stac-item
2023-06-25 11:50:07	ga_ls9c_ard_3-2-1_115074_2023-06-25_final.stac-item
2023-07-17 09:38:50	ga_ls9c_ard_3-2-1_093085_2023-07-17_final.stac-item
2023-07-21 10:51:48	ga_ls9c_ard_3-2-1_105082_2023-07-21_final.stac-item
2023-07-27 10:09:57	ga_ls9c_ard_3-2-1_099070_2023-07-27_final.stac-item
2023-07-28 09:19:56	ga_ls9c_ard_3-2-1_090084_2023-07-27_final.stac-item
2023-07-31 09:50:53	ga_ls9c_ard_3-2-1_095084_2023-07-31_final.stac-item
2023-08-05 10:09:53	ga_ls9c_ard_3-2-1_098085_2023-08-05_final.stac-item
2023-08-09 09:44:47	ga_ls9c_ard_3-2-1_094084_2023-08-09_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 10:53:22	ga_ls9c_ard_3-2-1_106070_2023-08-13_final.stac-item
2023-08-13 10:57:21	ga_ls9c_ard_3-2-1_106080_2023-08-13_final.stac-item
2023-08-15 10:45:47	ga_ls9c_ard_3-2-1_104082_2023-08-15_final.stac-item
2023-10-15 10:09:45	ga_ls9c_ard_3-2-1_099068_2023-10-15_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-10-19 11:30:20	ga_ls9c_ard_3-2-1_111084_2023-10-19_final.stac-item
2023-10-24 11:44:52	ga_ls9c_ard_3-2-1_114074_2023-10-24_final.stac-item
2023-10-28 09:41:14	ga_ls9c_ard_3-2-1_094074_2023-10-28_final.stac-item
2023-11-04 09:47:20	ga_ls9c_ard_3-2-1_095074_2023-11-04_final.stac-item
2023-11-14 10:28:03	ga_ls9c_ard_3-2-1_101083_2023-11-14_final.stac-item
2023-11-16 11:53:22	ga_ls9c_ard_3-2-1_115080_2023-11-16_final.stac-item
2023-11-25 10:03:39	ga_ls9c_ard_3-2-1_098068_2023-11-25_final.stac-item
2023-11-25 10:08:26	ga_ls9c_ard_3-2-1_098080_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