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
2021-11-09 10:38:12	ga_ls9c_ard_3-2-1_103077_2021-11-09_final.stac-item
2021-11-12 10:59:01	ga_ls9c_ard_3-2-1_106076_2021-11-12_final.stac-item
2021-11-22 09:28:27	ga_ls9c_ard_3-2-1_091084_2021-11-21_final.stac-item
2021-12-06 10:49:00	ga_ls9c_ard_3-2-1_105073_2021-12-06_final.stac-item
2021-12-07 09:55:21	ga_ls9c_ard_3-2-1_096078_2021-12-07_final.stac-item
2021-12-11 09:32:35	ga_ls9c_ard_3-2-1_092083_2021-12-11_final.stac-item
2021-12-13 10:57:53	ga_ls9c_ard_3-2-1_106080_2021-12-13_final.stac-item
2021-12-17 10:28:44	ga_ls9c_ard_3-2-1_102069_2021-12-17_final.stac-item
2021-12-17 10:29:08	ga_ls9c_ard_3-2-1_102070_2021-12-17_final.stac-item
2021-12-21 10:09:37	ga_ls9c_ard_3-2-1_098083_2021-12-21_final.stac-item
2022-01-14 10:57:48	ga_ls9c_ard_3-2-1_106080_2022-01-14_final.stac-item
2022-01-19 09:40:41	ga_ls9c_ard_3-2-1_093088_2022-01-19_final.stac-item
2022-01-20 10:17:34	ga_ls9c_ard_3-2-1_100072_2022-01-20_final.stac-item
2022-01-25 10:39:19	ga_ls9c_ard_3-2-1_103080_2022-01-25_final.stac-item
2022-01-28 11:10:37	ga_ls9c_ard_3-2-1_108081_2022-01-28_final.stac-item
2022-01-30 10:57:51	ga_ls9c_ard_3-2-1_106080_2022-01-30_final.stac-item
2022-02-02 09:52:16	ga_ls9c_ard_3-2-1_095086_2022-02-02_final.stac-item
2022-02-06 11:04:49	ga_ls9c_ard_3-2-1_107082_2022-02-06_final.stac-item
2022-02-18 09:46:34	ga_ls9c_ard_3-2-1_095072_2022-02-18_final.stac-item
2022-02-22 11:04:41	ga_ls9c_ard_3-2-1_107082_2022-02-22_final.stac-item
2022-03-07 10:28:30	ga_ls9c_ard_3-2-1_102069_2022-03-07_final.stac-item
2022-04-14 09:57:38	ga_ls9c_ard_3-2-1_096085_2022-04-14_final.stac-item
2022-04-21 10:03:43	ga_ls9c_ard_3-2-1_097085_2022-04-21_final.stac-item
2022-05-02 09:45:09	ga_ls9c_ard_3-2-1_094085_2022-05-02_final.stac-item
2022-05-08 10:45:18	ga_ls9c_ard_3-2-1_104081_2022-05-08_final.stac-item
2022-05-11 11:13:22	ga_ls9c_ard_3-2-1_109074_2022-05-11_final.stac-item
2022-05-15 10:47:48	ga_ls9c_ard_3-2-1_105072_2022-05-15_final.stac-item
2022-05-18 09:45:45	ga_ls9c_ard_3-2-1_094087_2022-05-18_final.stac-item
2022-05-22 09:16:36	ga_ls9c_ard_3-2-1_090076_2022-05-21_final.stac-item
2022-05-25 09:48:42	ga_ls9c_ard_3-2-1_095079_2022-05-25_final.stac-item
2022-05-29 11:02:28	ga_ls9c_ard_3-2-1_107078_2022-05-29_final.stac-item
2022-06-09 10:45:09	ga_ls9c_ard_3-2-1_104081_2022-06-09_final.stac-item
2022-06-14 11:04:10	ga_ls9c_ard_3-2-1_107082_2022-06-14_final.stac-item
2022-06-17 09:57:49	ga_ls9c_ard_3-2-1_096086_2022-06-17_final.stac-item
2022-06-27 10:28:21	ga_ls9c_ard_3-2-1_102069_2022-06-27_final.stac-item
2022-07-07 09:32:54	ga_ls9c_ard_3-2-1_092085_2022-07-07_final.stac-item
2022-07-16 11:02:23	ga_ls9c_ard_3-2-1_107077_2022-07-16_final.stac-item
2022-08-14 10:28:16	ga_ls9c_ard_3-2-1_102068_2022-08-14_final.stac-item
2022-08-17 11:03:10	ga_ls9c_ard_3-2-1_107078_2022-08-17_final.stac-item
2022-08-21 10:36:04	ga_ls9c_ard_3-2-1_103072_2022-08-21_final.stac-item
2022-09-07 11:20:08	ga_ls9c_ard_3-2-1_110074_2022-09-07_final.stac-item
2022-09-20 09:11:39	ga_ls9c_ard_3-2-1_089077_2022-09-19_final.stac-item
2022-09-20 10:50:08	ga_ls9c_ard_3-2-1_105076_2022-09-20_final.stac-item
2022-09-21 09:55:19	ga_ls9c_ard_3-2-1_096078_2022-09-21_final.stac-item
2022-09-29 10:43:59	ga_ls9c_ard_3-2-1_104076_2022-09-29_final.stac-item
2022-09-30 09:47:10	ga_ls9c_ard_3-2-1_095073_2022-09-30_final.stac-item
2022-10-11 11:10:20	ga_ls9c_ard_3-2-1_108080_2022-10-11_final.stac-item
2022-10-15 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-10-15_final.stac-item
2022-10-16 11:26:08	ga_ls9c_ard_3-2-1_111073_2022-10-16_final.stac-item
2022-10-16 11:26:32	ga_ls9c_ard_3-2-1_111074_2022-10-16_final.stac-item
2022-10-20 11:00:13	ga_ls9c_ard_3-2-1_107070_2022-10-20_final.stac-item
2022-10-20 11:01:25	ga_ls9c_ard_3-2-1_107073_2022-10-20_final.stac-item
2022-10-22 10:50:39	ga_ls9c_ard_3-2-1_105077_2022-10-22_final.stac-item
2022-10-25 09:41:29	ga_ls9c_ard_3-2-1_094074_2022-10-25_final.stac-item
2022-10-30 10:02:47	ga_ls9c_ard_3-2-1_097081_2022-10-30_final.stac-item
2022-11-07 10:51:50	ga_ls9c_ard_3-2-1_105080_2022-11-07_final.stac-item
2022-11-12 09:31:31	ga_ls9c_ard_3-2-1_092080_2022-11-12_final.stac-item
2022-11-13 10:16:23	ga_ls9c_ard_3-2-1_099084_2022-11-13_final.stac-item
2022-11-21 09:23:21	ga_ls9c_ard_3-2-1_091075_2022-11-20_final.stac-item
2022-11-25 10:35:06	ga_ls9c_ard_3-2-1_103069_2022-11-25_final.stac-item
2022-11-28 11:11:10	ga_ls9c_ard_3-2-1_108082_2022-11-28_final.stac-item
2022-11-30 10:58:48	ga_ls9c_ard_3-2-1_106082_2022-11-30_final.stac-item
2022-12-07 11:03:00	ga_ls9c_ard_3-2-1_107077_2022-12-07_final.stac-item
2022-12-09 09:14:33	ga_ls9c_ard_3-2-1_089084_2022-12-08_final.stac-item
2022-12-17 09:58:48	ga_ls9c_ard_3-2-1_097071_2022-12-17_final.stac-item
2022-12-27 10:35:52	ga_ls9c_ard_3-2-1_103071_2022-12-27_final.stac-item
2023-01-04 11:24:33	ga_ls9c_ard_3-2-1_111069_2023-01-04_final.stac-item
2023-01-08 11:05:00	ga_ls9c_ard_3-2-1_107082_2023-01-08_final.stac-item
2023-01-11 11:36:41	ga_ls9c_ard_3-2-1_112084_2023-01-11_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
2023-01-25 10:04:07	ga_ls9c_ard_3-2-1_098069_2023-01-25_final.stac-item
2023-01-25 10:04:55	ga_ls9c_ard_3-2-1_098071_2023-01-25_final.stac-item
2023-02-01 10:14:47	ga_ls9c_ard_3-2-1_099080_2023-02-01_final.stac-item
2023-02-06 10:31:22	ga_ls9c_ard_3-2-1_102075_2023-02-06_final.stac-item
2023-02-07 11:15:02	ga_ls9c_ard_3-2-1_109076_2023-02-07_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-02-19 09:58:45	ga_ls9c_ard_3-2-1_097071_2023-02-19_final.stac-item
2023-03-09 11:25:50	ga_ls9c_ard_3-2-1_111073_2023-03-09_final.stac-item
2023-03-22 10:58:29	ga_ls9c_ard_3-2-1_106082_2023-03-22_final.stac-item
2023-04-14 09:21:56	ga_ls9c_ard_3-2-1_091073_2023-04-13_final.stac-item
2023-04-26 09:51:48	ga_ls9c_ard_3-2-1_095086_2023-04-26_final.stac-item
2023-04-28 11:13:30	ga_ls9c_ard_3-2-1_109074_2023-04-28_final.stac-item
2023-04-30 11:02:18	ga_ls9c_ard_3-2-1_107077_2023-04-30_final.stac-item
2023-05-02 09:11:01	ga_ls9c_ard_3-2-1_089077_2023-05-01_final.stac-item
2023-05-14 11:13:21	ga_ls9c_ard_3-2-1_109074_2023-05-14_final.stac-item
2023-06-12 10:44:59	ga_ls9c_ard_3-2-1_104081_2023-06-12_final.stac-item
2023-06-24 11:10:27	ga_ls9c_ard_3-2-1_108083_2023-06-24_final.stac-item
2023-06-29 09:51:01	ga_ls9c_ard_3-2-1_095085_2023-06-29_final.stac-item
2023-07-03 09:25:34	ga_ls9c_ard_3-2-1_091083_2023-07-02_final.stac-item
2023-07-03 11:02:28	ga_ls9c_ard_3-2-1_107078_2023-07-03_final.stac-item
2023-07-03 11:04:03	ga_ls9c_ard_3-2-1_107082_2023-07-03_final.stac-item
2023-07-09 10:22:15	ga_ls9c_ard_3-2-1_101070_2023-07-09_final.stac-item
2023-09-16 10:45:42	ga_ls9c_ard_3-2-1_104081_2023-09-16_final.stac-item
2023-09-21 11:04:38	ga_ls9c_ard_3-2-1_107082_2023-09-21_final.stac-item
2023-09-22 10:09:48	ga_ls9c_ard_3-2-1_098084_2023-09-22_final.stac-item
2023-09-28 11:07:56	ga_ls9c_ard_3-2-1_108075_2023-09-28_final.stac-item
2023-09-28 11:11:32	ga_ls9c_ard_3-2-1_108084_2023-09-28_final.stac-item
2023-09-30 09:21:07	ga_ls9c_ard_3-2-1_090086_2023-09-29_final.stac-item
2023-10-01 11:41:18	ga_ls9c_ard_3-2-1_113081_2023-10-01_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