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
2021-11-06 10:16:35	ga_ls9c_ard_3-2-1_100076_2021-11-06_final.stac-item
2021-11-10 09:40:41	ga_ls9c_ard_3-2-1_094080_2021-11-10_final.stac-item
2021-11-19 10:39:32	ga_ls9c_ard_3-2-1_104068_2021-11-19_final.stac-item
2021-12-18 09:34:43	ga_ls9c_ard_3-2-1_093073_2021-12-18_final.stac-item
2021-12-25 11:20:36	ga_ls9c_ard_3-2-1_110075_2021-12-25_final.stac-item
2021-12-27 11:08:14	ga_ls9c_ard_3-2-1_108075_2021-12-27_final.stac-item
2022-01-03 09:40:42	ga_ls9c_ard_3-2-1_093088_2022-01-03_final.stac-item
2022-01-09 10:34:30	ga_ls9c_ard_3-2-1_103068_2022-01-09_final.stac-item
2022-01-23 09:16:47	ga_ls9c_ard_3-2-1_089090_2022-01-22_final.stac-item
2022-01-29 11:51:29	ga_ls9c_ard_3-2-1_115075_2022-01-29_final.stac-item
2022-02-16 10:01:21	ga_ls9c_ard_3-2-1_097078_2022-02-16_final.stac-item
2022-02-27 11:20:22	ga_ls9c_ard_3-2-1_110075_2022-02-27_final.stac-item
2022-03-03 10:55:36	ga_ls9c_ard_3-2-1_106075_2022-03-03_final.stac-item
2022-03-11 10:03:23	ga_ls9c_ard_3-2-1_098068_2022-03-11_final.stac-item
2022-03-21 10:40:25	ga_ls9c_ard_3-2-1_104068_2022-03-21_final.stac-item
2022-03-22 11:24:52	ga_ls9c_ard_3-2-1_111071_2022-03-22_final.stac-item
2022-03-23 10:28:27	ga_ls9c_ard_3-2-1_102069_2022-03-23_final.stac-item
2022-04-08 10:27:59	ga_ls9c_ard_3-2-1_102068_2022-04-08_final.stac-item
2022-04-09 09:33:57	ga_ls9c_ard_3-2-1_093072_2022-04-09_final.stac-item
2022-04-09 09:35:33	ga_ls9c_ard_3-2-1_093076_2022-04-09_final.stac-item
2022-04-19 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-04-19_final.stac-item
2022-04-26 10:21:03	ga_ls9c_ard_3-2-1_100082_2022-04-26_final.stac-item
2022-04-29 10:49:09	ga_ls9c_ard_3-2-1_105075_2022-04-29_final.stac-item
2022-05-10 10:28:56	ga_ls9c_ard_3-2-1_102071_2022-05-10_final.stac-item
2022-05-25 09:51:30	ga_ls9c_ard_3-2-1_095086_2022-05-25_final.stac-item
2022-05-25 11:24:24	ga_ls9c_ard_3-2-1_111071_2022-05-25_final.stac-item
2022-05-30 10:02:28	ga_ls9c_ard_3-2-1_098067_2022-05-30_final.stac-item
2022-06-12 11:14:06	ga_ls9c_ard_3-2-1_109076_2022-06-12_final.stac-item
2022-06-14 10:59:22	ga_ls9c_ard_3-2-1_107070_2022-06-14_final.stac-item
2022-06-15 10:02:34	ga_ls9c_ard_3-2-1_098067_2022-06-15_final.stac-item
2022-06-24 11:41:06	ga_ls9c_ard_3-2-1_113081_2022-06-24_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 11:25:30	ga_ls9c_ard_3-2-1_111073_2022-07-12_final.stac-item
2022-08-01 09:28:32	ga_ls9c_ard_3-2-1_091089_2022-07-31_final.stac-item
2022-08-07 10:28:00	ga_ls9c_ard_3-2-1_101083_2022-08-07_final.stac-item
2022-08-24 11:11:46	ga_ls9c_ard_3-2-1_108084_2022-08-24_final.stac-item
2022-08-31 09:35:05	ga_ls9c_ard_3-2-1_093074_2022-08-31_final.stac-item
2022-08-31 09:40:16	ga_ls9c_ard_3-2-1_093087_2022-08-31_final.stac-item
2022-09-04 09:11:57	ga_ls9c_ard_3-2-1_089078_2022-09-03_final.stac-item
2022-09-25 09:29:49	ga_ls9c_ard_3-2-1_092076_2022-09-24_final.stac-item
2022-10-11 11:08:21	ga_ls9c_ard_3-2-1_108075_2022-10-11_final.stac-item
2022-10-20 11:01:49	ga_ls9c_ard_3-2-1_107074_2022-10-20_final.stac-item
2022-11-03 09:38:26	ga_ls9c_ard_3-2-1_093082_2022-11-03_final.stac-item
2022-11-22 10:04:13	ga_ls9c_ard_3-2-1_098069_2022-11-22_final.stac-item
2022-11-26 11:18:45	ga_ls9c_ard_3-2-1_110070_2022-11-26_final.stac-item
2022-11-30 09:22:42	ga_ls9c_ard_3-2-1_090089_2022-11-29_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-18 10:40:52	ga_ls9c_ard_3-2-1_104068_2022-12-18_final.stac-item
2022-12-23 09:26:04	ga_ls9c_ard_3-2-1_091082_2022-12-22_final.stac-item
2023-01-03 10:40:53	ga_ls9c_ard_3-2-1_104068_2023-01-03_final.stac-item
2023-01-08 09:26:55	ga_ls9c_ard_3-2-1_091084_2023-01-07_final.stac-item
2023-01-10 10:52:38	ga_ls9c_ard_3-2-1_105082_2023-01-10_final.stac-item
2023-01-17 09:21:27	ga_ls9c_ard_3-2-1_090086_2023-01-16_final.stac-item
2023-01-21 10:33:33	ga_ls9c_ard_3-2-1_102081_2023-01-21_final.stac-item
2023-01-31 09:33:30	ga_ls9c_ard_3-2-1_092085_2023-01-31_final.stac-item
2023-02-18 09:22:18	ga_ls9c_ard_3-2-1_090088_2023-02-17_final.stac-item
2023-03-02 11:23:21	ga_ls9c_ard_3-2-1_110082_2023-03-02_final.stac-item
2023-03-16 09:57:55	ga_ls9c_ard_3-2-1_096085_2023-03-16_final.stac-item
2023-04-02 10:35:48	ga_ls9c_ard_3-2-1_103072_2023-04-02_final.stac-item
2023-04-09 09:06:15	ga_ls9c_ard_3-2-1_088080_2023-04-08_final.stac-item
2023-04-14 09:28:43	ga_ls9c_ard_3-2-1_091090_2023-04-13_final.stac-item
2023-04-16 10:46:51	ga_ls9c_ard_3-2-1_105069_2023-04-16_final.stac-item
2023-04-22 11:52:39	ga_ls9c_ard_3-2-1_115079_2023-04-22_final.stac-item
2023-05-01 10:03:28	ga_ls9c_ard_3-2-1_098069_2023-05-01_final.stac-item
2023-05-08 11:52:03	ga_ls9c_ard_3-2-1_115078_2023-05-08_final.stac-item
2023-05-14 09:39:15	ga_ls9c_ard_3-2-1_093086_2023-05-14_final.stac-item
2023-06-03 09:12:46	ga_ls9c_ard_3-2-1_089082_2023-06-02_final.stac-item
2023-06-16 10:16:13	ga_ls9c_ard_3-2-1_100071_2023-06-16_final.stac-item
2023-07-01 09:33:55	ga_ls9c_ard_3-2-1_093073_2023-07-01_final.stac-item
2023-07-04 11:46:32	ga_ls9c_ard_3-2-1_114080_2023-07-04_final.stac-item
2023-07-08 09:45:46	ga_ls9c_ard_3-2-1_094087_2023-07-08_final.stac-item
2023-08-20 09:28:16	ga_ls9c_ard_3-2-1_091089_2023-08-19_final.stac-item
2023-08-28 11:52:19	ga_ls9c_ard_3-2-1_115078_2023-08-28_final.stac-item
2023-09-05 10:59:45	ga_ls9c_ard_3-2-1_107070_2023-09-05_final.stac-item
2023-09-14 09:16:46	ga_ls9c_ard_3-2-1_090075_2023-09-13_final.stac-item
2023-09-15 09:56:51	ga_ls9c_ard_3-2-1_097067_2023-09-15_final.stac-item
2023-10-14 09:29:17	ga_ls9c_ard_3-2-1_092075_2023-10-13_final.stac-item
2023-10-16 09:22:31	ga_ls9c_ard_3-2-1_090089_2023-10-15_final.stac-item
2023-10-17 11:38:41	ga_ls9c_ard_3-2-1_113074_2023-10-17_final.stac-item
2023-11-10 09:11:30	ga_ls9c_ard_3-2-1_089077_2023-11-09_final.stac-item
2023-11-17 10:55:22	ga_ls9c_ard_3-2-1_106074_2023-11-17_final.stac-item
2023-11-23 10:21:59	ga_ls9c_ard_3-2-1_100083_2023-11-23_final.stac-item
2023-12-08 11:11:57	ga_ls9c_ard_3-2-1_109069_2023-12-08_final.stac-item
2023-12-09 10:17:32	ga_ls9c_ard_3-2-1_100072_2023-12-09_final.stac-item
2023-12-10 09:23:56	ga_ls9c_ard_3-2-1_091077_2023-12-09_final.stac-item
2024-01-05 09:57:48	ga_ls9c_ard_3-2-1_097069_2024-01-05_final.stac-item
2024-01-09 09:39:53	ga_ls9c_ard_3-2-1_093086_2024-01-09_final.stac-item
2024-01-11 09:27:08	ga_ls9c_ard_3-2-1_091085_2024-01-10_final.stac-item
2024-01-20 09:21:21	ga_ls9c_ard_3-2-1_090086_2024-01-19_final.stac-item
2024-01-29 09:16:47	ga_ls9c_ard_3-2-1_089090_2024-01-28_final.stac-item
2024-02-05 09:18:13	ga_ls9c_ard_3-2-1_090078_2024-02-04_final.stac-item
2024-02-06 09:57:53	ga_ls9c_ard_3-2-1_097069_2024-02-06_final.stac-item
2024-02-14 09:16:46	ga_ls9c_ard_3-2-1_089090_2024-02-13_final.stac-item
2024-02-18 10:27:40	ga_ls9c_ard_3-2-1_101082_2024-02-18_final.stac-item
2024-02-19 11:05:43	ga_ls9c_ard_3-2-1_108069_2024-02-19_final.stac-item
2024-03-27 09:52:26	ga_ls9c_ard_3-2-1_095087_2024-03-27_final.stac-item
2024-03-30 10:17:43	ga_ls9c_ard_3-2-1_100073_2024-03-30_final.stac-item
2024-04-02 09:10:08	ga_ls9c_ard_3-2-1_089074_2024-04-01_final.stac-item
2024-04-18 09:12:44	ga_ls9c_ard_3-2-1_089081_2024-04-17_final.stac-item
2024-04-22 10:25:34	ga_ls9c_ard_3-2-1_101078_2024-04-22_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