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
2021-11-22 09:23:40	ga_ls9c_ard_3-2-1_091072_2021-11-21_final.stac-item
2021-12-06 09:12:30	ga_ls9c_ard_3-2-1_089079_2021-12-05_final.stac-item
2021-12-11 09:28:12	ga_ls9c_ard_3-2-1_092072_2021-12-10_final.stac-item
2021-12-11 09:34:11	ga_ls9c_ard_3-2-1_092087_2021-12-11_final.stac-item
2021-12-21 10:10:01	ga_ls9c_ard_3-2-1_098084_2021-12-21_final.stac-item
2021-12-22 09:10:48	ga_ls9c_ard_3-2-1_089075_2021-12-21_final.stac-item
2021-12-29 10:57:28	ga_ls9c_ard_3-2-1_106079_2021-12-29_final.stac-item
2022-01-12 11:08:11	ga_ls9c_ard_3-2-1_108075_2022-01-12_final.stac-item
2022-01-14 10:53:01	ga_ls9c_ard_3-2-1_106068_2022-01-14_final.stac-item
2022-01-23 09:11:35	ga_ls9c_ard_3-2-1_089077_2022-01-22_final.stac-item
2022-02-09 09:52:02	ga_ls9c_ard_3-2-1_096070_2022-02-09_final.stac-item
2022-02-14 10:09:44	ga_ls9c_ard_3-2-1_099068_2022-02-14_final.stac-item
2022-02-17 09:07:19	ga_ls9c_ard_3-2-1_088082_2022-02-16_final.stac-item
2022-02-20 11:11:53	ga_ls9c_ard_3-2-1_109069_2022-02-20_final.stac-item
2022-02-22 09:22:36	ga_ls9c_ard_3-2-1_091074_2022-02-21_final.stac-item
2022-02-22 10:59:53	ga_ls9c_ard_3-2-1_107070_2022-02-22_final.stac-item
2022-02-27 11:19:10	ga_ls9c_ard_3-2-1_110072_2022-02-27_final.stac-item
2022-03-03 09:16:43	ga_ls9c_ard_3-2-1_090075_2022-03-02_final.stac-item
2022-04-04 09:21:50	ga_ls9c_ard_3-2-1_090088_2022-04-03_final.stac-item
2022-04-08 10:33:10	ga_ls9c_ard_3-2-1_102081_2022-04-08_final.stac-item
2022-04-12 10:02:50	ga_ls9c_ard_3-2-1_098067_2022-04-12_final.stac-item
2022-04-23 11:24:38	ga_ls9c_ard_3-2-1_111071_2022-04-23_final.stac-item
2022-04-23 11:25:02	ga_ls9c_ard_3-2-1_111072_2022-04-23_final.stac-item
2022-04-29 10:46:22	ga_ls9c_ard_3-2-1_105068_2022-04-29_final.stac-item
2022-05-05 10:09:14	ga_ls9c_ard_3-2-1_099068_2022-05-05_final.stac-item
2022-05-05 10:13:38	ga_ls9c_ard_3-2-1_099079_2022-05-05_final.stac-item
2022-05-21 11:50:19	ga_ls9c_ard_3-2-1_115074_2022-05-21_final.stac-item
2022-06-04 10:25:01	ga_ls9c_ard_3-2-1_101077_2022-06-04_final.stac-item
2022-06-14 09:22:29	ga_ls9c_ard_3-2-1_091075_2022-06-13_final.stac-item
2022-06-15 10:07:21	ga_ls9c_ard_3-2-1_098079_2022-06-15_final.stac-item
2022-07-01 10:02:49	ga_ls9c_ard_3-2-1_098067_2022-07-01_final.stac-item
2022-07-18 10:49:39	ga_ls9c_ard_3-2-1_105076_2022-07-18_final.stac-item
2022-07-19 11:31:21	ga_ls9c_ard_3-2-1_112072_2022-07-19_final.stac-item
2022-07-24 10:10:17	ga_ls9c_ard_3-2-1_099070_2022-07-24_final.stac-item
2022-07-25 09:17:04	ga_ls9c_ard_3-2-1_090076_2022-07-24_final.stac-item
2022-08-02 10:03:02	ga_ls9c_ard_3-2-1_098067_2022-08-02_final.stac-item
2022-08-06 11:24:01	ga_ls9c_ard_3-2-1_110084_2022-08-06_final.stac-item
2022-08-14 10:33:27	ga_ls9c_ard_3-2-1_102081_2022-08-14_final.stac-item
2022-08-18 10:03:57	ga_ls9c_ard_3-2-1_098069_2022-08-18_final.stac-item
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final.stac-item
2022-09-01 10:18:44	ga_ls9c_ard_3-2-1_100075_2022-09-01_final.stac-item
2022-09-08 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-09-08_final.stac-item
2022-09-14 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-09-14_final.stac-item
2022-09-16 09:34:44	ga_ls9c_ard_3-2-1_093073_2022-09-16_final.stac-item
2022-09-29 09:07:06	ga_ls9c_ard_3-2-1_088081_2022-09-28_final.stac-item
2022-11-03 09:38:02	ga_ls9c_ard_3-2-1_093081_2022-11-03_final.stac-item
2022-11-03 09:40:02	ga_ls9c_ard_3-2-1_093086_2022-11-03_final.stac-item
2022-11-11 10:23:33	ga_ls9c_ard_3-2-1_101071_2022-11-11_final.stac-item
2022-11-12 09:29:08	ga_ls9c_ard_3-2-1_092074_2022-11-11_final.stac-item
2022-11-13 10:10:48	ga_ls9c_ard_3-2-1_099070_2022-11-13_final.stac-item
2022-11-19 11:14:36	ga_ls9c_ard_3-2-1_109075_2022-11-19_final.stac-item
2022-11-21 11:00:38	ga_ls9c_ard_3-2-1_107071_2022-11-21_final.stac-item
2022-11-22 10:03:25	ga_ls9c_ard_3-2-1_098067_2022-11-22_final.stac-item
2022-12-07 09:22:31	ga_ls9c_ard_3-2-1_091073_2022-12-06_final.stac-item
2022-12-08 10:03:24	ga_ls9c_ard_3-2-1_098067_2022-12-08_final.stac-item
2022-12-15 10:10:46	ga_ls9c_ard_3-2-1_099070_2022-12-15_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2023-01-09 10:04:11	ga_ls9c_ard_3-2-1_098069_2023-01-09_final.stac-item
2023-01-25 10:04:07	ga_ls9c_ard_3-2-1_098069_2023-01-25_final.stac-item
2023-01-26 09:16:30	ga_ls9c_ard_3-2-1_089089_2023-01-25_final.stac-item
2023-01-30 10:23:56	ga_ls9c_ard_3-2-1_101072_2023-01-30_final.stac-item
2023-03-01 10:34:31	ga_ls9c_ard_3-2-1_103068_2023-03-01_final.stac-item
2023-03-11 09:34:11	ga_ls9c_ard_3-2-1_093072_2023-03-11_final.stac-item
2023-04-02 10:39:24	ga_ls9c_ard_3-2-1_103081_2023-04-02_final.stac-item
2023-04-26 09:45:48	ga_ls9c_ard_3-2-1_095071_2023-04-26_final.stac-item
2023-05-07 09:33:06	ga_ls9c_ard_3-2-1_092086_2023-05-07_final.stac-item
2023-05-12 11:24:32	ga_ls9c_ard_3-2-1_111071_2023-05-12_final.stac-item
2023-05-14 11:14:09	ga_ls9c_ard_3-2-1_109076_2023-05-14_final.stac-item
2023-06-09 10:09:44	ga_ls9c_ard_3-2-1_099070_2023-06-09_final.stac-item
2023-06-11 11:37:02	ga_ls9c_ard_3-2-1_113072_2023-06-11_final.stac-item
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final.stac-item
2023-08-20 09:26:16	ga_ls9c_ard_3-2-1_091084_2023-08-19_final.stac-item
2023-09-01 11:24:02	ga_ls9c_ard_3-2-1_111069_2023-09-01_final.stac-item
2023-09-07 09:11:44	ga_ls9c_ard_3-2-1_089078_2023-09-06_final.stac-item
2023-09-07 09:16:07	ga_ls9c_ard_3-2-1_089089_2023-09-06_final.stac-item
2023-09-14 10:52:52	ga_ls9c_ard_3-2-1_106068_2023-09-14_final.stac-item
2023-10-03 09:46:05	ga_ls9c_ard_3-2-1_095071_2023-10-03_final.stac-item
2023-10-03 09:46:53	ga_ls9c_ard_3-2-1_095073_2023-10-03_final.stac-item
2023-10-03 11:24:10	ga_ls9c_ard_3-2-1_111069_2023-10-03_final.stac-item
2023-10-06 11:57:54	ga_ls9c_ard_3-2-1_116076_2023-10-06_final.stac-item
2023-11-18 09:56:59	ga_ls9c_ard_3-2-1_097067_2023-11-18_final.stac-item
2023-11-24 09:23:10	ga_ls9c_ard_3-2-1_091075_2023-11-23_final.stac-item
2023-11-25 10:04:27	ga_ls9c_ard_3-2-1_098070_2023-11-25_final.stac-item
2023-11-26 10:52:54	ga_ls9c_ard_3-2-1_105083_2023-11-26_final.stac-item
2023-12-02 10:11:01	ga_ls9c_ard_3-2-1_099071_2023-12-02_final.stac-item
2023-12-05 09:06:36	ga_ls9c_ard_3-2-1_088080_2023-12-04_final.stac-item
2023-12-08 09:34:16	ga_ls9c_ard_3-2-1_093072_2023-12-08_final.stac-item
2023-12-15 11:19:25	ga_ls9c_ard_3-2-1_110072_2023-12-15_final.stac-item
2023-12-18 10:13:51	ga_ls9c_ard_3-2-1_099078_2023-12-18_final.stac-item
2024-01-01 10:25:46	ga_ls9c_ard_3-2-1_101077_2024-01-01_final.stac-item
2024-01-03 10:10:11	ga_ls9c_ard_3-2-1_099069_2024-01-03_final.stac-item
2024-01-07 09:47:02	ga_ls9c_ard_3-2-1_095073_2024-01-07_final.stac-item
2024-01-09 09:34:42	ga_ls9c_ard_3-2-1_093073_2024-01-09_final.stac-item
2024-01-13 09:14:47	ga_ls9c_ard_3-2-1_089085_2024-01-12_final.stac-item
2024-01-15 10:39:43	ga_ls9c_ard_3-2-1_103081_2024-01-15_final.stac-item
2024-01-19 11:53:04	ga_ls9c_ard_3-2-1_115079_2024-01-19_final.stac-item
2024-01-26 10:19:08	ga_ls9c_ard_3-2-1_100076_2024-01-26_final.stac-item
2024-01-29 09:16:23	ga_ls9c_ard_3-2-1_089089_2024-01-28_final.stac-item
2024-02-07 09:06:39	ga_ls9c_ard_3-2-1_088080_2024-02-06_final.stac-item
2024-02-08 11:24:24	ga_ls9c_ard_3-2-1_111069_2024-02-08_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