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

75 results

Time (local)	Label
2021-11-05 11:12:53	ga_ls9c_ard_3-2-1_109070_2021-11-05_final.stac-item
2021-11-10 09:38:18	ga_ls9c_ard_3-2-1_094074_2021-11-10_final.stac-item
2021-12-04 09:22:53	ga_ls9c_ard_3-2-1_091074_2021-12-03_final.stac-item
2021-12-23 09:52:04	ga_ls9c_ard_3-2-1_096070_2021-12-23_final.stac-item
2022-01-05 09:27:09	ga_ls9c_ard_3-2-1_091085_2022-01-04_final.stac-item
2022-01-13 10:16:09	ga_ls9c_ard_3-2-1_099084_2022-01-13_final.stac-item
2022-02-11 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-02-11_final.stac-item
2022-03-03 09:21:30	ga_ls9c_ard_3-2-1_090087_2022-03-02_final.stac-item
2022-03-11 10:03:47	ga_ls9c_ard_3-2-1_098069_2022-03-11_final.stac-item
2022-04-09 11:11:38	ga_ls9c_ard_3-2-1_109069_2022-04-09_final.stac-item
2022-04-20 09:22:28	ga_ls9c_ard_3-2-1_090090_2022-04-19_final.stac-item
2022-05-04 09:33:10	ga_ls9c_ard_3-2-1_092086_2022-05-04_final.stac-item
2022-05-16 09:57:21	ga_ls9c_ard_3-2-1_096085_2022-05-16_final.stac-item
2022-06-03 09:42:09	ga_ls9c_ard_3-2-1_094078_2022-06-03_final.stac-item
2022-06-15 10:03:22	ga_ls9c_ard_3-2-1_098069_2022-06-15_final.stac-item
2022-06-22 10:08:56	ga_ls9c_ard_3-2-1_099067_2022-06-22_final.stac-item
2022-07-08 10:10:34	ga_ls9c_ard_3-2-1_099071_2022-07-08_final.stac-item
2022-07-17 10:07:10	ga_ls9c_ard_3-2-1_098078_2022-07-17_final.stac-item
2022-07-23 11:07:29	ga_ls9c_ard_3-2-1_108074_2022-07-23_final.stac-item
2022-08-15 09:39:26	ga_ls9c_ard_3-2-1_093085_2022-08-15_final.stac-item
2022-08-19 10:50:01	ga_ls9c_ard_3-2-1_105076_2022-08-19_final.stac-item
2022-09-02 11:05:35	ga_ls9c_ard_3-2-1_107084_2022-09-02_final.stac-item
2022-09-18 09:27:59	ga_ls9c_ard_3-2-1_091087_2022-09-17_final.stac-item
2022-09-20 09:10:51	ga_ls9c_ard_3-2-1_089075_2022-09-19_final.stac-item
2022-09-28 09:57:56	ga_ls9c_ard_3-2-1_097069_2022-09-28_final.stac-item
2022-10-02 11:12:53	ga_ls9c_ard_3-2-1_109071_2022-10-02_final.stac-item
2022-10-02 11:16:29	ga_ls9c_ard_3-2-1_109080_2022-10-02_final.stac-item
2022-10-11 09:33:51	ga_ls9c_ard_3-2-1_092086_2022-10-11_final.stac-item
2022-10-30 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-30_final.stac-item
2022-11-15 09:57:14	ga_ls9c_ard_3-2-1_097067_2022-11-15_final.stac-item
2022-11-21 11:00:38	ga_ls9c_ard_3-2-1_107071_2022-11-21_final.stac-item
2022-12-03 11:24:30	ga_ls9c_ard_3-2-1_111069_2022-12-03_final.stac-item
2022-12-14 09:30:18	ga_ls9c_ard_3-2-1_092077_2022-12-14_final.stac-item
2022-12-27 10:36:16	ga_ls9c_ard_3-2-1_103072_2022-12-27_final.stac-item
2023-01-06 11:12:59	ga_ls9c_ard_3-2-1_109071_2023-01-06_final.stac-item
2023-01-09 10:03:24	ga_ls9c_ard_3-2-1_098067_2023-01-09_final.stac-item
2023-01-16 10:11:30	ga_ls9c_ard_3-2-1_099072_2023-01-16_final.stac-item
2023-02-01 10:09:12	ga_ls9c_ard_3-2-1_099066_2023-02-01_final.stac-item
2023-03-08 09:04:54	ga_ls9c_ard_3-2-1_088076_2023-03-07_interim.stac-item
2023-03-22 09:22:23	ga_ls9c_ard_3-2-1_090089_2023-03-21_final.stac-item
2023-04-23 12:31:07	ga_ls9c_ard_3-2-1_122067_2023-04-23_final.stac-item
2023-05-16 12:37:04	ga_ls9c_ard_3-2-1_123067_2023-05-16_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-06-11 09:56:57	ga_ls9c_ard_3-2-1_097069_2023-06-11_final.stac-item
2023-07-05 09:11:38	ga_ls9c_ard_3-2-1_089079_2023-07-04_final.stac-item
2023-07-18 11:57:00	ga_ls9c_ard_3-2-1_116075_2023-07-18_final.stac-item
2023-07-18 11:57:23	ga_ls9c_ard_3-2-1_116076_2023-07-18_final.stac-item
2023-07-19 09:27:40	ga_ls9c_ard_3-2-1_091088_2023-07-18_final.stac-item
2023-08-11 09:33:37	ga_ls9c_ard_3-2-1_092087_2023-08-11_final.stac-item
2023-08-12 10:08:54	ga_ls9c_ard_3-2-1_099067_2023-08-12_final.stac-item
2023-08-12 11:52:11	ga_ls9c_ard_3-2-1_115078_2023-08-12_final.stac-item
2023-08-30 09:56:42	ga_ls9c_ard_3-2-1_097067_2023-08-30_final.stac-item
2023-09-21 09:22:57	ga_ls9c_ard_3-2-1_091075_2023-09-20_final.stac-item
2023-09-29 10:10:20	ga_ls9c_ard_3-2-1_099070_2023-09-29_final.stac-item
2023-10-02 09:07:12	ga_ls9c_ard_3-2-1_088082_2023-10-01_final.stac-item
2023-10-21 09:34:42	ga_ls9c_ard_3-2-1_093073_2023-10-21_final.stac-item
2023-10-23 09:22:43	ga_ls9c_ard_3-2-1_091074_2023-10-22_final.stac-item
2023-11-16 10:09:18	ga_ls9c_ard_3-2-1_099067_2023-11-16_final.stac-item
2023-12-20 09:58:18	ga_ls9c_ard_3-2-1_097070_2023-12-20_final.stac-item
2023-12-27 10:07:40	ga_ls9c_ard_3-2-1_098078_2023-12-27_final.stac-item
2024-01-05 09:59:00	ga_ls9c_ard_3-2-1_097072_2024-01-05_final.stac-item
2024-01-27 09:23:31	ga_ls9c_ard_3-2-1_091076_2024-01-26_final.stac-item
2024-01-28 11:44:53	ga_ls9c_ard_3-2-1_114074_2024-01-28_final.stac-item
2024-02-21 10:52:54	ga_ls9c_ard_3-2-1_106068_2024-02-21_final.stac-item
2024-03-04 09:40:48	ga_ls9c_ard_3-2-1_094073_2024-03-04_final.stac-item
2024-03-08 10:52:58	ga_ls9c_ard_3-2-1_106068_2024-03-08_final.stac-item
2024-03-20 11:18:27	ga_ls9c_ard_3-2-1_110070_2024-03-20_final.stac-item
2024-03-24 10:52:54	ga_ls9c_ard_3-2-1_106068_2024-03-24_final.stac-item
2024-03-27 11:25:44	ga_ls9c_ard_3-2-1_111073_2024-03-27_final.stac-item
2024-04-09 09:20:16	ga_ls9c_ard_3-2-1_090084_2024-04-08_final.stac-item
2024-04-18 09:15:56	ga_ls9c_ard_3-2-1_089089_2024-04-17_final.stac-item
2024-04-24 10:08:45	ga_ls9c_ard_3-2-1_099067_2024-04-24_final.stac-item
2024-04-25 10:52:25	ga_ls9c_ard_3-2-1_106068_2024-04-25_final.stac-item
2024-05-13 09:07:06	ga_ls9c_ard_3-2-1_088083_2024-05-12_nrt.stac-item
2024-05-17 10:19:10	ga_ls9c_ard_3-2-1_100078_2024-05-17_nrt.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