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

94 results

Time (local)	Label
2021-11-22 09:28:03	ga_ls9c_ard_3-2-1_091083_2021-11-21_final.stac-item
2021-12-05 10:03:21	ga_ls9c_ard_3-2-1_098067_2021-12-05_final.stac-item
2021-12-05 10:09:44	ga_ls9c_ard_3-2-1_098083_2021-12-05_final.stac-item
2021-12-06 09:16:54	ga_ls9c_ard_3-2-1_089090_2021-12-05_final.stac-item
2021-12-27 11:06:38	ga_ls9c_ard_3-2-1_108071_2021-12-27_final.stac-item
2021-12-28 10:16:12	ga_ls9c_ard_3-2-1_099084_2021-12-28_final.stac-item
2021-12-31 09:07:49	ga_ls9c_ard_3-2-1_088083_2021-12-30_final.stac-item
2022-01-16 10:40:40	ga_ls9c_ard_3-2-1_104068_2022-01-16_final.stac-item
2022-01-23 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-22_final.stac-item
2022-01-23 10:48:52	ga_ls9c_ard_3-2-1_105073_2022-01-23_final.stac-item
2022-01-24 09:58:26	ga_ls9c_ard_3-2-1_096086_2022-01-24_final.stac-item
2022-03-02 11:53:13	ga_ls9c_ard_3-2-1_115080_2022-03-02_final.stac-item
2022-05-04 09:32:22	ga_ls9c_ard_3-2-1_092084_2022-05-04_final.stac-item
2022-06-11 10:27:38	ga_ls9c_ard_3-2-1_102068_2022-06-11_final.stac-item
2022-06-22 10:08:56	ga_ls9c_ard_3-2-1_099067_2022-06-22_final.stac-item
2022-06-22 10:09:44	ga_ls9c_ard_3-2-1_099069_2022-06-22_final.stac-item
2022-06-27 10:29:09	ga_ls9c_ard_3-2-1_102071_2022-06-27_final.stac-item
2022-07-26 09:57:33	ga_ls9c_ard_3-2-1_097069_2022-07-26_final.stac-item
2022-07-31 10:18:57	ga_ls9c_ard_3-2-1_100076_2022-07-31_final.stac-item
2022-08-08 11:05:41	ga_ls9c_ard_3-2-1_108069_2022-08-08_final.stac-item
2022-08-08 11:08:05	ga_ls9c_ard_3-2-1_108075_2022-08-08_final.stac-item
2022-08-09 10:10:29	ga_ls9c_ard_3-2-1_099070_2022-08-09_final.stac-item
2022-08-09 10:10:53	ga_ls9c_ard_3-2-1_099071_2022-08-09_final.stac-item
2022-08-13 11:24:40	ga_ls9c_ard_3-2-1_111070_2022-08-13_final.stac-item
2022-08-15 09:38:14	ga_ls9c_ard_3-2-1_093082_2022-08-15_final.stac-item
2022-08-19 09:10:44	ga_ls9c_ard_3-2-1_089075_2022-08-18_final.stac-item
2022-09-09 09:33:16	ga_ls9c_ard_3-2-1_092085_2022-09-09_final.stac-item
2022-09-10 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-09-10_final.stac-item
2022-09-16 09:39:56	ga_ls9c_ard_3-2-1_093086_2022-09-16_final.stac-item
2022-09-16 09:40:44	ga_ls9c_ard_3-2-1_093088_2022-09-16_final.stac-item
2022-09-21 11:32:12	ga_ls9c_ard_3-2-1_112073_2022-09-21_final.stac-item
2022-10-03 10:17:40	ga_ls9c_ard_3-2-1_100072_2022-10-03_final.stac-item
2022-10-06 10:48:09	ga_ls9c_ard_3-2-1_105071_2022-10-06_final.stac-item
2022-10-12 11:53:37	ga_ls9c_ard_3-2-1_115080_2022-10-12_final.stac-item
2022-10-14 10:04:23	ga_ls9c_ard_3-2-1_097085_2022-10-14_final.stac-item
2022-10-14 11:42:28	ga_ls9c_ard_3-2-1_113083_2022-10-14_final.stac-item
2022-11-12 11:08:01	ga_ls9c_ard_3-2-1_108074_2022-11-12_final.stac-item
2022-11-12 11:08:25	ga_ls9c_ard_3-2-1_108075_2022-11-12_final.stac-item
2022-11-20 10:17:46	ga_ls9c_ard_3-2-1_100072_2022-11-20_final.stac-item
2022-12-05 09:34:04	ga_ls9c_ard_3-2-1_093071_2022-12-05_final.stac-item
2022-12-14 11:08:48	ga_ls9c_ard_3-2-1_108076_2022-12-14_final.stac-item
2022-12-23 09:26:28	ga_ls9c_ard_3-2-1_091083_2022-12-22_final.stac-item
2022-12-25 10:47:01	ga_ls9c_ard_3-2-1_105068_2022-12-25_final.stac-item
2022-12-29 10:28:18	ga_ls9c_ard_3-2-1_101083_2022-12-29_final.stac-item
2023-01-01 09:18:21	ga_ls9c_ard_3-2-1_090078_2022-12-31_final.stac-item
2023-01-27 11:32:40	ga_ls9c_ard_3-2-1_112074_2023-01-27_final.stac-item
2023-02-01 10:13:59	ga_ls9c_ard_3-2-1_099078_2023-02-01_final.stac-item
2023-02-02 10:55:40	ga_ls9c_ard_3-2-1_106074_2023-02-02_final.stac-item
2023-02-07 09:35:45	ga_ls9c_ard_3-2-1_093075_2023-02-07_final.stac-item
2023-02-09 09:26:11	ga_ls9c_ard_3-2-1_091082_2023-02-08_final.stac-item
2023-03-01 10:34:55	ga_ls9c_ard_3-2-1_103069_2023-03-01_final.stac-item
2023-03-15 09:15:52	ga_ls9c_ard_3-2-1_089088_2023-03-14_final.stac-item
2023-03-18 09:41:10	ga_ls9c_ard_3-2-1_094074_2023-03-18_final.stac-item
2023-03-28 10:19:41	ga_ls9c_ard_3-2-1_100078_2023-03-28_final.stac-item
2023-04-07 10:55:31	ga_ls9c_ard_3-2-1_106075_2023-04-07_final.stac-item
2023-04-11 10:33:09	ga_ls9c_ard_3-2-1_102081_2023-04-11_final.stac-item
2023-04-20 10:27:44	ga_ls9c_ard_3-2-1_101083_2023-04-20_final.stac-item
2023-04-29 10:21:27	ga_ls9c_ard_3-2-1_100083_2023-04-29_final.stac-item
2023-05-10 10:02:48	ga_ls9c_ard_3-2-1_097083_2023-05-10_final.stac-item
2023-05-17 10:09:19	ga_ls9c_ard_3-2-1_098084_2023-05-17_final.stac-item
2023-07-28 10:55:37	ga_ls9c_ard_3-2-1_106076_2023-07-28_final.stac-item
2023-07-31 09:46:05	ga_ls9c_ard_3-2-1_095072_2023-07-31_final.stac-item
2023-07-31 11:25:46	ga_ls9c_ard_3-2-1_111074_2023-07-31_final.stac-item
2023-08-02 11:13:26	ga_ls9c_ard_3-2-1_109074_2023-08-02_final.stac-item
2023-08-03 10:19:25	ga_ls9c_ard_3-2-1_100078_2023-08-03_final.stac-item
2023-08-05 10:03:29	ga_ls9c_ard_3-2-1_098069_2023-08-05_final.stac-item
2023-08-13 09:21:16	ga_ls9c_ard_3-2-1_090087_2023-08-12_final.stac-item
2023-08-21 10:02:46	ga_ls9c_ard_3-2-1_098067_2023-08-21_final.stac-item
2023-09-03 09:34:24	ga_ls9c_ard_3-2-1_093073_2023-09-03_final.stac-item
2023-09-03 09:35:12	ga_ls9c_ard_3-2-1_093075_2023-09-03_final.stac-item
2023-09-14 09:17:10	ga_ls9c_ard_3-2-1_090076_2023-09-13_final.stac-item
2023-10-23 09:23:07	ga_ls9c_ard_3-2-1_091075_2023-10-22_final.stac-item
2023-10-24 10:07:35	ga_ls9c_ard_3-2-1_098078_2023-10-24_final.stac-item
2023-11-01 09:17:15	ga_ls9c_ard_3-2-1_090076_2023-10-31_final.stac-item
2023-11-01 09:17:39	ga_ls9c_ard_3-2-1_090077_2023-10-31_final.stac-item
2023-11-01 10:58:31	ga_ls9c_ard_3-2-1_106082_2023-11-01_final.stac-item
2023-11-06 09:33:48	ga_ls9c_ard_3-2-1_093071_2023-11-06_final.stac-item
2023-11-12 10:34:50	ga_ls9c_ard_3-2-1_103069_2023-11-12_final.stac-item
2023-11-22 09:35:55	ga_ls9c_ard_3-2-1_093076_2023-11-22_final.stac-item
2023-12-18 11:53:32	ga_ls9c_ard_3-2-1_115080_2023-12-18_final.stac-item
2024-01-02 09:34:32	ga_ls9c_ard_3-2-1_092088_2024-01-02_final.stac-item
2024-01-07 11:26:19	ga_ls9c_ard_3-2-1_111074_2024-01-07_final.stac-item
2024-02-05 09:17:01	ga_ls9c_ard_3-2-1_090075_2024-02-04_final.stac-item
2024-02-05 10:55:54	ga_ls9c_ard_3-2-1_106075_2024-02-05_final.stac-item
2024-02-12 09:23:34	ga_ls9c_ard_3-2-1_091076_2024-02-11_final.stac-item
2024-02-19 11:06:07	ga_ls9c_ard_3-2-1_108070_2024-02-19_final.stac-item
2024-02-26 09:35:21	ga_ls9c_ard_3-2-1_093075_2024-02-26_final.stac-item
2024-02-29 10:03:06	ga_ls9c_ard_3-2-1_098067_2024-02-29_final.stac-item
2024-03-08 09:17:41	ga_ls9c_ard_3-2-1_090077_2024-03-07_final.stac-item
2024-03-08 10:58:34	ga_ls9c_ard_3-2-1_106082_2024-03-08_final.stac-item
2024-03-29 09:34:03	ga_ls9c_ard_3-2-1_093072_2024-03-29_final.stac-item
2024-04-07 09:30:39	ga_ls9c_ard_3-2-1_092079_2024-04-07_final.stac-item
2024-04-08 10:09:07	ga_ls9c_ard_3-2-1_099067_2024-04-08_final.stac-item
2024-04-11 09:07:05	ga_ls9c_ard_3-2-1_088082_2024-04-10_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