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
2021-11-05 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final.stac-item
2021-12-06 09:15:18	ga_ls9c_ard_3-2-1_089086_2021-12-05_final.stac-item
2021-12-25 11:21:24	ga_ls9c_ard_3-2-1_110077_2021-12-25_final.stac-item
2021-12-25 11:24:11	ga_ls9c_ard_3-2-1_110084_2021-12-25_final.stac-item
2022-01-03 11:17:12	ga_ls9c_ard_3-2-1_109082_2022-01-03_final.stac-item
2022-02-02 11:29:09	ga_ls9c_ard_3-2-1_111081_2022-02-02_final.stac-item
2022-02-07 10:07:36	ga_ls9c_ard_3-2-1_098078_2022-02-07_final.stac-item
2022-02-09 11:32:07	ga_ls9c_ard_3-2-1_112073_2022-02-09_final.stac-item
2022-02-13 09:28:05	ga_ls9c_ard_3-2-1_092072_2022-02-12_final.stac-item
2022-03-04 10:01:11	ga_ls9c_ard_3-2-1_097078_2022-03-04_final.stac-item
2022-03-27 10:08:05	ga_ls9c_ard_3-2-1_098080_2022-03-27_final.stac-item
2022-03-29 11:31:25	ga_ls9c_ard_3-2-1_112072_2022-03-29_final.stac-item
2022-03-31 11:21:03	ga_ls9c_ard_3-2-1_110077_2022-03-31_final.stac-item
2022-04-02 09:34:36	ga_ls9c_ard_3-2-1_092089_2022-04-02_final.stac-item
2022-04-04 09:20:14	ga_ls9c_ard_3-2-1_090084_2022-04-03_final.stac-item
2022-04-10 10:18:00	ga_ls9c_ard_3-2-1_100074_2022-04-10_final.stac-item
2022-05-11 11:11:23	ga_ls9c_ard_3-2-1_109069_2022-05-11_final.stac-item
2022-05-12 10:18:08	ga_ls9c_ard_3-2-1_100075_2022-05-12_final.stac-item
2022-05-30 10:04:28	ga_ls9c_ard_3-2-1_098072_2022-05-30_final.stac-item
2022-06-07 09:18:14	ga_ls9c_ard_3-2-1_090080_2022-06-06_final.stac-item
2022-06-08 11:37:11	ga_ls9c_ard_3-2-1_113072_2022-06-08_final.stac-item
2022-06-14 09:24:29	ga_ls9c_ard_3-2-1_091080_2022-06-13_final.stac-item
2022-06-24 10:01:49	ga_ls9c_ard_3-2-1_097080_2022-06-24_final.stac-item
2022-06-24 11:38:19	ga_ls9c_ard_3-2-1_113074_2022-06-24_final.stac-item
2022-07-23 09:31:48	ga_ls9c_ard_3-2-1_092082_2022-07-23_final.stac-item
2022-07-27 10:43:13	ga_ls9c_ard_3-2-1_104075_2022-07-27_final.stac-item
2022-07-30 09:36:52	ga_ls9c_ard_3-2-1_093079_2022-07-30_final.stac-item
2022-07-30 11:17:45	ga_ls9c_ard_3-2-1_109084_2022-07-30_final.stac-item
2022-08-02 11:45:06	ga_ls9c_ard_3-2-1_114075_2022-08-02_final.stac-item
2022-08-08 11:07:41	ga_ls9c_ard_3-2-1_108074_2022-08-08_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-13 11:23:52	ga_ls9c_ard_3-2-1_111068_2022-08-13_final.stac-item
2022-09-02 11:02:00	ga_ls9c_ard_3-2-1_107075_2022-09-02_final.stac-item
2022-09-05 11:33:18	ga_ls9c_ard_3-2-1_112076_2022-09-05_final.stac-item
2022-09-12 11:37:54	ga_ls9c_ard_3-2-1_113072_2022-09-12_final.stac-item
2022-09-27 10:56:20	ga_ls9c_ard_3-2-1_106076_2022-09-27_final.stac-item
2022-10-14 10:01:59	ga_ls9c_ard_3-2-1_097079_2022-10-14_final.stac-item
2022-10-20 09:22:08	ga_ls9c_ard_3-2-1_091072_2022-10-19_final.stac-item
2022-10-20 09:27:19	ga_ls9c_ard_3-2-1_091085_2022-10-19_final.stac-item
2022-10-25 09:40:17	ga_ls9c_ard_3-2-1_094071_2022-10-25_final.stac-item
2022-11-03 09:35:15	ga_ls9c_ard_3-2-1_093074_2022-11-03_final.stac-item
2022-11-16 09:08:00	ga_ls9c_ard_3-2-1_088083_2022-11-15_final.stac-item
2022-11-21 09:28:56	ga_ls9c_ard_3-2-1_091089_2022-11-20_final.stac-item
2022-12-19 09:48:26	ga_ls9c_ard_3-2-1_095076_2022-12-19_final.stac-item
2022-12-30 09:33:29	ga_ls9c_ard_3-2-1_092085_2022-12-30_final.stac-item
2023-01-06 09:38:53	ga_ls9c_ard_3-2-1_093083_2023-01-06_final.stac-item
2023-01-06 09:39:17	ga_ls9c_ard_3-2-1_093084_2023-01-06_final.stac-item
2023-01-10 10:46:39	ga_ls9c_ard_3-2-1_105067_2023-01-10_final.stac-item
2023-01-16 10:16:17	ga_ls9c_ard_3-2-1_099084_2023-01-16_final.stac-item
2023-01-24 11:02:07	ga_ls9c_ard_3-2-1_107075_2023-01-24_final.stac-item
2023-02-01 10:12:47	ga_ls9c_ard_3-2-1_099075_2023-02-01_final.stac-item
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final.stac-item
2023-02-11 09:13:25	ga_ls9c_ard_3-2-1_089081_2023-02-10_final.stac-item
2023-02-19 10:00:45	ga_ls9c_ard_3-2-1_097076_2023-02-19_final.stac-item
2023-02-23 11:14:48	ga_ls9c_ard_3-2-1_109076_2023-02-23_final.stac-item
2023-02-25 11:04:25	ga_ls9c_ard_3-2-1_107081_2023-02-25_final.stac-item
2023-03-09 09:50:32	ga_ls9c_ard_3-2-1_095082_2023-03-09_final.stac-item
2023-03-21 10:11:38	ga_ls9c_ard_3-2-1_099073_2023-03-21_final.stac-item
2023-04-01 11:34:37	ga_ls9c_ard_3-2-1_112080_2023-04-01_final.stac-item
2023-04-10 11:28:47	ga_ls9c_ard_3-2-1_111081_2023-04-10_final.stac-item
2023-04-24 11:37:29	ga_ls9c_ard_3-2-1_113072_2023-04-24_final.stac-item
2023-05-10 11:40:05	ga_ls9c_ard_3-2-1_113079_2023-05-10_final.stac-item
2023-06-03 09:15:58	ga_ls9c_ard_3-2-1_089090_2023-06-02_final.stac-item
2023-06-04 09:57:14	ga_ls9c_ard_3-2-1_096085_2023-06-04_final.stac-item
2023-06-04 11:33:43	ga_ls9c_ard_3-2-1_112079_2023-06-04_final.stac-item
2023-06-10 10:53:23	ga_ls9c_ard_3-2-1_106071_2023-06-10_final.stac-item
2023-06-17 09:24:36	ga_ls9c_ard_3-2-1_091081_2023-06-16_final.stac-item
2023-06-20 09:57:06	ga_ls9c_ard_3-2-1_096085_2023-06-20_final.stac-item
2023-07-03 11:02:04	ga_ls9c_ard_3-2-1_107077_2023-07-03_final.stac-item
2023-07-20 10:03:21	ga_ls9c_ard_3-2-1_098069_2023-07-20_final.stac-item
2023-07-20 10:07:44	ga_ls9c_ard_3-2-1_098080_2023-07-20_final.stac-item
2023-07-27 11:51:37	ga_ls9c_ard_3-2-1_115077_2023-07-27_final.stac-item
2023-07-27 11:52:25	ga_ls9c_ard_3-2-1_115079_2023-07-27_final.stac-item
2023-08-02 09:33:21	ga_ls9c_ard_3-2-1_093071_2023-08-02_final.stac-item
2023-08-11 09:32:25	ga_ls9c_ard_3-2-1_092084_2023-08-11_final.stac-item
2023-08-13 10:54:57	ga_ls9c_ard_3-2-1_106074_2023-08-13_final.stac-item
2023-08-18 09:34:36	ga_ls9c_ard_3-2-1_093074_2023-08-18_final.stac-item
2023-08-20 09:21:29	ga_ls9c_ard_3-2-1_091072_2023-08-19_final.stac-item
2023-08-20 09:25:04	ga_ls9c_ard_3-2-1_091081_2023-08-19_final.stac-item
2023-08-25 11:19:23	ga_ls9c_ard_3-2-1_110073_2023-08-25_final.stac-item
2023-08-27 09:34:33	ga_ls9c_ard_3-2-1_092089_2023-08-27_final.stac-item
2023-09-03 09:34:00	ga_ls9c_ard_3-2-1_093072_2023-09-03_final.stac-item
2023-09-03 11:16:28	ga_ls9c_ard_3-2-1_109081_2023-09-03_final.stac-item
2023-09-04 10:20:28	ga_ls9c_ard_3-2-1_100080_2023-09-04_final.stac-item
2023-09-19 11:12:12	ga_ls9c_ard_3-2-1_109070_2023-09-19_final.stac-item
2023-09-23 10:48:39	ga_ls9c_ard_3-2-1_105073_2023-09-23_final.stac-item
2023-09-29 10:14:20	ga_ls9c_ard_3-2-1_099080_2023-09-29_final.stac-item
2023-10-05 11:14:38	ga_ls9c_ard_3-2-1_109076_2023-10-05_final.stac-item
2023-10-08 10:03:53	ga_ls9c_ard_3-2-1_098069_2023-10-08_final.stac-item
2023-10-08 11:45:09	ga_ls9c_ard_3-2-1_114075_2023-10-08_final.stac-item
2023-10-16 09:18:08	ga_ls9c_ard_3-2-1_090078_2023-10-15_final.stac-item
2023-11-02 09:58:29	ga_ls9c_ard_3-2-1_097071_2023-11-02_final.stac-item
2023-11-02 10:02:05	ga_ls9c_ard_3-2-1_097080_2023-11-02_final.stac-item
2023-11-08 09:21:51	ga_ls9c_ard_3-2-1_091072_2023-11-07_final.stac-item
2023-11-09 11:46:00	ga_ls9c_ard_3-2-1_114077_2023-11-09_final.stac-item
2023-11-17 09:19:41	ga_ls9c_ard_3-2-1_090082_2023-11-16_final.stac-item
2023-12-01 11:06:15	ga_ls9c_ard_3-2-1_108070_2023-12-01_final.stac-item
2023-12-23 10:28:49	ga_ls9c_ard_3-2-1_102069_2023-12-23_final.stac-item
2024-01-01 10:24:58	ga_ls9c_ard_3-2-1_101075_2024-01-01_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years