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
2021-11-02 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-09 10:37:48	ga_ls9c_ard_3-2-1_103076_2021-11-09_final.stac-item
2021-12-04 09:23:41	ga_ls9c_ard_3-2-1_091076_2021-12-03_final.stac-item
2021-12-09 09:40:59	ga_ls9c_ard_3-2-1_094073_2021-12-09_final.stac-item
2021-12-13 10:53:30	ga_ls9c_ard_3-2-1_106069_2021-12-13_final.stac-item
2021-12-26 10:25:46	ga_ls9c_ard_3-2-1_101077_2021-12-26_final.stac-item
2022-01-04 10:19:34	ga_ls9c_ard_3-2-1_100077_2022-01-04_final.stac-item
2022-02-01 09:07:48	ga_ls9c_ard_3-2-1_088083_2022-01-31_final.stac-item
2022-02-02 11:26:45	ga_ls9c_ard_3-2-1_111075_2022-02-02_final.stac-item
2022-02-20 11:14:40	ga_ls9c_ard_3-2-1_109076_2022-02-20_final.stac-item
2022-02-25 11:32:21	ga_ls9c_ard_3-2-1_112074_2022-02-25_final.stac-item
2022-03-06 11:25:19	ga_ls9c_ard_3-2-1_111072_2022-03-06_final.stac-item
2022-03-20 09:57:10	ga_ls9c_ard_3-2-1_097068_2022-03-20_final.stac-item
2022-04-03 10:09:04	ga_ls9c_ard_3-2-1_099067_2022-04-03_final.stac-item
2022-04-12 10:02:50	ga_ls9c_ard_3-2-1_098067_2022-04-12_final.stac-item
2022-04-19 11:51:24	ga_ls9c_ard_3-2-1_115076_2022-04-19_final.stac-item
2022-05-04 09:32:22	ga_ls9c_ard_3-2-1_092084_2022-05-04_final.stac-item
2022-05-11 11:16:34	ga_ls9c_ard_3-2-1_109082_2022-05-11_final.stac-item
2022-05-11 11:17:22	ga_ls9c_ard_3-2-1_109084_2022-05-11_final.stac-item
2022-05-13 09:21:18	ga_ls9c_ard_3-2-1_091072_2022-05-12_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 11:25:36	ga_ls9c_ard_3-2-1_111074_2022-05-25_final.stac-item
2022-06-01 09:57:42	ga_ls9c_ard_3-2-1_096086_2022-06-01_final.stac-item
2022-06-06 10:15:27	ga_ls9c_ard_3-2-1_099084_2022-06-06_final.stac-item
2022-06-17 11:34:42	ga_ls9c_ard_3-2-1_112081_2022-06-17_final.stac-item
2022-06-19 09:44:18	ga_ls9c_ard_3-2-1_094083_2022-06-19_final.stac-item
2022-07-02 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-07-02_final.stac-item
2022-07-04 10:39:18	ga_ls9c_ard_3-2-1_103081_2022-07-04_final.stac-item
2022-07-17 10:03:35	ga_ls9c_ard_3-2-1_098069_2022-07-17_final.stac-item
2022-07-19 09:58:03	ga_ls9c_ard_3-2-1_096086_2022-07-19_final.stac-item
2022-07-19 11:32:08	ga_ls9c_ard_3-2-1_112074_2022-07-19_final.stac-item
2022-07-22 10:25:24	ga_ls9c_ard_3-2-1_101077_2022-07-22_final.stac-item
2022-07-25 10:52:46	ga_ls9c_ard_3-2-1_106068_2022-07-25_final.stac-item
2022-07-28 11:26:06	ga_ls9c_ard_3-2-1_111074_2022-07-28_final.stac-item
2022-08-10 10:52:57	ga_ls9c_ard_3-2-1_106068_2022-08-10_final.stac-item
2022-08-17 09:27:29	ga_ls9c_ard_3-2-1_091086_2022-08-16_final.stac-item
2022-09-09 09:29:17	ga_ls9c_ard_3-2-1_092075_2022-09-08_final.stac-item
2022-09-10 11:51:26	ga_ls9c_ard_3-2-1_115075_2022-09-10_final.stac-item
2022-09-11 09:21:20	ga_ls9c_ard_3-2-1_090086_2022-09-10_final.stac-item
2022-09-11 10:53:02	ga_ls9c_ard_3-2-1_106068_2022-09-11_final.stac-item
2022-10-09 09:45:23	ga_ls9c_ard_3-2-1_094084_2022-10-09_final.stac-item
2022-10-16 11:25:20	ga_ls9c_ard_3-2-1_111071_2022-10-16_final.stac-item
2022-10-22 10:47:04	ga_ls9c_ard_3-2-1_105068_2022-10-22_final.stac-item
2022-10-25 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-10-25_final.stac-item
2022-10-26 10:28:20	ga_ls9c_ard_3-2-1_101083_2022-10-26_final.stac-item
2022-11-02 10:33:40	ga_ls9c_ard_3-2-1_102081_2022-11-02_final.stac-item
2022-11-05 09:22:06	ga_ls9c_ard_3-2-1_091072_2022-11-04_final.stac-item
2022-11-05 11:00:35	ga_ls9c_ard_3-2-1_107071_2022-11-05_final.stac-item
2022-11-09 10:34:42	ga_ls9c_ard_3-2-1_103068_2022-11-09_final.stac-item
2022-11-19 11:14:12	ga_ls9c_ard_3-2-1_109074_2022-11-19_final.stac-item
2022-11-28 09:29:53	ga_ls9c_ard_3-2-1_092076_2022-11-27_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-12-05 11:14:09	ga_ls9c_ard_3-2-1_109074_2022-12-05_final.stac-item
2022-12-15 10:09:59	ga_ls9c_ard_3-2-1_099068_2022-12-15_final.stac-item
2022-12-15 10:13:34	ga_ls9c_ard_3-2-1_099077_2022-12-15_final.stac-item
2022-12-16 10:53:38	ga_ls9c_ard_3-2-1_106069_2022-12-16_final.stac-item
2022-12-19 11:24:07	ga_ls9c_ard_3-2-1_111068_2022-12-19_final.stac-item
2023-01-01 09:21:32	ga_ls9c_ard_3-2-1_090086_2022-12-31_final.stac-item
2023-01-18 09:57:54	ga_ls9c_ard_3-2-1_097069_2023-01-18_final.stac-item
2023-01-18 11:39:11	ga_ls9c_ard_3-2-1_113075_2023-01-18_final.stac-item
2023-01-22 09:35:33	ga_ls9c_ard_3-2-1_093075_2023-01-22_final.stac-item
2023-01-26 10:47:48	ga_ls9c_ard_3-2-1_105070_2023-01-26_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-23 11:14:48	ga_ls9c_ard_3-2-1_109076_2023-02-23_final.stac-item
2023-02-27 10:50:04	ga_ls9c_ard_3-2-1_105076_2023-02-27_final.stac-item
2023-03-05 10:13:44	ga_ls9c_ard_3-2-1_099078_2023-03-05_final.stac-item
2023-03-12 10:19:51	ga_ls9c_ard_3-2-1_100078_2023-03-12_final.stac-item
2023-03-20 11:07:40	ga_ls9c_ard_3-2-1_108074_2023-03-20_final.stac-item
2023-03-22 10:54:05	ga_ls9c_ard_3-2-1_106071_2023-03-22_final.stac-item
2023-04-07 10:58:19	ga_ls9c_ard_3-2-1_106082_2023-04-07_final.stac-item
2023-04-08 09:58:18	ga_ls9c_ard_3-2-1_097071_2023-04-08_final.stac-item
2023-04-14 09:22:44	ga_ls9c_ard_3-2-1_091075_2023-04-13_final.stac-item
2023-04-17 09:52:02	ga_ls9c_ard_3-2-1_096071_2023-04-17_final.stac-item
2023-04-18 10:34:06	ga_ls9c_ard_3-2-1_103068_2023-04-18_final.stac-item
2023-04-21 11:07:23	ga_ls9c_ard_3-2-1_108074_2023-04-21_final.stac-item
2023-04-22 10:10:58	ga_ls9c_ard_3-2-1_099072_2023-04-22_final.stac-item
2023-04-23 10:55:25	ga_ls9c_ard_3-2-1_106075_2023-04-23_final.stac-item
2023-04-29 10:19:27	ga_ls9c_ard_3-2-1_100078_2023-04-29_final.stac-item
2023-05-24 10:10:12	ga_ls9c_ard_3-2-1_099071_2023-05-24_final.stac-item
2023-05-28 09:45:53	ga_ls9c_ard_3-2-1_095072_2023-05-28_final.stac-item
2023-06-10 09:20:29	ga_ls9c_ard_3-2-1_090086_2023-06-09_final.stac-item
2023-07-11 10:09:07	ga_ls9c_ard_3-2-1_099068_2023-07-11_final.stac-item
2023-09-10 11:23:57	ga_ls9c_ard_3-2-1_110084_2023-09-10_final.stac-item
2023-09-12 09:29:07	ga_ls9c_ard_3-2-1_092075_2023-09-11_final.stac-item
2023-09-26 11:23:31	ga_ls9c_ard_3-2-1_110083_2023-09-26_final.stac-item
2023-09-29 10:13:56	ga_ls9c_ard_3-2-1_099079_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
2023-10-07 09:23:24	ga_ls9c_ard_3-2-1_091076_2023-10-06_final.stac-item
2023-10-07 09:26:36	ga_ls9c_ard_3-2-1_091084_2023-10-06_final.stac-item
2023-10-23 11:05:12	ga_ls9c_ard_3-2-1_107083_2023-10-23_final.stac-item
2023-11-06 11:11:53	ga_ls9c_ard_3-2-1_109069_2023-11-06_final.stac-item
2023-11-10 09:11:30	ga_ls9c_ard_3-2-1_089077_2023-11-09_final.stac-item
2023-11-23 10:17:35	ga_ls9c_ard_3-2-1_100072_2023-11-23_final.stac-item
2023-12-01 09:32:09	ga_ls9c_ard_3-2-1_092082_2023-12-01_final.stac-item
2023-12-01 09:34:57	ga_ls9c_ard_3-2-1_092089_2023-12-01_final.stac-item
2023-12-09 10:17:32	ga_ls9c_ard_3-2-1_100072_2023-12-09_final.stac-item
2023-12-29 09:58:30	ga_ls9c_ard_3-2-1_096086_2023-12-29_final.stac-item
2024-01-06 10:40:39	ga_ls9c_ard_3-2-1_104068_2024-01-06_final.stac-item
2024-01-09 09:33:54	ga_ls9c_ard_3-2-1_093071_2024-01-09_final.stac-item
2024-01-26 10:18:44	ga_ls9c_ard_3-2-1_100075_2024-01-26_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