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
2021-11-12 09:19:57	ga_ls9c_ard_3-2-1_091075_2021-11-11_final.stac-item
2021-11-20 09:42:01	ga_ls9c_ard_3-2-1_094071_2021-11-20_final.stac-item
2021-12-06 10:49:48	ga_ls9c_ard_3-2-1_105075_2021-12-06_final.stac-item
2021-12-12 10:10:39	ga_ls9c_ard_3-2-1_099070_2021-12-12_final.stac-item
2021-12-12 10:13:50	ga_ls9c_ard_3-2-1_099078_2021-12-12_final.stac-item
2021-12-22 09:13:36	ga_ls9c_ard_3-2-1_089082_2021-12-21_final.stac-item
2021-12-28 10:16:36	ga_ls9c_ard_3-2-1_099085_2021-12-28_final.stac-item
2022-01-02 10:33:56	ga_ls9c_ard_3-2-1_102082_2022-01-02_final.stac-item
2022-01-14 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-01-13_final.stac-item
2022-01-23 09:11:59	ga_ls9c_ard_3-2-1_089078_2022-01-22_final.stac-item
2022-02-23 11:47:32	ga_ls9c_ard_3-2-1_114081_2022-02-23_final.stac-item
2022-03-08 09:34:28	ga_ls9c_ard_3-2-1_093073_2022-03-08_final.stac-item
2022-03-11 10:02:59	ga_ls9c_ard_3-2-1_098067_2022-03-11_final.stac-item
2022-03-24 11:13:41	ga_ls9c_ard_3-2-1_109074_2022-03-24_final.stac-item
2022-04-27 09:24:14	ga_ls9c_ard_3-2-1_091079_2022-04-26_final.stac-item
2022-05-10 10:32:55	ga_ls9c_ard_3-2-1_102081_2022-05-10_final.stac-item
2022-05-18 09:39:22	ga_ls9c_ard_3-2-1_094071_2022-05-18_final.stac-item
2022-05-21 10:13:26	ga_ls9c_ard_3-2-1_099079_2022-05-21_final.stac-item
2022-05-22 10:52:18	ga_ls9c_ard_3-2-1_106068_2022-05-22_final.stac-item
2022-06-05 11:06:41	ga_ls9c_ard_3-2-1_108073_2022-06-05_final.stac-item
2022-06-05 11:09:52	ga_ls9c_ard_3-2-1_108081_2022-06-05_final.stac-item
2022-06-08 11:39:11	ga_ls9c_ard_3-2-1_113077_2022-06-08_final.stac-item
2022-06-25 10:42:19	ga_ls9c_ard_3-2-1_104073_2022-06-25_final.stac-item
2022-06-30 09:23:09	ga_ls9c_ard_3-2-1_091076_2022-06-29_final.stac-item
2022-07-08 10:15:21	ga_ls9c_ard_3-2-1_099083_2022-07-08_final.stac-item
2022-07-08 11:53:03	ga_ls9c_ard_3-2-1_115080_2022-07-08_final.stac-item
2022-07-10 09:57:00	ga_ls9c_ard_3-2-1_097068_2022-07-10_final.stac-item
2022-07-12 09:46:37	ga_ls9c_ard_3-2-1_095073_2022-07-12_final.stac-item
2022-07-13 10:33:04	ga_ls9c_ard_3-2-1_102081_2022-07-13_final.stac-item
2022-08-05 10:39:33	ga_ls9c_ard_3-2-1_103081_2022-08-05_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-08-24 09:32:05	ga_ls9c_ard_3-2-1_092082_2022-08-24_final.stac-item
2022-08-25 11:53:26	ga_ls9c_ard_3-2-1_115080_2022-08-25_final.stac-item
2022-08-31 09:35:05	ga_ls9c_ard_3-2-1_093074_2022-08-31_final.stac-item
2022-09-05 11:32:06	ga_ls9c_ard_3-2-1_112073_2022-09-05_final.stac-item
2022-09-09 11:10:33	ga_ls9c_ard_3-2-1_108081_2022-09-09_final.stac-item
2022-09-11 10:55:50	ga_ls9c_ard_3-2-1_106075_2022-09-11_final.stac-item
2022-09-12 10:03:49	ga_ls9c_ard_3-2-1_097084_2022-09-12_final.stac-item
2022-09-26 10:16:16	ga_ls9c_ard_3-2-1_099084_2022-09-26_final.stac-item
2022-09-30 11:26:51	ga_ls9c_ard_3-2-1_111075_2022-09-30_final.stac-item
2022-10-04 11:03:43	ga_ls9c_ard_3-2-1_107079_2022-10-04_final.stac-item
2022-10-11 11:06:45	ga_ls9c_ard_3-2-1_108071_2022-10-11_final.stac-item
2022-12-10 11:32:19	ga_ls9c_ard_3-2-1_112073_2022-12-10_final.stac-item
2022-12-17 11:42:05	ga_ls9c_ard_3-2-1_113082_2022-12-17_final.stac-item
2023-01-13 09:40:14	ga_ls9c_ard_3-2-1_094071_2023-01-13_final.stac-item
2023-01-25 10:05:19	ga_ls9c_ard_3-2-1_098072_2023-01-25_final.stac-item
2023-01-26 10:52:59	ga_ls9c_ard_3-2-1_105083_2023-01-26_final.stac-item
2023-02-07 09:36:57	ga_ls9c_ard_3-2-1_093078_2023-02-07_final.stac-item
2023-02-08 10:18:37	ga_ls9c_ard_3-2-1_100074_2023-02-08_final.stac-item
2023-02-10 10:05:51	ga_ls9c_ard_3-2-1_098073_2023-02-10_final.stac-item
2023-02-12 09:53:29	ga_ls9c_ard_3-2-1_096073_2023-02-12_final.stac-item
2023-02-20 10:40:47	ga_ls9c_ard_3-2-1_104068_2023-02-20_final.stac-item
2023-03-15 10:46:46	ga_ls9c_ard_3-2-1_105068_2023-03-15_final.stac-item
2023-03-15 10:49:57	ga_ls9c_ard_3-2-1_105076_2023-03-15_final.stac-item
2023-04-06 10:09:05	ga_ls9c_ard_3-2-1_099067_2023-04-06_final.stac-item
2023-04-08 09:58:42	ga_ls9c_ard_3-2-1_097072_2023-04-08_final.stac-item
2023-04-12 11:11:37	ga_ls9c_ard_3-2-1_109069_2023-04-12_final.stac-item
2023-04-12 11:12:01	ga_ls9c_ard_3-2-1_109070_2023-04-12_final.stac-item
2023-05-24 10:08:13	ga_ls9c_ard_3-2-1_099066_2023-05-24_final.stac-item
2023-05-24 10:09:24	ga_ls9c_ard_3-2-1_099069_2023-05-24_final.stac-item
2023-05-26 11:41:55	ga_ls9c_ard_3-2-1_113084_2023-05-26_final.stac-item
2023-06-02 11:46:53	ga_ls9c_ard_3-2-1_114081_2023-06-02_final.stac-item
2023-06-09 10:08:32	ga_ls9c_ard_3-2-1_099067_2023-06-09_final.stac-item
2023-06-09 11:52:37	ga_ls9c_ard_3-2-1_115080_2023-06-09_final.stac-item
2023-06-24 11:05:16	ga_ls9c_ard_3-2-1_108070_2023-06-24_final.stac-item
2023-06-25 11:51:19	ga_ls9c_ard_3-2-1_115077_2023-06-25_final.stac-item
2023-07-12 10:55:10	ga_ls9c_ard_3-2-1_106075_2023-07-12_final.stac-item
2023-07-24 11:23:29	ga_ls9c_ard_3-2-1_110084_2023-07-24_final.stac-item
2023-08-06 09:14:40	ga_ls9c_ard_3-2-1_089086_2023-08-05_final.stac-item
2023-08-15 09:06:54	ga_ls9c_ard_3-2-1_088082_2023-08-14_final.stac-item
2023-08-22 09:11:09	ga_ls9c_ard_3-2-1_089077_2023-08-21_final.stac-item
2023-08-26 10:25:22	ga_ls9c_ard_3-2-1_101077_2023-08-26_final.stac-item
2023-08-28 11:53:07	ga_ls9c_ard_3-2-1_115080_2023-08-28_final.stac-item
2023-09-07 10:49:01	ga_ls9c_ard_3-2-1_105074_2023-09-07_final.stac-item
2023-10-16 10:56:13	ga_ls9c_ard_3-2-1_106076_2023-10-16_final.stac-item
2023-11-03 09:06:51	ga_ls9c_ard_3-2-1_088081_2023-11-02_final.stac-item
2023-11-11 11:32:27	ga_ls9c_ard_3-2-1_112074_2023-11-11_final.stac-item
2023-11-12 10:39:13	ga_ls9c_ard_3-2-1_103080_2023-11-12_final.stac-item
2023-11-18 09:56:59	ga_ls9c_ard_3-2-1_097067_2023-11-18_final.stac-item
2023-11-22 09:34:43	ga_ls9c_ard_3-2-1_093073_2023-11-22_final.stac-item
2023-12-02 10:10:37	ga_ls9c_ard_3-2-1_099070_2023-12-02_final.stac-item
2023-12-08 09:34:16	ga_ls9c_ard_3-2-1_093072_2023-12-08_final.stac-item
2023-12-10 11:05:36	ga_ls9c_ard_3-2-1_107084_2023-12-10_final.stac-item
2023-12-19 09:22:37	ga_ls9c_ard_3-2-1_090089_2023-12-18_final.stac-item
2023-12-20 11:37:59	ga_ls9c_ard_3-2-1_113072_2023-12-20_final.stac-item
2023-12-22 11:24:50	ga_ls9c_ard_3-2-1_111070_2023-12-22_final.stac-item
2024-01-03 11:53:28	ga_ls9c_ard_3-2-1_115080_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
2024-01-10 10:19:10	ga_ls9c_ard_3-2-1_100076_2024-01-10_final.stac-item
2024-01-11 09:26:44	ga_ls9c_ard_3-2-1_091084_2024-01-10_final.stac-item
2024-01-13 09:12:48	ga_ls9c_ard_3-2-1_089080_2024-01-12_final.stac-item
2024-01-26 10:19:08	ga_ls9c_ard_3-2-1_100076_2024-01-26_final.stac-item
2024-01-27 09:23:55	ga_ls9c_ard_3-2-1_091077_2024-01-26_final.stac-item
2024-02-05 09:17:25	ga_ls9c_ard_3-2-1_090076_2024-02-04_final.stac-item
2024-02-18 10:27:40	ga_ls9c_ard_3-2-1_101082_2024-02-18_final.stac-item
2024-02-26 09:34:33	ga_ls9c_ard_3-2-1_093073_2024-02-26_final.stac-item
2024-02-28 09:25:25	ga_ls9c_ard_3-2-1_091081_2024-02-27_final.stac-item
2024-02-28 11:02:18	ga_ls9c_ard_3-2-1_107076_2024-02-28_final.stac-item
2024-03-12 10:29:26	ga_ls9c_ard_3-2-1_102071_2024-03-12_final.stac-item
2024-04-07 11:07:32	ga_ls9c_ard_3-2-1_108074_2024-04-07_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