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
2021-11-23 10:01:38	ga_ls9c_ard_3-2-1_098067_2021-11-23_final.stac-item
2021-12-04 09:24:05	ga_ls9c_ard_3-2-1_091077_2021-12-03_final.stac-item
2021-12-11 09:29:00	ga_ls9c_ard_3-2-1_092074_2021-12-10_final.stac-item
2021-12-30 10:02:15	ga_ls9c_ard_3-2-1_097080_2021-12-30_final.stac-item
2022-02-02 11:29:33	ga_ls9c_ard_3-2-1_111082_2022-02-02_final.stac-item
2022-02-15 10:54:35	ga_ls9c_ard_3-2-1_106072_2022-02-15_final.stac-item
2022-02-20 09:33:48	ga_ls9c_ard_3-2-1_093071_2022-02-20_final.stac-item
2022-03-04 11:37:40	ga_ls9c_ard_3-2-1_113072_2022-03-04_final.stac-item
2022-03-09 10:20:08	ga_ls9c_ard_3-2-1_100079_2022-03-09_final.stac-item
2022-03-20 11:40:50	ga_ls9c_ard_3-2-1_113080_2022-03-20_final.stac-item
2022-04-16 11:18:33	ga_ls9c_ard_3-2-1_110071_2022-04-16_final.stac-item
2022-04-23 09:50:33	ga_ls9c_ard_3-2-1_095083_2022-04-23_final.stac-item
2022-04-23 09:50:57	ga_ls9c_ard_3-2-1_095084_2022-04-23_final.stac-item
2022-04-26 10:17:04	ga_ls9c_ard_3-2-1_100072_2022-04-26_final.stac-item
2022-04-30 11:36:00	ga_ls9c_ard_3-2-1_112084_2022-04-30_final.stac-item
2022-05-02 09:43:57	ga_ls9c_ard_3-2-1_094082_2022-05-02_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-18 11:17:51	ga_ls9c_ard_3-2-1_110070_2022-05-18_final.stac-item
2022-05-25 11:29:35	ga_ls9c_ard_3-2-1_111084_2022-05-25_final.stac-item
2022-05-27 11:17:13	ga_ls9c_ard_3-2-1_109084_2022-05-27_final.stac-item
2022-08-10 10:56:32	ga_ls9c_ard_3-2-1_106077_2022-08-10_final.stac-item
2022-08-20 11:35:17	ga_ls9c_ard_3-2-1_112081_2022-08-20_final.stac-item
2022-08-27 10:03:47	ga_ls9c_ard_3-2-1_097084_2022-08-27_final.stac-item
2022-08-27 11:37:53	ga_ls9c_ard_3-2-1_113072_2022-08-27_final.stac-item
2022-09-03 10:04:47	ga_ls9c_ard_3-2-1_098071_2022-09-03_final.stac-item
2022-09-04 10:47:14	ga_ls9c_ard_3-2-1_105069_2022-09-04_final.stac-item
2022-09-11 10:53:50	ga_ls9c_ard_3-2-1_106070_2022-09-11_final.stac-item
2022-09-16 09:37:08	ga_ls9c_ard_3-2-1_093079_2022-09-16_final.stac-item
2022-09-18 09:23:36	ga_ls9c_ard_3-2-1_091076_2022-09-17_final.stac-item
2022-09-26 10:14:40	ga_ls9c_ard_3-2-1_099080_2022-09-26_final.stac-item
2022-10-02 09:39:59	ga_ls9c_ard_3-2-1_093086_2022-10-02_final.stac-item
2022-10-02 09:40:23	ga_ls9c_ard_3-2-1_093087_2022-10-02_final.stac-item
2022-10-09 09:44:35	ga_ls9c_ard_3-2-1_094082_2022-10-09_final.stac-item
2022-10-18 09:39:41	ga_ls9c_ard_3-2-1_093085_2022-10-18_final.stac-item
2022-11-10 11:21:10	ga_ls9c_ard_3-2-1_110076_2022-11-10_final.stac-item
2022-11-10 11:24:45	ga_ls9c_ard_3-2-1_110085_2022-11-10_final.stac-item
2022-11-15 09:59:14	ga_ls9c_ard_3-2-1_097072_2022-11-15_final.stac-item
2022-11-18 10:28:33	ga_ls9c_ard_3-2-1_102068_2022-11-18_final.stac-item
2022-11-23 10:47:28	ga_ls9c_ard_3-2-1_105069_2022-11-23_final.stac-item
2022-11-26 09:45:27	ga_ls9c_ard_3-2-1_094084_2022-11-26_final.stac-item
2023-01-01 09:19:33	ga_ls9c_ard_3-2-1_090081_2022-12-31_final.stac-item
2023-01-26 09:12:06	ga_ls9c_ard_3-2-1_089078_2023-01-25_final.stac-item
2023-02-03 10:03:14	ga_ls9c_ard_3-2-1_097082_2023-02-03_final.stac-item
2023-02-07 09:37:21	ga_ls9c_ard_3-2-1_093079_2023-02-07_final.stac-item
2023-02-07 11:12:14	ga_ls9c_ard_3-2-1_109069_2023-02-07_final.stac-item
2023-02-09 09:28:11	ga_ls9c_ard_3-2-1_091087_2023-02-08_final.stac-item
2023-02-12 09:52:41	ga_ls9c_ard_3-2-1_096071_2023-02-12_final.stac-item
2023-02-14 09:44:41	ga_ls9c_ard_3-2-1_094082_2023-02-14_final.stac-item
2023-02-25 09:23:33	ga_ls9c_ard_3-2-1_091076_2023-02-24_final.stac-item
2023-03-08 09:07:42	ga_ls9c_ard_3-2-1_088083_2023-03-07_final.stac-item
2023-03-14 11:46:22	ga_ls9c_ard_3-2-1_114078_2023-03-14_final.stac-item
2023-03-18 09:46:21	ga_ls9c_ard_3-2-1_094087_2023-03-18_final.stac-item
2023-03-27 09:35:15	ga_ls9c_ard_3-2-1_093075_2023-03-27_final.stac-item
2023-04-14 09:25:08	ga_ls9c_ard_3-2-1_091081_2023-04-13_final.stac-item
2023-04-21 11:10:59	ga_ls9c_ard_3-2-1_108083_2023-04-21_final.stac-item
2023-05-12 11:24:56	ga_ls9c_ard_3-2-1_111072_2023-05-12_final.stac-item
2023-05-14 09:37:39	ga_ls9c_ard_3-2-1_093082_2023-05-14_final.stac-item
2023-05-14 11:16:56	ga_ls9c_ard_3-2-1_109083_2023-05-14_final.stac-item
2023-05-19 11:35:49	ga_ls9c_ard_3-2-1_112084_2023-05-19_final.stac-item
2023-05-22 10:22:36	ga_ls9c_ard_3-2-1_101071_2023-05-22_final.stac-item
2023-05-31 10:19:58	ga_ls9c_ard_3-2-1_100080_2023-05-31_final.stac-item
2023-06-13 11:24:15	ga_ls9c_ard_3-2-1_111071_2023-06-13_final.stac-item
2023-06-24 09:32:46	ga_ls9c_ard_3-2-1_092086_2023-06-24_final.stac-item
2023-06-26 10:53:19	ga_ls9c_ard_3-2-1_106071_2023-06-26_final.stac-item
2023-06-29 11:28:42	ga_ls9c_ard_3-2-1_111082_2023-06-29_final.stac-item
2023-07-14 09:07:08	ga_ls9c_ard_3-2-1_088083_2023-07-13_final.stac-item
2023-07-17 11:17:19	ga_ls9c_ard_3-2-1_109084_2023-07-17_final.stac-item
2023-07-19 11:03:22	ga_ls9c_ard_3-2-1_107080_2023-07-19_final.stac-item
2023-07-21 09:14:07	ga_ls9c_ard_3-2-1_089085_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
2023-07-29 11:38:06	ga_ls9c_ard_3-2-1_113074_2023-07-29_final.stac-item
2023-08-06 09:15:51	ga_ls9c_ard_3-2-1_089089_2023-08-05_final.stac-item
2023-08-14 09:58:08	ga_ls9c_ard_3-2-1_097071_2023-08-14_final.stac-item
2023-09-01 09:50:20	ga_ls9c_ard_3-2-1_095082_2023-09-01_final.stac-item
2023-09-17 11:29:46	ga_ls9c_ard_3-2-1_111083_2023-09-17_final.stac-item
2023-09-22 10:07:00	ga_ls9c_ard_3-2-1_098077_2023-09-22_final.stac-item
2023-09-23 10:47:04	ga_ls9c_ard_3-2-1_105069_2023-09-23_final.stac-item
2023-09-25 10:36:17	ga_ls9c_ard_3-2-1_103073_2023-09-25_final.stac-item
2023-10-03 11:23:47	ga_ls9c_ard_3-2-1_111068_2023-10-03_final.stac-item
2023-10-03 11:24:34	ga_ls9c_ard_3-2-1_111070_2023-10-03_final.stac-item
2023-10-09 10:47:57	ga_ls9c_ard_3-2-1_105071_2023-10-09_final.stac-item
2023-10-16 09:20:56	ga_ls9c_ard_3-2-1_090085_2023-10-15_final.stac-item
2023-10-17 10:01:24	ga_ls9c_ard_3-2-1_097078_2023-10-17_final.stac-item
2023-10-18 10:43:04	ga_ls9c_ard_3-2-1_104074_2023-10-18_final.stac-item
2023-11-10 09:15:05	ga_ls9c_ard_3-2-1_089086_2023-11-09_final.stac-item
2023-11-14 10:28:03	ga_ls9c_ard_3-2-1_101083_2023-11-14_final.stac-item
2023-11-16 11:51:47	ga_ls9c_ard_3-2-1_115076_2023-11-16_final.stac-item
2023-11-17 10:55:22	ga_ls9c_ard_3-2-1_106074_2023-11-17_final.stac-item
2023-11-20 09:47:27	ga_ls9c_ard_3-2-1_095074_2023-11-20_final.stac-item
2023-11-22 09:39:54	ga_ls9c_ard_3-2-1_093086_2023-11-22_final.stac-item
2023-11-25 10:07:38	ga_ls9c_ard_3-2-1_098078_2023-11-25_final.stac-item
2023-12-13 09:58:28	ga_ls9c_ard_3-2-1_096086_2023-12-13_final.stac-item
2023-12-15 09:45:43	ga_ls9c_ard_3-2-1_094085_2023-12-15_final.stac-item
2023-12-25 10:21:14	ga_ls9c_ard_3-2-1_100081_2023-12-25_final.stac-item
2023-12-27 10:05:17	ga_ls9c_ard_3-2-1_098072_2023-12-27_final.stac-item
2024-01-02 09:35:19	ga_ls9c_ard_3-2-1_092090_2024-01-02_final.stac-item
2024-01-10 10:21:33	ga_ls9c_ard_3-2-1_100082_2024-01-10_final.stac-item
2024-01-10 10:22:21	ga_ls9c_ard_3-2-1_100084_2024-01-10_final.stac-item
2024-02-01 11:18:12	ga_ls9c_ard_3-2-1_110069_2024-02-01_final.stac-item
2024-02-01 11:19:24	ga_ls9c_ard_3-2-1_110072_2024-02-01_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