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
2021-11-03 09:57:21	ga_ls9c_ard_3-2-1_096081_2021-11-03_final.stac-item
2021-11-16 10:23:06	ga_ls9c_ard_3-2-1_100080_2021-11-16_final.stac-item
2021-11-22 09:29:15	ga_ls9c_ard_3-2-1_091086_2021-11-21_final.stac-item
2021-11-23 10:03:14	ga_ls9c_ard_3-2-1_098071_2021-11-23_final.stac-item
2021-12-11 11:11:52	ga_ls9c_ard_3-2-1_108084_2021-12-11_final.stac-item
2021-12-12 10:14:38	ga_ls9c_ard_3-2-1_099080_2021-12-12_final.stac-item
2022-01-09 10:35:18	ga_ls9c_ard_3-2-1_103070_2022-01-09_final.stac-item
2022-01-10 09:45:16	ga_ls9c_ard_3-2-1_094084_2022-01-10_final.stac-item
2022-01-13 11:51:02	ga_ls9c_ard_3-2-1_115074_2022-01-13_final.stac-item
2022-02-06 09:26:44	ga_ls9c_ard_3-2-1_091084_2022-02-05_final.stac-item
2022-02-11 09:45:15	ga_ls9c_ard_3-2-1_094084_2022-02-11_final.stac-item
2022-02-18 11:29:03	ga_ls9c_ard_3-2-1_111081_2022-02-18_final.stac-item
2022-03-06 09:51:13	ga_ls9c_ard_3-2-1_095084_2022-03-06_final.stac-item
2022-03-07 10:31:41	ga_ls9c_ard_3-2-1_102077_2022-03-07_final.stac-item
2022-03-08 11:16:57	ga_ls9c_ard_3-2-1_109082_2022-03-08_final.stac-item
2022-03-20 10:03:33	ga_ls9c_ard_3-2-1_097084_2022-03-20_final.stac-item
2022-03-22 11:27:40	ga_ls9c_ard_3-2-1_111078_2022-03-22_final.stac-item
2022-04-09 09:40:20	ga_ls9c_ard_3-2-1_093088_2022-04-09_final.stac-item
2022-04-13 10:47:17	ga_ls9c_ard_3-2-1_105070_2022-04-13_final.stac-item
2022-04-29 09:14:39	ga_ls9c_ard_3-2-1_089086_2022-04-28_final.stac-item
2022-05-02 09:43:57	ga_ls9c_ard_3-2-1_094082_2022-05-02_final.stac-item
2022-05-11 11:16:58	ga_ls9c_ard_3-2-1_109083_2022-05-11_final.stac-item
2022-05-18 09:42:58	ga_ls9c_ard_3-2-1_094080_2022-05-18_final.stac-item
2022-05-18 09:45:45	ga_ls9c_ard_3-2-1_094087_2022-05-18_final.stac-item
2022-05-19 10:24:12	ga_ls9c_ard_3-2-1_101075_2022-05-19_final.stac-item
2022-05-23 10:01:04	ga_ls9c_ard_3-2-1_097079_2022-05-23_final.stac-item
2022-05-25 09:49:54	ga_ls9c_ard_3-2-1_095082_2022-05-25_final.stac-item
2022-06-05 11:10:16	ga_ls9c_ard_3-2-1_108082_2022-06-05_final.stac-item
2022-06-12 11:11:18	ga_ls9c_ard_3-2-1_109069_2022-06-12_final.stac-item
2022-06-21 11:10:54	ga_ls9c_ard_3-2-1_108083_2022-06-21_final.stac-item
2022-06-23 09:20:31	ga_ls9c_ard_3-2-1_090085_2022-06-22_final.stac-item
2022-06-24 10:01:25	ga_ls9c_ard_3-2-1_097079_2022-06-24_final.stac-item
2022-07-14 11:14:43	ga_ls9c_ard_3-2-1_109077_2022-07-14_final.stac-item
2022-07-18 09:11:10	ga_ls9c_ard_3-2-1_089077_2022-07-17_final.stac-item
2022-08-13 09:52:34	ga_ls9c_ard_3-2-1_095087_2022-08-13_final.stac-item
2022-09-09 11:06:58	ga_ls9c_ard_3-2-1_108072_2022-09-09_final.stac-item
2022-09-12 10:01:49	ga_ls9c_ard_3-2-1_097079_2022-09-12_final.stac-item
2022-09-15 10:29:33	ga_ls9c_ard_3-2-1_102071_2022-09-15_final.stac-item
2022-09-16 11:13:13	ga_ls9c_ard_3-2-1_109072_2022-09-16_final.stac-item
2022-09-21 09:56:30	ga_ls9c_ard_3-2-1_096081_2022-09-21_final.stac-item
2022-10-04 09:24:02	ga_ls9c_ard_3-2-1_091077_2022-10-03_final.stac-item
2022-10-09 11:21:05	ga_ls9c_ard_3-2-1_110076_2022-10-09_final.stac-item
2022-11-23 10:52:15	ga_ls9c_ard_3-2-1_105081_2022-11-23_final.stac-item
2022-12-03 09:50:48	ga_ls9c_ard_3-2-1_095082_2022-12-03_final.stac-item
2023-01-10 09:11:45	ga_ls9c_ard_3-2-1_089077_2023-01-09_final.stac-item
2023-01-15 09:28:15	ga_ls9c_ard_3-2-1_092072_2023-01-14_final.stac-item
2023-01-15 11:10:19	ga_ls9c_ard_3-2-1_108080_2023-01-15_final.stac-item
2023-01-22 11:15:14	ga_ls9c_ard_3-2-1_109077_2023-01-22_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-02-03 11:41:20	ga_ls9c_ard_3-2-1_113080_2023-02-03_final.stac-item
2023-03-02 09:45:40	ga_ls9c_ard_3-2-1_094085_2023-03-02_final.stac-item
2023-03-02 11:22:09	ga_ls9c_ard_3-2-1_110079_2023-03-02_final.stac-item
2023-03-14 10:03:06	ga_ls9c_ard_3-2-1_098067_2023-03-14_final.stac-item
2023-03-27 09:35:15	ga_ls9c_ard_3-2-1_093075_2023-03-27_final.stac-item
2023-03-31 09:14:28	ga_ls9c_ard_3-2-1_089085_2023-03-30_final.stac-item
2023-03-31 10:50:09	ga_ls9c_ard_3-2-1_105077_2023-03-31_final.stac-item
2023-04-10 09:50:18	ga_ls9c_ard_3-2-1_095082_2023-04-10_final.stac-item
2023-04-30 09:23:25	ga_ls9c_ard_3-2-1_091077_2023-04-29_final.stac-item
2023-05-05 11:18:21	ga_ls9c_ard_3-2-1_110071_2023-05-05_final.stac-item
2023-05-09 10:56:50	ga_ls9c_ard_3-2-1_106079_2023-05-09_final.stac-item
2023-06-08 11:04:58	ga_ls9c_ard_3-2-1_108069_2023-06-08_final.stac-item
2023-06-16 10:21:01	ga_ls9c_ard_3-2-1_100083_2023-06-16_final.stac-item
2023-06-17 11:03:29	ga_ls9c_ard_3-2-1_107081_2023-06-17_final.stac-item
2023-06-26 10:57:42	ga_ls9c_ard_3-2-1_106082_2023-06-26_final.stac-item
2023-07-01 11:16:23	ga_ls9c_ard_3-2-1_109082_2023-07-01_final.stac-item
2023-07-05 09:13:14	ga_ls9c_ard_3-2-1_089083_2023-07-04_final.stac-item
2023-07-10 11:07:07	ga_ls9c_ard_3-2-1_108074_2023-07-10_final.stac-item
2023-07-15 09:50:48	ga_ls9c_ard_3-2-1_095084_2023-07-15_final.stac-item
2023-07-19 09:21:17	ga_ls9c_ard_3-2-1_091072_2023-07-18_final.stac-item
2023-07-19 09:22:53	ga_ls9c_ard_3-2-1_091076_2023-07-18_final.stac-item
2023-07-19 11:03:46	ga_ls9c_ard_3-2-1_107081_2023-07-19_final.stac-item
2023-07-31 09:51:17	ga_ls9c_ard_3-2-1_095085_2023-07-31_final.stac-item
2023-08-04 11:01:54	ga_ls9c_ard_3-2-1_107076_2023-08-04_final.stac-item
2023-08-08 10:39:36	ga_ls9c_ard_3-2-1_103082_2023-08-08_final.stac-item
2023-08-21 10:03:58	ga_ls9c_ard_3-2-1_098070_2023-08-21_final.stac-item
2023-08-22 10:46:27	ga_ls9c_ard_3-2-1_105068_2023-08-22_final.stac-item
2023-09-01 09:47:09	ga_ls9c_ard_3-2-1_095074_2023-09-01_final.stac-item
2023-09-07 10:48:37	ga_ls9c_ard_3-2-1_105073_2023-09-07_final.stac-item
2023-09-29 10:14:20	ga_ls9c_ard_3-2-1_099080_2023-09-29_final.stac-item
2023-10-01 11:40:54	ga_ls9c_ard_3-2-1_113080_2023-10-01_final.stac-item
2023-10-09 09:14:39	ga_ls9c_ard_3-2-1_089085_2023-10-08_final.stac-item
2023-10-13 10:27:17	ga_ls9c_ard_3-2-1_101081_2023-10-13_final.stac-item
2023-10-21 11:13:11	ga_ls9c_ard_3-2-1_109072_2023-10-21_final.stac-item
2023-11-19 10:43:27	ga_ls9c_ard_3-2-1_104075_2023-11-19_final.stac-item
2023-11-22 09:37:06	ga_ls9c_ard_3-2-1_093079_2023-11-22_final.stac-item
2023-11-22 11:13:12	ga_ls9c_ard_3-2-1_109072_2023-11-22_final.stac-item
2023-11-25 10:04:03	ga_ls9c_ard_3-2-1_098069_2023-11-25_final.stac-item
2023-12-03 10:58:40	ga_ls9c_ard_3-2-1_106082_2023-12-03_final.stac-item
2023-12-15 09:43:43	ga_ls9c_ard_3-2-1_094080_2023-12-15_final.stac-item
2023-12-20 09:59:30	ga_ls9c_ard_3-2-1_097073_2023-12-20_final.stac-item
2023-12-29 09:56:54	ga_ls9c_ard_3-2-1_096082_2023-12-29_final.stac-item
2024-01-02 09:33:44	ga_ls9c_ard_3-2-1_092086_2024-01-02_final.stac-item
2024-01-27 09:27:31	ga_ls9c_ard_3-2-1_091086_2024-01-26_final.stac-item
2024-02-15 11:35:18	ga_ls9c_ard_3-2-1_112081_2024-02-15_final.stac-item
2024-02-17 09:46:25	ga_ls9c_ard_3-2-1_094087_2024-02-17_final.stac-item
2024-03-16 11:45:59	ga_ls9c_ard_3-2-1_114077_2024-03-16_final.stac-item
2024-03-17 09:15:04	ga_ls9c_ard_3-2-1_089086_2024-03-16_final.stac-item
2024-03-19 10:37:36	ga_ls9c_ard_3-2-1_103076_2024-03-19_final.stac-item
2024-03-25 11:40:56	ga_ls9c_ard_3-2-1_113080_2024-03-25_final.stac-item
2024-03-25 11:41:20	ga_ls9c_ard_3-2-1_113081_2024-03-25_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