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 09:58:56	ga_ls9c_ard_3-2-1_096085_2021-11-03_final.stac-item
2021-11-09 10:40:11	ga_ls9c_ard_3-2-1_103082_2021-11-09_final.stac-item
2021-11-18 10:05:57	ga_ls9c_ard_3-2-1_097084_2021-11-18_final.stac-item
2021-11-23 10:02:26	ga_ls9c_ard_3-2-1_098069_2021-11-23_final.stac-item
2021-11-24 10:44:46	ga_ls9c_ard_3-2-1_104075_2021-11-24_final.stac-item
2021-11-25 09:44:52	ga_ls9c_ard_3-2-1_095072_2021-11-25_final.stac-item
2021-12-04 09:28:05	ga_ls9c_ard_3-2-1_091087_2021-12-03_final.stac-item
2021-12-05 10:04:09	ga_ls9c_ard_3-2-1_098069_2021-12-05_final.stac-item
2021-12-06 10:48:12	ga_ls9c_ard_3-2-1_105071_2021-12-06_final.stac-item
2021-12-07 11:31:51	ga_ls9c_ard_3-2-1_112072_2021-12-07_final.stac-item
2021-12-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2021-12-08_final.stac-item
2021-12-14 10:03:51	ga_ls9c_ard_3-2-1_097084_2021-12-14_final.stac-item
2021-12-15 10:43:31	ga_ls9c_ard_3-2-1_104075_2021-12-15_final.stac-item
2021-12-17 10:31:32	ga_ls9c_ard_3-2-1_102076_2021-12-17_final.stac-item
2021-12-18 09:39:54	ga_ls9c_ard_3-2-1_093086_2021-12-18_final.stac-item
2021-12-21 11:45:42	ga_ls9c_ard_3-2-1_114076_2021-12-21_final.stac-item
2021-12-22 10:48:06	ga_ls9c_ard_3-2-1_105071_2021-12-22_final.stac-item
2021-12-23 11:31:45	ga_ls9c_ard_3-2-1_112072_2021-12-23_final.stac-item
2021-12-29 10:55:28	ga_ls9c_ard_3-2-1_106074_2021-12-29_final.stac-item
2022-01-03 09:39:55	ga_ls9c_ard_3-2-1_093086_2022-01-03_final.stac-item
2022-01-06 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-06_final.stac-item
2022-01-10 09:40:04	ga_ls9c_ard_3-2-1_094071_2022-01-10_final.stac-item
2022-01-12 09:33:17	ga_ls9c_ard_3-2-1_092085_2022-01-12_final.stac-item
2022-01-13 10:15:45	ga_ls9c_ard_3-2-1_099083_2022-01-13_final.stac-item
2022-01-14 10:55:25	ga_ls9c_ard_3-2-1_106074_2022-01-14_final.stac-item
2022-01-19 09:39:53	ga_ls9c_ard_3-2-1_093086_2022-01-19_final.stac-item
2022-01-22 11:45:41	ga_ls9c_ard_3-2-1_114076_2022-01-22_final.stac-item
2022-01-24 11:31:44	ga_ls9c_ard_3-2-1_112072_2022-01-24_final.stac-item
2022-01-26 11:19:47	ga_ls9c_ard_3-2-1_110073_2022-01-26_final.stac-item
2022-01-29 10:15:47	ga_ls9c_ard_3-2-1_099083_2022-01-29_final.stac-item
2022-01-30 10:55:28	ga_ls9c_ard_3-2-1_106074_2022-01-30_final.stac-item
2022-02-09 11:31:43	ga_ls9c_ard_3-2-1_112072_2022-02-09_final.stac-item
2022-02-11 09:40:03	ga_ls9c_ard_3-2-1_094071_2022-02-11_final.stac-item
2022-02-11 11:19:44	ga_ls9c_ard_3-2-1_110073_2022-02-11_final.stac-item
2022-02-14 10:14:08	ga_ls9c_ard_3-2-1_099079_2022-02-14_final.stac-item
2022-02-15 10:55:23	ga_ls9c_ard_3-2-1_106074_2022-02-15_final.stac-item
2022-02-20 11:17:04	ga_ls9c_ard_3-2-1_109082_2022-02-20_final.stac-item
2022-02-27 09:39:53	ga_ls9c_ard_3-2-1_094071_2022-02-27_final.stac-item
2022-02-27 09:45:52	ga_ls9c_ard_3-2-1_094086_2022-02-27_final.stac-item
2022-03-02 10:13:56	ga_ls9c_ard_3-2-1_099079_2022-03-02_final.stac-item
2022-03-06 09:51:37	ga_ls9c_ard_3-2-1_095085_2022-03-06_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-21 09:07:31	ga_ls9c_ard_3-2-1_088083_2022-03-20_final.stac-item
2022-03-22 09:51:34	ga_ls9c_ard_3-2-1_095085_2022-03-22_final.stac-item
2022-03-25 10:20:27	ga_ls9c_ard_3-2-1_100080_2022-03-25_final.stac-item
2022-03-27 10:03:41	ga_ls9c_ard_3-2-1_098069_2022-03-27_final.stac-item
2022-04-20 09:18:04	ga_ls9c_ard_3-2-1_090079_2022-04-19_final.stac-item
2022-04-20 10:54:58	ga_ls9c_ard_3-2-1_106074_2022-04-20_final.stac-item
2022-04-23 09:51:21	ga_ls9c_ard_3-2-1_095085_2022-04-23_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-01 10:39:34	ga_ls9c_ard_3-2-1_103082_2022-05-01_final.stac-item
2022-05-09 09:48:28	ga_ls9c_ard_3-2-1_095078_2022-05-09_final.stac-item
2022-05-10 10:30:55	ga_ls9c_ard_3-2-1_102076_2022-05-10_final.stac-item
2022-05-11 09:39:17	ga_ls9c_ard_3-2-1_093086_2022-05-11_final.stac-item
2022-05-17 10:39:24	ga_ls9c_ard_3-2-1_103082_2022-05-17_final.stac-item
2022-05-23 10:01:04	ga_ls9c_ard_3-2-1_097079_2022-05-23_final.stac-item
2022-05-31 10:47:20	ga_ls9c_ard_3-2-1_105071_2022-05-31_final.stac-item
2022-06-03 11:19:02	ga_ls9c_ard_3-2-1_110073_2022-06-03_final.stac-item
2022-06-05 11:10:40	ga_ls9c_ard_3-2-1_108083_2022-06-05_final.stac-item
2022-06-12 11:14:30	ga_ls9c_ard_3-2-1_109077_2022-06-12_final.stac-item
2022-06-16 10:47:26	ga_ls9c_ard_3-2-1_105071_2022-06-16_final.stac-item
2022-06-17 09:57:25	ga_ls9c_ard_3-2-1_096085_2022-06-17_final.stac-item
2022-06-17 11:31:07	ga_ls9c_ard_3-2-1_112072_2022-06-17_final.stac-item
2022-06-23 10:58:37	ga_ls9c_ard_3-2-1_106083_2022-06-23_final.stac-item
2022-06-28 11:14:48	ga_ls9c_ard_3-2-1_109077_2022-06-28_final.stac-item
2022-07-07 09:30:06	ga_ls9c_ard_3-2-1_092078_2022-07-07_final.stac-item
2022-07-15 10:19:06	ga_ls9c_ard_3-2-1_100077_2022-07-15_final.stac-item
2022-07-24 10:15:52	ga_ls9c_ard_3-2-1_099084_2022-07-24_final.stac-item
2022-07-26 09:59:09	ga_ls9c_ard_3-2-1_097073_2022-07-26_final.stac-item
2022-07-31 10:19:21	ga_ls9c_ard_3-2-1_100077_2022-07-31_final.stac-item
2022-08-03 09:11:24	ga_ls9c_ard_3-2-1_089077_2022-08-02_final.stac-item
2022-08-03 10:49:53	ga_ls9c_ard_3-2-1_105076_2022-08-03_final.stac-item
2022-08-06 09:45:56	ga_ls9c_ard_3-2-1_094086_2022-08-06_final.stac-item
2022-08-09 10:16:04	ga_ls9c_ard_3-2-1_099084_2022-08-09_final.stac-item
2022-08-11 09:56:56	ga_ls9c_ard_3-2-1_097067_2022-08-11_final.stac-item
2022-08-22 09:46:02	ga_ls9c_ard_3-2-1_094086_2022-08-22_final.stac-item
2022-09-06 10:40:04	ga_ls9c_ard_3-2-1_103082_2022-09-06_final.stac-item
2022-09-23 09:46:09	ga_ls9c_ard_3-2-1_094086_2022-09-23_final.stac-item
2022-09-26 11:52:46	ga_ls9c_ard_3-2-1_115078_2022-09-26_final.stac-item
2023-05-22 10:22:12	ga_ls9c_ard_3-2-1_101070_2023-05-22_final.stac-item
2023-05-22 10:22:36	ga_ls9c_ard_3-2-1_101071_2023-05-22_final.stac-item
2023-05-22 10:23:00	ga_ls9c_ard_3-2-1_101072_2023-05-22_final.stac-item
2023-05-22 10:23:24	ga_ls9c_ard_3-2-1_101073_2023-05-22_final.stac-item
2023-05-22 10:23:48	ga_ls9c_ard_3-2-1_101074_2023-05-22_final.stac-item
2023-05-22 10:24:12	ga_ls9c_ard_3-2-1_101075_2023-05-22_final.stac-item
2023-05-22 10:24:36	ga_ls9c_ard_3-2-1_101076_2023-05-22_final.stac-item
2023-05-22 10:25:00	ga_ls9c_ard_3-2-1_101077_2023-05-22_final.stac-item
2023-05-22 10:25:24	ga_ls9c_ard_3-2-1_101078_2023-05-22_final.stac-item
2023-05-22 10:25:48	ga_ls9c_ard_3-2-1_101079_2023-05-22_final.stac-item
2023-05-22 10:26:12	ga_ls9c_ard_3-2-1_101080_2023-05-22_final.stac-item
2023-05-22 10:26:36	ga_ls9c_ard_3-2-1_101081_2023-05-22_final.stac-item
2023-05-22 10:27:00	ga_ls9c_ard_3-2-1_101082_2023-05-22_final.stac-item
2023-05-22 10:27:24	ga_ls9c_ard_3-2-1_101083_2023-05-22_final.stac-item
2023-05-23 09:26:58	ga_ls9c_ard_3-2-1_092071_2023-05-22_final.stac-item
2023-05-23 09:27:22	ga_ls9c_ard_3-2-1_092072_2023-05-22_final.stac-item
2023-05-23 09:27:46	ga_ls9c_ard_3-2-1_092073_2023-05-22_final.stac-item
2023-05-23 09:28:10	ga_ls9c_ard_3-2-1_092074_2023-05-22_final.stac-item
2023-05-23 09:28:34	ga_ls9c_ard_3-2-1_092075_2023-05-22_final.stac-item
2023-05-23 09:28:58	ga_ls9c_ard_3-2-1_092076_2023-05-22_final.stac-item
2023-05-23 09:29:21	ga_ls9c_ard_3-2-1_092077_2023-05-22_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