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
2021-11-15 11:19:02	ga_ls9c_ard_3-2-1_110073_2021-11-15_final.stac-item
2021-12-13 10:57:53	ga_ls9c_ard_3-2-1_106080_2021-12-13_final.stac-item
2021-12-30 10:00:39	ga_ls9c_ard_3-2-1_097076_2021-12-30_final.stac-item
2021-12-30 10:01:27	ga_ls9c_ard_3-2-1_097078_2021-12-30_final.stac-item
2022-01-02 10:30:45	ga_ls9c_ard_3-2-1_102074_2022-01-02_final.stac-item
2022-01-05 09:26:21	ga_ls9c_ard_3-2-1_091083_2022-01-04_final.stac-item
2022-01-09 10:36:54	ga_ls9c_ard_3-2-1_103074_2022-01-09_final.stac-item
2022-02-18 09:51:22	ga_ls9c_ard_3-2-1_095084_2022-02-18_final.stac-item
2022-02-19 10:28:38	ga_ls9c_ard_3-2-1_102069_2022-02-19_final.stac-item
2022-02-23 11:45:56	ga_ls9c_ard_3-2-1_114077_2022-02-23_final.stac-item
2022-04-04 09:20:14	ga_ls9c_ard_3-2-1_090084_2022-04-03_final.stac-item
2022-04-12 11:44:30	ga_ls9c_ard_3-2-1_114074_2022-04-12_final.stac-item
2022-04-23 11:29:26	ga_ls9c_ard_3-2-1_111083_2022-04-23_final.stac-item
2022-05-05 11:51:19	ga_ls9c_ard_3-2-1_115076_2022-05-05_final.stac-item
2022-05-21 10:15:25	ga_ls9c_ard_3-2-1_099084_2022-05-21_final.stac-item
2022-06-24 11:40:42	ga_ls9c_ard_3-2-1_113080_2022-06-24_final.stac-item
2022-07-16 11:03:58	ga_ls9c_ard_3-2-1_107081_2022-07-16_final.stac-item
2022-08-14 10:31:03	ga_ls9c_ard_3-2-1_102075_2022-08-14_final.stac-item
2022-08-20 09:52:00	ga_ls9c_ard_3-2-1_096070_2022-08-20_final.stac-item
2022-09-01 11:58:49	ga_ls9c_ard_3-2-1_116078_2022-09-01_final.stac-item
2022-09-15 10:28:45	ga_ls9c_ard_3-2-1_102069_2022-09-15_final.stac-item
2022-09-25 11:11:05	ga_ls9c_ard_3-2-1_108082_2022-09-25_final.stac-item
2022-10-29 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-10-29_final.stac-item
2022-11-17 09:48:28	ga_ls9c_ard_3-2-1_095076_2022-11-17_final.stac-item
2022-11-20 10:18:34	ga_ls9c_ard_3-2-1_100074_2022-11-20_final.stac-item
2022-11-26 09:46:39	ga_ls9c_ard_3-2-1_094087_2022-11-26_final.stac-item
2022-12-10 11:33:07	ga_ls9c_ard_3-2-1_112075_2022-12-10_final.stac-item
2022-12-11 10:35:30	ga_ls9c_ard_3-2-1_103070_2022-12-11_final.stac-item
2022-12-14 09:33:54	ga_ls9c_ard_3-2-1_092086_2022-12-14_final.stac-item
2022-12-14 11:09:59	ga_ls9c_ard_3-2-1_108079_2022-12-14_final.stac-item
2022-12-30 09:33:53	ga_ls9c_ard_3-2-1_092086_2022-12-30_final.stac-item
2023-01-20 09:51:05	ga_ls9c_ard_3-2-1_095083_2023-01-20_final.stac-item
2023-01-22 11:12:50	ga_ls9c_ard_3-2-1_109071_2023-01-22_final.stac-item
2023-02-03 10:02:02	ga_ls9c_ard_3-2-1_097079_2023-02-03_final.stac-item
2023-02-10 10:07:27	ga_ls9c_ard_3-2-1_098077_2023-02-10_final.stac-item
2023-02-14 09:45:29	ga_ls9c_ard_3-2-1_094084_2023-02-14_final.stac-item
2023-02-19 11:41:13	ga_ls9c_ard_3-2-1_113080_2023-02-19_final.stac-item
2023-02-26 10:06:25	ga_ls9c_ard_3-2-1_098075_2023-02-26_final.stac-item
2023-03-07 11:41:02	ga_ls9c_ard_3-2-1_113080_2023-03-07_final.stac-item
2023-03-09 11:29:25	ga_ls9c_ard_3-2-1_111082_2023-03-09_final.stac-item
2023-03-11 11:13:04	ga_ls9c_ard_3-2-1_109072_2023-03-11_final.stac-item
2023-03-13 09:27:01	ga_ls9c_ard_3-2-1_091085_2023-03-12_final.stac-item
2023-04-21 11:06:12	ga_ls9c_ard_3-2-1_108071_2023-04-21_final.stac-item
2023-04-28 09:39:24	ga_ls9c_ard_3-2-1_093086_2023-04-28_final.stac-item
2023-05-03 09:52:16	ga_ls9c_ard_3-2-1_096072_2023-05-03_final.stac-item
2023-05-04 10:37:30	ga_ls9c_ard_3-2-1_103077_2023-05-04_final.stac-item
2023-05-06 10:23:08	ga_ls9c_ard_3-2-1_101072_2023-05-06_final.stac-item
2023-05-08 11:51:39	ga_ls9c_ard_3-2-1_115077_2023-05-08_final.stac-item
2023-05-19 09:51:21	ga_ls9c_ard_3-2-1_096070_2023-05-19_final.stac-item
2023-05-26 09:58:38	ga_ls9c_ard_3-2-1_097073_2023-05-26_final.stac-item
2023-05-26 10:00:38	ga_ls9c_ard_3-2-1_097078_2023-05-26_final.stac-item
2023-05-26 11:41:31	ga_ls9c_ard_3-2-1_113083_2023-05-26_final.stac-item
2023-06-01 09:25:33	ga_ls9c_ard_3-2-1_091083_2023-05-31_final.stac-item
2023-06-12 10:43:23	ga_ls9c_ard_3-2-1_104077_2023-06-12_final.stac-item
2023-06-17 09:22:36	ga_ls9c_ard_3-2-1_091076_2023-06-16_final.stac-item
2023-07-08 09:44:34	ga_ls9c_ard_3-2-1_094084_2023-07-08_final.stac-item
2023-07-15 11:29:41	ga_ls9c_ard_3-2-1_111084_2023-07-15_final.stac-item
2023-07-21 09:14:30	ga_ls9c_ard_3-2-1_089086_2023-07-20_final.stac-item
2023-07-24 11:18:17	ga_ls9c_ard_3-2-1_110071_2023-07-24_final.stac-item
2023-08-15 10:43:00	ga_ls9c_ard_3-2-1_104075_2023-08-15_final.stac-item
2023-08-18 09:34:36	ga_ls9c_ard_3-2-1_093074_2023-08-18_final.stac-item
2023-08-18 11:16:17	ga_ls9c_ard_3-2-1_109081_2023-08-18_final.stac-item
2023-08-20 09:24:40	ga_ls9c_ard_3-2-1_091080_2023-08-19_final.stac-item
2023-08-20 09:27:52	ga_ls9c_ard_3-2-1_091088_2023-08-19_final.stac-item
2023-08-22 09:12:45	ga_ls9c_ard_3-2-1_089081_2023-08-21_final.stac-item
2023-09-19 11:13:24	ga_ls9c_ard_3-2-1_109073_2023-09-19_final.stac-item
2023-09-25 10:38:16	ga_ls9c_ard_3-2-1_103078_2023-09-25_final.stac-item
2023-09-26 11:18:43	ga_ls9c_ard_3-2-1_110071_2023-09-26_final.stac-item
2023-10-05 09:35:21	ga_ls9c_ard_3-2-1_093075_2023-10-05_final.stac-item
2023-10-24 11:47:16	ga_ls9c_ard_3-2-1_114080_2023-10-24_final.stac-item
2023-10-30 09:32:02	ga_ls9c_ard_3-2-1_092082_2023-10-30_final.stac-item
2023-11-02 11:40:58	ga_ls9c_ard_3-2-1_113080_2023-11-02_final.stac-item
2023-11-08 09:28:38	ga_ls9c_ard_3-2-1_091089_2023-11-07_final.stac-item
2023-11-09 11:45:12	ga_ls9c_ard_3-2-1_114075_2023-11-09_final.stac-item
2023-11-18 10:01:22	ga_ls9c_ard_3-2-1_097078_2023-11-18_final.stac-item
2023-11-29 11:21:25	ga_ls9c_ard_3-2-1_110077_2023-11-29_final.stac-item
2023-12-01 09:35:21	ga_ls9c_ard_3-2-1_092090_2023-12-01_final.stac-item
2023-12-04 10:03:49	ga_ls9c_ard_3-2-1_097084_2023-12-04_final.stac-item
2023-12-11 11:45:17	ga_ls9c_ard_3-2-1_114075_2023-12-11_final.stac-item
2023-12-27 10:08:04	ga_ls9c_ard_3-2-1_098079_2023-12-27_final.stac-item
2023-12-27 11:45:22	ga_ls9c_ard_3-2-1_114075_2023-12-27_final.stac-item
2023-12-27 11:46:10	ga_ls9c_ard_3-2-1_114077_2023-12-27_final.stac-item
2024-01-07 11:29:31	ga_ls9c_ard_3-2-1_111082_2024-01-07_final.stac-item
2024-01-09 11:13:11	ga_ls9c_ard_3-2-1_109072_2024-01-09_final.stac-item
2024-01-14 11:35:44	ga_ls9c_ard_3-2-1_112082_2024-01-14_final.stac-item
2024-01-29 09:14:23	ga_ls9c_ard_3-2-1_089084_2024-01-28_final.stac-item
2024-01-30 09:58:03	ga_ls9c_ard_3-2-1_096085_2024-01-30_final.stac-item
2024-02-23 10:41:41	ga_ls9c_ard_3-2-1_104071_2024-02-23_final.stac-item
2024-03-10 09:07:43	ga_ls9c_ard_3-2-1_088083_2024-03-09_final.stac-item
2024-03-11 11:25:04	ga_ls9c_ard_3-2-1_111071_2024-03-11_final.stac-item
2024-03-29 11:12:56	ga_ls9c_ard_3-2-1_109072_2024-03-29_final.stac-item
2024-04-03 11:35:52	ga_ls9c_ard_3-2-1_112083_2024-04-03_final.stac-item
2024-04-06 10:23:53	ga_ls9c_ard_3-2-1_101073_2024-04-06_final.stac-item
2024-04-07 11:09:32	ga_ls9c_ard_3-2-1_108079_2024-04-07_final.stac-item
2024-04-10 11:40:48	ga_ls9c_ard_3-2-1_113080_2024-04-10_final.stac-item
2024-04-10 11:41:36	ga_ls9c_ard_3-2-1_113082_2024-04-10_final.stac-item
2024-04-14 09:34:45	ga_ls9c_ard_3-2-1_093074_2024-04-14_final.stac-item
2024-04-14 11:15:14	ga_ls9c_ard_3-2-1_109078_2024-04-14_final.stac-item
2024-04-16 10:59:38	ga_ls9c_ard_3-2-1_107070_2024-04-16_final.stac-item
2024-04-30 11:12:56	ga_ls9c_ard_3-2-1_109073_2024-04-30_nrt.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