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
2021-12-14 11:38:45	ga_ls9c_ard_3-2-1_113074_2021-12-14_final.stac-item
2021-12-20 09:23:34	ga_ls9c_ard_3-2-1_091076_2021-12-19_final.stac-item
2022-01-18 10:31:07	ga_ls9c_ard_3-2-1_102075_2022-01-18_final.stac-item
2022-02-02 09:51:04	ga_ls9c_ard_3-2-1_095083_2022-02-02_final.stac-item
2022-02-15 10:53:47	ga_ls9c_ard_3-2-1_106070_2022-02-15_final.stac-item
2022-02-21 10:18:38	ga_ls9c_ard_3-2-1_100075_2022-02-21_final.stac-item
2022-02-22 11:05:29	ga_ls9c_ard_3-2-1_107084_2022-02-22_final.stac-item
2022-03-04 09:57:59	ga_ls9c_ard_3-2-1_097070_2022-03-04_final.stac-item
2022-03-10 11:00:12	ga_ls9c_ard_3-2-1_107071_2022-03-10_final.stac-item
2022-04-12 10:08:01	ga_ls9c_ard_3-2-1_098080_2022-04-12_final.stac-item
2022-04-18 09:28:52	ga_ls9c_ard_3-2-1_092075_2022-04-17_final.stac-item
2022-05-09 09:47:40	ga_ls9c_ard_3-2-1_095076_2022-05-09_final.stac-item
2022-05-09 09:50:04	ga_ls9c_ard_3-2-1_095082_2022-05-09_final.stac-item
2022-05-22 09:21:48	ga_ls9c_ard_3-2-1_090089_2022-05-21_final.stac-item
2022-05-25 09:50:42	ga_ls9c_ard_3-2-1_095084_2022-05-25_final.stac-item
2022-06-21 09:28:49	ga_ls9c_ard_3-2-1_092075_2022-06-20_final.stac-item
2022-07-20 10:39:44	ga_ls9c_ard_3-2-1_103082_2022-07-20_final.stac-item
2022-07-23 11:07:05	ga_ls9c_ard_3-2-1_108073_2022-07-23_final.stac-item
2022-07-23 11:11:29	ga_ls9c_ard_3-2-1_108084_2022-07-23_final.stac-item
2022-08-10 09:22:27	ga_ls9c_ard_3-2-1_090089_2022-08-09_final.stac-item
2022-08-29 09:49:50	ga_ls9c_ard_3-2-1_095080_2022-08-29_final.stac-item
2022-09-07 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-09-07_final.stac-item
2022-09-09 11:06:58	ga_ls9c_ard_3-2-1_108072_2022-09-09_final.stac-item
2022-09-20 10:46:32	ga_ls9c_ard_3-2-1_105067_2022-09-20_final.stac-item
2022-10-02 09:37:36	ga_ls9c_ard_3-2-1_093080_2022-10-02_final.stac-item
2022-10-08 10:36:36	ga_ls9c_ard_3-2-1_103073_2022-10-08_final.stac-item
2022-10-10 10:27:52	ga_ls9c_ard_3-2-1_101082_2022-10-10_final.stac-item
2022-10-16 09:51:38	ga_ls9c_ard_3-2-1_095084_2022-10-16_final.stac-item
2022-10-18 09:37:17	ga_ls9c_ard_3-2-1_093079_2022-10-18_final.stac-item
2022-10-21 10:07:24	ga_ls9c_ard_3-2-1_098077_2022-10-21_final.stac-item
2022-11-03 09:40:26	ga_ls9c_ard_3-2-1_093087_2022-11-03_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-12 09:33:07	ga_ls9c_ard_3-2-1_092084_2022-11-12_final.stac-item
2022-11-19 09:38:06	ga_ls9c_ard_3-2-1_093081_2022-11-19_final.stac-item
2022-11-27 10:23:31	ga_ls9c_ard_3-2-1_101071_2022-11-27_final.stac-item
2022-12-17 09:58:00	ga_ls9c_ard_3-2-1_097069_2022-12-17_final.stac-item
2022-12-25 09:16:30	ga_ls9c_ard_3-2-1_089089_2022-12-24_final.stac-item
2022-12-26 09:55:47	ga_ls9c_ard_3-2-1_096079_2022-12-26_final.stac-item
2022-12-26 09:57:47	ga_ls9c_ard_3-2-1_096084_2022-12-26_final.stac-item
2022-12-31 10:12:46	ga_ls9c_ard_3-2-1_099075_2022-12-31_final.stac-item
2023-01-04 09:46:52	ga_ls9c_ard_3-2-1_095072_2023-01-04_final.stac-item
2023-01-10 09:12:33	ga_ls9c_ard_3-2-1_089079_2023-01-09_final.stac-item
2023-01-10 09:15:21	ga_ls9c_ard_3-2-1_089086_2023-01-09_final.stac-item
2023-02-09 11:02:16	ga_ls9c_ard_3-2-1_107075_2023-02-09_final.stac-item
2023-02-11 09:16:13	ga_ls9c_ard_3-2-1_089088_2023-02-10_final.stac-item
2023-02-14 11:23:34	ga_ls9c_ard_3-2-1_110082_2023-02-14_final.stac-item
2023-02-16 11:07:35	ga_ls9c_ard_3-2-1_108073_2023-02-16_final.stac-item
2023-02-18 10:56:23	ga_ls9c_ard_3-2-1_106076_2023-02-18_final.stac-item
2023-02-25 09:27:32	ga_ls9c_ard_3-2-1_091086_2023-02-24_final.stac-item
2023-03-04 11:09:46	ga_ls9c_ard_3-2-1_108079_2023-03-04_final.stac-item
2023-03-21 10:14:26	ga_ls9c_ard_3-2-1_099080_2023-03-21_final.stac-item
2023-03-28 10:22:05	ga_ls9c_ard_3-2-1_100084_2023-03-28_final.stac-item
2023-04-03 09:44:10	ga_ls9c_ard_3-2-1_094082_2023-04-03_final.stac-item
2023-04-05 09:29:01	ga_ls9c_ard_3-2-1_092075_2023-04-04_final.stac-item
2023-04-22 10:15:45	ga_ls9c_ard_3-2-1_099084_2023-04-22_final.stac-item
2023-04-24 09:58:36	ga_ls9c_ard_3-2-1_097072_2023-04-24_final.stac-item
2023-04-29 10:21:51	ga_ls9c_ard_3-2-1_100084_2023-04-29_final.stac-item
2023-04-30 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-04-29_final.stac-item
2023-05-05 09:40:16	ga_ls9c_ard_3-2-1_094073_2023-05-05_final.stac-item
2023-05-16 09:26:52	ga_ls9c_ard_3-2-1_091086_2023-05-15_final.stac-item
2023-05-18 10:48:11	ga_ls9c_ard_3-2-1_105073_2023-05-18_final.stac-item
2023-05-24 10:12:12	ga_ls9c_ard_3-2-1_099076_2023-05-24_final.stac-item
2023-05-25 10:52:40	ga_ls9c_ard_3-2-1_106069_2023-05-25_final.stac-item
2023-06-01 09:21:33	ga_ls9c_ard_3-2-1_091073_2023-05-31_final.stac-item
2023-06-09 10:09:44	ga_ls9c_ard_3-2-1_099070_2023-06-09_final.stac-item
2023-06-10 09:22:05	ga_ls9c_ard_3-2-1_090090_2023-06-09_final.stac-item
2023-06-27 10:02:31	ga_ls9c_ard_3-2-1_097083_2023-06-27_final.stac-item
2023-07-05 10:49:44	ga_ls9c_ard_3-2-1_105077_2023-07-05_final.stac-item
2023-07-06 09:56:07	ga_ls9c_ard_3-2-1_096082_2023-07-06_final.stac-item
2023-07-19 09:26:29	ga_ls9c_ard_3-2-1_091085_2023-07-18_final.stac-item
2023-08-02 11:14:38	ga_ls9c_ard_3-2-1_109077_2023-08-02_final.stac-item
2023-08-13 10:53:22	ga_ls9c_ard_3-2-1_106070_2023-08-13_final.stac-item
2023-08-21 10:04:46	ga_ls9c_ard_3-2-1_098072_2023-08-21_final.stac-item
2023-08-22 09:11:57	ga_ls9c_ard_3-2-1_089079_2023-08-21_final.stac-item
2023-08-30 11:42:22	ga_ls9c_ard_3-2-1_113084_2023-08-30_final.stac-item
2023-09-05 09:22:04	ga_ls9c_ard_3-2-1_091073_2023-09-04_final.stac-item
2023-09-10 09:39:52	ga_ls9c_ard_3-2-1_094071_2023-09-10_final.stac-item
2023-09-30 10:54:49	ga_ls9c_ard_3-2-1_106073_2023-09-30_final.stac-item
2023-10-01 09:58:25	ga_ls9c_ard_3-2-1_097071_2023-10-01_final.stac-item
2023-10-07 10:59:53	ga_ls9c_ard_3-2-1_107070_2023-10-07_final.stac-item
2023-10-23 11:01:36	ga_ls9c_ard_3-2-1_107074_2023-10-23_final.stac-item
2023-11-01 09:22:02	ga_ls9c_ard_3-2-1_090088_2023-10-31_final.stac-item
2023-11-06 09:37:00	ga_ls9c_ard_3-2-1_093079_2023-11-06_final.stac-item
2023-11-06 11:11:53	ga_ls9c_ard_3-2-1_109069_2023-11-06_final.stac-item
2023-12-17 11:06:40	ga_ls9c_ard_3-2-1_108071_2023-12-17_final.stac-item
2023-12-29 09:56:06	ga_ls9c_ard_3-2-1_096080_2023-12-29_final.stac-item
2024-01-05 10:01:23	ga_ls9c_ard_3-2-1_097078_2024-01-05_final.stac-item
2024-01-22 10:45:03	ga_ls9c_ard_3-2-1_104079_2024-01-22_final.stac-item
2024-01-30 11:36:32	ga_ls9c_ard_3-2-1_112084_2024-01-30_final.stac-item
2024-02-07 09:07:03	ga_ls9c_ard_3-2-1_088081_2024-02-06_final.stac-item
2024-02-19 09:32:25	ga_ls9c_ard_3-2-1_092083_2024-02-19_final.stac-item
2024-02-22 11:42:31	ga_ls9c_ard_3-2-1_113084_2024-02-22_final.stac-item
2024-02-28 11:00:42	ga_ls9c_ard_3-2-1_107072_2024-02-28_final.stac-item
2024-03-11 09:51:46	ga_ls9c_ard_3-2-1_095085_2024-03-11_final.stac-item
2024-03-23 10:12:03	ga_ls9c_ard_3-2-1_099074_2024-03-23_final.stac-item
2024-03-24 10:56:29	ga_ls9c_ard_3-2-1_106077_2024-03-24_final.stac-item
2024-04-04 10:36:15	ga_ls9c_ard_3-2-1_103073_2024-04-04_final.stac-item
2024-04-25 10:53:13	ga_ls9c_ard_3-2-1_106070_2024-04-25_final.stac-item
2024-04-28 09:51:37	ga_ls9c_ard_3-2-1_095086_2024-04-28_final.stac-item
2024-04-30 11:11:21	ga_ls9c_ard_3-2-1_109069_2024-04-30_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