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
2021-11-08 09:57:02	ga_ls9c_ard_3-2-1_097074_2021-11-08_final.stac-item
2021-12-14 11:41:32	ga_ls9c_ard_3-2-1_113081_2021-12-14_final.stac-item
2021-12-16 11:27:33	ga_ls9c_ard_3-2-1_111077_2021-12-16_final.stac-item
2021-12-17 10:29:32	ga_ls9c_ard_3-2-1_102071_2021-12-17_final.stac-item
2021-12-25 09:44:06	ga_ls9c_ard_3-2-1_094081_2021-12-25_final.stac-item
2021-12-29 10:57:28	ga_ls9c_ard_3-2-1_106079_2021-12-29_final.stac-item
2021-12-30 11:39:32	ga_ls9c_ard_3-2-1_113076_2021-12-30_final.stac-item
2022-01-04 11:58:28	ga_ls9c_ard_3-2-1_116077_2022-01-04_final.stac-item
2022-01-14 10:57:25	ga_ls9c_ard_3-2-1_106079_2022-01-14_final.stac-item
2022-01-15 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-01-15_final.stac-item
2022-01-17 09:50:38	ga_ls9c_ard_3-2-1_095082_2022-01-17_final.stac-item
2022-01-19 11:11:59	ga_ls9c_ard_3-2-1_109069_2022-01-19_final.stac-item
2022-01-20 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-01-20_final.stac-item
2022-01-26 09:44:05	ga_ls9c_ard_3-2-1_094081_2022-01-26_final.stac-item
2022-01-31 11:39:31	ga_ls9c_ard_3-2-1_113076_2022-01-31_final.stac-item
2022-02-09 11:35:42	ga_ls9c_ard_3-2-1_112082_2022-02-09_final.stac-item
2022-02-11 09:44:03	ga_ls9c_ard_3-2-1_094081_2022-02-11_final.stac-item
2022-02-16 09:56:58	ga_ls9c_ard_3-2-1_097067_2022-02-16_final.stac-item
2022-02-16 11:39:26	ga_ls9c_ard_3-2-1_113076_2022-02-16_final.stac-item
2022-02-22 09:23:48	ga_ls9c_ard_3-2-1_091077_2022-02-21_final.stac-item
2022-02-25 11:35:33	ga_ls9c_ard_3-2-1_112082_2022-02-25_final.stac-item
2022-02-27 09:43:52	ga_ls9c_ard_3-2-1_094081_2022-02-27_final.stac-item
2022-03-04 09:56:47	ga_ls9c_ard_3-2-1_097067_2022-03-04_final.stac-item
2022-03-04 11:39:16	ga_ls9c_ard_3-2-1_113076_2022-03-04_final.stac-item
2022-03-08 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-03-08_final.stac-item
2022-03-10 09:23:42	ga_ls9c_ard_3-2-1_091077_2022-03-09_final.stac-item
2022-03-19 10:54:47	ga_ls9c_ard_3-2-1_106073_2022-03-19_final.stac-item
2022-03-20 10:03:09	ga_ls9c_ard_3-2-1_097083_2022-03-20_final.stac-item
2022-03-20 11:39:14	ga_ls9c_ard_3-2-1_113076_2022-03-20_final.stac-item
2022-03-29 11:35:24	ga_ls9c_ard_3-2-1_112082_2022-03-29_final.stac-item
2022-04-03 10:15:27	ga_ls9c_ard_3-2-1_099083_2022-04-03_final.stac-item
2022-04-05 11:39:11	ga_ls9c_ard_3-2-1_113076_2022-04-05_final.stac-item
2022-04-08 10:29:11	ga_ls9c_ard_3-2-1_102071_2022-04-08_final.stac-item
2022-04-14 11:35:19	ga_ls9c_ard_3-2-1_112082_2022-04-14_final.stac-item
2022-04-16 09:43:39	ga_ls9c_ard_3-2-1_094081_2022-04-16_final.stac-item
2022-04-19 10:15:18	ga_ls9c_ard_3-2-1_099083_2022-04-19_final.stac-item
2022-04-21 11:39:00	ga_ls9c_ard_3-2-1_113076_2022-04-21_final.stac-item
2022-04-24 10:29:01	ga_ls9c_ard_3-2-1_102071_2022-04-24_final.stac-item
2022-05-04 09:28:47	ga_ls9c_ard_3-2-1_092075_2022-05-03_final.stac-item
2022-05-07 09:59:15	ga_ls9c_ard_3-2-1_097074_2022-05-07_final.stac-item
2022-05-07 11:38:56	ga_ls9c_ard_3-2-1_113076_2022-05-07_final.stac-item
2022-05-14 10:06:33	ga_ls9c_ard_3-2-1_098077_2022-05-14_final.stac-item
2022-05-14 11:47:02	ga_ls9c_ard_3-2-1_114081_2022-05-14_final.stac-item
2022-05-19 10:23:24	ga_ls9c_ard_3-2-1_101073_2022-05-19_final.stac-item
2022-05-21 10:15:01	ga_ls9c_ard_3-2-1_099083_2022-05-21_final.stac-item
2022-05-23 11:38:45	ga_ls9c_ard_3-2-1_113076_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
2022-06-04 10:23:25	ga_ls9c_ard_3-2-1_101073_2022-06-04_final.stac-item
2022-06-06 10:15:03	ga_ls9c_ard_3-2-1_099083_2022-06-06_final.stac-item
2022-06-07 10:56:43	ga_ls9c_ard_3-2-1_106079_2022-06-07_final.stac-item
2022-06-08 11:38:47	ga_ls9c_ard_3-2-1_113076_2022-06-08_final.stac-item
2022-06-15 11:47:02	ga_ls9c_ard_3-2-1_114081_2022-06-15_final.stac-item
2022-06-19 09:43:30	ga_ls9c_ard_3-2-1_094081_2022-06-19_final.stac-item
2022-06-20 10:23:37	ga_ls9c_ard_3-2-1_101073_2022-06-20_final.stac-item
2022-06-21 09:34:01	ga_ls9c_ard_3-2-1_092088_2022-06-21_final.stac-item
2022-06-22 10:15:19	ga_ls9c_ard_3-2-1_099083_2022-06-22_final.stac-item
2022-06-24 09:59:26	ga_ls9c_ard_3-2-1_097074_2022-06-24_final.stac-item
2022-06-24 11:39:07	ga_ls9c_ard_3-2-1_113076_2022-06-24_final.stac-item
2022-07-01 11:47:18	ga_ls9c_ard_3-2-1_114081_2022-07-01_final.stac-item
2022-07-03 09:55:39	ga_ls9c_ard_3-2-1_096080_2022-07-03_final.stac-item
2022-07-05 09:43:40	ga_ls9c_ard_3-2-1_094081_2022-07-05_final.stac-item
2022-07-06 10:23:44	ga_ls9c_ard_3-2-1_101073_2022-07-06_final.stac-item
2022-07-21 09:43:43	ga_ls9c_ard_3-2-1_094081_2022-07-21_final.stac-item
2022-07-22 10:23:49	ga_ls9c_ard_3-2-1_101073_2022-07-22_final.stac-item
2022-07-24 10:15:28	ga_ls9c_ard_3-2-1_099083_2022-07-24_final.stac-item
2022-08-06 09:41:56	ga_ls9c_ard_3-2-1_094076_2022-08-06_final.stac-item
2022-08-06 09:43:56	ga_ls9c_ard_3-2-1_094081_2022-08-06_final.stac-item
2022-08-07 10:24:01	ga_ls9c_ard_3-2-1_101073_2022-08-07_final.stac-item
2022-08-09 10:15:40	ga_ls9c_ard_3-2-1_099083_2022-08-09_final.stac-item
2022-08-25 10:09:22	ga_ls9c_ard_3-2-1_099067_2022-08-25_final.stac-item
2022-09-05 09:56:00	ga_ls9c_ard_3-2-1_096080_2022-09-05_final.stac-item
2022-09-20 10:46:56	ga_ls9c_ard_3-2-1_105068_2022-09-20_final.stac-item
2022-09-23 11:23:50	ga_ls9c_ard_3-2-1_110083_2022-09-23_final.stac-item
2023-05-23 09:30:09	ga_ls9c_ard_3-2-1_092079_2023-05-23_final.stac-item
2023-05-23 09:30:33	ga_ls9c_ard_3-2-1_092080_2023-05-23_final.stac-item
2023-05-23 09:30:57	ga_ls9c_ard_3-2-1_092081_2023-05-23_final.stac-item
2023-05-23 09:31:21	ga_ls9c_ard_3-2-1_092082_2023-05-23_final.stac-item
2023-05-23 09:31:45	ga_ls9c_ard_3-2-1_092083_2023-05-23_final.stac-item
2023-05-23 09:32:09	ga_ls9c_ard_3-2-1_092084_2023-05-23_final.stac-item
2023-05-23 09:32:33	ga_ls9c_ard_3-2-1_092085_2023-05-23_final.stac-item
2023-05-23 09:32:57	ga_ls9c_ard_3-2-1_092086_2023-05-23_final.stac-item
2023-05-23 09:33:21	ga_ls9c_ard_3-2-1_092087_2023-05-23_final.stac-item
2023-05-23 09:33:45	ga_ls9c_ard_3-2-1_092088_2023-05-23_final.stac-item
2023-05-23 09:34:09	ga_ls9c_ard_3-2-1_092089_2023-05-23_final.stac-item
2023-05-23 09:34:33	ga_ls9c_ard_3-2-1_092090_2023-05-23_final.stac-item
2023-05-23 11:05:03	ga_ls9c_ard_3-2-1_108069_2023-05-23_final.stac-item
2023-05-23 11:05:27	ga_ls9c_ard_3-2-1_108070_2023-05-23_final.stac-item
2023-05-23 11:05:51	ga_ls9c_ard_3-2-1_108071_2023-05-23_final.stac-item
2023-05-23 11:06:15	ga_ls9c_ard_3-2-1_108072_2023-05-23_final.stac-item
2023-05-23 11:06:39	ga_ls9c_ard_3-2-1_108073_2023-05-23_final.stac-item
2023-05-23 11:07:03	ga_ls9c_ard_3-2-1_108074_2023-05-23_final.stac-item
2023-05-23 11:07:27	ga_ls9c_ard_3-2-1_108075_2023-05-23_final.stac-item
2023-05-23 11:07:50	ga_ls9c_ard_3-2-1_108076_2023-05-23_final.stac-item
2023-05-23 11:08:14	ga_ls9c_ard_3-2-1_108077_2023-05-23_final.stac-item
2023-05-23 11:08:38	ga_ls9c_ard_3-2-1_108078_2023-05-23_final.stac-item
2023-05-23 11:09:02	ga_ls9c_ard_3-2-1_108079_2023-05-23_final.stac-item
2023-05-23 11:09:26	ga_ls9c_ard_3-2-1_108080_2023-05-23_final.stac-item
2023-05-23 11:09:50	ga_ls9c_ard_3-2-1_108081_2023-05-23_final.stac-item
2023-05-23 11:10:14	ga_ls9c_ard_3-2-1_108082_2023-05-23_final.stac-item
2023-05-23 11:10:38	ga_ls9c_ard_3-2-1_108083_2023-05-23_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