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
2021-11-02 10:52:52	ga_ls9c_ard_3-2-1_106073_2021-11-02_final.stac-item
2021-11-07 10:55:21	ga_ls9c_ard_3-2-1_106073_2021-11-07_final.stac-item
2021-12-04 09:25:17	ga_ls9c_ard_3-2-1_091080_2021-12-03_final.stac-item
2021-12-05 10:07:20	ga_ls9c_ard_3-2-1_098077_2021-12-05_final.stac-item
2021-12-09 09:44:10	ga_ls9c_ard_3-2-1_094081_2021-12-09_final.stac-item
2021-12-10 10:26:37	ga_ls9c_ard_3-2-1_101079_2021-12-10_final.stac-item
2021-12-18 11:12:00	ga_ls9c_ard_3-2-1_109069_2021-12-18_final.stac-item
2021-12-20 09:25:09	ga_ls9c_ard_3-2-1_091080_2021-12-19_final.stac-item
2021-12-21 11:47:42	ga_ls9c_ard_3-2-1_114081_2021-12-21_final.stac-item
2021-12-23 09:56:04	ga_ls9c_ard_3-2-1_096080_2021-12-23_final.stac-item
2021-12-29 09:20:11	ga_ls9c_ard_3-2-1_090083_2021-12-28_final.stac-item
2021-12-30 09:59:51	ga_ls9c_ard_3-2-1_097074_2021-12-30_final.stac-item
2022-01-01 09:50:41	ga_ls9c_ard_3-2-1_095082_2022-01-01_final.stac-item
2022-01-05 09:23:57	ga_ls9c_ard_3-2-1_091077_2022-01-04_final.stac-item
2022-01-06 11:47:41	ga_ls9c_ard_3-2-1_114081_2022-01-06_final.stac-item
2022-01-08 11:35:43	ga_ls9c_ard_3-2-1_112082_2022-01-08_final.stac-item
2022-01-10 09:44:04	ga_ls9c_ard_3-2-1_094081_2022-01-10_final.stac-item
2022-01-15 09:57:00	ga_ls9c_ard_3-2-1_097067_2022-01-15_final.stac-item
2022-01-15 11:39:29	ga_ls9c_ard_3-2-1_113076_2022-01-15_final.stac-item
2022-01-20 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-01-20_final.stac-item
2022-01-21 09:23:56	ga_ls9c_ard_3-2-1_091077_2022-01-20_final.stac-item
2022-01-24 11:35:44	ga_ls9c_ard_3-2-1_112082_2022-01-24_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 09:57:03	ga_ls9c_ard_3-2-1_097067_2022-01-31_final.stac-item
2022-01-31 11:39:31	ga_ls9c_ard_3-2-1_113076_2022-01-31_final.stac-item
2022-02-04 11:12:00	ga_ls9c_ard_3-2-1_109069_2022-02-04_final.stac-item
2022-02-05 11:58:27	ga_ls9c_ard_3-2-1_116077_2022-02-05_final.stac-item
2022-02-15 10:57:23	ga_ls9c_ard_3-2-1_106079_2022-02-15_final.stac-item
2022-02-16 09:56:58	ga_ls9c_ard_3-2-1_097067_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 09:55:52	ga_ls9c_ard_3-2-1_096080_2022-02-25_final.stac-item
2022-02-25 11:35:33	ga_ls9c_ard_3-2-1_112082_2022-02-25_final.stac-item
2022-03-03 10:54:48	ga_ls9c_ard_3-2-1_106073_2022-03-03_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
2022-03-22 09:50:23	ga_ls9c_ard_3-2-1_095082_2022-03-22_final.stac-item
2022-03-24 11:12:06	ga_ls9c_ard_3-2-1_109070_2022-03-24_final.stac-item
2022-04-07 09:50:19	ga_ls9c_ard_3-2-1_095082_2022-04-07_final.stac-item
2022-04-08 10:29:11	ga_ls9c_ard_3-2-1_102071_2022-04-08_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 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-04-19_final.stac-item
2022-04-21 09:56:32	ga_ls9c_ard_3-2-1_097067_2022-04-21_final.stac-item
2022-04-21 09:59:19	ga_ls9c_ard_3-2-1_097074_2022-04-21_final.stac-item
2022-04-21 11:39:00	ga_ls9c_ard_3-2-1_113076_2022-04-21_final.stac-item
2022-05-07 09:56:28	ga_ls9c_ard_3-2-1_097067_2022-05-07_final.stac-item
2022-05-21 10:11:26	ga_ls9c_ard_3-2-1_099074_2022-05-21_final.stac-item
2022-05-21 10:15:01	ga_ls9c_ard_3-2-1_099083_2022-05-21_final.stac-item
2022-05-25 09:49:54	ga_ls9c_ard_3-2-1_095082_2022-05-25_final.stac-item
2022-05-27 11:11:38	ga_ls9c_ard_3-2-1_109070_2022-05-27_final.stac-item
2022-06-04 10:23:25	ga_ls9c_ard_3-2-1_101073_2022-06-04_final.stac-item
2022-06-05 09:33:47	ga_ls9c_ard_3-2-1_092088_2022-06-05_final.stac-item
2022-06-06 10:11:27	ga_ls9c_ard_3-2-1_099074_2022-06-06_final.stac-item
2022-06-08 09:56:18	ga_ls9c_ard_3-2-1_097067_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
2022-06-21 09:31:37	ga_ls9c_ard_3-2-1_092082_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
2022-06-22 11:51:00	ga_ls9c_ard_3-2-1_115075_2022-06-22_final.stac-item
2022-06-24 11:39:07	ga_ls9c_ard_3-2-1_113076_2022-06-24_final.stac-item
2022-07-02 10:46:29	ga_ls9c_ard_3-2-1_105068_2022-07-02_final.stac-item
2022-07-07 09:31:42	ga_ls9c_ard_3-2-1_092082_2022-07-07_final.stac-item
2022-07-15 11:57:59	ga_ls9c_ard_3-2-1_116077_2022-07-15_final.stac-item
2022-07-16 10:59:35	ga_ls9c_ard_3-2-1_107070_2022-07-16_final.stac-item
2022-07-30 11:12:10	ga_ls9c_ard_3-2-1_109070_2022-07-30_final.stac-item
2022-08-01 10:59:50	ga_ls9c_ard_3-2-1_107070_2022-08-01_final.stac-item
2022-08-06 09:41:56	ga_ls9c_ard_3-2-1_094076_2022-08-06_final.stac-item
2022-08-15 09:35:50	ga_ls9c_ard_3-2-1_093076_2022-08-15_final.stac-item
2022-08-16 11:58:23	ga_ls9c_ard_3-2-1_116077_2022-08-16_final.stac-item
2022-08-19 10:46:50	ga_ls9c_ard_3-2-1_105068_2022-08-19_final.stac-item
2022-08-22 09:42:03	ga_ls9c_ard_3-2-1_094076_2022-08-22_final.stac-item
2022-08-23 10:26:30	ga_ls9c_ard_3-2-1_101079_2022-08-23_final.stac-item
2022-09-05 09:56:00	ga_ls9c_ard_3-2-1_096080_2022-09-05_final.stac-item
2022-09-23 11:23:50	ga_ls9c_ard_3-2-1_110083_2022-09-23_final.stac-item
2022-09-29 10:45:35	ga_ls9c_ard_3-2-1_104080_2022-09-29_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