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
2021-11-05 09:37:01	ga_ls9c_ard_3-2-1_093077_2021-11-05_final.stac-item
2021-11-08 10:00:13	ga_ls9c_ard_3-2-1_097082_2021-11-08_final.stac-item
2021-11-10 09:43:28	ga_ls9c_ard_3-2-1_094087_2021-11-10_final.stac-item
2021-11-18 09:59:35	ga_ls9c_ard_3-2-1_097068_2021-11-18_final.stac-item
2021-11-18 10:04:45	ga_ls9c_ard_3-2-1_097081_2021-11-18_final.stac-item
2021-12-06 09:11:19	ga_ls9c_ard_3-2-1_089076_2021-12-05_final.stac-item
2021-12-06 09:13:18	ga_ls9c_ard_3-2-1_089081_2021-12-05_final.stac-item
2021-12-07 09:54:34	ga_ls9c_ard_3-2-1_096076_2021-12-07_final.stac-item
2021-12-14 09:57:28	ga_ls9c_ard_3-2-1_097068_2021-12-14_final.stac-item
2021-12-14 10:02:39	ga_ls9c_ard_3-2-1_097081_2021-12-14_final.stac-item
2021-12-18 09:36:19	ga_ls9c_ard_3-2-1_093077_2021-12-18_final.stac-item
2021-12-20 09:23:34	ga_ls9c_ard_3-2-1_091076_2021-12-19_final.stac-item
2021-12-22 09:11:12	ga_ls9c_ard_3-2-1_089076_2021-12-21_final.stac-item
2021-12-22 09:13:12	ga_ls9c_ard_3-2-1_089081_2021-12-21_final.stac-item
2021-12-23 09:54:28	ga_ls9c_ard_3-2-1_096076_2021-12-23_final.stac-item
2021-12-30 09:57:27	ga_ls9c_ard_3-2-1_097068_2021-12-30_final.stac-item
2021-12-30 10:00:15	ga_ls9c_ard_3-2-1_097075_2021-12-30_final.stac-item
2022-01-01 09:47:05	ga_ls9c_ard_3-2-1_095073_2022-01-01_final.stac-item
2022-01-03 09:36:19	ga_ls9c_ard_3-2-1_093077_2022-01-03_final.stac-item
2022-01-05 09:23:33	ga_ls9c_ard_3-2-1_091076_2022-01-04_final.stac-item
2022-01-07 09:13:11	ga_ls9c_ard_3-2-1_089081_2022-01-06_final.stac-item
2022-01-12 09:35:17	ga_ls9c_ard_3-2-1_092090_2022-01-12_final.stac-item
2022-01-14 09:19:43	ga_ls9c_ard_3-2-1_090082_2022-01-13_final.stac-item
2022-01-17 09:47:03	ga_ls9c_ard_3-2-1_095073_2022-01-17_final.stac-item
2022-01-21 09:23:32	ga_ls9c_ard_3-2-1_091076_2022-01-20_final.stac-item
2022-01-26 09:43:41	ga_ls9c_ard_3-2-1_094080_2022-01-26_final.stac-item
2022-01-28 09:30:08	ga_ls9c_ard_3-2-1_092077_2022-01-28_final.stac-item
2022-01-28 09:35:19	ga_ls9c_ard_3-2-1_092090_2022-01-28_final.stac-item
2022-01-30 09:19:46	ga_ls9c_ard_3-2-1_090082_2022-01-29_final.stac-item
2022-02-02 09:47:04	ga_ls9c_ard_3-2-1_095073_2022-02-02_final.stac-item
2022-02-09 09:56:49	ga_ls9c_ard_3-2-1_096082_2022-02-09_final.stac-item
2022-02-11 09:43:39	ga_ls9c_ard_3-2-1_094080_2022-02-11_final.stac-item
2022-02-13 09:30:05	ga_ls9c_ard_3-2-1_092077_2022-02-13_final.stac-item
2022-02-13 09:35:16	ga_ls9c_ard_3-2-1_092090_2022-02-13_final.stac-item
2022-02-15 09:17:18	ga_ls9c_ard_3-2-1_090076_2022-02-14_final.stac-item
2022-02-15 09:19:42	ga_ls9c_ard_3-2-1_090082_2022-02-14_final.stac-item
2022-02-15 09:22:05	ga_ls9c_ard_3-2-1_090088_2022-02-14_final.stac-item
2022-02-23 10:03:28	ga_ls9c_ard_3-2-1_098068_2022-02-23_final.stac-item
2022-02-23 10:09:03	ga_ls9c_ard_3-2-1_098082_2022-02-23_final.stac-item
2022-02-25 09:56:40	ga_ls9c_ard_3-2-1_096082_2022-02-25_final.stac-item
2022-02-27 09:43:28	ga_ls9c_ard_3-2-1_094080_2022-02-27_final.stac-item
2022-03-01 09:29:53	ga_ls9c_ard_3-2-1_092077_2022-02-28_final.stac-item
2022-03-02 10:12:44	ga_ls9c_ard_3-2-1_099076_2022-03-02_final.stac-item
2022-03-03 09:17:07	ga_ls9c_ard_3-2-1_090076_2022-03-02_final.stac-item
2022-03-03 09:21:54	ga_ls9c_ard_3-2-1_090088_2022-03-02_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-03-10 09:27:18	ga_ls9c_ard_3-2-1_091086_2022-03-09_final.stac-item
2022-03-11 10:03:23	ga_ls9c_ard_3-2-1_098068_2022-03-11_final.stac-item
2022-03-11 10:08:58	ga_ls9c_ard_3-2-1_098082_2022-03-11_final.stac-item
2022-03-26 09:27:13	ga_ls9c_ard_3-2-1_091086_2022-03-25_final.stac-item
2022-03-27 10:08:52	ga_ls9c_ard_3-2-1_098082_2022-03-27_final.stac-item
2022-03-29 09:56:31	ga_ls9c_ard_3-2-1_096082_2022-03-29_final.stac-item
2022-04-02 09:28:36	ga_ls9c_ard_3-2-1_092074_2022-04-01_final.stac-item
2022-04-03 10:12:40	ga_ls9c_ard_3-2-1_099076_2022-04-03_final.stac-item
2022-04-04 09:17:02	ga_ls9c_ard_3-2-1_090076_2022-04-03_final.stac-item
2022-04-04 09:21:50	ga_ls9c_ard_3-2-1_090088_2022-04-03_final.stac-item
2022-04-05 10:01:06	ga_ls9c_ard_3-2-1_097078_2022-04-05_final.stac-item
2022-04-05 10:03:53	ga_ls9c_ard_3-2-1_097085_2022-04-05_final.stac-item
2022-04-09 09:37:09	ga_ls9c_ard_3-2-1_093080_2022-04-09_final.stac-item
2022-04-11 09:25:10	ga_ls9c_ard_3-2-1_091081_2022-04-10_final.stac-item
2022-04-11 09:27:10	ga_ls9c_ard_3-2-1_091086_2022-04-10_final.stac-item
2022-04-18 09:28:28	ga_ls9c_ard_3-2-1_092074_2022-04-17_final.stac-item
2022-04-19 10:12:31	ga_ls9c_ard_3-2-1_099076_2022-04-19_final.stac-item
2022-04-20 09:20:28	ga_ls9c_ard_3-2-1_090085_2022-04-19_final.stac-item
2022-04-21 09:59:43	ga_ls9c_ard_3-2-1_097075_2022-04-21_final.stac-item
2022-04-21 10:00:55	ga_ls9c_ard_3-2-1_097078_2022-04-21_final.stac-item
2022-04-21 10:03:43	ga_ls9c_ard_3-2-1_097085_2022-04-21_final.stac-item
2022-04-25 09:36:59	ga_ls9c_ard_3-2-1_093080_2022-04-25_final.stac-item
2022-04-27 09:25:02	ga_ls9c_ard_3-2-1_091081_2022-04-26_final.stac-item
2022-04-28 10:06:17	ga_ls9c_ard_3-2-1_098076_2022-04-28_final.stac-item
2022-04-30 09:51:56	ga_ls9c_ard_3-2-1_096071_2022-04-30_final.stac-item
2022-05-04 09:31:58	ga_ls9c_ard_3-2-1_092083_2022-05-04_final.stac-item
2022-05-06 09:20:24	ga_ls9c_ard_3-2-1_090085_2022-05-05_final.stac-item
2022-05-07 09:59:39	ga_ls9c_ard_3-2-1_097075_2022-05-07_final.stac-item
2022-05-07 10:00:51	ga_ls9c_ard_3-2-1_097078_2022-05-07_final.stac-item
2022-05-07 10:03:39	ga_ls9c_ard_3-2-1_097085_2022-05-07_final.stac-item
2022-05-09 09:50:52	ga_ls9c_ard_3-2-1_095084_2022-05-09_final.stac-item
2022-05-11 09:36:53	ga_ls9c_ard_3-2-1_093080_2022-05-11_final.stac-item
2022-05-14 10:06:09	ga_ls9c_ard_3-2-1_098076_2022-05-14_final.stac-item
2022-05-16 09:51:46	ga_ls9c_ard_3-2-1_096071_2022-05-16_final.stac-item
2022-05-20 09:31:46	ga_ls9c_ard_3-2-1_092083_2022-05-20_final.stac-item
2022-05-21 10:13:02	ga_ls9c_ard_3-2-1_099078_2022-05-21_final.stac-item
2022-05-22 09:16:36	ga_ls9c_ard_3-2-1_090076_2022-05-21_final.stac-item
2022-05-25 09:48:42	ga_ls9c_ard_3-2-1_095079_2022-05-25_final.stac-item
2022-05-30 10:06:04	ga_ls9c_ard_3-2-1_098076_2022-05-30_final.stac-item
2022-06-01 09:51:43	ga_ls9c_ard_3-2-1_096071_2022-06-01_final.stac-item
2022-06-07 09:16:38	ga_ls9c_ard_3-2-1_090076_2022-06-06_final.stac-item
2022-06-10 09:48:44	ga_ls9c_ard_3-2-1_095079_2022-06-10_final.stac-item
2022-06-10 09:50:44	ga_ls9c_ard_3-2-1_095084_2022-06-10_final.stac-item
2022-06-23 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-06-22_final.stac-item
2022-07-01 10:03:13	ga_ls9c_ard_3-2-1_098068_2022-07-01_final.stac-item
2022-07-07 09:30:30	ga_ls9c_ard_3-2-1_092079_2022-07-07_final.stac-item
2022-07-23 09:30:36	ga_ls9c_ard_3-2-1_092079_2022-07-23_final.stac-item
2022-08-01 09:25:44	ga_ls9c_ard_3-2-1_091082_2022-07-31_final.stac-item
2022-08-06 09:44:44	ga_ls9c_ard_3-2-1_094083_2022-08-06_final.stac-item
2022-08-12 09:07:18	ga_ls9c_ard_3-2-1_088082_2022-08-11_final.stac-item
2022-08-15 09:38:38	ga_ls9c_ard_3-2-1_093083_2022-08-15_final.stac-item
2022-08-28 09:07:22	ga_ls9c_ard_3-2-1_088082_2022-08-27_final.stac-item
2022-08-31 09:40:16	ga_ls9c_ard_3-2-1_093087_2022-08-31_final.stac-item
2022-09-21 09:56:54	ga_ls9c_ard_3-2-1_096082_2022-09-21_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years