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
2021-10-31 11:11:36	ga_ls9c_ard_3-2-1_109073_2021-10-31_final.stac-item
2021-11-05 09:40:12	ga_ls9c_ard_3-2-1_093085_2021-11-05_final.stac-item
2021-11-08 10:01:01	ga_ls9c_ard_3-2-1_097084_2021-11-08_final.stac-item
2021-12-10 10:23:50	ga_ls9c_ard_3-2-1_101072_2021-12-10_final.stac-item
2021-12-12 11:53:31	ga_ls9c_ard_3-2-1_115080_2021-12-12_final.stac-item
2021-12-18 09:33:55	ga_ls9c_ard_3-2-1_093071_2021-12-18_final.stac-item
2021-12-29 09:17:47	ga_ls9c_ard_3-2-1_090077_2021-12-28_final.stac-item
2022-01-23 10:48:28	ga_ls9c_ard_3-2-1_105072_2022-01-23_final.stac-item
2022-02-03 10:28:44	ga_ls9c_ard_3-2-1_102069_2022-02-03_final.stac-item
2022-02-09 09:52:50	ga_ls9c_ard_3-2-1_096072_2022-02-09_final.stac-item
2022-02-28 10:25:55	ga_ls9c_ard_3-2-1_101078_2022-02-28_final.stac-item
2022-03-12 09:13:20	ga_ls9c_ard_3-2-1_089082_2022-03-11_final.stac-item
2022-04-04 10:53:08	ga_ls9c_ard_3-2-1_106069_2022-04-04_final.stac-item
2022-04-13 10:52:04	ga_ls9c_ard_3-2-1_105082_2022-04-13_final.stac-item
2022-04-19 10:13:43	ga_ls9c_ard_3-2-1_099079_2022-04-19_final.stac-item
2022-04-20 09:20:52	ga_ls9c_ard_3-2-1_090086_2022-04-19_final.stac-item
2022-04-25 11:16:40	ga_ls9c_ard_3-2-1_109082_2022-04-25_final.stac-item
2022-05-04 09:33:10	ga_ls9c_ard_3-2-1_092086_2022-05-04_final.stac-item
2022-05-14 10:02:57	ga_ls9c_ard_3-2-1_098068_2022-05-14_final.stac-item
2022-05-18 09:40:34	ga_ls9c_ard_3-2-1_094074_2022-05-18_final.stac-item
2022-05-26 10:27:58	ga_ls9c_ard_3-2-1_102069_2022-05-26_final.stac-item
2022-05-28 10:21:36	ga_ls9c_ard_3-2-1_100084_2022-05-28_final.stac-item
2022-05-30 10:02:52	ga_ls9c_ard_3-2-1_098068_2022-05-30_final.stac-item
2022-06-06 10:13:27	ga_ls9c_ard_3-2-1_099079_2022-06-06_final.stac-item
2022-06-14 11:01:46	ga_ls9c_ard_3-2-1_107076_2022-06-14_final.stac-item
2022-06-15 10:02:58	ga_ls9c_ard_3-2-1_098068_2022-06-15_final.stac-item
2022-06-22 10:10:55	ga_ls9c_ard_3-2-1_099072_2022-06-22_final.stac-item
2022-07-02 10:48:05	ga_ls9c_ard_3-2-1_105072_2022-07-02_final.stac-item
2022-07-04 10:34:07	ga_ls9c_ard_3-2-1_103068_2022-07-04_final.stac-item
2022-07-05 11:20:34	ga_ls9c_ard_3-2-1_110076_2022-07-05_final.stac-item
2022-07-16 09:24:41	ga_ls9c_ard_3-2-1_091080_2022-07-15_final.stac-item
2022-07-20 10:34:08	ga_ls9c_ard_3-2-1_103068_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
2022-07-28 09:51:12	ga_ls9c_ard_3-2-1_095084_2022-07-28_final.stac-item
2022-07-31 10:17:21	ga_ls9c_ard_3-2-1_100072_2022-07-31_final.stac-item
2022-08-19 09:11:32	ga_ls9c_ard_3-2-1_089077_2022-08-18_final.stac-item
2022-08-19 09:16:19	ga_ls9c_ard_3-2-1_089089_2022-08-18_final.stac-item
2022-09-25 09:34:36	ga_ls9c_ard_3-2-1_092088_2022-09-25_final.stac-item
2022-10-04 11:00:31	ga_ls9c_ard_3-2-1_107071_2022-10-04_final.stac-item
2022-10-08 10:40:12	ga_ls9c_ard_3-2-1_103082_2022-10-08_final.stac-item
2022-11-06 10:10:33	ga_ls9c_ard_3-2-1_098085_2022-11-06_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-14 10:54:51	ga_ls9c_ard_3-2-1_106072_2022-11-14_final.stac-item
2022-11-15 09:58:50	ga_ls9c_ard_3-2-1_097071_2022-11-15_final.stac-item
2022-11-19 09:35:19	ga_ls9c_ard_3-2-1_093074_2022-11-19_final.stac-item
2022-11-19 09:37:42	ga_ls9c_ard_3-2-1_093080_2022-11-19_final.stac-item
2022-11-21 09:25:20	ga_ls9c_ard_3-2-1_091080_2022-11-20_final.stac-item
2022-11-24 09:58:14	ga_ls9c_ard_3-2-1_096085_2022-11-24_final.stac-item
2022-12-02 10:40:50	ga_ls9c_ard_3-2-1_104068_2022-12-02_final.stac-item
2022-12-04 10:29:41	ga_ls9c_ard_3-2-1_102071_2022-12-04_final.stac-item
2022-12-06 10:17:44	ga_ls9c_ard_3-2-1_100072_2022-12-06_final.stac-item
2022-12-10 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-12-10_final.stac-item
2022-12-12 11:20:21	ga_ls9c_ard_3-2-1_110074_2022-12-12_final.stac-item
2022-12-14 11:10:23	ga_ls9c_ard_3-2-1_108080_2022-12-14_final.stac-item
2022-12-18 09:07:10	ga_ls9c_ard_3-2-1_088081_2022-12-17_final.stac-item
2022-12-30 09:29:30	ga_ls9c_ard_3-2-1_092075_2022-12-29_final.stac-item
2022-12-31 11:52:51	ga_ls9c_ard_3-2-1_115078_2022-12-31_final.stac-item
2023-01-06 09:40:53	ga_ls9c_ard_3-2-1_093088_2023-01-06_final.stac-item
2023-01-16 10:14:17	ga_ls9c_ard_3-2-1_099079_2023-01-16_final.stac-item
2023-01-16 11:51:34	ga_ls9c_ard_3-2-1_115075_2023-01-16_final.stac-item
2023-01-19 09:06:39	ga_ls9c_ard_3-2-1_088080_2023-01-18_final.stac-item
2023-01-22 09:40:44	ga_ls9c_ard_3-2-1_093088_2023-01-22_final.stac-item
2023-01-31 11:07:12	ga_ls9c_ard_3-2-1_108072_2023-01-31_final.stac-item
2023-02-23 11:12:25	ga_ls9c_ard_3-2-1_109070_2023-02-23_final.stac-item
2023-02-27 10:49:40	ga_ls9c_ard_3-2-1_105075_2023-02-27_final.stac-item
2023-03-25 11:29:20	ga_ls9c_ard_3-2-1_111082_2023-03-25_final.stac-item
2023-03-28 10:20:53	ga_ls9c_ard_3-2-1_100081_2023-03-28_final.stac-item
2023-03-30 10:04:06	ga_ls9c_ard_3-2-1_098070_2023-03-30_final.stac-item
2023-04-05 09:33:00	ga_ls9c_ard_3-2-1_092085_2023-04-05_final.stac-item
2023-04-23 10:55:01	ga_ls9c_ard_3-2-1_106074_2023-04-23_final.stac-item
2023-04-29 11:57:32	ga_ls9c_ard_3-2-1_116076_2023-04-29_final.stac-item
2023-04-30 09:27:48	ga_ls9c_ard_3-2-1_091088_2023-04-29_final.stac-item
2023-05-01 10:03:52	ga_ls9c_ard_3-2-1_098070_2023-05-01_final.stac-item
2023-05-02 10:51:30	ga_ls9c_ard_3-2-1_105081_2023-05-02_final.stac-item
2023-05-07 09:32:42	ga_ls9c_ard_3-2-1_092085_2023-05-07_final.stac-item
2023-05-08 10:10:47	ga_ls9c_ard_3-2-1_099072_2023-05-08_final.stac-item
2023-05-12 11:24:56	ga_ls9c_ard_3-2-1_111072_2023-05-12_final.stac-item
2023-05-14 09:39:15	ga_ls9c_ard_3-2-1_093086_2023-05-14_final.stac-item
2023-05-14 11:12:57	ga_ls9c_ard_3-2-1_109073_2023-05-14_final.stac-item
2023-05-16 09:24:05	ga_ls9c_ard_3-2-1_091079_2023-05-15_final.stac-item
2023-05-17 10:02:56	ga_ls9c_ard_3-2-1_098068_2023-05-17_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-05-31 10:20:22	ga_ls9c_ard_3-2-1_100081_2023-05-31_final.stac-item
2023-06-01 11:01:38	ga_ls9c_ard_3-2-1_107076_2023-06-01_final.stac-item
2023-06-24 11:06:28	ga_ls9c_ard_3-2-1_108073_2023-06-24_final.stac-item
2023-06-26 09:20:01	ga_ls9c_ard_3-2-1_090085_2023-06-25_final.stac-item
2023-07-01 11:17:11	ga_ls9c_ard_3-2-1_109084_2023-07-01_final.stac-item
2023-07-19 11:01:46	ga_ls9c_ard_3-2-1_107076_2023-07-19_final.stac-item
2023-07-21 09:10:55	ga_ls9c_ard_3-2-1_089077_2023-07-20_final.stac-item
2023-07-29 09:59:13	ga_ls9c_ard_3-2-1_097074_2023-07-29_final.stac-item
2023-07-29 11:40:30	ga_ls9c_ard_3-2-1_113080_2023-07-29_final.stac-item
2023-08-05 10:09:53	ga_ls9c_ard_3-2-1_098085_2023-08-05_final.stac-item
2023-08-11 09:33:13	ga_ls9c_ard_3-2-1_092086_2023-08-11_final.stac-item
2023-10-15 10:11:21	ga_ls9c_ard_3-2-1_099072_2023-10-15_final.stac-item
2023-10-16 09:20:56	ga_ls9c_ard_3-2-1_090085_2023-10-15_final.stac-item
2023-10-17 09:58:36	ga_ls9c_ard_3-2-1_097071_2023-10-17_final.stac-item
2023-11-05 10:28:37	ga_ls9c_ard_3-2-1_102069_2023-11-05_final.stac-item
2023-11-16 11:51:23	ga_ls9c_ard_3-2-1_115075_2023-11-16_final.stac-item
2023-11-22 09:35:07	ga_ls9c_ard_3-2-1_093074_2023-11-22_final.stac-item
2023-11-26 10:48:07	ga_ls9c_ard_3-2-1_105071_2023-11-26_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