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
2021-11-06 10:19:22	ga_ls9c_ard_3-2-1_100083_2021-11-06_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 11:47:25	ga_ls9c_ard_3-2-1_114080_2021-12-05_final.stac-item
2021-12-16 09:46:17	ga_ls9c_ard_3-2-1_095071_2021-12-16_final.stac-item
2021-12-20 09:25:09	ga_ls9c_ard_3-2-1_091080_2021-12-19_final.stac-item
2021-12-20 11:05:14	ga_ls9c_ard_3-2-1_107083_2021-12-20_final.stac-item
2021-12-29 10:53:53	ga_ls9c_ard_3-2-1_106070_2021-12-29_final.stac-item
2022-01-01 11:26:22	ga_ls9c_ard_3-2-1_111074_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
2022-01-07 10:49:16	ga_ls9c_ard_3-2-1_105074_2022-01-07_final.stac-item
2022-01-15 09:57:00	ga_ls9c_ard_3-2-1_097067_2022-01-15_final.stac-item
2022-01-24 09:58:26	ga_ls9c_ard_3-2-1_096086_2022-01-24_final.stac-item
2022-02-11 11:20:32	ga_ls9c_ard_3-2-1_110075_2022-02-11_final.stac-item
2022-02-21 10:20:14	ga_ls9c_ard_3-2-1_100079_2022-02-21_final.stac-item
2022-02-24 10:49:54	ga_ls9c_ard_3-2-1_105076_2022-02-24_final.stac-item
2022-02-25 09:52:16	ga_ls9c_ard_3-2-1_096071_2022-02-25_final.stac-item
2022-02-26 10:35:55	ga_ls9c_ard_3-2-1_103072_2022-02-26_final.stac-item
2022-03-03 09:16:43	ga_ls9c_ard_3-2-1_090075_2022-03-02_final.stac-item
2022-03-06 09:46:02	ga_ls9c_ard_3-2-1_095071_2022-03-06_final.stac-item
2022-03-06 09:46:50	ga_ls9c_ard_3-2-1_095073_2022-03-06_final.stac-item
2022-03-06 09:50:49	ga_ls9c_ard_3-2-1_095083_2022-03-06_final.stac-item
2022-03-08 09:34:28	ga_ls9c_ard_3-2-1_093073_2022-03-08_final.stac-item
2022-03-11 10:09:46	ga_ls9c_ard_3-2-1_098084_2022-03-11_final.stac-item
2022-03-12 09:13:44	ga_ls9c_ard_3-2-1_089083_2022-03-11_final.stac-item
2022-03-20 11:42:02	ga_ls9c_ard_3-2-1_113083_2022-03-20_final.stac-item
2022-03-29 09:51:44	ga_ls9c_ard_3-2-1_096070_2022-03-29_final.stac-item
2022-04-02 09:29:00	ga_ls9c_ard_3-2-1_092075_2022-04-01_final.stac-item
2022-04-19 11:52:36	ga_ls9c_ard_3-2-1_115079_2022-04-19_final.stac-item
2022-04-20 09:21:16	ga_ls9c_ard_3-2-1_090087_2022-04-19_final.stac-item
2022-05-05 10:15:37	ga_ls9c_ard_3-2-1_099084_2022-05-05_final.stac-item
2022-05-09 09:51:40	ga_ls9c_ard_3-2-1_095086_2022-05-09_final.stac-item
2022-05-23 11:37:57	ga_ls9c_ard_3-2-1_113074_2022-05-23_final.stac-item
2022-05-24 09:06:39	ga_ls9c_ard_3-2-1_088082_2022-05-23_final.stac-item
2022-06-16 09:10:57	ga_ls9c_ard_3-2-1_089077_2022-06-15_final.stac-item
2022-06-23 09:16:56	ga_ls9c_ard_3-2-1_090076_2022-06-22_final.stac-item
2022-06-28 11:14:00	ga_ls9c_ard_3-2-1_109075_2022-06-28_final.stac-item
2022-07-07 09:32:54	ga_ls9c_ard_3-2-1_092085_2022-07-07_final.stac-item
2022-07-15 10:21:29	ga_ls9c_ard_3-2-1_100083_2022-07-15_final.stac-item
2022-08-03 09:11:48	ga_ls9c_ard_3-2-1_089078_2022-08-02_final.stac-item
2022-09-04 09:16:20	ga_ls9c_ard_3-2-1_089089_2022-09-03_final.stac-item
2022-09-13 09:06:36	ga_ls9c_ard_3-2-1_088080_2022-09-12_final.stac-item
2022-09-16 09:34:44	ga_ls9c_ard_3-2-1_093073_2022-09-16_final.stac-item
2022-09-17 10:19:12	ga_ls9c_ard_3-2-1_100076_2022-09-17_final.stac-item
2022-09-17 10:21:36	ga_ls9c_ard_3-2-1_100082_2022-09-17_final.stac-item
2022-09-18 09:22:48	ga_ls9c_ard_3-2-1_091074_2022-09-17_final.stac-item
2022-09-25 09:34:12	ga_ls9c_ard_3-2-1_092087_2022-09-25_final.stac-item
2022-09-27 09:22:39	ga_ls9c_ard_3-2-1_090089_2022-09-26_final.stac-item
2022-10-09 09:41:24	ga_ls9c_ard_3-2-1_094074_2022-10-09_final.stac-item
2022-10-12 10:13:56	ga_ls9c_ard_3-2-1_099078_2022-10-12_final.stac-item
2022-11-02 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-11-02_final.stac-item
2022-11-03 09:37:38	ga_ls9c_ard_3-2-1_093080_2022-11-03_final.stac-item
2022-11-14 10:53:40	ga_ls9c_ard_3-2-1_106069_2022-11-14_final.stac-item
2022-12-04 10:30:05	ga_ls9c_ard_3-2-1_102072_2022-12-04_final.stac-item
2022-12-09 09:14:57	ga_ls9c_ard_3-2-1_089085_2022-12-08_final.stac-item
2022-12-14 09:34:42	ga_ls9c_ard_3-2-1_092088_2022-12-14_final.stac-item
2023-01-09 10:07:23	ga_ls9c_ard_3-2-1_098077_2023-01-09_final.stac-item
2023-01-24 11:05:18	ga_ls9c_ard_3-2-1_107083_2023-01-24_final.stac-item
2023-01-25 10:10:06	ga_ls9c_ard_3-2-1_098084_2023-01-25_final.stac-item
2023-01-27 11:32:40	ga_ls9c_ard_3-2-1_112074_2023-01-27_final.stac-item
2023-02-04 10:41:19	ga_ls9c_ard_3-2-1_104069_2023-02-04_final.stac-item
2023-02-12 11:32:46	ga_ls9c_ard_3-2-1_112074_2023-02-12_final.stac-item
2023-02-21 09:46:20	ga_ls9c_ard_3-2-1_095071_2023-02-21_final.stac-item
2023-03-02 09:41:16	ga_ls9c_ard_3-2-1_094074_2023-03-02_final.stac-item
2023-03-06 10:58:35	ga_ls9c_ard_3-2-1_106082_2023-03-06_final.stac-item
2023-03-13 09:22:38	ga_ls9c_ard_3-2-1_091074_2023-03-12_final.stac-item
2023-04-03 11:23:27	ga_ls9c_ard_3-2-1_110083_2023-04-03_final.stac-item
2023-04-27 10:27:52	ga_ls9c_ard_3-2-1_102068_2023-04-27_final.stac-item
2023-04-30 09:28:12	ga_ls9c_ard_3-2-1_091089_2023-04-29_final.stac-item
2023-05-02 10:51:54	ga_ls9c_ard_3-2-1_105082_2023-05-02_final.stac-item
2023-05-03 09:57:27	ga_ls9c_ard_3-2-1_096085_2023-05-03_final.stac-item
2023-05-16 09:28:04	ga_ls9c_ard_3-2-1_091089_2023-05-15_final.stac-item
2023-05-19 09:57:44	ga_ls9c_ard_3-2-1_096086_2023-05-19_final.stac-item
2023-05-30 09:33:31	ga_ls9c_ard_3-2-1_093072_2023-05-30_final.stac-item
2023-06-03 09:11:35	ga_ls9c_ard_3-2-1_089079_2023-06-02_final.stac-item
2023-06-12 09:06:54	ga_ls9c_ard_3-2-1_088083_2023-06-11_final.stac-item
2023-06-19 09:12:38	ga_ls9c_ard_3-2-1_089082_2023-06-18_final.stac-item
2023-06-25 11:51:43	ga_ls9c_ard_3-2-1_115078_2023-06-25_final.stac-item
2023-06-26 10:52:07	ga_ls9c_ard_3-2-1_106068_2023-06-26_final.stac-item
2023-06-26 10:52:55	ga_ls9c_ard_3-2-1_106070_2023-06-26_final.stac-item
2023-07-03 09:27:34	ga_ls9c_ard_3-2-1_091088_2023-07-02_final.stac-item
2023-07-28 09:17:08	ga_ls9c_ard_3-2-1_090077_2023-07-27_final.stac-item
2023-07-31 11:24:58	ga_ls9c_ard_3-2-1_111072_2023-07-31_final.stac-item
2023-08-07 11:31:14	ga_ls9c_ard_3-2-1_112072_2023-08-07_final.stac-item
2023-08-14 09:56:33	ga_ls9c_ard_3-2-1_097067_2023-08-14_final.stac-item
2023-08-30 09:56:42	ga_ls9c_ard_3-2-1_097067_2023-08-30_final.stac-item
2023-09-06 10:02:57	ga_ls9c_ard_3-2-1_098067_2023-09-06_final.stac-item
2023-09-19 11:11:49	ga_ls9c_ard_3-2-1_109069_2023-09-19_final.stac-item
2023-09-28 11:07:08	ga_ls9c_ard_3-2-1_108073_2023-09-28_final.stac-item
2023-09-29 10:11:08	ga_ls9c_ard_3-2-1_099072_2023-09-29_final.stac-item
2023-10-01 10:04:00	ga_ls9c_ard_3-2-1_097085_2023-10-01_final.stac-item
2023-10-12 11:20:30	ga_ls9c_ard_3-2-1_110075_2023-10-12_final.stac-item
2023-10-14 09:33:40	ga_ls9c_ard_3-2-1_092086_2023-10-14_final.stac-item
2023-11-01 10:56:08	ga_ls9c_ard_3-2-1_106076_2023-11-01_final.stac-item
2023-11-13 11:23:40	ga_ls9c_ard_3-2-1_110083_2023-11-13_final.stac-item
2023-11-18 11:38:39	ga_ls9c_ard_3-2-1_113074_2023-11-18_final.stac-item
2023-11-26 09:13:13	ga_ls9c_ard_3-2-1_089081_2023-11-25_final.stac-item
2023-11-30 10:27:23	ga_ls9c_ard_3-2-1_101081_2023-11-30_final.stac-item
2023-12-03 10:59:04	ga_ls9c_ard_3-2-1_106083_2023-12-03_final.stac-item
2023-12-04 11:37:55	ga_ls9c_ard_3-2-1_113072_2023-12-04_final.stac-item
2023-12-17 09:28:11	ga_ls9c_ard_3-2-1_092072_2023-12-16_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