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

82 results

Time (local)	Label
2021-11-16 10:19:55	ga_ls9c_ard_3-2-1_100072_2021-11-16_final.stac-item
2021-12-11 11:07:53	ga_ls9c_ard_3-2-1_108074_2021-12-11_final.stac-item
2022-01-01 11:29:10	ga_ls9c_ard_3-2-1_111081_2022-01-01_final.stac-item
2022-01-17 09:52:14	ga_ls9c_ard_3-2-1_095086_2022-01-17_final.stac-item
2022-02-10 10:36:05	ga_ls9c_ard_3-2-1_103072_2022-02-10_final.stac-item
2022-02-23 11:47:08	ga_ls9c_ard_3-2-1_114080_2022-02-23_final.stac-item
2022-03-01 11:09:34	ga_ls9c_ard_3-2-1_108079_2022-03-01_final.stac-item
2022-03-02 11:52:01	ga_ls9c_ard_3-2-1_115077_2022-03-02_final.stac-item
2022-04-09 09:38:21	ga_ls9c_ard_3-2-1_093083_2022-04-09_final.stac-item
2022-05-17 10:34:13	ga_ls9c_ard_3-2-1_103069_2022-05-17_final.stac-item
2022-05-20 11:06:39	ga_ls9c_ard_3-2-1_108073_2022-05-20_final.stac-item
2022-05-25 09:45:31	ga_ls9c_ard_3-2-1_095071_2022-05-25_final.stac-item
2022-05-25 11:25:59	ga_ls9c_ard_3-2-1_111075_2022-05-25_final.stac-item
2022-07-02 10:46:05	ga_ls9c_ard_3-2-1_105067_2022-07-02_final.stac-item
2022-07-03 11:32:08	ga_ls9c_ard_3-2-1_112074_2022-07-03_final.stac-item
2022-07-18 10:46:28	ga_ls9c_ard_3-2-1_105068_2022-07-18_final.stac-item
2022-07-27 09:07:08	ga_ls9c_ard_3-2-1_088082_2022-07-26_final.stac-item
2022-08-03 09:11:48	ga_ls9c_ard_3-2-1_089078_2022-08-02_final.stac-item
2022-08-18 10:03:34	ga_ls9c_ard_3-2-1_098068_2022-08-18_final.stac-item
2022-08-22 11:22:55	ga_ls9c_ard_3-2-1_110081_2022-08-22_final.stac-item
2022-08-23 10:25:42	ga_ls9c_ard_3-2-1_101077_2022-08-23_final.stac-item
2022-08-26 09:16:56	ga_ls9c_ard_3-2-1_090075_2022-08-25_final.stac-item
2022-08-26 09:21:43	ga_ls9c_ard_3-2-1_090087_2022-08-25_final.stac-item
2022-08-30 10:30:42	ga_ls9c_ard_3-2-1_102074_2022-08-30_final.stac-item
2022-09-04 10:47:14	ga_ls9c_ard_3-2-1_105069_2022-09-04_final.stac-item
2022-09-07 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-09-07_final.stac-item
2022-09-16 09:33:56	ga_ls9c_ard_3-2-1_093071_2022-09-16_final.stac-item
2022-09-19 10:04:04	ga_ls9c_ard_3-2-1_098069_2022-09-19_final.stac-item
2022-09-19 10:08:27	ga_ls9c_ard_3-2-1_098080_2022-09-19_final.stac-item
2022-09-27 10:55:32	ga_ls9c_ard_3-2-1_106074_2022-09-27_final.stac-item
2022-10-04 09:26:50	ga_ls9c_ard_3-2-1_091084_2022-10-03_final.stac-item
2022-10-17 10:30:31	ga_ls9c_ard_3-2-1_102073_2022-10-17_final.stac-item
2022-10-29 10:56:01	ga_ls9c_ard_3-2-1_106075_2022-10-29_final.stac-item
2022-10-30 10:00:00	ga_ls9c_ard_3-2-1_097074_2022-10-30_final.stac-item
2022-10-31 10:45:39	ga_ls9c_ard_3-2-1_104080_2022-10-31_final.stac-item
2022-11-22 10:03:49	ga_ls9c_ard_3-2-1_098068_2022-11-22_final.stac-item
2022-11-28 09:31:29	ga_ls9c_ard_3-2-1_092080_2022-11-28_final.stac-item
2022-11-28 11:06:23	ga_ls9c_ard_3-2-1_108070_2022-11-28_final.stac-item
2022-11-29 10:13:09	ga_ls9c_ard_3-2-1_099076_2022-11-29_final.stac-item
2022-12-04 10:29:17	ga_ls9c_ard_3-2-1_102070_2022-12-04_final.stac-item
2022-12-25 09:12:07	ga_ls9c_ard_3-2-1_089078_2022-12-24_final.stac-item
2023-01-03 10:44:52	ga_ls9c_ard_3-2-1_104078_2023-01-03_final.stac-item
2023-01-08 11:05:24	ga_ls9c_ard_3-2-1_107083_2023-01-08_final.stac-item
2023-02-18 09:21:06	ga_ls9c_ard_3-2-1_090085_2023-02-17_final.stac-item
2023-03-02 09:40:29	ga_ls9c_ard_3-2-1_094072_2023-03-02_final.stac-item
2023-03-07 10:04:08	ga_ls9c_ard_3-2-1_097085_2023-03-07_final.stac-item
2023-03-23 11:42:08	ga_ls9c_ard_3-2-1_113083_2023-03-23_final.stac-item
2023-04-08 09:58:42	ga_ls9c_ard_3-2-1_097072_2023-04-08_final.stac-item
2023-05-01 10:03:28	ga_ls9c_ard_3-2-1_098069_2023-05-01_final.stac-item
2023-05-02 09:15:48	ga_ls9c_ard_3-2-1_089089_2023-05-01_final.stac-item
2023-05-29 10:29:32	ga_ls9c_ard_3-2-1_102073_2023-05-29_final.stac-item
2023-07-30 09:06:00	ga_ls9c_ard_3-2-1_088080_2023-07-29_final.stac-item
2023-08-09 09:39:35	ga_ls9c_ard_3-2-1_094071_2023-08-09_final.stac-item
2023-08-11 11:08:07	ga_ls9c_ard_3-2-1_108076_2023-08-11_final.stac-item
2023-08-16 11:24:15	ga_ls9c_ard_3-2-1_111070_2023-08-16_final.stac-item
2023-08-20 09:26:40	ga_ls9c_ard_3-2-1_091085_2023-08-19_final.stac-item
2023-09-26 09:39:51	ga_ls9c_ard_3-2-1_094071_2023-09-26_final.stac-item
2023-09-30 09:21:55	ga_ls9c_ard_3-2-1_090088_2023-09-29_final.stac-item
2023-09-30 09:22:19	ga_ls9c_ard_3-2-1_090089_2023-09-29_final.stac-item
2023-09-30 10:55:37	ga_ls9c_ard_3-2-1_106075_2023-09-30_final.stac-item
2023-10-05 11:13:50	ga_ls9c_ard_3-2-1_109074_2023-10-05_final.stac-item
2023-10-14 09:28:05	ga_ls9c_ard_3-2-1_092072_2023-10-13_final.stac-item
2023-10-22 10:20:21	ga_ls9c_ard_3-2-1_100079_2023-10-22_final.stac-item
2023-10-30 09:28:50	ga_ls9c_ard_3-2-1_092074_2023-10-29_final.stac-item
2023-11-08 09:26:39	ga_ls9c_ard_3-2-1_091084_2023-11-07_final.stac-item
2023-11-17 09:22:05	ga_ls9c_ard_3-2-1_090088_2023-11-16_final.stac-item
2023-11-25 10:09:38	ga_ls9c_ard_3-2-1_098083_2023-11-25_final.stac-item
2023-12-15 11:20:13	ga_ls9c_ard_3-2-1_110074_2023-12-15_final.stac-item
2024-01-02 09:29:44	ga_ls9c_ard_3-2-1_092076_2024-01-01_final.stac-item
2024-01-03 11:51:28	ga_ls9c_ard_3-2-1_115075_2024-01-03_final.stac-item
2024-01-24 10:30:40	ga_ls9c_ard_3-2-1_102074_2024-01-24_final.stac-item
2024-02-05 09:17:25	ga_ls9c_ard_3-2-1_090076_2024-02-04_final.stac-item
2024-02-18 10:27:16	ga_ls9c_ard_3-2-1_101081_2024-02-18_final.stac-item
2024-02-20 10:12:04	ga_ls9c_ard_3-2-1_099074_2024-02-20_final.stac-item
2024-03-07 11:51:23	ga_ls9c_ard_3-2-1_115075_2024-03-07_final.stac-item
2024-03-13 11:14:41	ga_ls9c_ard_3-2-1_109076_2024-03-13_final.stac-item
2024-03-17 10:47:10	ga_ls9c_ard_3-2-1_105069_2024-03-17_final.stac-item
2024-04-11 09:06:17	ga_ls9c_ard_3-2-1_088080_2024-04-10_final.stac-item
2024-04-16 09:21:57	ga_ls9c_ard_3-2-1_091073_2024-04-15_final.stac-item
2024-05-01 10:16:55	ga_ls9c_ard_3-2-1_100072_2024-05-01_nrt.stac-item
2024-05-02 10:59:46	ga_ls9c_ard_3-2-1_107071_2024-05-02_nrt.stac-item
2024-05-06 10:33:51	ga_ls9c_ard_3-2-1_103068_2024-05-06_nrt.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