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
2022-01-30 09:16:35	ga_ls9c_ard_3-2-1_090074_2022-01-29_final.stac-item
2022-01-30 09:21:46	ga_ls9c_ard_3-2-1_090087_2022-01-29_final.stac-item
2022-01-31 09:58:38	ga_ls9c_ard_3-2-1_097071_2022-01-31_final.stac-item
2022-02-15 09:16:30	ga_ls9c_ard_3-2-1_090074_2022-02-14_final.stac-item
2022-03-28 09:10:04	ga_ls9c_ard_3-2-1_089074_2022-03-27_final.stac-item
2022-04-04 10:57:55	ga_ls9c_ard_3-2-1_106081_2022-04-04_final.stac-item
2022-04-19 10:08:55	ga_ls9c_ard_3-2-1_099067_2022-04-19_final.stac-item
2022-04-25 09:37:23	ga_ls9c_ard_3-2-1_093081_2022-04-25_final.stac-item
2022-05-11 09:37:17	ga_ls9c_ard_3-2-1_093081_2022-05-11_final.stac-item
2022-05-20 09:28:34	ga_ls9c_ard_3-2-1_092075_2022-05-19_final.stac-item
2022-06-07 09:21:02	ga_ls9c_ard_3-2-1_090087_2022-06-06_final.stac-item
2022-07-01 10:06:49	ga_ls9c_ard_3-2-1_098077_2022-07-01_final.stac-item
2022-07-23 09:34:11	ga_ls9c_ard_3-2-1_092088_2022-07-23_final.stac-item
2022-08-12 09:07:18	ga_ls9c_ard_3-2-1_088082_2022-08-11_final.stac-item
2023-01-29 09:45:03	ga_ls9c_ard_3-2-1_094083_2023-01-29_final.stac-item
2023-01-29 09:46:14	ga_ls9c_ard_3-2-1_094086_2023-01-29_final.stac-item
2023-01-29 09:46:38	ga_ls9c_ard_3-2-1_094087_2023-01-29_final.stac-item
2023-02-04 09:06:50	ga_ls9c_ard_3-2-1_088080_2023-02-03_final.stac-item
2023-02-05 09:46:30	ga_ls9c_ard_3-2-1_095071_2023-02-05_final.stac-item
2023-02-07 09:40:32	ga_ls9c_ard_3-2-1_093087_2023-02-07_final.stac-item
2023-02-14 09:40:18	ga_ls9c_ard_3-2-1_094071_2023-02-14_final.stac-item
2023-02-14 09:41:06	ga_ls9c_ard_3-2-1_094073_2023-02-14_final.stac-item
2023-04-21 09:34:30	ga_ls9c_ard_3-2-1_092089_2023-04-21_final.stac-item
2023-04-21 09:34:54	ga_ls9c_ard_3-2-1_092090_2023-04-21_final.stac-item
2023-04-24 09:57:24	ga_ls9c_ard_3-2-1_097069_2023-04-24_final.stac-item
2023-04-24 11:37:52	ga_ls9c_ard_3-2-1_113073_2023-04-24_final.stac-item
2023-04-24 11:41:04	ga_ls9c_ard_3-2-1_113081_2023-04-24_final.stac-item
2023-04-25 09:06:09	ga_ls9c_ard_3-2-1_088080_2023-04-24_final.stac-item
2023-04-25 09:07:21	ga_ls9c_ard_3-2-1_088083_2023-04-24_final.stac-item
2023-05-28 11:23:10	ga_ls9c_ard_3-2-1_111068_2023-05-28_final.stac-item
2023-05-28 11:29:33	ga_ls9c_ard_3-2-1_111084_2023-05-28_final.stac-item
2023-07-05 10:49:20	ga_ls9c_ard_3-2-1_105076_2023-07-05_final.stac-item
2023-07-29 10:01:36	ga_ls9c_ard_3-2-1_097080_2023-07-29_final.stac-item
2023-07-29 11:37:42	ga_ls9c_ard_3-2-1_113073_2023-07-29_final.stac-item
2023-08-04 11:02:42	ga_ls9c_ard_3-2-1_107078_2023-08-04_final.stac-item
2023-08-05 10:09:05	ga_ls9c_ard_3-2-1_098083_2023-08-05_final.stac-item
2023-08-06 09:09:52	ga_ls9c_ard_3-2-1_089074_2023-08-05_final.stac-item
2023-08-06 09:10:40	ga_ls9c_ard_3-2-1_089076_2023-08-05_final.stac-item
2023-08-06 09:13:28	ga_ls9c_ard_3-2-1_089083_2023-08-05_final.stac-item
2023-10-14 09:27:41	ga_ls9c_ard_3-2-1_092071_2023-10-13_final.stac-item
2023-10-14 09:28:29	ga_ls9c_ard_3-2-1_092073_2023-10-13_final.stac-item
2023-10-14 09:33:16	ga_ls9c_ard_3-2-1_092085_2023-10-14_final.stac-item
2023-10-14 09:35:16	ga_ls9c_ard_3-2-1_092090_2023-10-14_final.stac-item
2023-10-15 10:16:32	ga_ls9c_ard_3-2-1_099085_2023-10-15_final.stac-item
2023-10-16 09:16:32	ga_ls9c_ard_3-2-1_090074_2023-10-15_final.stac-item
2023-10-16 09:21:20	ga_ls9c_ard_3-2-1_090086_2023-10-15_final.stac-item
2023-10-16 09:21:43	ga_ls9c_ard_3-2-1_090087_2023-10-15_final.stac-item
2023-10-17 11:38:17	ga_ls9c_ard_3-2-1_113073_2023-10-17_final.stac-item
2023-10-18 09:06:35	ga_ls9c_ard_3-2-1_088080_2023-10-17_final.stac-item
2023-10-18 09:06:59	ga_ls9c_ard_3-2-1_088081_2023-10-17_final.stac-item
2023-10-18 09:07:23	ga_ls9c_ard_3-2-1_088082_2023-10-17_final.stac-item
2023-10-18 09:07:47	ga_ls9c_ard_3-2-1_088083_2023-10-17_final.stac-item
2023-10-19 09:46:15	ga_ls9c_ard_3-2-1_095071_2023-10-19_final.stac-item
2023-10-19 11:25:08	ga_ls9c_ard_3-2-1_111071_2023-10-19_final.stac-item
2023-10-20 10:33:54	ga_ls9c_ard_3-2-1_102082_2023-10-20_final.stac-item
2023-10-21 09:40:17	ga_ls9c_ard_3-2-1_093087_2023-10-21_final.stac-item
2023-10-21 11:11:59	ga_ls9c_ard_3-2-1_109069_2023-10-21_final.stac-item
2023-10-23 11:05:36	ga_ls9c_ard_3-2-1_107084_2023-10-23_final.stac-item
2023-10-25 09:11:09	ga_ls9c_ard_3-2-1_089076_2023-10-24_final.stac-item
2023-10-25 09:16:44	ga_ls9c_ard_3-2-1_089090_2023-10-24_final.stac-item
2023-10-25 10:52:50	ga_ls9c_ard_3-2-1_105083_2023-10-25_final.stac-item
2023-10-26 11:32:05	ga_ls9c_ard_3-2-1_112073_2023-10-26_final.stac-item
2023-10-26 11:36:29	ga_ls9c_ard_3-2-1_112084_2023-10-26_final.stac-item
2023-10-28 11:18:07	ga_ls9c_ard_3-2-1_110069_2023-10-28_final.stac-item
2023-10-28 11:22:06	ga_ls9c_ard_3-2-1_110079_2023-10-28_final.stac-item
2023-10-28 11:24:30	ga_ls9c_ard_3-2-1_110085_2023-10-28_final.stac-item
2023-10-30 09:27:39	ga_ls9c_ard_3-2-1_092071_2023-10-29_final.stac-item
2023-10-30 09:28:26	ga_ls9c_ard_3-2-1_092073_2023-10-29_final.stac-item
2023-10-30 09:32:50	ga_ls9c_ard_3-2-1_092084_2023-10-30_final.stac-item
2023-10-30 09:34:50	ga_ls9c_ard_3-2-1_092089_2023-10-30_final.stac-item
2023-10-30 09:35:14	ga_ls9c_ard_3-2-1_092090_2023-10-30_final.stac-item
2023-10-31 10:16:29	ga_ls9c_ard_3-2-1_099085_2023-10-31_final.stac-item
2023-11-01 09:16:27	ga_ls9c_ard_3-2-1_090074_2023-10-31_final.stac-item
2023-11-01 09:21:38	ga_ls9c_ard_3-2-1_090087_2023-10-31_final.stac-item
2023-11-02 11:38:10	ga_ls9c_ard_3-2-1_113073_2023-11-02_final.stac-item
2023-11-03 09:07:39	ga_ls9c_ard_3-2-1_088083_2023-11-02_final.stac-item
2023-11-03 10:42:56	ga_ls9c_ard_3-2-1_104074_2023-11-03_final.stac-item
2023-11-04 09:52:31	ga_ls9c_ard_3-2-1_095087_2023-11-04_final.stac-item
2023-11-15 09:27:38	ga_ls9c_ard_3-2-1_092071_2023-11-14_final.stac-item
2023-11-15 09:28:26	ga_ls9c_ard_3-2-1_092073_2023-11-14_final.stac-item
2023-11-15 09:35:13	ga_ls9c_ard_3-2-1_092090_2023-11-15_final.stac-item
2023-11-16 10:16:29	ga_ls9c_ard_3-2-1_099085_2023-11-16_final.stac-item
2023-11-17 09:16:29	ga_ls9c_ard_3-2-1_090074_2023-11-16_final.stac-item
2023-11-17 10:57:22	ga_ls9c_ard_3-2-1_106079_2023-11-17_final.stac-item
2023-11-17 10:57:46	ga_ls9c_ard_3-2-1_106080_2023-11-17_final.stac-item
2023-11-17 10:58:10	ga_ls9c_ard_3-2-1_106081_2023-11-17_final.stac-item
2023-11-17 10:58:34	ga_ls9c_ard_3-2-1_106082_2023-11-17_final.stac-item
2023-11-18 11:38:15	ga_ls9c_ard_3-2-1_113073_2023-11-18_final.stac-item
2023-11-19 10:42:39	ga_ls9c_ard_3-2-1_104073_2023-11-19_final.stac-item
2023-11-20 09:48:14	ga_ls9c_ard_3-2-1_095076_2023-11-20_final.stac-item
2023-11-21 10:31:07	ga_ls9c_ard_3-2-1_102075_2023-11-21_final.stac-item
2023-11-22 09:36:42	ga_ls9c_ard_3-2-1_093078_2023-11-22_final.stac-item
2023-11-24 09:25:34	ga_ls9c_ard_3-2-1_091081_2023-11-23_final.stac-item
2023-11-24 09:26:22	ga_ls9c_ard_3-2-1_091083_2023-11-23_final.stac-item
2023-11-24 11:02:51	ga_ls9c_ard_3-2-1_107077_2023-11-24_final.stac-item
2023-11-25 10:04:51	ga_ls9c_ard_3-2-1_098071_2023-11-25_final.stac-item
2023-11-25 10:06:50	ga_ls9c_ard_3-2-1_098076_2023-11-25_final.stac-item
2023-11-26 09:11:14	ga_ls9c_ard_3-2-1_089076_2023-11-25_final.stac-item
2023-11-26 09:16:25	ga_ls9c_ard_3-2-1_089089_2023-11-25_final.stac-item
2023-11-26 09:16:49	ga_ls9c_ard_3-2-1_089090_2023-11-25_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