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 09:36:37	ga_ls9c_ard_3-2-1_093076_2021-11-05_final.stac-item
2021-11-10 09:38:42	ga_ls9c_ard_3-2-1_094075_2021-11-10_final.stac-item
2021-11-10 09:39:05	ga_ls9c_ard_3-2-1_094076_2021-11-10_final.stac-item
2021-11-17 09:24:52	ga_ls9c_ard_3-2-1_091081_2021-11-16_final.stac-item
2021-11-22 09:27:39	ga_ls9c_ard_3-2-1_091082_2021-11-21_final.stac-item
2021-12-18 09:37:30	ga_ls9c_ard_3-2-1_093080_2021-12-18_final.stac-item
2021-12-25 09:42:07	ga_ls9c_ard_3-2-1_094076_2021-12-25_final.stac-item
2021-12-27 09:31:21	ga_ls9c_ard_3-2-1_092080_2021-12-27_final.stac-item
2022-01-03 09:37:31	ga_ls9c_ard_3-2-1_093080_2022-01-03_final.stac-item
2022-01-10 09:41:40	ga_ls9c_ard_3-2-1_094075_2022-01-10_final.stac-item
2022-01-12 09:31:18	ga_ls9c_ard_3-2-1_092080_2022-01-12_final.stac-item
2022-01-19 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-01-19_final.stac-item
2022-01-19 09:37:29	ga_ls9c_ard_3-2-1_093080_2022-01-19_final.stac-item
2022-01-26 09:42:06	ga_ls9c_ard_3-2-1_094076_2022-01-26_final.stac-item
2022-01-28 09:31:20	ga_ls9c_ard_3-2-1_092080_2022-01-28_final.stac-item
2022-02-04 09:35:54	ga_ls9c_ard_3-2-1_093076_2022-02-04_final.stac-item
2022-02-04 09:37:30	ga_ls9c_ard_3-2-1_093080_2022-02-04_final.stac-item
2022-02-11 09:41:39	ga_ls9c_ard_3-2-1_094075_2022-02-11_final.stac-item
2022-02-13 09:31:16	ga_ls9c_ard_3-2-1_092080_2022-02-13_final.stac-item
2022-02-20 09:35:47	ga_ls9c_ard_3-2-1_093076_2022-02-20_final.stac-item
2022-02-27 09:41:29	ga_ls9c_ard_3-2-1_094075_2022-02-27_final.stac-item
2022-02-27 09:41:53	ga_ls9c_ard_3-2-1_094076_2022-02-27_final.stac-item
2022-03-01 09:31:05	ga_ls9c_ard_3-2-1_092080_2022-03-01_final.stac-item
2022-03-08 09:37:16	ga_ls9c_ard_3-2-1_093080_2022-03-08_final.stac-item
2022-03-24 09:35:36	ga_ls9c_ard_3-2-1_093076_2022-03-24_final.stac-item
2022-04-02 09:31:00	ga_ls9c_ard_3-2-1_092080_2022-04-02_final.stac-item
2022-04-09 09:35:33	ga_ls9c_ard_3-2-1_093076_2022-04-09_final.stac-item
2022-04-16 09:41:39	ga_ls9c_ard_3-2-1_094076_2022-04-16_final.stac-item
2022-04-18 09:30:52	ga_ls9c_ard_3-2-1_092080_2022-04-18_final.stac-item
2022-04-25 09:35:24	ga_ls9c_ard_3-2-1_093076_2022-04-25_final.stac-item
2022-04-25 09:36:59	ga_ls9c_ard_3-2-1_093080_2022-04-25_final.stac-item
2022-05-04 09:30:46	ga_ls9c_ard_3-2-1_092080_2022-05-04_final.stac-item
2022-05-11 09:35:17	ga_ls9c_ard_3-2-1_093076_2022-05-11_final.stac-item
2022-05-11 09:36:53	ga_ls9c_ard_3-2-1_093080_2022-05-11_final.stac-item
2022-05-18 09:41:22	ga_ls9c_ard_3-2-1_094076_2022-05-18_final.stac-item
2022-05-20 09:30:34	ga_ls9c_ard_3-2-1_092080_2022-05-20_final.stac-item
2022-06-03 09:40:57	ga_ls9c_ard_3-2-1_094075_2022-06-03_final.stac-item
2022-06-03 09:41:21	ga_ls9c_ard_3-2-1_094076_2022-06-03_final.stac-item
2022-06-19 09:41:07	ga_ls9c_ard_3-2-1_094075_2022-06-19_final.stac-item
2022-06-19 09:41:31	ga_ls9c_ard_3-2-1_094076_2022-06-19_final.stac-item
2022-06-28 09:35:31	ga_ls9c_ard_3-2-1_093076_2022-06-28_final.stac-item
2022-07-05 09:41:41	ga_ls9c_ard_3-2-1_094076_2022-07-05_final.stac-item
2022-08-22 09:42:03	ga_ls9c_ard_3-2-1_094076_2022-08-22_final.stac-item
2022-08-31 09:37:28	ga_ls9c_ard_3-2-1_093080_2022-08-31_final.stac-item
2022-09-09 09:31:16	ga_ls9c_ard_3-2-1_092080_2022-09-09_final.stac-item
2022-09-16 09:37:32	ga_ls9c_ard_3-2-1_093080_2022-09-16_final.stac-item
2022-10-18 09:36:05	ga_ls9c_ard_3-2-1_093076_2022-10-18_final.stac-item
2022-10-18 09:37:41	ga_ls9c_ard_3-2-1_093080_2022-10-18_final.stac-item
2022-10-25 09:41:52	ga_ls9c_ard_3-2-1_094075_2022-10-25_final.stac-item
2022-11-10 09:41:53	ga_ls9c_ard_3-2-1_094075_2022-11-10_final.stac-item
2022-11-12 09:31:31	ga_ls9c_ard_3-2-1_092080_2022-11-12_final.stac-item
2022-11-28 09:31:29	ga_ls9c_ard_3-2-1_092080_2022-11-28_final.stac-item
2022-12-14 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-14_final.stac-item
2022-12-30 09:31:30	ga_ls9c_ard_3-2-1_092080_2022-12-30_final.stac-item
2022-12-30 09:31:54	ga_ls9c_ard_3-2-1_092081_2022-12-30_final.stac-item
2023-01-13 09:41:50	ga_ls9c_ard_3-2-1_094075_2023-01-13_final.stac-item
2023-01-15 09:31:26	ga_ls9c_ard_3-2-1_092080_2023-01-15_final.stac-item
2023-01-29 09:41:51	ga_ls9c_ard_3-2-1_094075_2023-01-29_final.stac-item
2023-01-31 09:31:55	ga_ls9c_ard_3-2-1_092081_2023-01-31_final.stac-item
2023-02-14 09:41:54	ga_ls9c_ard_3-2-1_094075_2023-02-14_final.stac-item
2023-02-16 09:31:54	ga_ls9c_ard_3-2-1_092081_2023-02-16_final.stac-item
2023-02-23 09:37:31	ga_ls9c_ard_3-2-1_093080_2023-02-23_final.stac-item
2023-03-04 09:31:17	ga_ls9c_ard_3-2-1_092080_2023-03-04_final.stac-item
2023-03-18 09:41:34	ga_ls9c_ard_3-2-1_094075_2023-03-18_final.stac-item
2023-03-20 09:31:11	ga_ls9c_ard_3-2-1_092080_2023-03-20_final.stac-item
2023-03-20 09:31:35	ga_ls9c_ard_3-2-1_092081_2023-03-20_final.stac-item
2023-04-03 09:41:23	ga_ls9c_ard_3-2-1_094075_2023-04-03_final.stac-item
2023-04-05 09:31:00	ga_ls9c_ard_3-2-1_092080_2023-04-05_final.stac-item
2023-04-19 09:41:16	ga_ls9c_ard_3-2-1_094075_2023-04-19_final.stac-item
2023-04-21 09:30:54	ga_ls9c_ard_3-2-1_092080_2023-04-21_final.stac-item
2023-04-21 09:31:18	ga_ls9c_ard_3-2-1_092081_2023-04-21_final.stac-item
2023-05-05 09:41:04	ga_ls9c_ard_3-2-1_094075_2023-05-05_final.stac-item
2023-05-07 09:30:42	ga_ls9c_ard_3-2-1_092080_2023-05-07_final.stac-item
2023-05-07 09:31:06	ga_ls9c_ard_3-2-1_092081_2023-05-07_final.stac-item
2023-05-21 09:40:57	ga_ls9c_ard_3-2-1_094075_2023-05-21_final.stac-item
2023-05-23 09:30:33	ga_ls9c_ard_3-2-1_092080_2023-05-23_final.stac-item
2023-05-23 09:30:57	ga_ls9c_ard_3-2-1_092081_2023-05-23_final.stac-item
2023-06-06 09:40:52	ga_ls9c_ard_3-2-1_094075_2023-06-06_final.stac-item
2023-06-15 09:36:33	ga_ls9c_ard_3-2-1_093080_2023-06-15_final.stac-item
2023-06-22 09:40:45	ga_ls9c_ard_3-2-1_094075_2023-06-22_final.stac-item
2023-06-24 09:30:46	ga_ls9c_ard_3-2-1_092081_2023-06-24_final.stac-item
2023-07-26 09:30:39	ga_ls9c_ard_3-2-1_092080_2023-07-26_final.stac-item
2023-09-19 09:37:19	ga_ls9c_ard_3-2-1_093080_2023-09-19_final.stac-item
2023-09-28 09:31:03	ga_ls9c_ard_3-2-1_092080_2023-09-28_final.stac-item
2023-10-05 09:37:21	ga_ls9c_ard_3-2-1_093080_2023-10-05_final.stac-item
2023-10-21 09:37:29	ga_ls9c_ard_3-2-1_093080_2023-10-21_final.stac-item
2023-10-30 09:31:14	ga_ls9c_ard_3-2-1_092080_2023-10-30_final.stac-item
2023-11-06 09:37:24	ga_ls9c_ard_3-2-1_093080_2023-11-06_final.stac-item
2023-11-15 09:31:13	ga_ls9c_ard_3-2-1_092080_2023-11-15_final.stac-item
2023-11-22 09:37:30	ga_ls9c_ard_3-2-1_093080_2023-11-22_final.stac-item
2024-01-02 09:31:20	ga_ls9c_ard_3-2-1_092080_2024-01-02_final.stac-item
2024-01-18 09:31:20	ga_ls9c_ard_3-2-1_092080_2024-01-18_final.stac-item
2024-02-10 09:37:32	ga_ls9c_ard_3-2-1_093080_2024-02-10_final.stac-item
2024-02-19 09:31:13	ga_ls9c_ard_3-2-1_092080_2024-02-19_final.stac-item
2024-02-26 09:37:21	ga_ls9c_ard_3-2-1_093080_2024-02-26_final.stac-item
2024-04-23 09:30:42	ga_ls9c_ard_3-2-1_092080_2024-04-23_final.stac-item
2024-04-30 09:36:51	ga_ls9c_ard_3-2-1_093080_2024-04-30_final.stac-item
2024-05-09 09:30:40	ga_ls9c_ard_3-2-1_092080_2024-05-09_final.stac-item
2024-05-16 09:36:44	ga_ls9c_ard_3-2-1_093080_2024-05-16_nrt.stac-item
2024-05-25 09:30:28	ga_ls9c_ard_3-2-1_092080_2024-05-25_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