DOI: 10.5281/zenodo.10776891
title: Landsat-based Spectral Indices for pan-EU 2000-2022

description: Description

General description

Here, we present the ARCO (analysis-ready and cloud-optimized) Landsat-based Spectral Indices data cube. Available at 30m resolution from 2000 to 2022, it includes multiple spectral indices and multi-tier predictors (bimonthly, annual, and long-term) for continental Europe, including Ukraine, the UK, and Turkey (excluding Svalbar). This data cube has a broad coverage of indices, each providing unique insights into different aspects, including: surface reflectance, vegetation, water, soil and crop. All data layers are cloud-masked and then gap-filled, ready for analysis, modeling, and mapping applications. Technical details:



Coordinate reference system: EPSG:3035

Bounding box (Xmin, Ymin, Xmax, Ymax): (900,000, 899,000, 7,401,000, 5,501,000)

Spatial resolution: 30m

Image size: 216,700P x 153,400L

File format: Cloud Optimized Geotiff (COG) format.


Considering the data volume, only bimonthly data layers for the years 2000 and 2022 are uploaded. However, all annual and long-term layers are available. For the full data cube, please visit this catalog. Due to Zenodo's storage limits, the data layers are stored in different buckets. Use the identifier-navigation list below to access the bucket of your interest and download the corresponding layers.

Identifier navigation list

This data cube includes 4 tiers of data, depending on the processing extend in the temporal scale:



Tier-1: Bimonthly Landsat reflectance bands2000 (Jan Mar May Jul Sep Nov) 2022 (Jan Mar May Jul Sep Nov)

Tier-2: Bimonthly spectral indices2000 (Jan Mar May Jul Sep Nov) 2022 (Jan Mar May Jul Sep Nov)

Tier-3: Annual predictors



Reflectance bands, NDVI and NDWI P252000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Reflectance bands, NDVI and NDWI P502000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Reflectance bands, NDVI and NDWI P752000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Aggregated spectral indices2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Cumulative spectral indices2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022



Tier-4: Long-term predictors 2000-2022trend P25 P50 P75


Name convention

To ensure consistency and ease of use across the data layers, we follow the standard Ai4SoilHealth and Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way users can search files, prepare data analysis etc, without needing to open files. The fields are:



generic variable name: ndti.min.slopes = the long term slope of minNDTI

variable procedure combination: glad.landsat.ard2.seasconv.yearly.min.theilslopes - theil slopes calculated from yearly minimum values of NDTI

Position in the probability distribution/variable type: m = mean | sd = standard deviation | n = number of observations | qa = quality assessment

Spatial support: 30m

Depth reference: s = surface

Time reference begin time: 20000101 = 2000-01-01

Time reference end time: 20221231 = 2022-12-31

Bounding box: eu = europe (without Svalbar)

EPSG code: epsg.3035

Version code: v20231218 = 2023-12-18 (creation date)


Citation

Please cite this dataset using the DOI: [10.5281/zenodo.10776891], which represents all versions of this dataset. This ensures your citation remains up to date with the latest version.

Support

If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a GitHub issue!

Long-term spectral indices trend

On this landing page of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube,  four long-term spectral indices trend data are stored, as Zenodo doesn't allow empty buckets. Therefore, this page serves not only as the landing page for the entire dataset but also as the bucket for the long-term trend of spectral indices.