Dr. Maximilian Lange 

Academic Staff

Department Remote Sensing

Helmholtz Centre for Environmental Research - UFZ
Permoserstraße 15
04318 Leipzig

Phone +49 341 6025 1968

maximilian.lange@ufz.de

Maximilian Lange

Research interests

  • Derivation of vegetation dynamics, land-use and land-use intensity with remote sensing and modelling techniques
  • Operation of ground-based automated multi- and hyperspectral sensor systems for satellite product validation
  • Organisation of big data: remote sensing datasets
  • Software maintaince: phenex and phenmod

Recent projects

  • 2019 - 2021 Mapping land-use intensities of grasslands in Germany using Copernicus Sentinel-2 time series: land-use-intensity

Curriculum Vitae

since 2019

UFZ Leipzig, Academic Staff

2016 - 2018

UFZ Leipzig, Ph.D., Project: EU 'Ecopotential' ('Horizon 2020'). 'Derivation of bio-physical variables from remotely sensed imagery' (2015-2018)

2012 - 2015

UFZ Leipzig, Ph.D., Project ‘Validierung von Sentinel-Produkten auf Basis kontinuierlicher spektraler und Eddy-Flux-Messungen’ of BMWi program ‚Vorbereitung der wissenschaftlichen und kommerziellen Nutzung der Sentinel-Missionen und nationalen Missionen‘

2010 - 2011

Department of Computational Landscape Ecology, Helmholtz-Centre for Environmental Research - UFZ, Leipzig: Research Assistant

2007 - 2012

Studies of Information Technologies at HTWK Leipzig, Germany, Degree: Bachelor and Master of Science

Peer-reviewed Publications

Lange M, Feilhauer H, Kühn I, Doktor D (2022) Mapping land-use intensity of grasslands in Germany with machine learning and Sentinel-2 time series. Remote Sensing of Environment 277:112888, doi:10.1016/j.rse.2022.112888 (doi)

Arnold R, Haug J-K, Lange M, Friesen J (2020). Impact of forest cover change on available water resources: Long-term forest cover dynamics of the semi-arid Dhofar cloud forest, Oman. Frontiers in Earth Science 8:299. doi: 10.3389/feart.2020.00299 (doi)

Preidl S, Lange M, Doktor D (2019) Introducing APiC for regionalised land-use mapping on the national scale using Sentinel-2A imagery. Remote Sensing of Environment 240:111673, doi:10.1016/j.rse.2020.111673 (doi)

Lange M, Dechant B, Rebmann C, Vohland M, Cuntz M, Doktor D (2017) Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors. Sensors 17(8):1855, doi:10.3390/s17081855 (doi)

Padró J-C, Pons X, Aragonés D, Díaz-Delgado R, García D, Bustamante J, Pesquer L, Domingo-Marimon C, González-Guerrero Ò, Cristóbal J, Doktor D, Lange M (2017) Radiometric Correction of Simultaneously Acquired Landsat-7/Landsat-8 and Sentinel-2A Imagery Using Pseudoinvariant Areas (PIA): Contributing to the Landsat Time Series Legacy. Remote Sensing 2017, 9(12):1319; doi:10.3390/rs9121319 (doi)

Lange M
, Schaber J, Marx A, Jäckel G, Badeck FW, Seppelt R, Doktor D (2016) Simulation of forest tree species’ bud burst dates for different climate scenarios: chilling requirements and photo-period may limit bud burst advancement. International Journal of Biometeorology 60(11):1711-1726, doi:10.1007/s00484-016-1161-8 (doi)

Other Publications

Lange M, Doktor D (2017) phenex: Auxiliary Functions for Phenological Data Analysis. R package version 1.4-5, https://CRAN.R-project.org/package=phenex (last access: 12 Feb 2020)

Lange M (2013) phenmod: Auxiliary functions for phenological data processing, modelling and result handling. R package version 1.2-3, http://CRAN.R-project.org/package=phenmod (last access: 12 Feb 2020)

Lange M (2012) sperich: Auxiliary Functions to Estimate Centers of Biodiversity. R package version 1.5-8, http://CRAN.R-project.org/package=sperich (last access: 12 Feb 2020)