@incollection{fdi:010071831,
  title = {{L}essons and challenges in land change modeling derived from synthesis of cross-case comparisons},
  author = {{P}ontius, {R}.{G}. and {C}astella, {J}ean-{C}hristophe and de {N}ijs, {T}. and {D}uan, {Z}. and {F}otsing, {E}. and {G}oldstein, {N}. and {K}ok, {K}. and {K}oomen, {E}. and {L}ippitt, {C}. {D}. and {M}c{C}onnell, {W}. and {S}ood, {A}. {M}. and {P}ijanowski, {B} and {V}erburg, {P}. {H}. and {V}eldkamp, {A}. {T}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his chapter presents the lessons and challenges in land change modeling that emerged from years of reflection and numerous panel discussions at scientific conferences concerning a collaborative cross-case comparison in which the authors have participated. {W}e summarize the lessons as nine challenges grouped under three themes: mapping, modeling, and learning. {T}he mapping challenges are: to prepare data appropriately, to select relevant resolutions, and to differentiate types of land change. {T}he modeling challenges are: to separate calibration from validation, to predict small amounts of change, and to interpret the influence of quantity error. {T}he learning challenges are: to use appropriate map comparison measurements, to learn about land change processes, and to collaborate openly. {T}o quantify the pattern validation of predictions of change, we recommend that modelers report as a percentage of the spatial extent the following measurements: misses, hits, wrong hits and false alarms. {T}he chapter explains why the lessons and challenges are essential for the future research agenda concerning land change modeling.},
  keywords = {},
  booktitle = {{T}rends in spatial analysis and modelling},
  numero = {19},
  pages = {143--164},
  address = {{C}ham},
  publisher = {{S}pringer},
  series = {{G}eotechnologies and the {E}nvironment},
  year = {2018},
  DOI = {10.1007/978-3-319-52522-8_8},
  ISBN = {978-3-319-52520-4},
  URL = {https://www.documentation.ird.fr/hor/fdi:010071831},
}