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\begin{document}

\title{Backstory:~Mapping~global cropland and field size}



\author[1]{Linda See}%
\author[1]{Steffen Fritz}%
\affil[1]{Ecosystem Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria}%


\vspace{-1em}



  
  \date{June 17, 2024}


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\selectlanguage{english}
\begin{abstract}
This article is the backstory behind: S. Fritz, L. See, I. McCallum et
al., Mapping global cropland and field size.~\emph{Global Change
Biology}, 21(5), 1980-1992. doi: 10.1111/gcb.12838 ~%
\end{abstract}%



\sloppy


\section*{Context}

{\label{962847}}

To understand how the global cropland and field size paper came to be,
there are three key events that led to this research and the subsequent
publication:~

\par\null

\subsection*{1 Highlighting the Spatial Disagreement in Land Cover
Maps}

{\label{755295}}

As part of his previous job at the Joint Research Centre (JRC) of the
European Commission in Ispra, Italy, Steffen Fritz was responsible for
taking the individual regional land cover maps being produced for the
year 2000 by expert teams around the world and creating a single global
land cover product for the environmental baseline year 2000 (GLC2000 -
Fritz et al., 2003). As part of his work, Steffen then compared the
GLC2000 with other global land cover products such as that produced by
the team in Boston using data from the MODIS sensor (Friedl et al. 2010)
and he noticed large spatial discrepancies between the maps in some
locations. Papers showing these discrepancies and how to deal with them
from a user perspective were subsequently published (Fritz et al., 2005;
2008). This led to further work comparing three different global land
cover products (GLC2000, MODIS, GlobCover) that highlighted the
continued uncertainty in our knowledge of land cover, particularly in
cropland and forest cover (Fritz et al., 2011). For example, we showed
that there is a discrepancy in total cropland of between 325 to almost
400 Million hectares when comparing GLC2000 with MODIS and GlobCover,
respectively. Hence the global characterization of cropland is
problematic and needs to be improved.

\par\null

\subsection*{2 Geo-Wiki and the Crowdsourcing of Cropland and
Agricultural Field Size Data
~}

{\label{880171}}

As part of his job at the JRC, Steffen also compared global land cover
maps with freely available very high resolution satellite imagery
available through Google Earth. Based on this visual comparison, he also
realized that the global land cover maps are wrong in certain locations
and that Google Earth could be used to help improve these products. Out
of this realization, the~\href{http://www.geo-wiki.org}{Geo-Wiki}
project was born (Fritz et al., 2009; 2012). In the original version of
Geo-Wiki, users (i.e. members of the `crowd') were asked to determine
how good the GLC2000, MODIS and GlobCover land cover products were in
relation to what they could see on the satellite imagery (Figure 1).~\selectlanguage{english}
\begin{figure}[h!]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/GeoWiki1/GeoWiki1}
\caption{{The first Geo-Wiki interface, asking users to determine how good 3
different global land cover products are in relation to what they could
see from very high resolution satellite imagery
{\label{473317}}%
}}
\end{center}
\end{figure}

Since then, Geo-Wiki has evolved into a tool for collecting land cover
data at different resolutions (from 10 m to 1 km) via different
campaigns and mobile/gaming applications.~ During some of these
campaigns, which are documented in See et al. (2015), we collected data
on cropland and the size of agricultural fields (from very small to
large). These data were subsequently used as training and validation
data for the global cropland map as part of the hybrid data fusion
approach described in the paper.~

\par\null

\subsection*{3 Workshop on Characterizing and Validating Global
Agricultural Landcover
~}

{\label{741867}}

In 2011, we held a workshop at the International Institute for Applied
Systems Analysis (IIASA) in 2011 on global agricultural land cover. The
workshop was motivated by the fact~ that there is not a single product
that accurately characterizes global cropland and that many good
national land cover products exist (which include cropland) but they are
not shared. Thus, we agreed to fund the participation of people in the
workshop if they shared their national products for inclusion in the
global cropland product. The workshop resulted in the sharing of
cropland products from 14 different countries (which included the major
world crop producers) as well as the collection of various global and
regional data sets, e.g. CORINE land cover and Africover from FAO. The
data sets collected from the workshop became the inputs to the global
cropland map reported in the paper.

\par\null

\section*{What's Significant about the
Paper}

{\label{845354}}

For us this paper represents a community-based product on global
cropland for the year 2005, which brings together existing global,
regional and national products and fuses them into a single, better
product using crowdsourced data obtained from visual interpretation of
Google Earth imagery. This product is like a convergence of evidence,
using a data fusion approach to merge a range of information products on
cropland into a single, better global representation. This was only
possible because of the open sharing of cropland data sets, facilitated
through the aforementioned workshop. Such a workshop-based
approach~could be a model for producing future hybrid land cover
products or for the sharing of key data sets, e.g. in-situ or reference
data, which currently sit on computers and laptops around the world.~

\par\null

Another key point is that the product was calibrated using statistics
from the United Nations Food and Agriculture Organization (FAO).
Although there are definitely problems with FAO statistics, they
represent the only source of agreed national statistics on agriculture.
Hence this global product can be used in economic models that need to be
aligned with national figures. This product is also used in bulletins
produced by the Group on Earth Observation's Global Agricultural
Monitoring system
(\href{http://www.geoglam.org/index.php/en/}{GEOGLAM}).

\par\null

One thing that surprised is how much attention we got from the field
size map. Although there have been some regional and national field size
products produced in the past, this was the first global product. Field
size is an interesting parameter since it can be used to look at spatial
patterns of agricultural intensification,~or in agricultural monitoring,
it can determine what type and resolution of satellite sensor is needed
for operational monitoring. The field size product was subsequently used
in the research by Herrero et al.~(2017) on the spatial distribution of
nutrient production, which showed that the diversity of agricultural and
nutrient production diminishes as farm size increases. Hence smallholder
farming is a critical contributor to nutrient production. In September
2017, we held a new crowdsourcing campaign with Geo-Wiki focused on
gathering a much larger data set on agricultural field sizes globally,
which we will use to improve the current global field size map in the
future.

\par\null

\section*{References}

{\label{344112}}

~

Friedl, M.A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N.,
Sibley, A., and Huang, X. 2010. MODIS Collection 5 global land cover:
Algorithm refinements and characterization of new datasets.~\emph{Remote
Sensing of Environment}, 114(1), 168-182. ~

\par\null

Fritz, S., Bartholom\selectlanguage{ngerman}é, E., Belward, A., Hartley, A., Stibig H.J., Eva,
H., Mayaux, P., Bartalev, S., Latifovic, R., Kolmert, S., Roy, P.,
Agrawal, S., Bingfang, W., Wenting, X., Ledwith, M., Pekel, F.J., Giri,
C., Mücher, S., de Badts, E., Tateishi, R., Champeaux, J-L., Defourny,
P. 2003.~\emph{Harmonisation, mosaicing and production of the Global
Land Cover 2000 database (Beta Version)}, Luxembourg: Office for
Official Publications of the European Communities, EUR 20849 EN, 41 pp.,
ISBN 92-894-6332-5*.~

~ ~

Fritz, S., McCallum, I., Schill, C., Perger, C., Grillmayer, R., Achard,
F., Kraxner, F., Obersteiner, M.~ 2009. Geo-Wiki.Org: The use of
crowd-sourcing to improve global land cover.~ Rem. Sens., 1(3), 345-354.

Fritz, S., McCallum, I., Schill, C., Perger, C., See, L., Schepaschenko,
D., van der Velde, M., Kraxner, F., Obersteiner, M. 2012. Geo-Wiki: An
online platform for land cover validation and the improvement of global
land cover.~\emph{Environmental Modelling and Software}, 31, 110-123.

Fritz, S., See, L., McCallum, I., Schill, C., Obersteiner, M., van der
Velde, M., Boettcher, H., Havlik, P., Achard, F. 2011. Highlighting
continued uncertainty in global land cover maps to the user
community.~\emph{Environmental Research Letters}, 6, 044005.

\par\null

Fritz, S. and See, L. 2005. Comparison of land cover maps using fuzzy
agreement.~\emph{International Journal of GIS}, 19(7), 787-807. ~

Fritz, S. and See, L.M. 2008. Quantifying uncertainty and spatial
disagreement in the comparison of Global Land Cover for different
applications. \emph{Global Change Biology}, 14, 1-23, doi:
10.1111/j.1365-2486.2007.01519.x

\par\null

Herrero, M., Thornton, P.K., Power, B., Bogard, J.R., Remans, R., Fritz,
S., Gerber, J.S., Nelson, G., See, L., Waha, K., Watson, R.A., West,
P.C., Samberg, L.H., van de Steeg, J., Stephenson E., van Wijk, M.,
Havlík, P. 2017. Farming and the geography of nutrient production for
human use: a transdisciplinary analysis.~\emph{Lancet Planetary Health},
Apr 1(1):e33-e42. doi: 10.1016/S2542-5196(17)30007-4.

See, L., Fritz, S., Perger, C., Schill, C., McCallum, I., Schepaschenko,
D., Karner, M., Kraxner F., Obersteiner, M. 2015. Harnessing the power
of volunteers, the Internet and Google Earth to collect and validate
global spatial information using Geo-Wiki.~\emph{Technological
Forecasting and Social Change}, 98, 324--335.
doi:10.1016/j.techfore.2015.03.002

\par\null

~



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