TY - JOUR
T1 - Reimagining the potential of Earth observations for ecosystem service assessments
AU - Ramirez-Reyes, Carlos
AU - Brauman, Kate A.
AU - Chaplin-Kramer, Rebecca
AU - Galford, Gillian L.
AU - Adamo, Susana B.
AU - Anderson, Christopher B.
AU - Anderson, Clarissa
AU - Allington, Ginger R.H.
AU - Bagstad, Kenneth J.
AU - Coe, Michael T.
AU - Cord, Anna F.
AU - Dee, Laura E.
AU - Gould, Rachelle K.
AU - Jain, Meha
AU - Kowal, Virginia A.
AU - Muller-Karger, Frank E.
AU - Norriss, Jessica
AU - Potapov, Peter
AU - Qiu, Jiangxiao
AU - Rieb, Jesse T.
AU - Robinson, Brian E.
AU - Samberg, Leah H.
AU - Singh, Nagendra
AU - Szeto, Sabrina H.
AU - Voigt, Brian
AU - Watson, Keri
AU - Wright, T. Maxwell
N1 - Publisher Copyright:
© 2019 The Authors
PY - 2019/5/15
Y1 - 2019/5/15
N2 - The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.
AB - The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. This will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.
KW - Ecosystem benefits
KW - Monitoring
KW - Remote sensing
KW - Research priorities
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U2 - 10.1016/j.scitotenv.2019.02.150
DO - 10.1016/j.scitotenv.2019.02.150
M3 - Review article
C2 - 30893737
AN - SCOPUS:85061671375
SN - 0048-9697
VL - 665
SP - 1053
EP - 1063
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -