MDPI: Open access agreement for IIASA authors

IIASA has established an agreement with MDPI (Multidisciplinary Digital Publishing Institute) allowing authors to benefit from a 10% discount on article processing charges (APCs) when publishing in an MDPI journal. The agreement has been signed for 1 year and starts May 15, 2016.

MDPI (Multidisciplinary Digital Publishing Institute) is an academic open access publisher based in Basel, Switzerland, and was initially founded in 1996 t collect and preserve rare chemical research samples.

MDPI publishes 150 diverse peer-reviewed, scientific, open access, electronic journals, including Molecules (launched in 1996; Impact Factor 2.416), the International Journal of Molecular Sciences (launched in 2000; Impact Factor 2.862), Sensors (launched in 2001; Impact Factor 2.245), Marine Drugs (launched in 2003; Impact Factor 2.853), Energies (launched in 2008; Impact Factor 2.072), the International Journal of Environmental Research and Public Health (launched in 2004; Impact Factor 2.063), Viruses (launched in 2009; Impact Factor 3.353), Remote Sensing (launched in 2009; Impact Factor 3.180), Toxins (launched in 2009; Impact Factor 2.938) and Nutrients (launched in 2009; Impact Factor 3.270). Our publishing activities are supported by more than 9,900 active scientists and academic editors on our journals' international editorial boards, including several Nobelists. More than 187,500 individual authors have already published with MDPI. MDPI.com receives more than 4.2 million monthly webpage views. 

All MDPI content is open access, distributed under a Creative Commons License and hence freely accessible to readers. MDPI finances its publications through article processing charges (APC), paid by authors and their institutions. Please click here for a list of MDPI journals.


Find all relevant information for authors and about the editorial process on the MDPI website.


The following IIASA articles have been published in MDPI journals in the past:

Fritz, S.; McCallum, I.; Schill, C.; Perger, C.; Grillmayer, R.; Achard, F.; Kraxner, F.; Obersteiner, M. Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover. Remote Sens. 2009, 1(3), 345-354; doi:10.3390/rs1030345. http://www.mdpi.com/2072-4292/1/3/345

Rao, N.; Baer, P. "Decent Living" Emissions: A Conceptual Framework. Sustainability 2012, 4(4), 656- 681; doi:10.3390/su4040656. http://www.mdpi.com/2071-1050/4/4/656 

Reschke, J.; Bartsch, A.; Schlaffer, S.; Schepaschenko, D. Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes. Remote Sens. 2012, 4(10), 2923-2943; doi:l0.3390/rs4102923. http://www.mdpi.com/2072-4292/4/10/2923 

Vancutsem, C.; Marinho, E.; Kayitakire, F.; See, L.; Fritz, S. Harmonizing and Combining Existing Land Cover/Land Use Datasets for Cropland Area Monitoring at the African Continental Scale. Remote Sens. 2013, 5(1), 19-41; doi:l0.3390/rs5010019. http://www.mdpi.com/207 2-4292/5/1/19 

Santoro, M.; Cartus, O.; Franssen, J.; Shvidenko, A.; Mccallum, I.; Hall, R.; Beaudoin, A.; Beer, C.; Schmullius, C. Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Quebec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data. Remote Sens. 2013, 5(9), 4503- 4532; doi:10.3390/rs5094503. http://www.mdpi.com/2072-4292/5/9/4503 

See, L.; Fritz, S.; Leeuw, J. The Rise of Collaborative Mapping: Trends and Future Directions. ISPRS Int. J. Geo-Inf. 2013, 2(4), 955-958; doi:10.3390/ ijgi2040955. http://www.mdpi.com/2220-9964/2/4/955 

Rafaj, P.; Cofala, J.; Kuenen, J.; Wyrwa, A.; Zysk, J. Benefits of European Climate Policies for Mercury Air Pollution. Atmosphere 2014, 5(1), 45-59; doi:l0.3390/atmos5010045. http://www.mdpi.com/2073-4433/5/l/45 

Huttich, C.; Korets, M.; Bartalev, S.; Zharko, V.; Schepaschenko, D.; Shvidenko, A.; Schmullius, C. Exploiting Growing Stock Volume Maps for Large Scale Forest Resource Assessment: CrossComparisons of ASAR- and PALSAR-Based GSV Estimates with Forest Inventory in Central Siberia. Forests 2014, 5(7), 1753-1776; doi:l0.3390/f5071753. http://www.mdpi.com/1999-4907 /5/7 /1753 

Perger, C.; LeDrew, E.; See, L.; Fritz, S. Geography Geo-Wiki in the Classroom: Using Crowdsourcing to Enhance Geographical Teaching. Future Internet 2014, 6(4), 597-611; doi:10.3390/fi6040597. http://www.mdpi.com/1999-5903/6/4/597 

Bechtel, B.; Alexander, P.; Bohner, J.; Ching, J.; Conrad, O.; Feddema, J.; Mills, G.; See, L.; Stewart, I. Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities. ISPRS Int. J. Geo-Inf. 2015, 4(1), 199-219; doi:10.3390/ijgi4010199.http://www.mdpi.com/2220-9964/4/1/199 

Mihai, A.; Marincea, A.; Ekenberg, L. A MCDM Analysis of the Roi;;ia Montana Gold Mining Project. Sustainability 2015, 7(6), 7261-7288; doi:10.3390/su7067261. http://www.mdpi.com/2071-1050/7 /6/7261 

Waldner, F.; Fritz, S.; Di Gregorio, A.; Defourny, P. Mapping Priorities to Focus Cropland Mapping Activities: Fitness Assessment of Existing Global, Regional and National Cropland Maps. Remote Sens. 2015, 7(6), 7959-7986; doi:10.3390/rs70607959. http://www.mdpi.com/2072-4292/7 /6/7959 

Komendantova, N.; Vocciante, M.; Battaglini, A. Can the BestGrid Process Improve Stakeholder Involvement in Electricity Transmission Projects?. Energies 2015, 8(9), 9407-9433; doi: 10.3390/en8099407. http://www.mdpi.com/1996-1073/8/9/9407 

See, L. Spatial Analysis as a Transformative Technology for Decision-Making in Environmental Domains. ISPRS Int. J. Geo-Inf. 2015, 4(3), 1770-1773; doi:10.3390/ijgi4031770. http://www.mdpi.com/2220-9964/4/3/1770 

Tsendbazar, N.; de Bruin, S.; Fritz, S.; Herold, M. Spatial Accuracy Assessment and Integration of Global Land Cover Datasets. Remote Sens. 2015, 7(12), 15804-15821; doi:10.3390/rs71215804. http://www. md pi.com/207 2-4292/7 /12/15804 

Waldner, F.; Fritz, S.; Di Gregorio, A.; Plotnikov, D.; Bartalev, S.; Kussul, N.; Gong, P.; Thenkabail, P.; Hazeu, G.; Klein, I.; Lbw, F.; Miettinen, J.; Dadhwal, V.; Lamarche, C.; Bontemps, S.; Defourny, P. A Unified Cropland Layer at 250 m for Global Agriculture Monitoring. Data 2016, 1(1), 3; doi:10.3390/data1010003. http://www.mdpi.com/2306-5729/1/1/3 

Lesiv, M.; Moltchanova, E.; Schepaschenko, D.; See, L.; Shvidenko, A.; Comber, A.; Fritz, S. Comparison of Data Fusion Methods Using Crowdsourced Data in Creating a Hybrid Forest Cover Map. Remote Sens. 2016, 8(3), 261; doi:10.3390/rs8030261. http://www.mdpi.com/2072-4292/8/3/261 

Enenkel, M.; Steiner, C.; Mistelbauer, T.; Dorigo, W.; Wagner, W.; See, L.; Atzberger, C.; Schneider, S.; Rogenhofer, E. A Combined Satellite-Derived Drought Indicator to Support Humanitarian Aid Organizations. Remote Sens. 2016, 8(4), 340; doi:10.3390/rs8040340. http://www.mdpi.com/2072-4292/8/4/340 

See, L.; Mooney, P.; Foody, G.; Bastin, L.; Comber, A.; Estima, J.; Fritz, S.; Kerle, N.; Jiang, B.; Laakso, M.; Liu, H.; Milcinski, G.; Niksic, M.; Painho, M.; Podor, A.; Olteanu-Raimond, A.; Rutzinger, M. Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information. ISPRS Int. J. Geo-Inf. 2016, 5(5), 55; doi:l0.3390/ijgi5050055. http://www.mdpi.com/2220-9964/5/5/55



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Last edited: 19 May 2016

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