Marine Geospatial Ecology Tools: An integrated framework for ecological geoprocessing with ArcGIS, Python']Python, R, MATLAB, and C plus

被引:270
作者
Roberts, Jason J. [1 ]
Best, Benjamin D. [1 ]
Dunn, Daniel C. [1 ]
Treml, Eric A. [2 ]
Halpin, Patrick N. [1 ]
机构
[1] Duke Univ, Marine Geospatial Ecol Lab, Nicholas Sch Environm, Durham, NC 27708 USA
[2] Univ Queensland, Sch Biol Sci, St Lucia, Qld 4072, Australia
关键词
Marine ecology; Spatial ecology; Software integration; Interoperability; Informatics; Habitat modeling; Oceanography; GIS; SCIENTIFIC WORKFLOW; HABITAT; SEABIRDS;
D O I
10.1016/j.envsoft.2010.03.029
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
With the arrival of GPS, satellite remote sensing, and personal computers, the last two decades have witnessed rapid advances in the field of spatially-explicit marine ecological modeling. But with this innovation has come complexity. To keep up, ecologists must master multiple specialized software packages, such as ArcGIS for display and manipulation of geospatial data, R for statistical analysis, and MATLAB for matrix processing. This requires a costly investment of time and energy learning computer programming, a high hurdle for many ecologists. To provide easier access to advanced analytic methods, we developed Marine Geospatial Ecology Tools (MGET), an extensible collection of powerful, easy-to-use, open-source geoprocessing tools that ecologists can invoke from ArcGIS without resorting to computer programming. Internally, MGET integrates Python, R, MATLAB, and C++, bringing the power of these specialized platforms to tool developers without requiring developers to orchestrate the interoperability between them. In this paper, we describe MGETs software architecture and the tools in the collection. Next, we present an example application: a habitat model for Atlantic spotted dolphin (Stenella frontalis) that predicts dolphin presence using a statistical model fitted with oceanographic predictor variables. We conclude by discussing the lessons we learned engineering a highly integrated tool framework. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1197 / 1207
页数:11
相关论文
共 41 条
[1]  
[Anonymous], 2006, 2 MIN GRIDD GLOB REL
[2]   An overview of model integration for environmental application - components, frameworks and semantics [J].
Argent, RM .
ENVIRONMENTAL MODELLING & SOFTWARE, 2004, 19 (03) :219-234
[3]  
BEST BD, 2007, THESIS DUKE U
[4]  
BEST BD, 2006, ARCRSTATS MULTIVARIA
[5]  
BEST BD, 2006, CONNMOD CONNECTIVITY
[6]   Geospatial web services within a scientific workflow: Predicting marine mammal habitats in a dynamic environment [J].
Best, Benjamin D. ;
Halpin, Patrick N. ;
Fujioka, Ei ;
Read, Andrew J. ;
Qian, Song S. ;
Hazen, Lucie J. ;
Schick, Robert S. .
ECOLOGICAL INFORMATICS, 2007, 2 (03) :210-223
[7]  
CASEY KS, 2008, GLOBAL AVHRR 4 KM SS
[8]  
CAYULA JF, 1992, J ATMOS OCEAN TECH, V9, P67, DOI 10.1175/1520-0426(1992)009<0067:EDAFSI>2.0.CO
[9]  
2
[10]   Comparison of methods to spatially represent pelagic longline fishing effort in catch and bycatch studies [J].
Dunn, Daniel C. ;
Kot, Connie Y. ;
Halpin, Patrick N. .
FISHERIES RESEARCH, 2008, 92 (2-3) :268-276