5 Fourth Paradigm and landscape research

The world has changed tremendously through intensive technology data acquisition tools (Gray, 2009Jump To The Next Citation Point). By nature, landscape research is data intensive, and this makes it a strong stakeholder in the global data revolution. Most of the data for landscape queries come from the field and or through remotely sensed data platforms. Intensive and high-resolution data facilitate landscape research (Dozier, 2011Jump To The Next Citation Point; Perron and Fagherazzi, 2011). Undoubtedly, the new paradigm transforms the way in which landscape researchers search for and/or use data. Prior to this paradigm, scientific research thrived on three paradigms: empiricism, analysis, and simulation (Gray, 2009). Like its three predecessors, the Fourth Paradigm relies on the collection, curation, analysis and visualisation of data. Landscape researchers use theories or explanations (first paradigm); statistical, field and laboratory analyses (second paradigm) and computer-based simulation of landscapes (third paradigm). Therefore, there is no cause for alarm when landscape scientists adopt the new paradigm. Based on available records (Table 4), big data appears in some landscape-related disciplines, albeit to a small extent. In the opinion of Lynch (2009), the Fourth Paradigm provides an integrating framework that allows the first three paradigms (empiricism, analysis and simulation) to be integrated and to reinforce one another. It is much easier to integrate the Fourth Paradigm with the others in landscape research. Landscape researchers are familiar with the use of datasets and landscape tools of analysis most of which are open access (see Tables 5 and 6 below). A data deluge is certainly one of the best ways to support peer-reviewed research. Tolle et al. (2011) opine that the Fourth Paradigm aids transparency and accountability in research production and dissemination.

Table 4: State of Fourth Paradigm Research
Fourth Paradigm

Web of Science


No. of publications




2005 – 2011

2005 – 2011

Subject areas/category

Engineering (1), Science and technology (1), Environmental sciences & ecology; Physical geography (2)

Environmental science (1), Earth and planetary sciences (1), Agricultural and biological sciences (1), Arts and humanities (1), Engineering (5)

Document types

Editorial (1), book review (1), article (2)

Article (2), conference paper (3), conference review (1), short survey (1)

Source: (Dec. 20, 2011) and (Dec. 20, 2011)

Table 5: Research Tools for Second, Third and Fourth Paradigms
Satellite Images

Landscape research application scale

Landscape analysis tools

Applications to Landscape


Deep analysis

GIS packages, QGIS

Analysis, visualisation, mapping, modelling


Deeper analysis


Landscape metrics computation

Spot 1-5

Semi to detailed analysis

Nature Serve Vista 2.0

Spatial planning decision support


Deep analysis

Climate Wizard

Statistical analysis of past, current and future climate variables


Deep analysis

inVEST (Integrated Valuation of Ecosystem Services and Tradeoffs)

Ecosystem services analysis


Detailed analysis

Cellular Automata

Modelling spatial dimensions


Detailed analysis


Landscape fragmentation

Landsat 1-7

Semi detailed analysis

ALARM (Assessing Large Scale Risks for Biodiversity with Tested Methods)

Landscape risk management

Table 6: Databases for Second to Fourth Paradigms

Landscape database




C5 Landscape database API2.0

Open source

Outdoor recreational land use such as hunting, fishing, performance art

GIS based landscape mapping, navigation, analysis

LANMAP2 Pan-European Landscape Database

Open source

Hierarchical classification of 350 landscape types from intertidal flats, urban agglomerations to water bodies

Mapping database

Therapeutic landscape network

Open source

Healthy and green spaces

Landscape and health research


Open source / CIESIN / SEDAC / NASA

World gridded population / global urban rural mapping

Biodiversity management

Vitour Landscape Database

Open source

Wine landscape conservation and valorisation in Europe

Landscape policy

What is Out There Database

Open source

Designed heritage landscapes from 50 states of the US

Cataloguing of historic designed landscapes

The Landscape Toolbox

Open source (USDA/Nature Conservancy)

Abstracts of methods, terms, and tools on rangeland management

Landscape research tools


Open source / European Commission 2002 – 2005

European cultural landscapes and ecosystems

Data for researchers, students and public users


Open Source / UNISCAPE, 2005

Landscape higher education in Europe

Interactive website for landscape education, training and assessment

209 Database Management System

Open source / National Centre for Landscape Fire Analysis

Landscape fire incidences

Wild fire incident management

European Digital Archive on Soil Maps of the World

Open source / EC Directorate Generate Joint Research Centre

Land use and soils

Land use, soils

Global Spatial Database of Agricultural Land-use Statistics

Open source/FAO

Agricultural land uses

Land use and land cover

Open Landscapes

Open access / ZALF

Landscape science

Primary data, metadata, methods, wiki

TERRASTAT database

Open source / FAO

Land resource potentials and constraints potentials

Statistical data on agro allied land uses

Earth System Science Data

Open source / Copernicus Publications

Earth system science data



Open access / Alfred Wegener Institute (AWI),

Georeferenced data from earth system research

Earth system research data

Geo When Database

Open source / University of California at Berkeley

Geologic landscapes based on timescales

Landscape age specifications

USDA/ERS Major Land Uses

Open access / USDA

Major land uses (public/private in the US) based on agricultural census

Land uses from 1945 to 2007

With multiple sources of landscape data, researchers are given a new opportunity to observe landscapes simultaneously and squarely (Lehning et al., 2009). Similarly, Hunt et al. (2009) add that for the benefit of landscape and ecological research, the Fourth Paradigm synthesises ground data, remote sensing, internet connectivity and commodity computing, and the navigational ability of the data cyber-infrastructure. The capacity of this data-driven approach is particularly enlightening for complex ecological systems (Kelling et al., 2009). It is worth noting that even pioneer Fourth Paradigm literature (e.g., Hey, 2010) sees the potentials of physical sciences such as biology, astronomy, particle physics, environmental science, oceanography, as well as humanities and social sciences. Most of these disciplines are directly or indirectly related to landscape science and research interests.

The new paradigm is welcomed by leading international science hubs. The National Science Foundation supports it through its DataONE and Data Conservancy projects (Lagoze and Patzke, 2011). Institutional repositories also facilitate data sharing, scrutiny, collaboration and the discovery of older data sets (Nelson, 2009). The author maintains that what restricts the smooth use of big data projects across the world are the doubts concerning data precision, storage formats, suspicion by scientists and cloudy legal infrastructures. Apart from these, the worst threat is the external threat from intrusion attempts, hacking and cybercrimes (Perkel, 2010). Some of the challenges associated with the Fourth Paradigm extend to environmental data. Some data owners consider whether data should be used to measure indicators or to solve environmental crises (Goldston, 2008). In other words, it is feared that data could be used against the interests of its owners. For instance, industries could fear to release data on their pollutants.

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