Agricultural systems and landscape patterns: how can we build a relationship?

Deffontaines, Jean‐Pierre; Thenail, Claudine; Baudry, Jacques

doi:10.1016/0169-2046(94)01031-3

Cited by 61 publications

(31 citation statements)

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“…Land change science (LCS) addresses interactions among social systems and environmental factors regarding the behaviour of households or firms as the major proximate drivers of land change (Turner et al 2007). Agricultural sciences consider change in agricultural land-use in relation to farming systems viewed as adaptive socio-technological systems driven by land condition, household behaviour, technology, socio-economic environment and public policy (Deffontaines et al 1995;Dent et al 1995;Gibon 1999;Bontkes and van Keulen 2003). We combined concepts and methods from these scientific domains to address landscape changes in the Pyrenees by means of a case study.…”

Section: Overview Of the Study Methodsmentioning

confidence: 99%

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

et al. 2010

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Section: Overview Of the Study Methodsmentioning

confidence: 99%

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

et al. 2010

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“…In rural areas in China, farmland and rural settlements are the most important land use classes [71]. Most of the farming activities tend to cluster into the villages [72]. In addition, mining, road and dam construction are important human interventions in the landscapes of both study areas.…”

Section: Human Disturbance Factorsmentioning

confidence: 99%

Integration of Satellite Imagery, Topography and Human Disturbance Factors Based on Canonical Correspondence Analysis Ordination for Mountain Vegetation Mapping: A Case Study in Yunnan, China

Zhang

Coillie

et al. 2014

Remote Sensing

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Abstract:The integration between vegetation data, human disturbance factors, and geo-spatial data (Digital Elevation Model (DEM) and image data) is a particular challenge for vegetation mapping in mountainous areas. The present study aimed to incorporate the relationships between species distribution (or vegetation spatial distribution pattern) and topography and human disturbance factors with remote sensing data, to improve the accuracy of mountain vegetation maps. Two different mountainous areas located in Lancang (Mekong) watershed served as study sites. An Artificial Neural Network (ANN) architecture classification was used as image classification protocol. In addition, canonical correspondence analysis (CCA) ordination was applied to address the relationships between topography and human disturbance factors with the spatial distribution of vegetation patterns. We used ordinary kriging at unobserved locations to predict the CCA scores. The CCA ordination results showed that the vegetation spatial distribution patterns are strongly affected by topography and human disturbance factors. The overall accuracy of vegetation classification was significantly improved by incorporating DEM or four CCA axes as additional channels in both the northern and southern study areas. However, there was no significant difference between using DEM or four CCA axes as extra channels in OPEN ACCESSRemote Sens. 2014, 6 1027 the northern steep mountainous areas because of a strong redundancy between CCA axes and DEM data. In the southern lower mountainous areas, the accuracy was significantly higher using four CCA axes as extra bands, compared to using DEM as an extra band. In the southern study area, the variance of vegetation data explained by human disturbance factors was larger than the variance explained by topographic attributes.

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“…Therefore communities are considered as "collective actors", pursuing common goals. Referring to Deffontaines et al (1995) and Baudry et al (2000), this shall be defined as a holistic perspective on the relationships between human land use systems and landscape patterns.…”

Section: Methodological Remarkmentioning

confidence: 99%

Management Strategies and Landscape Diversity in Commonly Governed Mountain Pastures: A Case Study from Austrian Alps

Kurz

2013

European Countryside

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Agricultural systems and landscape patterns: how can we build a relationship?

Cited by 61 publications

References 1 publication

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

Modelling and simulating change in reforesting mountain landscapes using a social-ecological framework

Integration of Satellite Imagery, Topography and Human Disturbance Factors Based on Canonical Correspondence Analysis Ordination for Mountain Vegetation Mapping: A Case Study in Yunnan, China

Management Strategies and Landscape Diversity in Commonly Governed Mountain Pastures: A Case Study from Austrian Alps

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