Multicriterion Typology of Agriculture: A Spatial Dependence Approach

Abstract

At the turn of the 21st century Polish agriculture intensively changed as the consequence of: 1) the socio-economic transformation that started in 1989, 2) the general transition from a centrally-planned economy to a market economy and 3) Poland’s accession in 2004 to the European Union. In this paper, we try to describe, in a synthetic way, the spatial heterogeneity of development of agriculture in Poland. For this purpose we identified the types of contemporary Polish agriculture. We applied the measures of global (Moran 1950) and local (LISA) spatial autocorrelation devised by L. Anselin (1995) and used their calculations in classification methods. Our dataset consists of 69 variables and 3,069 spatial units at the LAU2 level. As the result of the analysis we identified 20 types of agriculture in Poland and presented their characteristic features. We have paid particular attention to a spatial distribution of identified types. We concluded that the distribution is not only a result of natural or socio-economic conditions and local spatial relationships, but also to a greater extent is still affected by historical conditions (mainly partitions and changes of borders after the First and Second World Wars).

A Spatially Explicit Approach for Targeting Resource-Poor Smallholders to Improve Their Participation in Agribusiness: A Case of Nyando and Vihiga County in Western Kenya

“…The outcome of these factor interactions within individual households is most pronounced at the local level (i.e., farms and neighborhoods). Their spatial manifestation can be observed from the resulting diverse smallholder farming typologies across rural landscapes [10]. However, how these factors interact spatially to influence smallholder farming decisions is little understood.…”

“…The spatial heterogeneity of household livelihood assets endowments has often been used to explain the diversity of smallholder farming typologies and choices across and within geographic locations [11][12][13][14]. The different typologies of smallholder farming systems in a given territory can thus be conceptualized as spatial manifestations of individual households' farm management decisions and actions arising from diverse interactions of household livelihood capitals and complex geographic environments [10,13,[15][16][17][18]. For example, household everyday farming decisions are influenced by the interactions of variabilities of socio-economic, agroecological, biophysical, and institutional variables [4,[19][20][21].…”

“…According to Głębocki, Kacprzak, and Kossowski [10], spatial dependence is considered a leading effect that influences agriculture practices and decision choices of households. In their study, Głębocki et al (ibid) was able to map and geo-visualize spatial distribution of smallholder farming typologies by analyzing their spatial dependence characteristics.…”

“…In their study, Głębocki et al (ibid) was able to map and geo-visualize spatial distribution of smallholder farming typologies by analyzing their spatial dependence characteristics. In the literature, spatial dependence is described as a condition where attribute values are observed at one location depending on the values of neighboring observations at nearby locations [10,23,24]. The assumption taken is that relationships between neighboring spatial units are much stronger than between distant ones [10].…”

“…In the literature, spatial dependence is described as a condition where attribute values are observed at one location depending on the values of neighboring observations at nearby locations [10,23,24]. The assumption taken is that relationships between neighboring spatial units are much stronger than between distant ones [10]. Spatial dependence can be captured and geo-visualized as spatial varying patterns across the landscape.…”