Landscape and Urban Planning 106 (2012) 103–114 Contents lists available at SciVerse ScienceDirect Landscape and Urban Planning jou rn al h om epa ge: www.elsevier.com/locate/landurbplan Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition Safaa Zakaria Aldwaik ∗ , Robert Gilmore Pontius Jr. School of Geography, Clark University, 950 Main Street, Worcester, MA 01610-1477, USA a r t i c l e i n f o Article history: Received 25 May 2011 Received in revised form 8 February 2012 Accepted 14 February 2012 Available online 14 March 2012 Keywords: LULCC Map Matrix Pattern Process Stationary a b s t r a c t This article presents a quantitative method to analyze maps of land categories from several points in time for a single site by considering cross-tabulation matrices, where one matrix summarizes the change in each time interval. There are three levels of analysis, starting from general to more detailed levels, where each level exposes different types of information given the previous level of analysis. First, the interval level examines how the size and speed of change vary across time intervals. Second, the category level examines how the size and intensity of gross losses and gross gains in each category vary across categories for each time interval. Third, the transition level examines how the size and intensity of a category’s transitions vary across the other categories that are available for that transition. At each level, the method tests for stationarity of patterns across time intervals. The unique contribution of this article is that it combines all three levels of analysis into one unified framework that we call intensity analysis, where the more detailed levels are conditional on the less detailed levels. The illustrative case study is for seven categories at the Plum Island Ecosystems site in northeastern Massachusetts, USA, where the largest transition is from Forest to Built during 1985, 1991, and 1999. We compare our approach to other established methods such as the Markov approach in order to show how our proposed intensity analysis gives more information concerning five possible reasons to explain why the transitions vary across time and space. © 2012 Elsevier B.V. All rights reserved. 1. Introduction 1.1. Research rationale Human activities and natural processes drive changes in land- use and land-cover that can have profound biophysical, ecological, economical, political, and social consequences (Turner & Meyer, 1994). Therefore, understanding the patterns and processes of Land-Use and Land-Cover Changes (LULCC) has become a funda- mental goal in studies that investigate the complex interactions between humans and the environment from local to global scales. The first step to develop understanding of LULCC is to describe the patterns of LULCC through characterizing them. After character- izing the land transformations, many studies propose strategies for monitoring environmental changes, predicting future changes, analyzing the consequences of LULCC, and managing natural resources, so it is essential that the initial characterization of the land changes be performed in a manner that facilitates understand- ing by a wide audience (Riebsame et al., 1994; Turner, 2002). ∗ Corresponding author. Tel.: +1 508 793 7761; fax: +1 508 793 8881. E-mail addresses: saldwaik@gmail.com (S.Z. Aldwaik), rpontius@clarku.edu (R.G. Pontius Jr.). The typical strategy for analyzing the spatial distribution of LULCC starts with revealing the land transitions, quantifying the pattern of change, and then identifying the processes of the change (Macleod & Congalton, 1998). Research usually combines quanti- tative and qualitative information to explain the changes in terms of explanatory factors, e.g. proximity to roads, to link the detected patterns with the driving causes (Nagendra, Munroe, & Southworth, 2004; Pontius, Shusas, & McEachern, 2004; Serneels & Lambin, 2001; Shoyama & Braimoh, 2011). Our method to characterize the observed patterns during the quantitative phase of research influ- ences all subsequent steps, including the conclusions that can be drawn. For example, some researchers might focus on only the net increase in the quantity of built land, while other researchers might focus more on the spatial patterns of the allocation of the land transformations. A broad array of models for LULCC has been proposed where the initial characterization of the change can influ- ence three important goals: (1) to reveal the driving forces and causes of the change (Lehmann & Reetz, 1994; Moser, 1996; Skole, 1994; Turner & Meyer, 1994), (2) to assess the impacts of change on humans and the environment (Kates, Turner, & Clark, 1990; Meyer & Turner, 1996), and (3) to forecast configurations of future land patterns under various scenarios (Pontius et al., 2008; Robinson et al., 1994; Wear & Bolstad, 1998). The efficiency of these models is influenced by the initial technique to characterize the observed 0169-2046/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.landurbplan.2012.02.010