Regional Niagara is the site of an intense three-way land-use conflict among urban, agricultural and natural uses. Large scale spatial and temporal land-use data were used to investigate the dynamics of land-use change in this area. A first order Markov chain was used as a stochastic model to make quantitative comparisons of the land-use changes between discrete time periods extending from 1935 to 1981. The Markov model allowed for two main conclusions about the historic dynamics of land-use change in the Regional Municipality of Niagara.

https://link.springer.com/content/pdf/10.1007/BF00124382.pdf

A Markov model of land-use change dynamics in the Niagara Region, Ontario, Canada

(1970). Univariate Spatial Forecasting. Economic Geography: Vol. 46, PROCEEDINGS International Geographical Union Commission on Quantitative Methods, pp. 241-258.

Univariate spatial forecasting

This paper examines the process of land use change as a Markov process. The model as developed in this paper ateempts to specify criteria to determine the stability and similarity of the process of land use change before it reaches the equilibrium state which may take an infinite number of time periods. It is shown that the model is capable of identifying the time horizon during which the system shows sufficient stability since prediction with respect to future pattern is more likely to conform to the actual pattern if the system in question is stable.

The determination of stability and similarity of Markovian land use change processes: A theoretical and empirical analysis

This study examined landcover change during 1940–1988 in two contiguous landscapes of approximately 12,400 hectares in central Ohio, USA: an inertial till plain area and a more dynamic moraine area. Agriculture dominated both landscapes throughout, however, the cover of natural vegetation and urban-suburban development increased over time on the moraine while natural vegetation decreased and agriculture increased on the till plain. Markov process models for landcover change were constructed for three 14–17-year time intervals and for the entire forty-eight-year study period. Probabilities of self-replacement for agricultural lands (0.91–0.97) were higher and those for forests (0.54–0.65) lower than those reported for other landscapes. Predictions of landcover percentages for fifty years in the future were made using Markov process models derived from actual cover changes in 1940–1957, 1971–1988, and 1940–1988. All three models produced similar predictions for the inertial till plain area. In contrast, the three models' predictions differed considerably for the moraine area. Only the 1971–1988 transition matrix was sensitive to increases in urbanization and reforestation which began on the moraine in the 1970s. These results indicate that reliance on lengthy study intervals and net rates of change can obscure spatial and temporal patterns of landcover change that are caused by natural and socioeconomic factors operating on shorter time scales.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1538-4632.1996.tb00921.x

Markov Models of Inertia and Dynamism on Two Contiguous Ohio Landscapes

Economic Investigation of Discount Factors for Agricultural Greenhouse Gas Emission Offsets. (May 2004) Man-Keun Kim, B.S., Korea University; M.S., Korea University Chair of Advisory Committee: Dr. Bruce A. McCarl This dissertation analyzes the basis for and magnitudes of discount factors based on the characteristics of greenhouse gas emission (GHGE) offsets that are applied to the GHGE reduction projects, concentrating on agricultural projects. Theoretical approaches to discount factors, estimation and incorporation of discount factors procedures are developed. Discount factors would be imposed by credit purchasers due to noncompliance with regulatory program of the credits with GHG program including consideration of shortfall penalties and limited durations. Discount factors are proposed for (i) additionality, (ii) leakage, (iii) permanence, and (iv) uncertainty. Additionality arise when the region where an AO project is being proposed would have substantial adoption of the AO practice in the absence of GHG programs (business as usual GHGE offset).

Economic investigation of discount factors for agricultural greenhouse gas emission offsets

/pdf/forecasting-land-occupancy-changes-through-markovian-4jffxnio2d.pdf

Larry S. Bourne

Papers

Forecasting land occupancy changes through Markovian probability matrices: a central city example