Different Models, Different Outcomes? A Comparison of Approaches to Land Use Modeling in the Dutch Limes

Current advances in spatial simulation bring unprecedented possibilities for spatio-temporal modeling. In this paper, we focus on modeling the impact of settlement on land use in the Roman period in the Dutch river area, on the northern frontier of the Roman Empire. During this period, the area witnessed a strong population increase that put more demands on the available land to produce food, not only for the local population, but also for the soldiers stationed on the frontier and the citizens of the newly founded towns. We compare an agent-based model (ABM) of agricultural production in the region (ROMFARMS), and a model using the Past Land Use Scanner (PLUS. Both were used to estimate the effects of increased agricultural demand through simulations of food production, taking into account the available workforce and the productivity and availability of suitable land. However, how should we evaluate the model outcomes? What are the advantages and limitations of each? We discuss issues of scale, temporal resolution and model inputs, together with questions of technical implementation and validation. In this way, we aim to point the way to future researchers to implement these approaches effectively in other contexts.

Recent Advances in Empirical Land-Use Modeling

Data sets providing repeated observations of land use at fine spatial scales have enabled a new generation of land-use studies. In the past decade, these analyses have put increasing emphasis on empirical research designs that provide more convincing causal estimates. I review the use of instrumental variables, matching, difference-in-differences, regression discontinuity design, and randomized controlled trials in the recent land-use economics literature, exploring how new data have made possible the use of these research designs. I show that these estimators have produced different results than were obtained with traditional approaches and have provided new insights into important land-use policy issues such as additionality and spillover effects. Expected final online publication date for the Annual Review of Resource Economics, Volume 13 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Assessing Long-Term Deforestation In Nam San Watershed, Loei Province, Thailand Using A Dyna-Clue Model

This research analyzed land-use changes (LUC) in the Nam San Watershed (NSW) by applying geoinformatics methods and land-use modeling approach to explore LUC in the past. Landsat satellite images from years 2002, 2007 and 2013 were classified using a maximum likelihood algorithm to create land-use maps. For assessing future LUC over a period of twenty years (2014–2033), land-use simulations were conducted using a dynamic LUC model (Dyna-CLUE model) in two land management scenarios: Scenario 1 is a simple projection of the LUC trend without reservation area, while Scenario 2 projects the LUC trend with reservation area in future periods. NSW land-use maps for 2002–2013 were analyzed using geoinformatics technology. The results revealed that the amount of forested area within the NSW has reduced drastically, from 380.40 km² to 267.23 km², changing to fields and perennial crops, which the logistic regression identified as being influenced by a slope factor. These data was used as a reference for LUC detection with the model simulation in two scenarios. Model results have shown that by 2033, Scenario 1 predicts a significant decrease in the overall forest area, from 72.21 km² to 41.55 km² in Phu Ruea district, and from 107.31 km² to 45.62 km² in Phu Luang district. Whereas Scenario 2 predicts slightly decreasing forest area within the reservation area, but rapid decrease, from 177.86 km² to 28.54 km² outside the reservation area, where the distance to village factor is the main influencer. These findings highlight the importance and the potential of model predictions for planning activities to protect forested areas.

What urban streamflow can tell us about changes in water storage and streamflow due to development

<p><span>The urbanization of a watershed radically impacts how watersheds store, transmit and discharge water. Although urbanization’s effects on floods, droughts, and water supply have been explored in recent decades through land-use modeling, hydrological modeling, remote sensing, and empirical approaches, clarification of these effects remains a challenge due to limited availability and accessibility of useful data. Streamflow records for three neighboring watersheds in Baltimore, an urbanized watershed, an urbanizing watershed and a natural watershed, provide a unique opportunity to study the influence of urbanization on watershed function.  The 5-minute instantaneous discharge records span an increase in residential development of the urbanizing watershed.  Coupling the streamflow and development records allows direct comparison of hydrologic changes with spatial patterns of land use change.  Recession analysis was used to evaluate altered hydrologic response, particularly relationships between watershed storage and streamflow that may occur during urbanization.  Recession approaches were applied using variable time steps to estimate the time derivative of streamflow (dQ/dt) to avoid known issues in parameter estimation driven by the time derivative of a noisy time series. Several hypotheses are tested, including comparisons to conceptual models of hydrologic change that would be expected in urbanizing watersheds.  Preliminary results suggest that hydrologic changes are notable during periods of intense development, with recession plot characteristics markedly variable in urbanizing and urban watersheds as compared to the natural watershed. Analysis of streamflow records during the process of urbanization reveals groundwater-surface water interactions driven by urban development previously only observed over relatively shorter time periods. These findings can inform implementation of sustainable design of storm water management and future development planning. </span></p>

THE CRITICAL ROLE OF CONVERSION COST AND COMPARATIVE ADVANTAGE IN MODELING AGRICULTURAL LAND USE CHANGE

The difference in land use modeling approaches is an important uncertain factor in evaluating future climate scenarios in global economic models. We compare five widely used land use modeling approaches: constrained optimization, constant elasticity of transformation (CET), the additive form of constant elasticity of transformation (ACET), logit, and Ricardian. We demonstrate that the approaches differ not only by the extent of parameter uses but also by the definition of conversion cost and the consideration of comparative advantage implied by land heterogeneity. We develop a generalized hybrid approach that incorporates ACET/logit and Ricardian to account for both conversion cost and comparative advantage. We use this hybrid approach to estimate future climate impacts on agriculture. We find a welfare loss of about 0.38–0.46% of the global GDP. We demonstrate that ignoring land heterogeneity or land conversion costs underestimates climate impacts on agricultural production and welfare.