Pokhara is one of the most naturally beautiful cities in the world with a unique geological setting. This important tourist city is under intense pressure from rapid urbanization and population growth. Multiple hazards and risks are rapidly increasing in Pokhara due to unsustainable land use practices, particularly the increase in built-up areas. This study examines the relationship among urbanization, land use/land cover dynamics and multiple hazard and risk analysis of the Pokhara valley from 1990 to 2013.

We developed an agent-based model (ABM) to simulate farmers’ decisions on crop type and fertilizer application in response to commodity and biofuel crop prices. Farm profit maximization constrained by farmers’ profit expectations for land committed to biofuel crop production was used as the decision rule. Empirical parameters characterizing farmers’ profit expectations were derived from an agricultural landowners and operators survey and integrated in the ABM.

Identifying patterns and drivers of regional land use changes is crucial for supporting land management and planning. Doing so for mountain ecosystems in East Asia, such as the So-yang River Basin in South Korea, has until now been a challenge because of extreme social and ecological complexities. Applying the techniques of geographic information systems (GIS) and statistical modeling via multinomial logistic regression (MNL), we attempted to examine various hypothesized drivers of land use changes, over the period 1980 to 2000.

Long-term intensive land use/cover changes (LUCCs) of the Yellow River Delta (YRD) have been happening since the 1960s. The land use patterns of the LUCCs are crucial for bio-diversity conservation and/or sustainable development. This study quantified patterns of the LUCCs, explored the systematic transitions, and identified wetland change trajectory for the period 1976–2014 in the YRD. Landsat imageries of 1976, 1984, 1995, 2006, and 2014 were used to derive nine land use classes.

The Long Island Sound Watersheds (LISW) are experiencing significant land use/cover change (LUCC), which affects the environment and ecosystems in the watersheds through water pollution, carbon emissions, and loss of wildlife. LUCC modeling is an important approach to understanding what has happened in the landscape and what may change in the future. Moreover, prospective modeling can provide sustainable and efficient decision support for land planning and environmental management.

Better recognition of public perceptions is called for in developing policies that affect landscape qualities, such as agri-environmental policies. The present study focused on the evaluation of typical agricultural landscapes in Finland. We utilized and operationalized the visual landscape quality scales introduced by Tveit et al. (2006) and further explored how these scales can be applied in citizen evaluation of agricultural landscapes.

Land change in the Greater Antilles differs markedly among countries because of varying socioeconomic histories and global influences. We assessed land change between 2001 and 2010 in municipalities (second administrative units) of Cuba, Dominican Republic, Haiti, Jamaica, and Puerto Rico. Our analysis used annual land-use/land-cover maps derived from MODIS satellite imagery to model linear change in woody vegetation, mixed-woody/plantations and agriculture/herbaceous vegetation. Using this approach, we focused on municipalities with significant change (p ≤ 0.05).

A one year field trial was carried out on three adjacent unfertilised plots; an 18 year old grassland, a 14 year old established Miscanthus crop, and a 7 month old newly planted Miscanthus crop. Measurements of N2O, soil temperature, water filled pore space (WFPS), and inorganic nitrogen concentrations, were made every one to two weeks. Soil temperature, WFPS and NO3− and NH4+ concentrations were all found to be significantly affected by land use.

Ulaanbaatar, the capital of Mongolia, has expanded rapidly over the past decade. Insufficient authority is in place to address this expansion, and many residential plots have been developed in the peripheral regions of the city. The aim of this study is to estimate changes in land cover within the central part of Ulaanbaatar, which has been affected by anthropogenic disturbances.

Estimating deforested areas and deforestation rates have become key steps for quantifying environmental services of tropical rain forests, particularly as linked to programs such as Reduced Emissions from Deforestation and Forest Degradation (REDD). In Southeastern Peru, reliable estimates of land-cover change (LCC) are important for monitoring changes in the landscape due to agricultural expansion, pasture creation and other socio-economic influences triggered by the Inter-Oceanic Highway (IOH).

Future forest cover changes were simulated under the business-as-usual (BAU), pessimistic and optimistic scenarios using the Markov-cellular automata (MCA) model in Pakxeng district, Lao People’s Democratic Republic (PDR). The Markov chain analysis was used to compute transition probabilities from satellite-derived forest cover maps (1993, 1996, 2000 and 2004), while the “weights of evidence” procedure was used to generate transition potential (suitability) maps.

In order to address the challenges in coastal regions, there is the need to understand the extent and impacts of past changes and their implications for future management. Land use data and remotely-sensed imagery are often used to provide insights into these changes. Often, however, existing land use data are inconsistent, thus differences observed through their analyses could also be attributable to error. The use of multiple layers of data, in addition and as related to basic land use layers, has been suggested in the literature as a method to mitigate such error.