Resources
Displaying 1211 - 1215 of 2258Erratum: Lee, J.-H.; Kim, D.-K. Mapping Environmental Conflicts Using Spatial Text Mining. Land 2020, 9, 287
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Climate-Wise Habitat Connectivity Takes Sustained Stakeholder Engagement
Well-managed and connected protected area networks are needed to combat the 6th mass extinction, yet the implementation of plans intended to secure landscape connectivity remains insufficient. The failure to translate planning efforts into effective action (i.e., the research-implementation gap) hinders our ability to conserve biodiversity threatened by ongoing climate change and habitat fragmentation.
Environmental Impacts of Planned Capitals and Lessons for Indonesia’s New Capital
Indonesia’s new planned capital in East Kalimantan is being touted as a “smart, green, beautiful and sustainable city” but has stoked fears of massive environmental damage to the island of Borneo, one of the world’s most important biodiversity hotspots and carbon sinks. Precedents of other planned capitals can contribute to an understanding of the potential long-term impacts of Indonesia’s new capital.
Assessment of Changes in a Viewshed in the Western Carpathians Landscape as a Result of Reforestation
A viewshed analysis is of great importance in mountainous areas characterized by high landscape values. The aim of this research was to determine the impact of reforestation occurring on former pasturelands on changes in the viewshed, and to quantify changes in the surface of glades. We combine a horizontal and a vertical approach to landscape analysis. The changes in non-forest areas and the viewshed from viewpoints located in glades were calculated using historical cartographic materials and a more recent Digital Elevation Model and Digital Surface Model.
A Regression-Based Procedure for Markov Transition Probability Estimation in Land Change Modeling
Land change models commonly model the expected quantity of change as a Markov chain. Markov transition probabilities can be estimated by tabulating the relative frequency of change for all transitions between two dates. To estimate the appropriate transition probability matrix for any future date requires the determination of an annualized matrix through eigendecomposition followed by matrix powering. However, the technique yields multiple solutions, commonly with imaginary parts and negative transitions, and possibly with no non-negative real stochastic matrix solution.