Coastal retreat is a non-recoverable phenomenon that—together with a relevant proneness to landslides—has economic, social and environmental impacts. Quantitative data on geological and geomorphologic features of such areas can help to predict and quantify the phenomena and to propose mitigation measures to reduce their impact. Coastal areas are often inaccessible for sampling and in situ surveys, in particular where steeply sloping cliffs are present. Uses and capability of infrared thermography (IRT) were reviewed, highlighting its suitability in geological and landslides hazard applications. Thanks to the high resolution of the cameras on the market, unmanned aerial vehicle-based IRT allows to acquire large amounts of data from inaccessible steep cliffs. Coupled structure-from-motion photogrammetry and coregistration of data can improve accuracy of IRT data. According to the strengths recognized in the reviewed literature, a three-step methodological approach to produce IRTs was proposed.

In the Wadi Biskra arid and semiarid areas, sustainable development is restricted by land degradation processes such as secondary salinization of soils. Being an important high-quality date production region of Algeria, this area needs continuous monitoring of desertification indicators, hence highly exposed to climate-related risks. Given the limited access to field data, appropriate methods were assessed for the identification and change detection of salt-affected areas, involving image interpretation and automated classifications employing Landsat imagery, ancillary and multisource ground truth data. First, a visual photointerpretation study of the land cover and land use classes was undergone according to acknowledged methodologies. Second, two automated classification approaches were developed: a customized decision tree classification (DTC) and an unsupervised one applied to the principal components of Knepper ratios composite. Five indices were employed in the DTC construction, among which also is a salinity index. The diachronic analysis was undergone for the 1984 to 2015 images (including seasonal approach), being supported by the interpreted land cover/land use map for error estimation. Considering also biophysical and socioeconomic data, comprehensive results are discussed. One of the most important aspects that emerged was that the accelerated expansion of agricultural land in the last three decades has led and continues to contribute to a secondary salinization of soils.

This paper presents the results of management-oriented research on energy, forest, and human health issues in a remote mountain area, the Sagarmatha National Park and Buffer Zone (SNPBZ), Nepal. The research was based on a broader, integrated participatory framework ultimately intended for use in adaptive management. The present study focused on the application of a participatory modeling framework to address problems related to energy demand and consumption, forest condition, and indoor air pollution, which were defined by the stakeholders as important issues to be addressed. The models were developed using a generalizing design that allows for user-friendly adaptation to other contexts (free download at http://hkkhpartnership.org). Moreover, we simulated management scenarios in collaboration with all modeling actors with the aim of building consensus on the understanding of the system as well as supporting decision-makers' capacity not only to respond to changes, but also to anticipate them. Importantly, the system dynamics assessment found that the SNPBZ forests are affected by an increasing demand for fuelwood (occurring due to tourism growth), as one of the main sources of energy. Selected forests show an average reduction of 38 in forest biomass from 1992 to 2008. This shows that the business-as-usual scenario is unlikely to result in the preservation of the current forest status; in fact, such preservation would require 75 of fuelwood to be replaced with alternative energy sources. At the same time, a 75 reduction of fuelwood use (and an 80 reduction of dung use) would reduce indoor carbon monoxide (CO) concentrations to the standard limits for CO exposure set by the World Health Organization. © 2010 International Mountain Society

Aeolian processes in drylands often transcend into sand encroachment, a common form of land degradation. Highly reflective desert features, hence sandy areas, often cause spectral confusion, and mapping through remote sensing techniques can be challenging. This work aims at designing an efficient classification method that minimises spectral confusion of desert features, hence two types of sandy areas. Moreover, we employ land cover (LC) change detection over the last 30 years. The extraction and spatiotemporal variations of LC and sand encroachment areas in the Dahar-Jeffara Medenine site (southeastern Tunisia) are assessed by employing Landsat imagery (1984 and 2014), a 30 m digital elevation model of Shuttle Radar Topography Mission (SRTMGL 1 arc second), field data and X-ray diffraction analyses of sand samples. Five new spectral indices were designed and employed in a Decision Tree (DT) classifier for the extraction of 11 LC classes, including two different types of sandy areas. The DT map yielded an overall accuracy of around 89%. Change detection results showed substantial change in several landscape components and an increase of sand units by 29% within the Jeffara-Medenine plain over the last three decades. Geomorphological observations and multi-temporal, spectral and mineral analyses indicate a main, possible in-situ source area of sand.