Arjan S. Gosal

TL;DR: In this article, a novel approach, borrowing techniques from machine learning (image analysis), natural language processing (Latent Semantic Analysis (LSA)) and self-organising maps (SOM), was demonstrated to collect and interpret >20,000 photos from the Camargue region in Southern France.

TL;DR: In this article, a spatial model was developed to predict and map landscape aesthetics across the whole site of the protected area of the Yorkshire Dales National Park, using publicly available images, paired-comparison surveys, probability modelling, machine-learning based text annotations, natural language processing and regression analysis.

TL;DR: This work describes the provision (level and spatial variability) of grassland ES under various management strategies and shows that management regime and intensity levels play an important role in ES provision but their impact depends on the ES.

TL;DR: A novel quantitative approach for assessing forest resilience that focuses on three components of resilience, namely resistance, recovery, and net change, using a spatially explicit model of forest dynamics is provided.

TL;DR: In this article, a comparative analysis of three approaches for non-monetary valuation of cultural ecosystem services (CES) is presented, namely a structured survey, participatory GIS (PGIS) and GPS tracking methods.