Vegetation type is one of many factors that affect watershed hydrology and is an especially important influence on surface hydrological processes. Canopy and ground cover vegetation provide a natural cushion against the impact energy of rainfall in headwater portions of a stream basin, increasing water filtration into the soil and reducing surface runoff, but effects of different vegetation types are not fully understood. We sought to evaluate the capacity of different vegetation communities to regulate surface runoff in an alpine landscape.

Non-Urbanised Areas (NUAs) are part of agricultural and green infrastructures that provide ecosystem services. Their role is fundamental for the minimization of urban pollution and adaptation to climate change. Like all natural ecosystems, NUAs are endangered by urban sprawl. The regulation of sprawl is a key issue for land-use planning. We propose a land use suitability strategy model to orient Land Uses of NUAs, based on integration of Land Cover Analysis (LCA) and Fragmentation Analysis (FA). With LCA the percentage of evapotranspiring surface is defined for each land use.

Modern ecological models often account for the influence of the surrounding environment by using landscape pattern indices (LPIs) as measures of landscape structure. Ideally, the landscape samples from which these LPIs are extracted should be centered on the locations where the response variable was measured. However, in situations where this is not possible due to a lack of adequate full-coverage landcover data, the question arises as to what degree this circumstance creates a bias in the value of the LPIs, thereby obscuring their relation with the response variable.

Ashfall and pyroclastic flows from the large eruption of June 1991 destroyed much of the vegetation on the flanks of Mt. Pinatubo. Subsequent vegetation recovery has helped stabilize slopes and reduce debris flow hazard. In this project, visible and near-infrared (VNIR) satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (ASTER) captured at a similar time of year in 2001, 2004 and 2008 were used to quantify vegetation recovery within 22 upland watersheds on the mountain, 10–16 years after the eruption took place.

A number of classification techniques to generate land cover maps from satellite imagery have been proposed but supervised classification with manual selection and delineation of training samples (TSs) continues to be the preferred technique. The current practices of field visits and manual delineation of TSs by visual recognition are highly demanding on both resources and time, with limited utility.

Oil exploration and production activities (OEPA) and other extractive endeavors can create large-scale and permanent landscape alterations through the establishment of infrastructure features such as roads, well pads, pipelines and production facilities. These structures can lead to or increase landscape fragmentation and degradation, reduce biodiversity, disrupt important ecosystem services and attract informal settlements that further alter the landscape, deplete area resources and lead to social conflict.

It is challenging to perform spatial geochemical modelling due to the spatial heterogeneity features of geochemical variables. Meanwhile, high quality geochemical maps are needed for better environmental management. Soil organic C (SOC) distribution maps are required for improvements in soil management and for the estimation of C stocks at regional scales. This study investigates the use of a geographically weighted regression (GWR) method for the spatial modelling of SOC in Ireland. A total of 1310 samples of SOC data were extracted from the National Soil Database of Ireland.

We assessed past and present vegetation patterns in relation to land use on a municipal commonage in South Africa. We asked specifically whether the reassignment of the commonage for the use of historically disadvantaged town residents after 1994 has impacted negatively on the vegetation of the commonage. Analysis of land cover change using aerial photography time series revealed that the most significant human impacts on the Bathurst commonage occurred prior to 1942 due to heavy and uncontrolled communal land use.

Question: What are the composition, structure and extent of contemporary, common woody vegetation communities in New Zealand? How do the woody plant communities we describe, based on representative sampling, compare to those of previous New Zealand classifications? Methods: We used cluster analysis to classify data from 1177 systematically located vegetation plots, calculated spatial extent and ecological statistics for each alliance defined, and combined forest alliances into groups to assess correspondence with earlier mapped classifications.

The Phase 1 Survey is the most comprehensive and widely used national level map of semi-natural habitats in Wales. However, the survey was based largely on field survey and was conducted over several decades, before being completed in 1997. Given that resources for a repeat survey were limited, this study has used an object-orientated rule-based classification implemented within eCognition of multi-temporal satellite sensor data acquired between 2003 and 2006 to map semi-natural habitats and agricultural land across Wales, thereby allowing a progressive update of the Phase 1 Survey.

Managing land resources using remote sensing techniques is becoming a common practice. However, data analysis procedures should satisfy the high accuracy levels demanded by users (public or private companies and governments) in order to be extensively used. This paper presents a multi-stage classification scheme to update the citrus Geographical Information System (GIS) of the Comunidad Valenciana region (Spain). Spain is the first citrus fruit producer in Europe and the fourth in the world.

This article describes the use of a Bayesian network (BN) for the classification of land cover from satellite imagery in northern Swaziland. The main objective of this work was to apply and evaluate the efficacy of a BN for land-cover classification using gap-filled and terrain-corrected Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery acquired on 15 May 2007. The posterior probabilities (parameters) were estimated using the expectation-maximization (EM) and conjugate gradient descent (CGD) algorithms.