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.

The expansion of built environments and agriculture land in the Nan watershed, Thailand, to support the rapid increase of the national population has resulted in deforestation, thus affecting the ecological balance. This deforestation, especially in high mountainous areas, has led to serious environmental degradation. Recent reports reveal an increasing soil-erosion problem in the watershed. This study analyses land-use and land-cover (LULC) changes and their potential impact on soil erosion during a study period between 1995 and 2005.

Many avian species persist in human‐dominated landscapes; however, little is known about the demographic consequences of urbanization in these populations. Given that urban habitats introduce novel benefits (e.g., anthropogenic resources) and pressures (e.g., mortality risks), conflicting mechanisms have been hypothesized to drive the dynamics of urban bird populations. Top‐down processes such as predation predict reduced survivorship in suburban and urban habitats, whereas bottom‐up processes, such as increased resource availability, predict peak survival in suburban habitats.

Land-use information is required for a number of purposes such as to address food security issues, to ensure the sustainable use of natural resources and to support decisions regarding food trade and crop insurance. Suitable land-use maps often either do not exist or are not readily available. This article presents a novel method to compile spatial and temporal land-use data sets using multi-temporal remote sensing in combination with existing data sources.

Habitat loss and fragmentation are known to reduce patch sizes and increase their isolation, consequently leading to modifications in species richness and community structure. Calcareous grasslands are among the richest ecosystems in Europe for insect species. About 10% (1,150 ha) of the total area of a calcareous ridge region (Calestienne, Belgium) and its butterfly community was analysed over a timeframe of about 100 years.

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.

Stream water temperature (tₛ) is a critical water quality parameter for aquatic ecosystems. However, tₛrecords are sparse or nonexistent in many river systems. In this work, we present an empirical model to predict tₛat the site scale across the USA. The model, derived using data from 171 reference sites selected from the Geospatial Attributes of Gages for Evaluating Streamflow database, describes the linear relationship between monthly mean air temperature (tₐ) and tₛ.

The Natural Resources Conservation Service curve–number (CN) method commonly uses three discrete levels (1, 2, and 3) of antecedent moisture condition (AMC) to describe soil moisture at the time of a runoff event. However, this may not adequately represent soil water conditions for watershed modeling purposes. The objectives of this study were to evaluate the use of individual–event watershed–scale AMC values to adjust field–scale CN, and to assess which hydrologic parameters would provide the best estimate of individual–event AMC.

- Brook charr (Salvelinus fontinalis) is a sentinel fish species that requires clean, cold water habitats generally resulting from landscapes that allow for surface water flows devoid of sediment and contaminants and high groundwater discharge of cold water. As such, brook charr are impacted by land cover changes that alter stream temperature regimes. We evaluated brook charr populations across their eastern and midwestern range in the United States with reference to thermal habitat availability in relationship to land cover and per cent baseflow.

The exploration of the relationships between plant biotic dynamics and scale can reveal important information on ecosystem spatial organization by addressing preservation of information integrity in upscaling/downscaling procedures of land-surface parameterization for environmental modeling applications. Scale-dependent relations of vegetation dynamics are investigated in this study by using emergent biophysical characteristics obtained through a predictive multidimensional model of vegetation anomalies derived from remote-sensing observations.