Strictly Protected Areas and riparian forests in Brazil are rarely large enough or connected enough to maintain viable populations of carnivores and animal movement over time, but these characteristics are fundamental for species conservation as they prevent the extinction of isolated animal populations. Therefore, the need to maintain connectivity for these species in human-dominated Atlantic landscapes is critical.

The role biodiversity plays in the provision of ecosystem services is widely recognized, yet few ecological studies have identified characteristics of natural systems that support and maintain ecosystem services. The purpose of this study was to identify landscape variables correlated with natural pest suppression carried out by arthropod natural enemies, predators and parasitoids. We conducted two field experiments, one observational and one experimental, where landscape variables at broad and local scales were measured and related to natural pest suppression.

A comprehensive Landslide Susceptibility Zonation (LSZ) map is sought for adopting any landslide preventive and mitigation measures. In the present study, LSZ map of landslide prone Ganeshganga watershed (known for Patalganga Landslide) has been generated using a binary logistic regression (BLR) model.

This study compared concentrations and export of total phosphorus (TP; including dissolved and particulate forms) and nitrogen (N) between quickflow and delayed flow at two adjacent agricultural catchments (Jennings and McLarens Creeks), one of which is undergoing increased urbanization. Annual runoff, frequency of quickflow events in the growing season (GS), and chloride (Cl⁻) concentrations and export were greater at the more urbanized Jennings Creek.

A novel approach to study vegetation dynamics is introduced, using the Empirical Mode Decomposition (EMD) to analyze NDVI time series. The NDVI time series which is nonlinear and nonstationary can be decomposed by EMD into components called intrinsic mode functions (IMFs), based on inherent temporal scales. The highest frequency component which has been found to represent noise is subtracted from the original NDVI series; thus smoothing the noisy signal. The different key features describing vegetation phenology have been extracted by analyzing the noise free signal.

Arctic soils contain three times as much carbon (C) as all aboveground biomass distributed globally, much of which is stored in permafrost soils. Here, we (1) determine the predictability of estimating soil organic carbon (SOC) using different satellite data, classifications, and methods; (2) estimate the quantity and distribution of SOC for the top 10 cm for the Ambolikha River watershed (~121 km ²) in northeast Siberia, a sub-watershed of the Kolyma River; and (3) produce a hybrid SOC map through data fusion, combining the strengths of each data type.

Urbanization is increasingly becoming a widespread phenomenon at all scales of development around the globe. Be it developing or developed nations, all are witnessing urbanization at very high pace. In order to study its impacts, various methodologies and techniques are being implemented to measure growth of urban extents over spatial and temporal domains. But urbanization being a very dynamic phenomenon has been facing ambiguities regarding methods to study its dynamism. This paper aims at quantifying urban expansion in Delhi, the capital city of India.

This study investigates the impact of using different combinations of Moderate Resolution Imaging Spectroradiometer (MODIS) and ancillary datasets on overall and per-class classification accuracies for nine land cover types modified from the classification system of the International Geosphere Biosphere Programme (IGBP).

Image fusion assists in visual interpretation, mapping, change detection and many other applications. Multispectral and Panchromatic images are fused to produce images having enhanced spatial and spectral properties. These properties are generally distorted from original images. The aim of this paper is to identify the effectiveness of the several fusion techniques based on the distortions and applications.

Digital image classification is the process of sorting all the pixels in an image into a finite number of individual classes. But, it is difficult to classify satellite images since they include both pure pixels and boundary pixels. The boundary pixels are ‘mixed’ pixels, representing an area occupied by more than one ground cover. That is, class boundaries represented by pixels, are not sharp but fuzzy. This paper discuses the application of Adaptive Neuro-Fuzzy inference system (ANFIS) for classification of remotely sensed images that contains mixed pixels.

Literature on environmental change often highlights the importance of public policies as a key driver of land use and land cover change. However, demonstration of policy impacts in agricultural settings has been hampered by the lack of systematic analysis across landholders, who may not universally adopt government policy incentives, or time periods, which may be associated with differing policy regimes.

In this paper solutions are proposed to improve the performance of a wheeled robot for rural environment. These solutions can be used for a wheeled mobile robot that moves upon curved surfaces, surfaces with irregularities and small coefficient of static friction between the wheels and the surface. The design and control of the robot are based on a new concept of a wheeled mobile robot, which can work in two different modes.