Canada’s National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 10⁶ km² of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data.

Although the designation of greenbelts around cities has been a common practice for several decades, some greenbelts have not been successfully protected from development. To explore the forces driving the construction of greenbelts, this paper examines how past land use and land cover decisions and current socioeconomic factors have affected the development of the artificial greenbelt zone in China’s Shanghai metropolitan area. Using aerial photographs from 1994, 2005, and 2010, we find that the area of afforested greenbelt was generally related to past land use/cover decisions.

In Canada, fire danger is predicted by the Canadian Forest Fire Danger Rating System (CFFDRS). One of its subsystems is the Canadian Fire Weather Index (FWI) system, which has two slow-drying fuel moisture codes: the drought code (DC) and the duff moisture code (DMC). Both codes are used in this study as a surrogate of dead fuel moisture. We evaluate the capability of Moderate Resolution Imaging Spectrometer (MODIS) observations to map DC and DMC.

Functional indicators are being increasingly used to assess waterway health but their responses to pressure in non-wadeable rivers have not been widely documented or applied in modern survey designs that provide unbiased estimates of extent. This study tests the response of river metabolism and loss in cotton strip tensile strength across a land use pressure gradient in non-wadeable rivers of northern New Zealand, and reports extent estimates for river metabolism and decomposition rates.

The purpose of this study was to find out whether a set of habitat characteristics, derived from the National Corine Land Cover (CLC) database of habitat types, could indicate the occurrence of white stork nests in a settlement. The analyses were performed for the settlements closer than 35 km from the Drava River (northern Croatia). Sixteen habitat characteristics were determined around 257 settlements occupied with white stork nests and 152 control sites without white stork nests within the same geographic region.

This paper examines the newly constructed geographically scaled economic output measure, Gross Cell Product (GCP), of Australia and New Zealand to quantify the impacts of climate change in the region. The paper discusses advantages of using the GCP instead of the Gross Domestic Product. The paper reveals that the GCP falls sharply as temperature increases in the region. A 1°C increase in temperature would decrease the productivity with an elasticity of −2.4. A 1 per cent decrease in precipitation would decrease productivity with an elasticity of −2.3.

We used boosted regression trees (BRT) to model stream biological condition as measured by benthic macroinvertebrate taxonomic completeness, the ratio of observed to expected (O/E) taxa. Models were developed with and without exclusion of rare taxa at a site. BRT models are robust, requiring few assumptions compared with traditional modeling techniques such as multiple linear regression.

This article presents a sufficient comparison of two types of advanced non-parametric classifiers implemented in remote sensing for land cover classification. A SPOT-5 HRG image of Yanqing County, Beijing, China, was used, in which agriculture and forest dominate land use. Artificial neural networks (ANNs), including the adaptive backpropagation (ABP) algorithm, Levenberg–Marquardt (LM) algorithm, Quasi-Newton (QN) algorithm and radial basis function (RBF) were carefully tested.

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, longterm time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol.

Human activity is one of the most important aerosol sources. Because the underlaying surface feature records most human activities, it is important to recognize the correlation between aerosol distribution and the underlaying surface.

An algorithm for supervised classification of multisensor images is proposed. The mixture of experts (ME) architecture with dynamic weight allocation is used for multiclass classification. Here the classification is treated as a maximum likelihood problem and the synaptic weights of the expert network and gating network are updated by a stochastic multigradient approach. Data from an optical sensor with four bands and a synthetic aperture radar (SAR) image of the same scene has been fused and classified.

The aim of this study is to extract landslide-related factors from remote-sensing data, such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery, and to examine their applicability to landslide susceptibility near Boun, Korea, using a geographic information system (GIS). Landslide was mapped from interpretation of aerial photographs and field surveying. Factors that influence landslide occurrence were extracted from ASTER imagery.