Search PubMed⌕ Search

PubMed · 11148766

Quantifying forest visibility with spatial data.

Abstract

We use spatial data representing transportation networks, elevation, stand height, and recreation use to construct and compare models of recreation use patterns and visibility in a forest. The recreation use pattern model depicts use frequencies along travel corridors. The visibility model quantifies visibility for all forest areas. We find that the models provide different but complementary types of information. Forest managers who are involved in scheduling harvest operations and want to address the visual concerns of forest visitors may benefit most from the visibility model. Managers who wish to know more about travel patterns or to reroute forest visitors affected by operations may benefit from the use pattern model. A combination of the two models has the highest potential for providing planning assistance in multiple-use forests. Both models may be able to enhance visual resource management (VRM) systems already in use by providing spatially explicit recreation use and visibility data.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M G Wing, R Johnson. 2001. Quantifying forest visibility with spatial data.. https://doi.org/10.1007/s002670010158

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5​ concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution↗

Lung lining liquid modifies PM(2.5) in favor of particle aggregation: a protective mechanism.

The health effects of particle inhalation including urban air pollution and tobacco smoke comprise a significant public health concern worldwide, although the mechanisms by which inhaled particles cause premature deaths remain undetermined. In this study, we assessed the physicochemical interactions of fine airborne particles (PM(2.5)) and lung lining liquid using scanning electron microscopy, atomic force microscopy, and X-ray photon spectroscopy. We provide experimental evidence to show that lung lining liquid modifies the chemistry and attractive forces at the surface of PM(2.5), which leads to enhanced particle aggregation. We propose that this is an important protective mechanism that aids particle clearance in the lung.

Air Pollution↗

Ambient urban Baltimore particulate-induced airway hyperresponsiveness and inflammation in mice.

Airborne particulate matter (PM) is hypothesized to play a role in increases in asthma prevalence, although a causal relationship has yet to be established. To investigate the effects of real-world PM exposure on airway reactivity (AHR) and bronchoalveolar lavage (BAL) cellularity, we exposed naive mice to a single dose (0.5 mg/ mouse) of ambient PM, coal fly ash, or diesel PM. We found that ambient PM exposure induced increases in AHR and BAL cellularity, whereas diesel PM induced significant increases in BAL cellularity, but not AHR. On the other hand, coal fly ash exposure did not elicit significant changes in either of these parameters. We further examined ambient PM-induced temporal changes in AHR, BAL cells, and lung cytokine levels over a 2-wk period. Ambient PM-induced AHR was sustained over 7 d. The increase in AHR was preceded by dramatic increases in BAL eosinophils, whereas a decline in AHR was associated with increases in macrophages. A Th2 cytokine pattern (IL-5, IL-13, eotaxin) was observed early on with a shift toward a Th1 pattern (IFN-gamma). In additional studies, we found that the active component(s) of ambient PM are not water-soluble and that ambient PM-induced AHR and inflammation are dose- dependent. We conclude that ambient PM can induce asthma-like parameters in naive mice, suggesting that PM exposure may be an important factor in increases in asthma prevalence.

Air Pollution↗