Can management effort be predicted for marine protected areas? New considerations for network design

This study examined the level of management complexity (simultaneously occurring licensed human activities) within the currently designated Marine Protected Areas (MPAs) in Scottish waters and through modelling and statistical analysis determined which variables play an important role in defining the level of management effort required for each MPA. This study utilised surveyed distribution data for Priority Marine Features and modelled distribution data showing potential “Most Suitable” Priority Marine Feature habitat through the species distribution model, Maxent. Prediction indicators were developed through Spearman׳s Rank coefficients and a linear regression model. Results showed that, (1) there was a significant negative correlation between the management complexity score within 5 km of a MPA and the number of casework events (defined as any work or statutory consultation associated with an MPA, such as planning applications, discharges or new fisheries); and (2) a significant positive correlation between the number of casework events and location, number of features, and the type of features and most suitable scores. Calculations showed that Lochs Duich, Long and Alsh, Loch Sunart, Loch Sween and Loch Creran may potentially require most effort to manage once they are designated as MPAs. This study showed that it is possible to evaluate options within an MPA network to achieve cost effective options for the biodiversity and socio-economic objectives of MPA networks and that some MPAs are likely to be more efficient than others in terms of management time.     

Relevance of systems approaches for implementing Integrated Coastal Zone Management principles in Europe

Integrated Coastal Zone Management (ICZM) development is described here in the broader context of European coastal management initiatives. The European approach to coastal governance revolves around the principles of ICZM, as enshrined in EC Recommendation 2002/413/EC. This study investigates the extent to which the FP6 funded project SPICOSA (Science Policy Integration for Coastal Systems Assessment) was able to implement these principles. The SPICOSA project aimed to test whether it was possible to develop and implement a systems approach framework via delivery of a structured engagement process between scientists and policymakers. A survey of representatives from 14 European study sites involved in the project revealed that the approach had been effective at implementing some ICZM principles, particularly the “holistic approach”. However, not all principles were fully implemented at all sites and the most challenging to implement was that of “a long term approach”. The paper concludes with a critical consideration of the role of a systems approach framework in progressing the current state of intellectual assent towards practical implementation of ICZM principles. The findings provide evidence of contributions and limitations of systems approaches to sustainability science and good governance.     

The use of ocean color remote sensing in integrated coastal zone management—A case study from Himmerfjärden,Sweden

In this study the use of ocean color data as a diagnostic tool in integrated coastal zone management was investigated as part of the Science Policy Integration for Coastal Systems Assessment (SPICOSA) project. Parallel to this, an operational coastal monitoring system has been set up in close collaboration with end-users. The core work of the bio-optical part in the project was to develop Secchi depth and attenuation of light as indicators for coastal zone management, by linking remote sensing with the socio-economic and ecological model developed in SPICOSA. The article emphasizes the benefits of stakeholder involvement and end-user feedback for efficient and improved system development. Furthermore, conceptual models were developed on how to integrate remote sensing data into coastal zone management and into a physical-biological model of the Baltic Sea. One of the work packages in the SPICOSA project was academic training. In this work package, on-line teaching material in the field of remote sensing and bio-optics was developed and disseminated on the SETnet web page. The article presented here may act as supportive material for training in bio-optics and remote sensing.     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.     

Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies

A computational canopy volume (CCV) based on airborne laser scanning (ALS) data is proposed to improve predictions of forest biomass and other related attributes like stem volume and basal area. An approach to derive the CCV based on computational geometry, topological connectivity and numerical optimization was tested with sparse-density, plot-level ALS data acquired from 40 field sample plots of 500–1000 m² located in a boreal forest in Norway. The CCV had a high correspondence with the biomass attributes considered when derived from optimized filtrations, i.e. ordered sets of simplices belonging to the triangulations based on the point data. Coefficients of determination (R²) between the CCV and total above-ground biomass, canopy biomass, stem volume, and basal area were 0.88–0.89, 0.89, 0.83–0.97, and 0.88–0.92, respectively, depending on the applied filtration. The magnitude of the required filtration was found to increase according to an increasing basal area, which indicated a possibility to predict this magnitude by means of ALS-based height and density metrics. A simple prediction model provided CCVs which had R² of 0.77–0.90 with the aforementioned forest attributes. The derived CCVs always produced complementary information and were mainly able to improve the predictions of forest biomass relative to models based on the height and density metrics, yet only by 0–1.9 percentage points in terms of relative root mean squared error. Possibilities to improve the CCVs by a further analysis of topological persistence are discussed.     

Characterization of aboveground biomass in an unmanaged boreal forest using Landsat temporal segmentation metrics

Canada is dominated by forested ecosystems which are subject to various inventory and management practices, with more northern boreal forests subject to neither. Our objectives were to measure the capacity of temporal trajectory metrics for estimating selected forest attributes in a northern Canadian boreal forest context using Landsat imagery and investigate the importance of different types of temporal trajectory metrics. Results indicated that Wetness was the best Tasseled Cap (TC) component for aboveground biomass estimation (R² = 50%, RMSE% = 56%), and the combination of simple and complex metrics from all TC components produced the highest R² (62%) and lowest RMSE% (49%). Using a similar combination of variables, other forest attributes were estimated equally reliably with lower RMSE% values. The most important temporal trajectory metrics were simple and described TC component values at each point of change in the temporal trajectory, however the most important variables overall were environmental variables.     

Forest law enforcement in the Brazilian Amazon: Costs and income effects

Despite recent success in reducing forest loss in the Brazilian Amazon, additional forest conservation efforts, for example, through ‘Reducing Emissions from Deforestation and Forest Degradation’ (REDD+), could significantly contribute to global climate-change mitigation. Economic incentives, such as payments for environmental services could promote conservation, but deforestation often occurs on land without crucial tenure-security prerequisites. Improving the enforcement of existing regulatory disincentives thus represents an important element of Brazil's anti-deforestation action plan. However, conservation law enforcement costs and benefits have been much less studied than for conditional payments. We develop a conceptual framework and a spatially explicit model to analyze field-based regulatory enforcement in the Brazilian Amazon. We validate our model, based on historical deforestation and enforcement mission data from 2003 to 2008. By simulating the current conservation law enforcement practice, we analyze the costs of liability establishment and legal coercion for alternative conservation targets, and evaluate corresponding income impacts. Our findings suggest that spatial patterns of both deforestation and inspection costs markedly influence enforcement patterns and their income effects. Field-based enforcement is a highly cost-effective forest conservation instrument from a regulator's point of view, but comes at high opportunity costs for land users. Payments for environmental services could compensate costs, but will increase budget outlays vis-à-vis a command-and-control dominated strategy. Both legal and institutional challenges have to be overcome to make conservation payments work at a larger scale. Decision-makers may have to innovatively combine incentive and disincentive-based policy instruments in order to make tropical forest conservation both financially viable and socially compatible.     

浅谈设备管理信息系统开发项目风险管理

由于信息技术的快速发展和开发工具的日趋成熟,影响管理信息系统开发成功的瓶颈已不再是以技术为主的问题,而更多的是以人为主的风险管理问题。本文主要从风险识别与评估、风险应对与监控、风险回顾与改进这四个方面,阐述了北京市测绘设计研究院设备管理信息系统开发项目的风险管理经验,证实了准确识别和评估项目所面临的风险并进行有效应对和监控,是提高项目成功率的有效手段。     

一种大文件多版本遥感影像数据组织管理方法

近年来,遥感技术的飞速发展使得影像数据的使用也越来越广泛和深入,而影像分辨率的增加,使得数据量急剧增长,对数据的存储和管理提出了很高的要求。针对传统遥感影像数据组织存储的不足,本文提出了一种大文件金字塔数据存储结构,用来高效存储管理影像数据;同时针对多时相遥感影像数据,提出了基于版本机制的影像数据管理模式。实验表明这种方法具有更高的存储检索效率。     

基于全景真三维斜射影像的数字城管应用研究

随着国家智慧城市试点工作如火如荼的开展,数字城管作为智慧城市业务应用体系的重要组成部分,正成为各地探索创新应用的重要领域。洛阳市数字城管率先采用先进的全景真三维斜射影像技术,实现了快速的城市部件数据普查,创造了全新的用户体验,满足了专业化的城市管理应用需求,创新了＂全景化＂的数字城管应用新模式。