Mapping montane tropical forest successional stage and land use with multi-date Landsat imagery

When mapping land cover with satellite imagery in montane tropical regions, varying illumination angles and ecological zones can obscure the differences between spectral responses of old-growth forest, secondary forest and agricultural lands. We used multi-date, Landsat Thematic Mapper (TM) imagery to map secondary forests, agricultural lands and old-growth forests in the Talamanca Mountain Range in southern Costa Rica. With stratification by illumination and ecological zone, the overall accuracy for this classification was 87% with a Kappa coefficient of 0.83. We also examined spectral responses to forest successional stage, ecological zone and aspect illumination for the TM Tasselled Cap indices, TM (2 x 6)/7, TM 4/5 and TM difference bands, and whether using digital data from multiple decades improved classification accuracy. Digital maps of ecological zones should be useful for large-scale mapping of land use and forest successional stage in complex montane regions such as those in Central America.     

Production and allocation policies in a two-class inventory system with time and quantity dependent waiting costs

This paper presents an integrated production and inventory allocation model in a two-echelon supply chain system. The higher echelon is a manufacturer, who produces a single commodity. The lower echelon consists of two types of major commodity distributors who might face stochastic or deterministic demands from multiple retailers. Our analytical model provides optimal decision policies that minimize total production and customer waiting costs from the manufacturer's perspective when there are time and quantity dependent customer waiting costs. We identify the value of the integrated policy and compare it with typical approximations such as aggregating the multiple demands or applying the single demand multiple times.     

多区域厂房空调系统控制策略的设计与实施

多区域厂房的环境比较特殊,且其空调控制系统存在耦合、时变、滞后等非线性特性.针对厂房的环境特点和空调控制系统的难点,提出了新风量控制、末端送风阀控制和风量协调控制等一系列控制策略.为保障多区域厂房空调在多工况环境下的控制品质和稳定性,运用模糊控制实现风量协调控制,从而满足厂房各区域负荷变化.工程实施结果表明,厂房各区域的温湿度很好地满足了预定要求,从而证明了该控制策略的有效性.     

Use of topographic correction in Landsat TM-based forest interpretation in Nepal

The land use of two districts in western Nepal was classified into forest and non-forest by satellite imagery with different topographical corrections. The accuracy of the forest biomass and timber volume estimates was also tested. The forest areas were interpretated correctly, with an accuracy of 82-88%. The best result was derived when the Minnaert constants of forest were separated from those of other land uses which were combined. The timber volume and biomass estimates were computed using the weighted nearest neighbour method. The coefficients of determination were 0.06 for timber volume and 0.09 for biomass. The use of the existing land use data seems to have potential for improving the results of topographic normalization. Because the reflectance in mountainous areas depends on many vegetative and terrain features, the simple non-Lambertian correction over broad categories did not significantly improve the results.     

Patching process optimization in an agent-controlled timber mill

Repair and patching of wood defects is a costly process of inline production in timber industry. A large variety of plain as well as laminated wooden products demands for offline human interaction and skilled handcrafting in order to achieve the desired quality of the final products. The EU FP7 project Hol-I-Wood PR demonstrates the transformation of a traditional wood patching line for shuttering panels into a fully automated, flexible patching plant. The focus of this paper is set on the optimization of the different production steps of a patching robot, which comprises optimal patch placement, path planning and trajectory generation. Based on this, the processing time of each workpiece can be accurately estimated. These computations serve as an input for advanced panel scheduling, which assigns panels to one of several identical parallel patching lines in a throughput-optimal manner. In order to ensure high modularity of the components and scalability for various wood mills, an agent-based approach was chosen for the implementation of the automation system.     

Coordination between strategic forest management and tactical logistic and production planning in the forestry supply chain

In this paper, we study the coordination mechanism in the forestry supply chain between strategic forest management and tactical production planning. We first formulate an integrated model to establish a theoretical benchmark for performance of the entire supply chain. It is a mixed integer programming model that involves harvesting, bucking, transportation, production, and sales decisions for both tactical and strategic planning levels. We then present two sequential approaches S‐A and S‐B where the coordination is done through internal pricing. S‐A is the approach currently used in practice where harvesting in the forest is the main driver of the supply chain activities and internal pricing is introduced to control bucking decision in a separate stage. In contrast, S‐B takes downstream demand information into consideration and internal pricing directly influences harvesting decision in the first stage. In order to find the appropriate setting of internal pricing that leads to the system optimum, we suggest two heuristics H‐I and H‐II. The internal pricing in H‐I is based on dual values and in H‐II, it is derived from a Lagrangian decomposition. A real‐life case study in the Chilean forestry industry is used to compare the results of different approaches. It is shown that the new sequential approach S‐B generates as good feasible solution as that obtained from the integrated approach but in much less time. Both heuristics H‐I and H‐II bring about near‐optimal feasible solutions. H‐II also provides optimistic bound of the optimal objective function value, which can be used as a measure of the solution quality.     

Forest canopy recovery from the 1938 hurricane and subsequent salvage damage measured with airborne LiDAR

The structure of a forest canopy often reflects its disturbance history. Such signatures of past disturbances or legacies can influence how the ecosystem functions across broad spatio-temporal scales. The 1938 hurricane and ensuing salvage operations which swept through New England represent the most recent large, infrequent disturbance (LID) in this region. Though devastating (downing ∼ 70% of the timber at Harvard Forest), the disturbance was not indiscriminate; it left behind a heterogeneous landscape comprised of different levels of canopy damage. We analyzed large-footprint LiDAR, from the Prospect Hill tract at Harvard Forest in central Massachusetts, to assess whether damage to the forest structure from the hurricane and subsequent timber extraction could be discerned after ∼ 65 years. Differences in LiDAR-derived measures of canopy height and vertical diversity were a function of the degree of damage from the 1938 hurricane and the predominant tree species which is, in part, a function of land use history. Higher levels of damage corresponded to slightly shorter canopies with a less even vertical distribution of return from the ground to the top. In addition, differences in canopy topography as revealed by spatial autocorrelation of canopy top heights were found among the damage classes. Less disturbed stands were characterized by lower levels of local autocorrelation for canopy height and higher levels of vertical diversity of LiDAR returns. These differences in canopy structure reveal that the forest tract has not completely recovered from the 1938 LID and salvage regime, which may have implications on arboreal and understory habitat and other ecosystem functions.     

Use of remote sensing and GIS for improved natural resources management: case study from different agroecological zones of West Africa

Historical and recent aerial photograph and satellite images were analysed to study the change of land use/land cover and soil degradation in different agroecological zones of Nigeria and Benin. The sites were characterized by an expansion of farmland at the expense of forest and shrub, fallow and uncultivated land, at an increasing rate due to population growth, food demand and land scarcity. Sheet and gully erosion were the consequences of the land use intensification and have destroyed extensive areas of farmland and grazing land. Reduced agricultural and livestock production, declining revenue, as well as increased conflict from resource competition between farmers and pastoralists are expected for the future. To combat these problems, improved land use management through continuing land inventory, generating an environmental database, developing land use plans and controlling erosion through adequate soil conservation measures are recommended.     

A hybrid constraint programming approach to a wood procurement problem with bucking decisions

In this article, we present a wood procurement problem that arises in Eastern Canada. We solve a multi-period wood supply planning problem, while taking into account bucking decisions. Furthermore, we present a new form of flexibility which allows the harvesting capacity to change from one time period to another. We study the impact of such flexibility upon the harvesting cost. We assess the performance of the problem by comparing it with a variant where the harvesting capacity is fixed during sites’ harvesting. To address this problem, we develop a hybrid approach based on both constraint and mathematical programming. In the first phase, we propose a constraint programming model dealing with forest sites harvesting and bucking problems. The result of this model is used as part of an initial solution for the whole problem formulated as a mixed integer model. We test the two versions of the problem on a set of different demand instances and we compare their results.     

A Stealth Integrity Targeted Cyber‐Attack in Distributed Electric Power Networks with Local Model Information

Electric power networks are critical infrastructures, and their correct operation is of vital importance. Nowadays, these systems are prone to cyber‐attacks because of new vulnerabilities in the system and access to shared networks. In this paper, a novel Stealth Integrity Targeted Attack (SITA) is proposed in the context of distributed power systems. A distributed power system comprises several sub‐networks, or zones with dedicated control and monitoring centers. The overall system is represented by linear time invariant state space models with coupled dynamical and algebraic equations. In the proposed strategy, the attacker has access to only one of the sub networks; therefore, the attacker only requires local information about one of the power system zones. Primarily, the proposed attack policy is defined based on zero‐dynamics of the sub network. The intruder injects predesigned signals to both the local generation unit controller as well as local unsecured and controllable loads in the attacked zone. Moreover, the local measurement system, or the sensors of the targeted zone are tampered. Furthermore, it will be proved that although the neighbor zones have physical connections with the attacked zone, the injected adversary signals are designed as they do not impact other zones directly in order to conceal the local attack from neighbor control centers as much as possible. We provide some advice to system administrators to make the intrusion unfeasible or to reveal the attack. The simulations on IEEE‐118 bus test system illustrate the validity of the assertions.     

Vertical pricing competition in supply chains: the effect of production experience and coordination

We consider a two‐echelon supply chain consisting of a single supplier (producer) and a retailer. The supplier determines the wholesale price with a production cost decreasing with experience. The retailer orders products from the supplier to meet demands. Negative effects of a vertical competition in static supply chain models are typically attributed to a double marginalization. Using an intertemporal supply chain problem, defined by a differential game, we show that in addition to the “cost” of double marginalization, the margin gained from reducing production costs affects the supply chain performance as well. In our analysis, performance is shown to deteriorate even more than the deterioration observed in static problems with no learning (experience). To improve the performance, we provide a time‐variant version to the well‐known, pure, two‐part tariff strategy, which in its dynamic framework may coordinate the supply chain only partially. Efficient coordination in a supply chain is shown to be possible if a mixed two‐part tariff strategy is employed, however.     

Contingent rerouting for enhancing supply chain resilience from supplier behavior perspective

This paper examines contingent rerouting strategy for enhancing supply chain resilience taking a supplier's point of view. We consider a supply chain with multiple suppliers at each stage and establish a mathematical model for product allocation behavior among different suppliers. The allocation model is based on each supplier's production capacity, product quality, production cost, as well as possible decision maker's preferences. As a performance measure for rerouting strategy, we use the total outflow of the supply chain. We propose an optimization model and its solution determines the rerouting strategy for product flow through the supply chain under disruptions. Numerical examples demonstrate the effect of the rerouting strategy and show the resilience of the supply chain.     

Modelling inter-supply chain competition with resource limitation and demand disruption

This paper proposes a comprehensive model for studying supply chain versus supply chain competition with resource limitation and demand disruption. We assume that there are supply chains with heterogeneous supply network structures that compete at multiple demand markets. Each supply chain is comprised of internal and external firms. The internal firms are coordinated in production and distribution and share some common but limited resources within the supply chain, whereas the external firms are independent and do not share the internal resources. The supply chain managers strive to develop optimal strategies in terms of production level and resource allocation in maximising their profit while facing competition at the end market. The Cournot–Nash equilibrium of this inter-supply chain competition is formulated as a variational inequality problem. We further study the case when there is demand disruption in the plan-execution phase. In such a case, the managers need to revise their planned strategy in order to maximise their profit with the new demand under disruption and minimise the cost of change. We present a bi-criteria decision-making model for supply chain managers and develop the optimal conditions in equilibrium, which again can be formulated by another variational inequality problem. Numerical examples are presented for illustrative purpose.     

Location and allocation decisions for multi-echelon supply chain network – A multi-objective evolutionary approach

This paper aims at multi-objective optimization of single-product for four-echelon supply chain architecture consisting of suppliers, production plants, distribution centers (DCs) and customer zones (CZs). The key design decisions considered are: the number and location of plants in the system, the flow of raw materials from suppliers to plants, the quantity of products to be shipped from plants to DCs, from DCs to CZs so as to minimize the combined facility location and shipment costs subject to a requirement that maximum customer demands be met. To optimize these two objectives simultaneously, four-echelon network model is mathematically represented considering the associated constraints, capacity, production and shipment costs and solved using swarm intelligence based Multi-objective Hybrid Particle Swarm Optimization (MOHPSO) algorithm. This evolutionary based algorithm incorporates non-dominated sorting algorithm into particle swarm optimization so as to allow this heuristic to optimize two objective functions simultaneously. This can be used as decision support system for location of facilities, allocation of demand points and monitoring of material flow for four-echelon supply chain network.     

Effects of satellite image spatial aggregation and resolution on estimates of forest land area

Satellite imagery is being used increasingly in association with national forest inventories (NFIs) to produce maps and enhance estimates of forest attributes. We simulated several image spatial resolutions within sparsely and heavily forested study areas to assess resolution effects on estimates of forest land area, independent of other sensor characteristics. We spatially aggregated 30 m datasets to coarser spatial resolutions (90, 150, 210, 270, 510 and 990 m) and produced estimates of forest proportion for each spatial resolution using both model‐ and design‐based approaches. Average‐based aggregation had no effect on per‐image estimates of forest proportion; image variability decreased with increasing spatial resolution and local variability peaked between 210 and 270 m. Majority‐based aggregation resulted in overestimation of forest land in a heavily forested landscape and underestimation of forest land in a sparsely forested landscape, with both trends following a natural log distribution. Of the spatial resolutions tested, 30 m was superior for obtaining estimates using model‐based approaches. However, standard errors of design‐based inventory estimates of forest proportion were smallest when accompanying stratification maps which were aggregated to between 90 and 150 m spatial resolutions and strata thresholds were optimized by study area. These results suggest that spatially aggregating existing 30 m land cover datasets can provide NFIs with gains in precision of their estimates of forest land area, while reducing image storage size and processing times; land cover datasets derived from coarser spatial resolution sensors may provide similar benefits.     

Super facilities versus chaining in mitigating disruptions impacts

Dealing disruptions has increasingly attracted researchers’ attention in the last decades due to recent events: weather deregulation, natural disasters, financial crisis, etc. Researchers often dealt with the strategic aspect of the problem while making facility location decisions to build a robust supply chain. In this paper we address the flexibility aspect. We consider the problem of allocating demand arising from a set of products to a set of dedicated facilities. The facilities are subject to disruption and the demand is then lost. To mitigate disruption impacts, we consider the use of a super facility that can hold the demand of products when the dedicated facilities are under failure. In systems with identical products and facilities, we propose an algorithm that can be used to determine the optimal capacity of the super facility so as to minimize the sum of capacity investment, demand allocation and lost sales cost. Finally we compare the performance of the super facility configuration to that of the single chain configuration. The single chain refers to a facility configuration where each facility is configured to fulfill only two products and each product can be assigned to only two facilities and the whole system forms a closed chain.     

Mapping forest vegetation using Landsat TM imagery and a canopy reflectance model

Estimates of mean tree size and cover for each forest stand from an invertible forest canopy reflectance model are part of a new forest vegetation mapping system. Image segmentation defines stands which are sorted into general growth forms using per-pixel image classifications. Ecological models based on terrain relations predict species associations for the conifer, hardwood, and brush growth forms. The combination of the model-based estimates of tree size and cover with species associations yields general-purpose vegetation maps useful for a variety of land management needs. Results of timber inventories in the Tahoe and Stanislaus National Forests indicate the vegetation maps form a useful basis for stratification. Patterns in timber volumes for the strata reveal that the cover estimates are more reliable than the tree size estimates. A map accuracy assessment of the Stanislaus National Forest shows high overall map accuracy and also illustrates the problems in estimating tree size.     

A sustainable and collaborative strategy for dynamic spectrum management in next generation wireless networks

Next generation wireless technologies offer various services from voice call to full motion pictures and even to high speed internet access. Consequently, the service providers (SP) armed with different wireless technologies (like 2.5G/3G/LTE) would require an adequate and significant amount of spectrum bandwidth for satisfying the need of their customers. Hence to achieve complete commercialization, the SPs, operating simultaneously, would demand for more and more spectrum from the regulatory body of the country. The spectrum demand on the part of the SP may vary with time (dynamic) because of varied kind of loads which are generated depending on the nature of the client-base, their requirements and their expected quality of experience. This work has addressed this challenging issue of allocating spectrum dynamically to different technologies under the portfolio of an SP. Here, we have conceived a scenario where service providers (SP) own multiple access networks (ANs) of different technologies. We envisage that an entity, called local spectrum controller (LSC) which is dedicated for managing the common pool of spectrum allocated to each SP. LSC is mainly responsible for distributing the spectrum to individual ANs of an SP in a fair manner. Since the available spectrum may not be sufficient enough to satisfy the aggregate demand from all ANs simultaneously, an LSC may face a situation, where satisfying individual demands from all ANs may result in a compromise between the demand and supply. This demand–supply situation would force an LSC or an SP to adhere to some dynamic spectrum management strategy, where demands of an AN would have to be satisfied depending on the current state of available spectrum and required usage of it. This calls for an adaptive dynamic strategy to be introduced by an SP for efficient spectrum distribution. The dynamic disparity of spectrum allocation can be idealized as a game between LSC and ANs. Hence, in the present work, we have modeled the problem of dynamic spectrum allocation as an n-player cooperative bankruptcy game and have solved the problem with the help of Shapley value and τ-value separately. We have investigated whether the ANs find it beneficial to cooperate with each other to make the solution sustainable enough. To evaluate the performances of the games that the ANs play, we have designed a novel utility function for each AN. We have identified plausible aims of an SP as minimizing overall dissatisfaction (MOD) and maximizing equality of distribution (MED). Next, we have studied performances of the above two solution concepts against max–min fairness algorithm (benchmarked in our case) with respect to the above objectives of LSC. Finally, we have proposed a unique heuristic in order to facilitate the decision making process of dynamic spectrum allocation, which leads to an adaptive yet optimized spectrum allocation strategy.     

Supply chain coordination under budget constraints

Budget constraints are commonly considered in real decision frameworks; however, the literature has rarely addressed the design of contracts for supply chains with budget-constrained members and in which capital costs are considered. In this article, we study supply chain coordination of budget-constrained members when a financial market is unavailable. We propose a revenue-sharing-and-buy-back (RSBB) contract that combines revenue-sharing (RS) and buy-back (BB) contracts. We compare the performance of RS, BB, and RSBB contracts under a coordinated two-stage supply chain in which members experience budget constraints. Results show that the RS and BB contracts are not feasible under certain budget scenarios, whereas the RSBB contract can always be used to coordinate the supply chain and arbitrarily divide profits. We propose a profit allocation approach to address information symmetry created by undisclosed budget thresholds. Our analytical and numerical results provide insight into how managers select an appropriate contract based on their budget scenarios and capital costs.