Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface reflectance of green, near infrared and shortwave infrared bands, and clearly delineate leaf phenology and length of plant growing season. We also estimate the fractions of photosynthetically active radiation (PAR) absorbed by vegetation canopy (FAPAR_canopy), leaf (FAPAR_leaf), and chlorophyll (FAPAR_chl), respectively, using a coupled leaf-canopy radiative transfer model (PROSAIL-2) and daily MODIS data. The Markov Chain Monte Carlo (MCMC) method (the Metropolis algorithm) is used for model inversion, which provides probability distributions of the retrieved variables. A two-step procedure is used to estimate the fractions of absorbed PAR: (1) to retrieve biophysical and biochemical variables from MODIS images using the PROSAIL-2 model; and (2) to calculate the fractions with the estimated model variables from the first step. Inversion and forward simulations of the PROSAIL-2 model are carried out for the temperate deciduous broadleaf forest during day of year (DOY) 184 to 201 in 2005. The reproduced reflectance values from the PROSAIL-2 model agree well with the observed MODIS reflectance for the five spectral bands (green, red, NIR₁, NIR₂, and SWIR₁). The estimated leaf area index, leaf dry matter, leaf chlorophyll content and FAPAR_canopy values are close to field measurements at the site. The results also showed significant differences between FAPAR_canopy and FAPAR_chl at the site. Our results show that MODIS imagery provides important information on biophysical and biochemical variables at both leaf and canopy levels.     

Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon

Detecting and characterizing continuous changes in early forest succession using multi-temporal satellite imagery requires atmospheric correction procedures that are both operationally reliable, and that result in comparable units (e.g., surface reflectance). This paper presents a comparison of five atmospheric correction methods (2 relative, 3 absolute) used to correct a nearly continuous 20-year Landsat TM/ETM+ image data set (19-images) covering western Oregon (path/row 46/29). In theory, full absolute correction of individual images in a time-series should effectively minimize atmospheric effects resulting in a series of images that appears more similar in spectral response than the same set of uncorrected images. Contradicting this theory, evidence is presented that demonstrates how absolute correction methods such as Second Simulation of the Satellite Signal in the Solar Spectrum (6 s), Modified Dense Dark Vegetation (MDDV), and Dark Object Subtraction (DOS) actually make images in a time-series somewhat less spectrally similar to one another. Since the development of meaningful spectral reflectance trajectories is more dependant on consistent measurement of surface reflectance rather than on accurate estimation of true surface reflectance, correction using image pairs is also tested. The relative methods tested are variants of an approach referred to as “absolute-normalization”, which matches images in a time-series to an atmospherically corrected reference image using pseudo-invariant features and reduced major axis (RMA) regression. An advantage of “absolute-normalization” is that all images in the time-series are converted to units of surface reflectance while simultaneously being corrected for atmospheric effects. Of the two relative correction methods used for “absolute-normalization”, the first employed an automated ordination algorithm called multivariate alteration detection (MAD) to statistically locate pseudo-invariant pixels between each subject and reference image, while the second used analyst selected pseudo-invariant features (PIF) common to the entire image set. Overall, relative correction employed in the “absolute-normalization” context produced the most consistent temporal reflectance response, with the automated MAD algorithm performing equally as well as the handpicked PIFs. Although both relative methods performed nearly equally in terms of observed errors, several reasons emerged for preferring the MAD algorithm. The paper concludes by demonstrating how “absolute-normalization” improves (i.e., reduces scatter in) spectral reflectance trajectory models used for characterizing patterns of early forest succession.     

Assessment of QuickBird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation

High spatial resolution remotely sensed data has the potential to complement existing forest health programs for both strategic planning over large areas, as well as for detailed and precise identification of tree crowns subject to stress and infestation. The area impacted by the current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia, Canada, has increased 40-fold over the previous 5 years, with approximately 8.5 million ha of forest infested in 2005. As a result of the spatial extent and intensity of the outbreak, new technologies are being assessed to help detect, map, and monitor the damage caused by the beetle, and to inform mitigation of future beetle outbreaks. In this paper, we evaluate the capacity of high spatial resolution QuickBird multi-spectral imagery to detect mountain pine beetle red attack damage. ANOVA testing of individual spectral bands, as well as the Normalized Difference Vegetation Index (NDVI) and a ratio of red to green reflectance (Red-Green Index or RGI), indicated that the RGI was the most successful (p < 0.001) at separating non-attack crowns from red attack crowns. Based on this result, the RGI was subsequently used to develop a binary classification of red attack and non-attack pixels. The total number of QuickBird pixels classified as having red attack damage within a 50 m buffer of a known forest health survey point were compared to the number of red attack trees recorded at the time of the forest health survey. The relationship between the number of red attack pixels and observed red attack crowns was assessed using independent validation data and was found to be significant (r² = 0.48, p < 0.001, standard error = 2.8 crowns). A comparison of the number of QuickBird pixels classified as red attack, and a broader scale index of mountain pine beetle red attack damage (Enhanced Wetness Difference Index, calculated from a time series of Landsat imagery), was significant (r² = 0.61, p < 0.001, standard error = 1.3 crowns). These results suggest that high spatial resolution imagery, in particular QuickBird satellite imagery, has a valuable role to play in identifying tree crowns with red attack damage. This information could subsequently be used to augment existing detailed forest health surveys, calibrate synoptic estimates of red attack damage generated from overview surveys and/or coarse scale remotely sensed data, and facilitate the generation of value-added information products, such as estimates of timber volume impacts at the forest stand level.     

Minimizing total costs of forest roads with computer-aided design model

Advances in personal computers (PCs) have increased interest in computer-based road-design systems to provide rapid evaluation of alternative alignments. Optimization techniques can provide road managers with a powerful tool that searches for large numbers of alternative alignments in short spans of time. A forest road optimization model, integrated with two optimization techniques, was developed to help a forest road engineer in evaluating alternative alignments in a faster and more systematic manner. The model aims at designing a path with minimum total road costs, while conforming to design specifications, environmental requirements, and driver safety. To monitor the sediment production of the alternative alignments, the average sediment delivered to a stream from a road section was estimated by using a road erosion/delivery model. The results indicated that this model has the potential to initiate a new procedure that will improve the forest road-design process by employing the advanced hardware and software capabilities of PCs and modern optimization techniques.     

Participatory landscape analysis to guide restoration of ponderosa pine ecosystems in the American Southwest

Over the past 5 decades, stand-replacing crown fires have increased in size and frequency throughout the long-needled pine forests of the American Southwest. Suppression of frequent, low-intensity ground fires has resulted in dense stands of fire-prone trees over large areas. Efforts to restore forest structure to conditions that would permit a return to historical fire regimes, characterized by frequent ground fire, are hindered by the inability of managers and the public to compare the effects of alternative forest management practices on fire behavior and a host of other issues. Currently, forest management is mired in controversy, endangering ecosystem function, biodiversity, public safety, and municipal watersheds. Our research program, motivated by the need to examine cumulative effects of many independent management decisions over large planning areas, focuses on the development of spatial data and modeling tools that enable diverse stakeholders to work together to guide landscape-scale planning efforts. Data layers describing forest composition and structure facilitate modeling of fire threat and wildlife habitat over areas of several hundred thousand hectares. Modeling alternative forest management scenarios via a collaborative, public process fosters informed discourse and helps conflicting parties forge appropriate policy and identify management responses that meet restoration objectives.     

Evaluation of the suitability of data base management systems: a case study at the US Forest Service

A methodology for assessing the feasibility of a data base management system is described, and its use demonstrated in a specific situation: the U.S. Forest service. A series of questions to be answered at the test organization is formulated, aimed at quantifying the benefits of a DBMS. Results of attempting to answer these questions at two test sites are provided. Implications of these results are given for both forest and higher level management.     

The Hydrogeochemistry of Arsenic in the Clara Mine,Germany

Abstract.   The oxidative dissolution of primary arsenic-bearing sulfide minerals in barite-fluorite veins is a potential source of arsenic in the Clara Mine. Geological structures, especially the mineral veins, provide potential pathways for the water. The highest arsenic concentrations are found in ground water within the eastern part of the mine. Arsenic and major ions are positively correlated and provide evidence that arsenic is likely derived locally from the water-vein/water-rock interaction. Geochemical modeling with PHREEQC shows all the arsenate mineral phases to be significantly undersaturated, although secondary arsenate minerals are common in the oxidized part of the deposit. The mine waters plot near the boundary of Fe(OH)₃ and Fe²⁺ in the pH-Eh diagram for the As-Fe-S-H₂O-system. Arsenic occurs as the 5-valent species and . Statistical analysis illustrates a strong association between As, Fe, pH, and HCO₃. Oxidation of the primary As-bearing minerals, such as pyrite and arsenopyrite, and the subsequent behavior of the oxyanion, arsenate, generally controls the distribution and speciation of arsenic. The low concentrations of dissolved As is due to co-precipitation and adsorption of arsenate by Fe, Al, and Mn (oxy)hydroxides.     

MODIS数据在树种长势监测中的应用

近年来,世界各国日益重视利用“3S”(遥感、地理信息系统和全球定位系统)技术对陆地表面植被进行研究。利用Terra-MODIS数据,分别采用了归一化植被指数(NDVI)、环境植被指数(EVI)、土壤调节植被指数(SAVI)以及比值植被指数(RVI)对实验区典型树种的长势进行了比较研究;同时对实验区典型树种的植被指数的地域变化和时间变化进行了分析,为探讨我国可燃物的时空变化规律打下了基础。     

Chemical Ecological Characteristics of Herbivory of Siparuna guianensis Seeds by Buffy-Headed Marmosets (Callithrix flaviceps) in the Atlantic Forest of Southeastern Brazil

The buffy-headed marmoset (Callithrix flaviceps) is apparently the only predispersal herbivore of the seeds of Siparuna guianensis at the Caratinga Biological Station in southeastern Brazil. Both the fruit receptacles and the frutioles (seeds) of S. guianensis are relatively rich in nutrients such as carbohydrates, proteins, and lipids, but the receptacles contain high concentrations of benzylisoquinoline alkaloids. The latter presumably act as a qualitative chemical defense, impeding the access of potential predators to the alkaloid-poor frutioles. However, on ripening, the receptacle splits open, exposing the frutioles, which enables C. flaviceps to avoid the plant's chemical defenses effectively. Taking care to avoid contact with the receptacle, the marmosets pluck out the frutioles and ingest the seeds. Qualitative and quantitative changes (in particular a significant reduction in daily ranging) in the marmosets' behavior during the period when S. guianensis frutioles were accessible indicate that this was a preferred plant resource. This is the first record of the consumption of S. guianensis seeds by callitrichine monkeys (which are not known to be systematic seed eaters), despite the fact that both are widely distributed in the Neotropics. It is thus possible that the behavioral strategy observed here is a unique phenomenon resulting from a specific combination of factors, including the abundance of S. guianensis within the study area. The lack of other records may nevertheless be a result of insufficient sampling effort, in which case, the feeding strategies of callitrichines may have an important influence on the reproductive biology of S. guianensis in many areas.     

DOM驱动型智能体在计算任务中的研究与实现

提出了一种能够实现复杂计算任务的以DOM驱动模式为基础的智能体实现方法。在复杂计算过程中，计算模型的调整和修改是一个烦琐的任务，利用智能体能自动完成此任务，弥补其中的不足。基本思路是根据智能体的抽象概念逐步实现智能体各基本结构，并采用XML文档存储智能体的组成部分和通信部分，再利用DOM这种驱动模式来读取XML的内容，利用Script组件解释该内容，设计出一个将XML技术与智能体相结合的计算架构。该智能体最后应用在森林生长仿真计算任务中，并取得了较佳预期效果。