Multiscale satellite and spatial information and analysis framework in support of a large-area forest monitoring and inventory update

Many countries undertake a national forest inventory to enable statistically valid monitoring in support of national and international reporting of forest conditions and change. Canada’s National Forest Inventory (NFI) program is designed to operate on a 10-year remeasurement cycle, with an interim report produced at the 5-year mid-point. The NFI is a sample-based inventory, with approximately 18,850 2 ×2-km photo plots across the country, distributed on a 20×20-km grid of sample points; these photo plots are the primary data source for the NFI. Capacity to provide annual monitoring information is required to keep policy and decision makers apprised of current forest conditions. In this study, we implemented a multistage monitoring framework and used a Moderate Resolution Imaging Spectroradiometer (MODIS) change product to successfully identify 78% of the changes in forest cover area that were captured with a Landsat change detection approach. Of the NFI photo plots that were identified by both the Landsat and MODIS approaches as having changes in forest cover, the proportion of change area within the plots was similar (R ²?=?0.78). Approximately 70% of the Landsat-derived change events occupied less than 40% of a single MODIS pixel, and more than 90% of the change events of this size were successfully detected with the MODIS product. Finally, MODIS estimates of the proportion of forest cover change at the NFI photo plot level were comparable to change estimates for the ecoregions as a whole (R ²?=?0.95). High-temporal, low-spatial resolution imagery such as MODIS, in combination with other remotely sensed data sources, can provide information on disturbance events within a national forest inventory remeasurement cycle, thereby satisfying the interim information needs of policy and decision makers as well as the requirements of national and international reporting commitments.     

Effects of changing forest land definitions on forest inventory on the West Coast, USA

A key function of forest inventory is to detect changes in the area of forest land over time, yet different definitions of forest land are used in different regions of the world. Changes in the definition of forest intended to improve international consistency can affect the ability to quantify true changes over time. The objective of this study was to evaluate the effects of a definitional change from relative stocking to canopy cover on the area classified as forest land and its relationship to species and forest density in California, Oregon, and Washington. Both western Juniper and ponderosa pine will yield higher estimates of forest land area using a canopy cover definition in comparison to a stocking-based definition, with the difference being most pronounced where land is marginally forested. The change in definition may result in an additional 146,000 ha of forest land identified on the West Coast. Measuring marginal forest lands with both metrics for the first cycle after implementation should make it possible to distinguish real change from definitional change.     

Development history and bibliography of the US Forest Service crown-condition indicator for forest health monitoring

Comprehensive assessment of individual-tree crown condition by the US Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program has its origins in the concerns about widespread forest decline in Europe and North America that developed in the late 1970s and early 1980s. Programs such as the US National Acid Precipitation Assessment Program, US National Vegetation Survey, Canadian Acid Rain National Early Warning System, and joint US–Canadian North American Sugar Maple Decline Project laid the groundwork for the development of the US Forest Service crown-condition indicator. The crown-condition assessment protocols were selected and refined through literature review, peer review, and field studies in several different forest types during the late 1980s and early 1990s. Between 1980 and 2011, 126 publications relating specifically to the crown-condition indicator were added to the literature. The majority of the articles were published by the US Department of Agriculture, Forest Service or other State or Federal government agency, and more than half were published after 2004.     

Status and future of the forest health indicators program of the USA

For two decades, the US Department of Agriculture, Forest Service, has been charged with implementing a nationwide field-based forest health monitoring effort. Given its extensive nature, the monitoring program has been gradually implemented across forest health indicators and inventoried states. Currently, the Forest Service??s Forest Inventory and Analysis program has initiated forest health inventories in all states, and most forest health indicators are being documented in terms of sampling protocols, data management structures, and estimation procedures. Field data from most sample years and indicators are available on-line with numerous analytical examples published both internally and externally. This investment in national forest health monitoring has begun to yield dividends by allowing evaluation of state/regional forest health issues (e.g., pollution and invasive pests) and contributing substantially to national/international reporting efforts (e.g., National Report on Sustainability and US EPA Annual Greenhouse Gas Estimates). With the emerging threat of climate change, full national implementation and remeasurement of a forest health inventory should allow for more robust assessment of forest communities that are undergoing unprecedented changes, aiding future land management and policy decisions.     

Mapping aboveground woody biomass using forest inventory,remote sensing and geostatistical techniques

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m?×?31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10–40, 40–70 and >70 % of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m³ ha^?1. The total growing stock of the forest was found to be 2,024,652.88 m³. The AGWB ranged from 143 to 421 Mgha^?1. Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE)?=?42.25 Mgha^?1) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha^?1 respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha^?1. The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.     

Top-down and bottom-up inventory approach for above ground forest biomass and carbon monitoring in REDD framework using multi-resolution satellite data

This study deals with the future scope of REDD (Reduced Emissions from Deforestation and forest Degradation) and REDD+ regimes for measuring and monitoring the current state and dynamics of carbon stocks over time with integrated geospatial and field-based biomass inventory approach. Multi-temporal and multi-resolution geospatial synergic approach incorporating satellite sensors from moderate to high resolution with stratified random sampling design is used. The inventory process involves a continuous forest inventory to facilitate the quantification of possible CO₂ reductions over time using statistical up-scaling procedures on various levels. The combined approach was applied on a regional scale taking Himachal Pradesh (India), as a case study, with a hierarchy of forest strata representing the forest structure found in India. Biophysical modeling implemented revealed power regression model as the best fit (R ²?=?0.82) to model the relationship between Normalized Difference Vegetation Index and biomass which was further implemented to calculate multi-temporal above ground biomass and carbon sequestration. The calculated value of net carbon sequestered by the forests totaled to 11.52 million tons (Mt) over the period of 20 years at the rate of 0.58 Mt per year since 1990 while CO₂ equivalent reduced from the environment by the forests under study during 20 years comes to 42.26 Mt in the study area.     

Detecting change in advance tree regeneration using forest inventory data: the implications of type II error

Achieving adequate and desirable forest regeneration is necessary for maintaining native tree species and forest composition. Advance tree seedling and sapling regeneration is the basis of the next stand and serves as an indicator of future composition. The Pennsylvania Regeneration Study was implemented statewide to monitor regeneration on a subset of Forest Inventory and Analysis plots measured by the U.S. Forest Service. As management techniques are implemented to improve advance regeneration, assessments of the change in the forest resource are needed. When the primary focus is on detecting change, hypothesis tests should have small type II (β) error rates. However, most analyses are based on minimizing type I (α) error rates and type II error rates can be quite large. When type II error rates are high, actual improvements in regeneration can remain undetected and the methods that brought these improvements may be deemed ineffective. The difficulty in detecting significant change in advance regeneration when small type I error rates are given priority is illustrated. For statewide assessments, power (1-β) to detect changes in proportion of area having adequate advance regeneration is relatively weak (≤0.5) when the change is smaller than 0.05. For evaluations conducted at smaller spatial scales, such as wildlife management units, the reduced sample size results in only marginal power even when relatively large changes (≥0.20) in area proportion occur. For fixed sample sizes, analysts can consider accepting larger type I error rates to increase the probability of detecting change (smaller type II error rates) when it occurs, such that management methods that positively affect regeneration can be identified.     

Monitoring global change: Comparison of forest cover estimates using remote sensing and inventory approaches

Satellite-based remote sensing offers great potential for frequent assessment of forest cover over broad spatial scales, however, calibration and validation using ground-based surveys are needed. In this study, forest cover estimates for the United States from a recently developed land surface cover map generated from satellite remote sensing data were compared to state-level inventory data from the U.S. National Resources Planning Act Timber Database. The land cover map was produced at the U.S. Geological Survey EROS Data Center and is based on imagery from the AVHRR sensor (spatial resolution 1.1 km). Vegetation type was classified using the temporal signal in the Normalized Difference Vegetation Index derived from AVHRR data. Comparisons revealed close agreement in the estimate of forest cover for extensively forested states with large polygons of relatively similar vegetation such as Oregon. Larger forest cover differences were observed in other states with some regional patterns in the level of agreement apparent.Comparisons in inventory- and remote sensing-based estimates of current forested area with potential vegetation maps indicated the magnitude of past land use change and the potential for future changes. The remote sensing approach appears to hold promise for conducting surveys of forest cover where inventory data are limited or where rates of vegetation change, due to human or climatic factors, are rapid.     

Nanotechnology applications and implications research supported by the US Environmental Protection Agency STAR grants program

Since 2002, the US Environmental Protection Agency (EPA) has been funding research on the environmental aspects of nanotechnology through its Science to Achieve Results (STAR) grants program. In total, more than $25 million has been awarded for 86 research projects on the environmental applications and implications of nanotechnology. In the applications area, grantees have produced promising results in green manufacturing, remediation, sensors, and treatment using nanotechnology and nanomaterials. Although there are many potential benefits of nanotechnology, there has also been increasing concern about the environmental and health effects of nanomaterials, and there are significant gaps in the data needed to address these concerns. Research performed by STAR grantees is beginning to address these needs.     

A computer-based program for the assessment of water-induced contamination in irrigated lands

The non-point characteristic of agrarian contamination hinders its quantification and assignation to a specific territory. The objectives of this work were to unify methodological criteria for agro-environmental evaluation and to propose indices to quantify irrigation-induced contamination. The computer program Irrigation Land Environmental Evaluation Tool (in Spanish, EMR; http://www.jcausape.es/investigacion/EMR.htm ) was developed to evaluate the quality of irrigation and the agro-environmental impacts, based on the water, salt, and nitrate balances in the hydrological irrigation basins. The behavior of the proposed indices was analyzed using data registered in various irrigation districts in the Ebro valley (Spain). The Salt and Nitrate Contamination Indices (SCI and NCI, respectively) were based on the unitary mass of exported pollutants, corrected by the "natural and socioeconomic" conditions of the irrigation districts evaluated. SCI and NCI were related to water and nitrogen use, key factors in minimizing contamination. SCI and NCI admit a greater mass of exported pollutants in disadvantaged irrigation districts, which does not allow the exclusion of adequate management in any evaluated irrigation lands. EMR is a user-friendly tool at the service of the agro-environmental surveillance of irrigation lands.     

A selection of forest condition indicators for monitoring

Regional monitoring and assessments of the health of forested ecosystems require indicators of forest conditions and environmental stresses. Indicator selections depend on objectives and the strategy for data collection and analysis. This paper recommends a set of indicators to signal changes in forest ecosystem distribution, productivity, and disturbance. Additional measurements are recommended to help ascribe those changes to climate variation, atmospheric deposition, and land use patterns. The rationale for these indicators is discussed in the context of a sequential monitoring and assessment strategy.     

A framework for assessment and monitoring of arthropods in a lowland tropical forest

By applying principles of adaptive management, and by using the valuable information that arthropods provide from assessment and monitoring programs, managers can identify and reduce possible impacts on biodiversity in development projects. In 1996, the Smithsonian Institution's Monitoring and Assessment of Biodiversity program worked together with Shell Prospecting and Development Peru to establish an adaptive management program to protect biodiversity in a natural gas exploration project in a Peruvian rainforest. In this paper, we outlined the conceptual steps involved in establishing an assessment and monitoring program for arthropods, including setting objectives, evaluating the results and making decisions. We also present the results of the assessment using some of groups of arthropods, and summarize the steps taken to identify appropriate groups for monitoring.     

A database for a multi-institutional environment monitoring program

A several year program is underway in Israel for monitoring a wastewater reclamation and storage complex for agriculture irrigation. The program covers wastewater treatment and storage, irrigation, aquifers, air pollution, crops, soil, geography and meteorology, and is operated by one Principal Institution and several Participant Institutions. The institutions feed their data to a central database. Multi-institutional databases are fed by research teams whose areas of activity are traditionally unrelated. The main problem of the Database Administrator consists in combining data created by different methods under different basic assumptions. And to make them available to investigators from several disciplines and institutions who are used to different data analysis procedures. Database Administrator's background should cover both computer and environmental sciences fields. The selection of a flexible multipurpose software is recommended, but there are several decisions on database design that depend not on the software but on the characteristics and requirements of the Monitoring Program. Entering the data from different sources in independent files facilitates input, debugging, administrative control of the contribution of each institution, and changes in units and parameters. This multi-file design also overcomes difficulties due to excessive file size, and better matchs the actual usage of the database in a multi-institutional program. To enter the data with their original characteristics and units also matchs better the database usage. Ready-to-use routines for file merging and unit conversion, and debugging and documentation needs are also discussed. The Database-User interactions are the mechanism that maintains an evolving dynamic Database.     

A framework for assessment and monitoring of small mammals in a lowland tropical forest

Development projects in tropical forests can impact biodiversity.Assessment and monitoring programs based on the principles of adaptive management assist managers to identify and reduce suchimpacts. The small mammal community is one important component ofa forest ecosystem that may be impacted by development projects. In 1996, a natural gas exploration project was initiated in a Peruvian rainforest. The Smithsonian Institution's Monitoring andAssessment of Biodiversity program cooperated with Shell Prospecting and Development Peru to establish an adaptive management program to protect the region's biodiversity. In thisarticle, we discuss the role of assessing and monitoring small mammals in relation to the natural gas project. We outline theconceptual issues involved in establishing an assessment andmonitoring program, including setting objectives, evaluating the results and making appropriate decisions. We also summarizethe steps taken to implement the small mammal assessment, provideresults from the assessment and discuss protocols to identifyappropriate species for monitoring.     

Ecological mapping: A framework for delimiting forest management units

Ecological mapping attempts to objectively and spatially delimit and represent the natural organization and structure of the landscape. It offers nested levels of resolution, based upon a regionalization process, and provides an ecological basis for planning activities that may impact upon the environment.The essential principles of ecological mapping, as applied by the Quebec Ministry of Environment and Wildlife, are summarized. A methodological mapping approach is proposed for the determination of significant land portions for forest management using an ecological map at a scale of 1:50 000. At this scale, two nested levels of perception are expressed: 1) the topographic complex, and 2) the topographic entity. The topographic entity can be further subdivided into working units based upon operational criteria oriented to forest management. Within each nested level from topographic complex to working unit, there is a corresponding increase in the amount of detailed information available. Ecological mapping undertaken at 1:50 000 scale can provide a reliable and robust tool for planning forest management activities. In most cases, major ecological variations can be expressed and mapped at this scale; however, a greater degree of generalization must be accepted in the planning process when working at this scale rather than at larger scales.     

A multiresidue method for the analysis of phenols and nitrophenols in the atmosphere

A method using GC-MS and derivatization with N-(t-butyldimethylsilyl)-N-methyltrifluoroacetamide (MTBSTFA) was developed for the analysis of 20 phenolic compounds in atmospheric samples (gas and particles). Air sampling was carried out using a Hi-Vol sampler with glass fibre filter and XAD-2 resin at a flow rate of 60 m(3) h(-1). The particle and gas phases were collected separately over a period of 4 h. Samples were Soxhlet extracted, evaporated to dryness under nitrogen and refilled with acetonitrile. 100 microl of these extracts were derivatized with 100 microl of MTBSTFA at 80 degrees C for 1 h under strong stirring. Phenolic compounds were injected into a GC-MS in splitless mode and quantified as their TBDMS derivatives in the SIM mode. Mass spectral analysis of the derivatives of the 20 compounds studied indicates that the spectra are highly specific showing an ion at [M - 57]+ which is useful for structure confirmation or analysis at low levels using selected ion monitoring. Quantification limits varied between 5 microg l(-1) and 10 microg l(-1) which correspond to 20 pg m(-3) and 40 pg m(-3) for 250 m(3) of air sampled. This method was successfully applied to atmospheric samples.