Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe’s WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product’s overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey)

In this study, landslide risk assessment for Izmir city (west Turkey) was carried out, and the environmental effects of landslides on further urban development were evaluated using geographical information systems and remote sensing techniques. For this purpose, two different data groups, namely conditioning and triggering data, were produced. With the help of conditioning data such as lithology, slope gradient, slope aspect, distance from roads, distance from faults and distance from drainage lines, a landslide susceptibility model was constructed by using logistic regression modelling approach. The accuracy assessment of the susceptibility map was carried out by the area under curvature (AUC) approach, and a 0.810 AUC value was obtained. This value shows that the map obtained is successful. Due to the fact that the study area is located in an active seismic region, earthquake data were considered as primary triggering factor contributing to landslide occurrence. In addition to this, precipitation data were also taken into account as a secondary triggering factor. Considering the susceptibility data and triggering factors, a landslide hazard index was obtained. Furthermore, using the Aster data, a land-cover map was produced with an overall kappa value of 0.94. From this map, settlement areas were extracted, and these extracted data were assessed as elements at risk in the study area. Next, a vulnerability index was created by using these data. Finally, the hazard index and the vulnerability index were combined, and a landslide risk map for Izmir city was obtained. Based on this final risk map, it was observed that especially south and north parts of the Izmir Bay, where urbanization is dense, are threatened to future landsliding. This result can be used for preliminary land use planning by local governmental authorities.     

Evaluating Kriging as a Tool to Improve Moderate Resolution Maps of Forest Biomass

The USDA Forest Service, Forest Inventory and Analysis program (FIA) recently produced a nationwide map of forest biomass by modeling biomass collected on forest inventory plots as nonparametric functions of moderate resolution satellite data and other environmental variables using Cubist software. Efforts are underway to develop methods to enhance this initial map. We explored the possibility of modeling spatial structure to make such improvements. Spatial structure in the field biomass data as well as in residuals from the map was investigated across 18 ecological zones in the Interior Western U.S. Exploratory tools included directional graphs of summary statistics, three dimensional maps, Moran’s I correlograms, and variograms. Where spatial pattern was present, field and residual biomass were kriged, and predictions made for an independent test set were evaluated for improvement over predictions in the initial biomass map. While kriging has some potential benefit when analyzing the field data and exploring spatial structure, kriging residuals resulted in little or no improvement in the initial biomass map developed using Cubist software. Stationarity assumptions, variogram behavior, and appropriate model fitting strategies are discussed.     

An approach to the assessment of the quality of environmental monitoring data

This paper reports an approach to the assessment of the validity of environmental monitoring data--a 'data filter'. The strategy has been developed through the UK National Marine Analytical Quality Control (AQC) Scheme for application to data collected for the UK National Marine Monitoring Plan, although the principles described are applicable more widely. The proposed data filter is divided into three components: Part A, 'QA/QC'--an assessment of the laboratory's practices in Quality Assurance/Quality Control; Part B, 'fitness for purpose'--an evaluation of the standard of accuracy that can be demonstrated by activities in (A), in relation to the intended application of the data; and Part C, the overall assessment on which data will be accepted as usable or rejected as being of suspect quality. A pilot application of the proposed approach is reported. The approach described in this paper is intended to formalise the assessment of environmental monitoring data for fitness for a chosen purpose. The issues important to fitness for purpose are discussed and assigned a relative priority order on which to judge the reliability/usefulness of monitoring data.     

State of the Estuaries in the Mid-Atlantic Region of the United States

The U.S. EPA has prepared a State of the Region Report for Mid-Atlantic Estuaries to increase knowledge of environmental condition for improved environmental management. Sources of information included the National Estuary Programs, the Chesapeake Bay Program, the state monitoring programs in Delaware, Maryland, and Virginia, Federal programs such as National Status & Trends, National Shellfish Register, National Wetlands Inventory, the Environmental Monitoring and Assessment Program, and other primary literature sources. The state of the estuarine environment was summarized using indicators for water and sediment quality, habitat change, condition of living resources, and aesthetic quality. Each indicator was briefly discussed relative to its importance in understanding estuarine condition. Wherever possible, data from multiple programs were used to depict condition. Finally, an overall evaluation of estuarine condition in the region was determined. The usefulness of monitoring programs that collect consistent information with a well-defined sampling design cannot be overemphasized.     

1,4-Dichlorobenzene Marine Risk Assessment with Special Reference to the Osparcom Region: North Sea

This risk assessment on 1,4-dichlorobenzene was carried out for the marine environment, following methodology given in the EU risk assessment Regulation (1488/94) and Guidance Document of the EU New and Existing Substances Regulation (TGD, 1996). Data from analytical monitoring programs in large rivers and estuaries in the North Sea area were collected and evaluated on effects and environmental concentrations. Risk is indicated by the ratio of predicted environmental concentration (PEC) to predicted no-effect concentration (PNEC) for the marine aquatic environment. In total, 17 data for fish, 9 data for invertebrates and 7 data for algae were evaluated. Acute and chronic toxicity studies were taken into account and appropriate assessment factors used to define a final PNEC value of 20 microg/l. Recent monitoring data indicate that 1,4-dichlorobenzene levels in coastal waters and estuaries are below the determination limit of 0.1 microg/l used in monitoring programs. The worst case value recorded in river water is below 0.45 microg/l. Using these values, calculated PEC/PNEC ratios give safety margins of about 40-200, taking no account of dilution in the sea. Environmental fate and bioaccumulation data indicate that current use of 1,4-dichlorobenzene poses no risk to the aquatic environment.     

Impact of sampling strategy on stream load estimates in till landscape of the Midwest

Accurately estimating various solute loads in streams during storms is critical to accurately determine maximum daily loads for regulatory purposes. This study investigates the impact of sampling strategy on solute load estimates in streams in the US Midwest. Three different solute types (nitrate, magnesium, and dissolved organic carbon (DOC)) and three sampling strategies are assessed. Regardless of the method, the average error on nitrate loads is higher than for magnesium or DOC loads, and all three methods generally underestimate DOC loads and overestimate magnesium loads. Increasing sampling frequency only slightly improves the accuracy of solute load estimates but generally improves the precision of load calculations. This type of investigation is critical for water management and environmental assessment so error on solute load calculations can be taken into account by landscape managers, and sampling strategies optimized as a function of monitoring objectives.     

Application of GNSS-RTK derived topographical maps for rapid environmental monitoring: a case study of Jack Finnery Lake (Perth, Australia)

In environmental monitoring, environmental impact assessments and environmental audits, topographical maps play an essential role in providing a means by which the locations of sampling sites may be selected, in assisting with the interpretation of physical features, and in indicating the impact or potential impact on an area due to changes in the system being monitored (e.g., spatially changing features such as wetlands). Global Navigation Satellite Systems (GNSS) are hereby presented as a rapid method for monitoring spatial changes to support environmental monitoring decisions and policies. To validate the GNSS-based method, a comparison is made of results from a small-scale topographic survey using radio-based real-time kinematic GNSS (GNSS-RTK) and total station survey methods at Jack Finnery Lake, Perth, Australia. The accuracies achieved by the total station in this study were 2 cm horizontally and 6 cm vertically, while the GNSS-RTK also achieved an accuracy of 2 cm horizontally, but only 28 cm vertically. While the GNSS-RTK measurements were less accurate in the height component compared to those from the total station method, it is still capable of achieving accuracies sufficient for a topographic map at a scale of 1:1,750 that could support environmental monitoring tasks such as identifying spatial changes in small water bodies or wetlands. The time taken to perform the survey using GNSS-RTK, however, was much shorter compared to the total station method, thereby making it quite suitable for monitoring spatial changes within an environmental context, e.g., dynamic mining activities that require rapid surveys and the updating of the monitored data at regular intervals.     

Accounting for intracultural variability in first nation environmental knowledge: A requisite for environmental monitoring and impact assessments

In many environmental monitoring and impact assessment processes, Indigenous communities are treated as intellectually homogenous and intracultural variation in environmental knowledge often goes unaccounted for. This not only poses obvious risks to the effectiveness of environmental impact assessments but also gives standing to those who question the credibility of traditional ecological knowledge and its contribution to environmental monitoring and assessment programs altogether. In this paper we describe the steps that were taken to account for intracultural variability in First Nation knowledge of fish and the potential impacts associated with the Peace River oil sands development in Alberta, Canada. Involving the delivery of a household survey to 1,127 First Nation households in 11 Peace River communities, our approach was successful in identifying regional, community, and household variability in fishing activity, and has allowed us to differentiate novice from expert knowledge holders. This research demonstrates the need to account for intracultural variability in First Nations environmental knowledge in order for traditional ecological knowledge to make meaningful contributions to environmental monitoring and assessment programs.     

Developing a National Indicator of Soil Quality on U.S Forestlands: Methods and Initial Results

The Montreal Process was formed in 1994 to develop an internationally agreed upon set of criteria and indicators for the conservation and sustainable management of temperate and boreal forests. In response to this initiative, the Forest Inventory and Analysis (FIA) and Forest Health Monitoring (FHM) programs of the United States Department of Agriculture Forest Service have implemented soil measurements as part of a national monitoring program to address specific questions related to the conservation of soil and water resources. Integration of soil assessments into the national FIA program provides for systematic monitoring of soil properties across all forested regions of the U.S. using standardized collection, laboratory, and statistical procedures that are compatible with existing forest inventory data. The resulting information will provide quantitative benchmarks for regional, national, and international reporting on sustainable forest management and enhance our understanding of management effects on soil quality. This paper presents an overview of the FIA soil monitoring program, outlines the field and laboratory protocols as currently implemented, and provides examples of how these data may be used to assess indicators of sustainable management as defined by the Montreal Process.     

Long-term environmental monitoring for assessment of change: measurement inconsistencies over time and potential solutions

The importance of long-term environmental monitoring and research for detecting and understanding changes in ecosystems and human impacts on natural systems is widely acknowledged. Over the last decades, a number of critical components for successful long-term monitoring have been identified. One basic component is quality assurance/quality control protocols to ensure consistency and comparability of data. In Norway, the authorities require environmental monitoring of the impacts of the offshore petroleum industry on the Norwegian continental shelf, and in 1996, a large-scale regional environmental monitoring program was established. As a case study, we used a sub-set of data from this monitoring to explore concepts regarding best practices for long-term environmental monitoring. Specifically, we examined data from physical and chemical sediment samples and benthic macroinvertebrate assemblages from 11 stations from six sampling occasions during the period 1996–2011. Despite the established quality assessment and quality control protocols for this monitoring program, we identified several data challenges, such as missing values and outliers, discrepancies in variable and station names, changes in procedures without calibration, and different taxonomic resolution. Furthermore, we show that the use of different laboratories over time makes it difficult to draw conclusions with regard to some of the observed changes. We offer recommendations to facilitate comparison of data over time. We also present a new procedure to handle different taxonomic resolution, so valuable historical data is not discarded. These topics have a broader relevance and application than for our case study.     

环境监测数据的可信度研究

从政府考核体制、监测网络管理、监测能力水平、监测质量管理、自动监控等方面系统地分析了影响环境监测数据可信度的原因,提出通过改变监测体系、政府考核体制、监测网络优化、改变监测机构的体制和性质、加大监测能力建设、强化监测规范化建设、加大技术人员的培训和"飞行"检查力度、加快现场监测视频监控指挥系统建设,建立监测数据可信度评估体系等手段来保证其准确、可靠,提高环境监测数据的可信度。     

The role of metadata and strategies to detect and control temporal data bias in environmental monitoring of soil contamination

It is crucial for environmental monitoring to fully control temporal bias, which is the distortion of real data evolution by varying bias through time. Temporal bias cannot be fully controlled by statistics alone but requires appropriate and sufficient metadata, which should be under rigorous and continuous quality assurance and control (QA/QC) to reliably document the degree of consistency of the monitoring system. All presented strategies to detect and control temporal data bias (QA/QC, harmonisation/homogenisation/standardisation, mass balance approach, use of tracers and analogues and control of changing boundary conditions) rely on metadata. The Will Rogers phenomenon, due to subsequent reclassification, is a particular source of temporal data bias introduced to environmental monitoring here. Sources and effects of temporal data bias are illustrated by examples from the Swiss soil monitoring network. The attempt to make a comprehensive compilation and assessment of required metadata for soil contamination monitoring reveals that most metadata are still far from being reliable. This leads to the conclusion that progress in environmental monitoring means further development of the concept of environmental metadata for the sake of temporal data bias control as a prerequisite for reliable interpretations and decisions.     

An Interactive, Spatial Inventory of Environmental Data in the Mid-Atlantic Region

The U.S. Environmental Protection Agency (EPA) is working with federal, state, local, and non-governmental partners to produce an interactive, spatial inventory of environmental data in the mid-Atlantic region. The inventory will include maps of sampling locations, lists of measurements, and design information for hundreds of research sites and monitoring programs. It will also feature user-defined queries, resulting in customized maps that satisfy search criteria. (For example, "Display the probability-based surveys that measure dry deposition and nutrient availability in soils"). The inventory will be used in an interagency pilot study, instigated by the National Science and Technology Council's Committee on the Environment and Natural Resources, to integrate environmental monitoring and research activities. The inventory will also provide information for a regional ecological assessment led by EPA Region 3 and the Office of Research and Development. In addition, an interagency consortium will use the inventory to identify suitable field data for assessing the accuracy of satellite imagery. In each of these three applications, the inventory will be tested and evaluated as a potential prototype for completing additional regions of the U.S. Maintained as an Oracle database, the inventory is accessible on the internet at http://www.epa.gov/monitor/. Currently, ten inventory records are on-line for demonstration. The complete federal inventory of approximately 180 records will be accessible on-line by October, 1997; approximately 200 state, local and non-governmental records are scheduled for on-line access by April, 1998.     

环境一号卫星CCD数据在生态环境监测和评价工作中的应用价值研究

基于环境一号卫星CCD传感器性能,从生态景观角度入手,针对江苏省地形地貌特征,开展了环境一号卫星CCD数据在生态环境监测和评价工作中的应用可行性研究,结果表明环境一号卫星CCD数据可以满足江苏省生态环境监测和评价工作需要,其时间分辨率和幅宽是开展生态监控和预警的重要优势。     

Economics of place-based monitoring under the safe drinking water act, part II: Design and development of place-based monitoring strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the United States. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Part II: Several factors affect the performance of monitoring strategies, including: measurable objectives, required precision in estimates, acceptable confidence levels of such estimates, available budget for sampling. In this paper, we develop place-based monitoring strategies based on extensive analysis of available historical water quality data (1960-1994) of 19 Iowa community water systems. These systems supply potable water to over 350,000 people. In the context of drinking water, the objective is to protect public health by utilizing monitoring resources to characterize contaminants that are detectable, and are close to exceeding health standards. A place-based monitoring strategy was developed in which contaminants were selected based on their historical occurrence, rather than their appearance on the SDWA contaminant list. In a subset of the water systems, the temporal frequency of monitoring for one ubiquitous contaminant, nitrate, was tailored to patterns in its historical occurrence and concentration. Three sampling allocation models (linear, quadratic, and cubic) based on historic patterns in peak occurrence were developed and evaluated. Random and fixed-interval sampling strategies within the context of such models were also developed and evaluated. Strategies were configured to incorporate a variety of options for frequency and number of samples (depending on budget and the desired precision in estimate of peak concentrations).     

The need for long-term stream monitoring programs in forest ecosystems of the Pacific Northwest

Concepts, planning and design procedures are examined that are needed in the development of long-term stream monitoring programs in forested regions. A long-term stream monitoring program is viewed as the key component for bringing together management organizations, researchers and decision-makers to improve the management of natural resources. The keystones of such ecosystem monitoring are long-term data records that provide the basis for analysis of environmental assessment objectives, predictions and analysis of outcomes which in-turn can be used to modify and improve future projects. Management organizations that initiate long-term monitoring programs are urged to use monitoring actions and information to facilitate decision-making processes that pertain to conserving and allocating resources for future beneficial uses. Recommendations are provided for careful planning and definition of interactive activities of monitoring programs and that should provide information feedbacks that can be used to evaluate issues pertaining to beneficial uses of resources. Procedural requirements and literature sources are suggested for developing long-term stream monitoring programs. They include reviews of background and historical information to provide precise definitions of long-term objectives, planning considerations and monitoring methods. Examples are given of specific procedures that need to be identified during the planning process. They include the application of management standards to variable conditions encountered within natural ecosystems and the detection of the timing of recovery phases of stream ecosystem development following a disturbance. These procedures are viewed as being essential for improving applications of management standards and perceived thresholds to stream and watershed ecosystems monitoring programs.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².