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.     

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.     

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.