Mapping of temperature and line-of-sight errors in constituent retrievals for MIPAS/ENVISAT measurements

An optimized code for the near real-time retrieval of line of sight, temperature and volume-mixing ratio profiles of five key species (O₃, H₂O, HNO₃, CH₄ and N₂O) from infrared limb spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) experiment on board the ENVISAT-1 satellite was developed as part of an ESA-supported study. In this code line of sight and temperature are retrieved simultaneously among themselves, but sequentially with respect to the volume-mixing ratio of the five key species. The sequential retrieval leaves unaccounted the mapping of line of sight and temperature errors in the retrieved volume-mixing ratio of the constituents. This paper illustrates an algorithm that provides the a-posteriori evaluation of temperature and line-of-sight-induced error on the retrieved volume-mixing ratio of the MIPAS key species. It is shown that in most cases temperature and line-of-sight-induced error provides a significant contribution to the total volume-mixing ratio error. The variability of this error as a function of latitude, season and atmospheric model is also analyzed.     

Trans-boundary air pollution over remote islands in Japan: observed data and estimates from a numerical model

Observations of air pollutants were conducted in remote Japanese islands (Oki Island and Okinawa Island) in early spring to clarify the extent of trans-boundary air pollution from the Asian continent. A three-dimensional Eulerian model calculation, which included parameters on emission, transport and transformation of sulfur oxides, nitrogen oxides and ammonia, was performed to compile sulfate isosurface concentrations over the observational sites. Concentrations of non-sea-salt sulfate (nss-SO₄²⁻) of greater than 10 μg m⁻³ were observed at Oki after the northeastward passage of low-pressure systems in the Sea of Japan. At these times, the weather showed a typical winter pattern and air pollutants over China were transported southeastward to Japan with the northwesterly wind. The model calculation reproduced the observed variations of nss-SO₄²⁻ concentration well, except for one case in which the model calculation could not reproduce the extremely low nss-SO₄²⁻ concentration observed on 8 March. In Hedo (Okinawa Island), we observed long-lasting (3 days) medium concentrations of nss-SO₄²⁻ (approximately 5 μg m⁻³). Although the model reproduced these observed medium concentrations well, in general the observed results were reproduced better for Oki than for Hedo. Under the synoptic weather conditions of early spring, high concentrations of nss-sulfate were sometimes transported to these remote Japanese islands from areas of continental Asia with a strong outflow of air pollutants.     

Decline of traditional rice farming constrains the recovery of the endangered Asian crested ibis (Nipponia nippon)

Traditional agriculture benefits a rich diversity of plants and animals. The winter-flooded rice fields in the Qinling Mountains, China, are the last refuge for the endangered Asian crested ibis (Nipponia nippon), and intensive efforts have been made to protect this anthropogenic habitat. Analyses of multi-temporal satellite data indicate that winter-flooded rice fields have been continuously reduced across the current range of crested ibis during the past two decades. The rate of loss of these fields in the core-protected areas has unexpectedly increased to a higher level than that in non-protected areas in the past decade. The best fit (R² = 0.87) numerical response model of the crested ibis population shows that a reduction of winter-flooded rice fields decreases population growth and predicts that the population growth will be constrained by the decline of traditional winter-flooded rice fields in the coming decades. Our findings suggest that the decline of traditional rice farming is likely to continue to pose a threat to the long-term survival and recovery of the crested ibis population in China.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0649-5) contains supplementary material, which is available to authorized users.     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.     

Montane Meadows as Indicators of Environmental Change

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change     

Beach topography mapping—a comparsion of techniques

A comparison of current techniques for measuring elevations in the beach and near-shore zones is presented. Techniques considered include traditional methods such as ground survey along transects and airborne stereophotogrammetry, and also newer methods based on remote sensing such as airborne scanning laser altimetry (LiDAR). The approach taken was to identify a representative group of users of beach elevation data, elicit their requirements regarding these data, then assess how well the different methods met these requirements on both technical and financial grounds. Potential users of beach height measurements include those concerned with coastal defence, coastal environmental management economic exploitation of the intertidal zone, and coastal flood forecasting. Three test areas in the UK were identified covering a range of such users and also different beach types. A total of 17 basic user requirements were elicited. For each requirement each method was scored according to the degree to which it could meet the requirement. Total scores were calculated and each method ranked. This was undertaken for all the requirements together, for a subset relating to survey of narrow beaches, and for a subset relating to survey of wide beaches. Approximate costs were also established for the top six methods. Airborne stereophotogrammetry proved to be the best method technically, but was also the most expensive. Ground survey provides very good technical performance on narrower beaches at moderate cost. Airborne LiDAR can achieve good technical performance on both narrow and wide beaches at lower cost than ground survey. The satellite-based waterline method was also inexpensive and gave good results on wide beaches. An overall conclusion is that, while the traditional methods of ground survey and airborne stereophotogrammetry remain the best for engineering-related surveys requiring high levels of accuracy, airborne LiDAR in particular looks set to have a significant impact on beach survey for applications for which a vertical accuracy of 20 cm is acceptable, provided that its technology evolves satisfactorily.     

Ecological modelling of nitrate pollution in small river basins by spreadsheets and GIS

With the increasing importance and awareness of water quality in the small basins, the modelling system is developed for monitoring and predictions of surface water pollution. The compartment model deals with basin characteristics extended by land cover attributes. The parameters of the model are estimated by experimental data of water quality together with land cover types that serve as nutrient detention media or transformers. The study examines methodology to determine the potential areas of nitrate pollution from point and non-point sources by remote sensing techniques. Classification of water, agricultural, forest and urban areas is processed with satellite images (LANDSAT 7). Whereas the agricultural and urban areas act as sources of pollution, forest zones operate as sinks. The nitrate levels are decreased downstream, if the proportion of the forest inside contribution zones increases. The modelling system is used to simulate amounts of nitrates in each compartment of the stream during the monitored period of one year. The number of compartments and their lengths are estimated on the basis of morphology of the basin. Simulation of the dynamic model is carried out with the TabSim. Geographic information system (GIS) and remote sensing tools are used to manage and estimate nitrate inflows from point and non-point sources of pollution. The article presents the spatial and time variation of the nitrate (NO₃⁻) within the basin of the stream Rakovnický (the west part of Bohemia, the whole area of 368 km²). It is shown that the model approach extended by the GIS and remote sensing can support decision-making process for better management practices in the basins.     

Modis reflectance and active fire data for burn mapping and assessment at regional level

This paper presents an algorithm for rapid and accurate burn mapping that is applied here to the forest fires occurred in Galicia (northwest Spain) in August 2006, when nearly 930 km² were almost entirely burned over the course of eight days. The algorithm synergistically combines remotely-sensed reflectance and active fire data as measured by the MODIS (MODerate resolution Imaging Spectrometer) sensor on board Terra and Aqua NASA (National Aeronautics and Space Administration) satellites. Burned area data collected from this work was compared to official fires statistics from the Spanish Ministry of Environment and to perimeters that were derived using a high spatial resolution satellite image. In a later step, burn patches area analyzed using information from the National Forest Map (1:50,000) and some Geographical Information Systems (GIS) tools.