Spatial variation is well known to exist in water quality parameters of the Great Lakes nearshore; however, strong patterns for extended reaches also have been observed and found to be robust across seasonal time frames. Less is known about robustness of inter-annual variation within parameters for water quality in the nearshore.
In this study, a terrain classification algorithm is presented that was derived from various properties of the returned full waveform signals collected from the Ice, Cloud and land elevation Satellite (ICESat) mission. Such an algorithm would be beneficial for current and future studies of the cryosphere, particularly Greenland and Antarctica, by helping to identify changes in the large scale surface properties over time. The algorithm developed was validated over a test region in the Dry Valleys of Antarctica, where the terrain is well known and regularly monitored.
Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus (ETM+) image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data.
This paper presents findings of a land-use and land-cover (LULC) change mapping exercise conducted in Freetown, Sierra Leone. Nine LULC classes were mapped from multi-temporal Landsat data of 1974, 1986 and 2000. Special attention was given to the growth or otherwise of agricultural land in relation to other LULC classes. Conversion of one land-use/-cover type to the other was identified, and its effects discussed. Major conversions occurred between agricultural lands, grasslands, evergreen forest, built-up areas and barren land.
Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico presents a number of significant challenges for the fine-scale land-cover information required of land-change science. Subtle variation in mature forest types across the regional ecocline is compounded by vegetation transitions following agricultural land uses. Such complex mapping environments require innovation in multispectral classification methodologies. This research presents an application of a step-wise maximum likelihood/In-Process Classification Assessment (IPCA) procedure.
This article explores the simultaneous use of pre-classification and post-classification change-detection techniques to map and monitor land-cover and land-use change using multi-temporal Landsat Multi-spectral Scanner and Enhanced Thematic Mapper plus data over one of the most important tourism centres of Italy (e.g.
Sediment profiles from the floodplain of Morava River in the Czech Republic have been collected from exposed river banks (4–6m long sections) and cores (2–4m deep) and investigated using a set of geochemical proxies validated by granulometry and conventional geochemical analysis, outlined in our previous paper. The work was conducted to evaluate the increase in sedimentation rate during Medieval and modern time periods.
Forest fire is a major cause of changes in forest structure and function. Among various floristic regions, the northeast region of India suffers maximum from the fires due to age-old practice of shifting cultivation and spread of fires from jhum fields. For proper mitigation and management, an early warning of forest fires through risk modeling is required. The study results demonstrate the potential use of remote sensing and Geographic Information System (GIS) in identifying forest fire prone areas in Manipur, southeastern part of Northeast India.
Urban land cover is expanding rapidly worldwide. This major phenomenon is often accompanied by an expansion of a green component. Urban green can itself be considered as a most important but often ignored land cover category. With this study we investigate how IKONOS data can be used more exhaustively for the detection and more importantly the quantification of urban green, compared to state-of-the art investigations.
Soil erosion in terrestrial ecosystems, as an important global environmental problem, significantly impacts on environmental quality and social economy. By protecting soil from wind and water erosion, terrestrial ecosystems supply human beings with soil erosion control service, one of the fundamental ecosystem services that ensure human welfare. The Loess Plateau was one of the regions in the world that suffered from severe soil erosion. In the past decades, restoration projects were implemented to improve soil erosion control in the region.
An optimal validation of a thematic map would ideally require in-situ observations of a large sample of units specifically conceived for the map under validation. This is often not possible due to budget limitations. The alternative can be using photo-interpretation of high or very high resolution images instead of in-situ observations or using available data sets that do not fully comply with the ideal characteristics: unit size, reference date or sampling plan. This paper illustrates some examples of use of available data in the European Union.
Quantification of spatial and temporal heterogeneity has been given much attention in order to link ecological patterns to processes. The patch mosaic model, as an operational paradigm, has led to major advances in the field of quantitative landscape ecology. However, it is more realistic to conceptualize landscapes based on continuous rather than discrete spatial heterogeneity. While a conceptual shift has been proposed to supplement the patch mosaic model, few studies use the surface gradient model as a context.