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Land Cover Classes (land + cover_class)
Selected AbstractsComparison of phenology trends by land cover class: a case study in the Great Basin, USAGLOBAL CHANGE BIOLOGY, Issue 2 2008BETHANY A. BRADLEY Abstract Direct impacts of human land use and indirect impacts of anthropogenic climate change may alter land cover and associated ecosystem function, affecting ecological goods and services. Considerable work has been done to identify long-term global trends in vegetation greenness, which is associated with primary productivity, using remote sensing. Trend analysis of satellite observations is subject to error, and ecosystem change can be confused with interannual variability. However, the relative trends of land cover classes may hold clues about differential ecosystem response to environmental forcing. Our aim was to identify phenological variability and 10-year trends for the major land cover classes in the Great Basin. This case study involved two steps: a regional, phenology-based land cover classification and an identification of phenological variability and 10-year trends stratified by land cover class. The analysis used a 10-year time series of Advanced Very High Resolution Radiometer satellite data to assess regional scale land cover variability and identify change. The phenology-based regional classification was more detailed and accurate than national or global products. Phenological variability over the 10-year period was high, with substantial shifts in timing of start of season of up to 9 weeks. The mean long-term trends of montane land cover classes were significantly different from valley land cover classes due to a poor response of montane shrubland and pinyon-juniper woodland to the early 1990s drought. The differential response during the 1990s suggests that valley ecosystems may be more resilient and montane ecosystems more susceptible to prolonged drought. This type of regional-scale land cover analysis is necessary to characterize current patterns of land cover phenology, distinguish between anthropogenically driven land cover change and interannual variability, and identify ecosystems potentially susceptible to regional and global change. [source] Can late summer Landsat data be used for locating Asian migratory locust, Locusta migratoria migratoria, oviposition sites in the Amudarya River delta, Uzbekistan?ENTOMOLOGIA EXPERIMENTALIS ET APPLICATA, Issue 2 2008Ramesh Sivanpillai Abstract Existing survey methods for assessing the Asian migratory locust, Locusta migratoria migratoria L. (Orthoptera: Acrididae), infestation risk in the Amudarya River delta, Uzbekistan, are largely constrained by economic resources and site accessibility. The surveys are restricted to a few easily accessible areas, which leads to a misinterpretation of the threat of locust infestation. This often results in indiscriminate blanket treatments of vast areas of wetlands with broad-spectrum insecticides, which may adversely impact non-target fauna and flora. In order to minimize the bias during surveys, one approach would be to allocate the sampling locations based on the distribution of the primary food and shelter plant of the locusts, the common reed, Phragmites australis (Cav.) Trin. ex Steud (Poaceae). In this study, we evaluated the utility of satellite-based remotely sensed data (Landsat TM) acquired in August 2006 to characterize reed distribution in the delta and identify potential locust oviposition sites. The overall accuracy of the Landsat data to map land cover classes in the delta was 84%. The Landsat TM data identified 90% of the reeds, but it was less useful in identifying areas where other vegetations (shrubs and grasses) were mixed with reeds. During the following summer field survey in June 2007, we identified 37 sites that were infested with early-instar locusts. The low migration capacity of young nymphs in dense reed vegetation allowed us to presume that these sites were used for oviposition in the previous summer. Twenty-eight (74%) of these 37 sites had reeds in the previous year. Results from these studies demonstrate that reed distribution maps derived from satellite data could be used for targeting locust egg-pod survey locations, in order to minimize sampling bias while predicting locust infestation risks for the following season. [source] Comparison of phenology trends by land cover class: a case study in the Great Basin, USAGLOBAL CHANGE BIOLOGY, Issue 2 2008BETHANY A. BRADLEY Abstract Direct impacts of human land use and indirect impacts of anthropogenic climate change may alter land cover and associated ecosystem function, affecting ecological goods and services. Considerable work has been done to identify long-term global trends in vegetation greenness, which is associated with primary productivity, using remote sensing. Trend analysis of satellite observations is subject to error, and ecosystem change can be confused with interannual variability. However, the relative trends of land cover classes may hold clues about differential ecosystem response to environmental forcing. Our aim was to identify phenological variability and 10-year trends for the major land cover classes in the Great Basin. This case study involved two steps: a regional, phenology-based land cover classification and an identification of phenological variability and 10-year trends stratified by land cover class. The analysis used a 10-year time series of Advanced Very High Resolution Radiometer satellite data to assess regional scale land cover variability and identify change. The phenology-based regional classification was more detailed and accurate than national or global products. Phenological variability over the 10-year period was high, with substantial shifts in timing of start of season of up to 9 weeks. The mean long-term trends of montane land cover classes were significantly different from valley land cover classes due to a poor response of montane shrubland and pinyon-juniper woodland to the early 1990s drought. The differential response during the 1990s suggests that valley ecosystems may be more resilient and montane ecosystems more susceptible to prolonged drought. This type of regional-scale land cover analysis is necessary to characterize current patterns of land cover phenology, distinguish between anthropogenically driven land cover change and interannual variability, and identify ecosystems potentially susceptible to regional and global change. [source] Multi-scale sampling and statistical linear estimators to assess land use status and changeAPPLIED VEGETATION SCIENCE, Issue 2 2009D. Rocchini Abstract Question: Multi-temporal analysis of remotely sensed imagery has proven to be a powerful tool for assessment and monitoring of landscape diversity. Here the feasibility of assessing land-use diversity and land-use change was tested at multiple scales and over time by means of statistical linear estimators based on a probabilistic sampling design. Location: The study area (the district of Asciano, Tuscany, Italy) is characterized by erosional forms typical of Pliocene claystone (i.e. calanchi and biancane) that have been subject to the phenomenon of biancane reworking over the past 50 years, mainly owing to the expansion of intensive agriculture. Methods: Cells at two different scales (50 m × 50 m and 10 m × 10 m) were classified by two operators according to a multilevel legend, using 1954 and 2000 aerial photographs. Inter-operator agreement and accuracy were tested by Cohen's K coefficient. Total land cover estimation for each class was carried out using a multistage estimator, while the variance was estimated by means of the Wolter estimator. Field-based information on plant species composition was recorded in order to test for a relationship between land use and plant community composition by anova and indicator species analysis. Results: Agreement between photointerpreters and accuracy were significantly higher than those expected by chance, proving that the approach proposed is reproducible, as long as proper quality assurance methods are used. Our data show that, at the two scales considered (50 m × 50 m and 10 m × 10 m), crops have increased against woodlands and semi-natural areas, the latter showing the highest and significantly different mean species richness. Meanwhile, an increase in the coverage of trees and shrubs was found within the semi-natural areas, probably as a result of secondary succession occurring on typical landscape elements such as biancane. Conclusions: Inferential statistics made it possible to acquire quantitative information on the abundance of land cover classes, allowing formal multi-temporal and multi-scale analysis. Sampling design-based statistical linear estimators were found to be a powerful tool for assessing landscape trends considering both time expenditure and other costs. They make it possible to maintain the same scale of analysis over time series data and to detect both coarse- and fine-grained changes in spatial patterns. [source] Combining land cover mapping of coastal dunes with vegetation analysisAPPLIED VEGETATION SCIENCE, Issue 2 2005A. Acosta Abstract Question: Coastal dune systems are characterized by a natural mosaic that promotes species diversity. This heterogeneity often represents a severe problem for traditional mapping or ground survey techniques. The work presented here proposes to apply a very detailed CORINE land cover map as baseline information for plant community sampling and analysis in a coastal dune landscape. Location: Molise coast, Central Italy. Method: We analysed through an error matrix the coherence between land cover classes and vegetation types identified through a field survey. The CORINE land cover map (scale 1: 5000) of the Molise coast was used with the CORINE legend expanded to a fourth level of detail for natural and semi-natural areas. Vegetation data were collected following a random stratified sampling design using the CORINE land cover classes as strata. An error matrix was used to compare, on a category-by-category basis, the relationship between vegetation types (obtained by cluster analyses of sampling plots) and land cover classes of the same area. Results: The coincidence between both classification approaches is quite good. Only one land cover class shows a very weak agreement with its corresponding vegetation type; this result was interpreted as being related to human disturbance. Conclusions: Since it is based on a standard land cover classification, the proposal has a potential for application to most European coastal systems. This method could represent a first step in the environmental planning of coastal systems. [source] | ||||||||||