Remote Sensing and Geographic Information Systems and risk of American visceral leishmaniasis in Bahia, Brazil

The spatial distribution of American visceral leishmaniasis (VL) was studied within the context of the environmental characteristics of northwest Bahia State in Brazil during an epidemic year. Geographic Information Systems (GIS) and Remote Sensing (RS) were used to characterize the landscape epidemiology of VL in order to identify and map high risk areas and endemic zones in a northwestern Bahia study area. Normalized Difference Vegetation Index (NDVI) was shown to be one of the most important risk factors in the area of study. Low NDVI values were related to high numbers of sand flies and high numbers of human and canine VL positive cases. Caatinga vegetation type was the dominant vegetation type in the endemic area. The use of RS and GIS allowed the identification of classes of VL risk that may be useful information to guide control program interventions.     

Statistical modelling of the spatial distribution of prevalence of Calicophoron daubneyi infection in sheep from central Italy

Statistical modelling for Disease Mapping and Ecological Analysis is of particular importance in veterinary parasitology because environmental characteristics can affect parasite distribution. However, the main difficulties relate to the concentration of animal populations within farms, which contrasts to the study of wild animal populations. In the present paper we report the results of a cross-sectional coprological survey designed to study the presence and distribution of the rumen fluke Calicophoron daubneyi--which causes paramphistomosis, a snail borne disease--in pastured sheep living in the Latina province of central Italy. We show how techniques derived from human epidemiology can be used to study the spatial distribution of parasite infection in animals. We proposed a hierarchical Bayesian model with random terms for unstructured variability (heterogeneity) to account for local farm characteristics and spatially structure terms (clustering) to cope with medium-large scale environmental characteristics.     

黄土高原归一化植被指数与自然环境因子的空间关联性——基于地理探测器

植被对改善黄土高原脆弱的生态环境有着关键作用,系统研究黄土高原归一化植被指数(NDVI)空间分布和环境因子的空间关联性,可为新时代黄土高原植被高质量建设提供科学依据。以黄土高原2000-2017年年均植被NDVI为研究对象,选取气候要素、地形因素、土壤类型和植被类型等自然环境因子,运用GIS和地理探测器技术手段,在剔除土地利用类型发生变化栅格的基础上,研究黄土高原年均NDVI与环境因子的空间关联性,结果表明:2000-2017年黄土高原年均NDVI值在0.016-0.72之间,呈地带性分布,由西北部向东南部逐渐升高,大于0.3的区域占50.23%;2000-2017年黄土高原年均植被NDVI分布具有空间异质性,且在不同植被区、地貌区、土壤区和气候区中,NDVI空间分布的主要环境驱动因子具有差异性。年均降雨量对NDVI空间分布具有强解释力,是黄土高原85.20%的区域植被生长的主要制约因子;约12.01%的区域主要受土壤类型影响,为中等解释力,其余区域的植被生长主要受年均气温,日照时数或海拔影响。建议综合考虑不同环境条件下植被NDVI的空间分布与环境影响因子的空间关联性,明确不同区域中植被NDVI的环境制约因子,以制约因子定植,在防止土壤干燥化、贫瘠化的前提下,提高植被覆盖率和生物多样性,以期促进黄土高原植被建设高质量发展。     

Ecotope mapping for landscape ecological assessment of habitat and ecosystem

An ecotope (spatial eco-space) map that considers topography and bio-organism-relevant variables emerges as an important basic framework when landscape-scale characteristics for ecosystem management and wildlife conservation are needed. A spatio-geoecological framework based on geographic information systems (GIS) and a vegetation survey were developed for wildlife habitat evaluation of national parks and applied to a representative rugged valley area of Mt. Sorak National Park in Korea. An ecotope map was classified into hundreds of types and dozens of groups by combining biological and geophysical variables. Variables included: forest vegetation type, topographic solar radiation, normalized difference vegetation index (NDVI), elevation, and anthropogenic factors, such as, streams and roads. Layers of GIS variables were produced by field surveys, modeling, satellite images, or digitalization. Vegetation surveys were carried out to identify finer-scale distribution of vegetation types in the rugged valley area. Digital forest vegetation maps from the Forestry Administrator were then modified using the field-surveyed vegetation maps. Topographic solar radiation was predicted with a daily topographic radiation model. The NDVI was calculated from the satellite imagery of a Landsat Thematic Mapper. A digital elevation model (DEM) was used and the other layers were digitized using topographical maps with a scale of 1:25000. The aim of this study is to determine the geoecological factors relating to the spatial pattern of plant community. It was cleared by the spatial pattern of environmental variables and vegetation characteristics by detrended correspondence analysis using plant species and the environmental variables of each plot. The ordination component value of the first axis shows significant regression to some environmental variables. A case study of habitat evaluation was carried out using the resultant ecotope map. The spatial distribution of potential goral habitat and vegetation characteristics were predicted and the impact of human trails on the neighboring vegetation was also examined for restoration planning. The GIS-based framework developed for wildlife habitat evaluation is useful for natural resource management and human activity control in national parks in Korea.     

鄂尔多斯植被盖度分布与环境因素的关系

 从植被指数分布与气象因素、地质地层和地质水文的关系入手, 利用遥感解译和地理信息系统的空间分析功能, 分析了不同尺度下, 气候因素、地质水文因素、基质和地貌等对鄂尔多斯高原植被盖度分布的影响。指出: 在区域尺度上, 研究区植被盖度分布主要受降水影响, 植被盖度呈从东南到西北逐渐减少的趋势; 高盖度植被主要分布在冲洪积地貌和丘陵地貌区。局部分析, 库布齐沙漠东向延伸的存在与发展与区域型断层的存在有密切的联系; 毛乌素沙地中的高盖度植被分布受地形和基质岩性组合的综合影响, 主要分布在第四系湖积物和第四系冲积物等渗水性差的基质上, 尤其集中分布于凹陷的湖相沉积。     

Advances in satellite remote sensing of pheno-climatic features for epidemiological applications

Geographical Information Systems (GIS) and Remote Sensing (RS) technologies are being used increasingly to study the spatial and temporal patterns of diseases. They can be used to complement conventional ecological monitoring and modelling techniques, and provide a means to portray complex relationships in the ecology of diseases with strong environmental determinants. In particular, satellite technology has been extraordinarily improved during recent years, providing new parameters useful to understand the epidemiology of parasites, such as vegetation indices, land surface temperatures, soil moisture and rainfall indices. In the present review, Normalized Difference Vegetation Index (NDVI) is primarily considered, since it is the index characterizing vegetation that is most used in epidemiological studies. Multi-temporal study of RS data allows collection of bio-climatic information about risk area distribution, along with predictive studies and anticipatory models of diseases, at different geographic scales ranging from global to local. The main physical and technological basis of a mathematical model, effective at different scales, for identification of landscape pheno-climatic features is described in the current paper.     

Spatio-temporal Transmission and Environmental Determinants of Schistosomiasis Japonica in Anhui Province,China

Background

Schistosomiasis japonica still remains of public health and economic significance in China, especially in the lake and marshland areas along the Yangtze River Basin, where the control of transmission has proven difficult. In the study, we investigated spatio-temporal variations of S. japonicum infection risk in Anhui Province and assessed the associations of the disease with key environmental factors with the aim of understanding the mechanism of the disease and seeking clues to effective and sustainable schistosomiasis control.

Methodology/Principal Findings

Infection data of schistosomiasis from annual conventional surveys were obtained at the village level in Anhui Province, China, from 2000 to 2010 and used in combination with environmental data. The spatio-temporal kriging model was used to assess how these environmental factors affected the spatio-temporal pattern of schistosomiasis risk. Our results suggested that seasonal variation of the normalized difference vegetation index (NDVI), seasonal variation of land surface temperature at daytime (LSTD), and distance to the Yangtze River were negatively significantly associated with risk of schistosomiasis. Predictive maps showed that schistosomiasis prevalence remained at a low level and schistosomiasis risk mainly evolved along the Yangtze River. Schistosomiasis risk also followed a focal spatial pattern, fluctuating temporally with a peak (the largest spatial extent) in 2005 and then contracting gradually but with a scattered distribution until 2010.

Conclusion

The fitted spatio-temporal kriging model can capture variations of schistosomiasis risk over space and time. Combined with techniques of geographic information system (GIS) and remote sensing (RS), this approach facilitates and enriches risk modeling of schistosomiasis, which in turn helps to identify prior areas for effective and sustainable control of schistosomiasis in Anhui Province and perhaps elsewhere in China.     

Methodological Reflections on the Use of Remote Sensing and Geographic Information Science in Human Ecological Research

Environmental analysts increasingly utilize remote sensing (RS) and geographic information science (GIS) techniques to study the relationship between human societies and their biophysical environment. This paper considers the influence these techniques have had on environmental research. Using the case of the Sahel, the paper first relates contemporary applications of RS/GIS to the history of the environmental scientific practice in the region. While facilitating an expansion of spatiotemporal scales, applications of these new techniques continue the methodological failings of the past by relying on visual measures of environmental change and problematic indicators of human land-use pressures. The human ecology fields (human, cultural, and political ecologies), by emphasizing the causal connections between local management and environmental change, can address the problems inherent with the spatial analytical turn in environmental science. Using the author's experience with the use of GIS in a political ecology study of grazing management in western Niger, ways of more closely integrating RS/GIS techniques into human ecological research are discussed.     

Biodiversity and distribution of water mites (Acari, Hydrachnidia) in spring habitats

1. The distribution, species richness and ecology of spring‐dwelling water mites in Italy were investigated with the aim to better elucidate the role of spring habitats to sustain high levels of biodiversity and their contribution to freshwater biodiversity at a local and regional scale. 2. More than 300 springs in different geographic areas (Alps, Central and Southern Apennines, Sicily and Sardinia), were examined with a total of 163 water mite species recorded. 3. Species richness in each area ranged from 33 species on Sardinia to 77 on Sicily. The highest diversity was found in the Gran Sasso (Central Apennines). The proportion of crenobionts (species strictly bound to this type of habitat) exceeded 50% in almost all the areas investigated. 4. A diverse (up to 20 species per spring) and highly specialised mite fauna was observed in undisturbed rheocrenes and in natural springs of intermediate typology (rheohelocrenes and rheopsammocrenes). In springs subjected to human impacts (pasture, deforestation, alteration and transformation of spring sources) species richness declined and crenobionts were replaced by unspecialised crenoxenes. 5. The zoogeographic importance of spring habitats is confirmed by the presence of 18 endemic species and by members of genera with an interesting disjunct and relict distribution. 6. A comparison with other geographic areas suggests that springs contain a significant fraction of the total number of species found in freshwater habitats and may contribute almost one third of regional freshwater biodiversity. The presence of endemic crenobionts and rare taxa highlights the importance of these habitats in maintaining high levels of biodiversity as well as their contribution to a better understanding of biodiversity patterns in freshwaters.     

基于GS和GIS的春尺蠖种群分布动态研究

本文利用杀虫灯诱杀春尺蠖雄成虫的数据,采用地统计学空间插值方法,借助遥感（RS）和地理信息系统（GIS）技术,得出2001～2003年和田地区春尺蠖种群空间分布格局及其动态。结果显示,3年中春尺蠖种群均为聚集分布,但聚集程度、种群空间分布和数量处于动态变化之中。通过TM卫片解译提取和田地区森林图层,在ARCGIS中完成对插值模拟图的切割,从而把春尺蠖种群动态的年际分布显示在具体的森林斑块内。研究结果可作为进一步研究春尺蠖种群暴发机理和系统控制的基础。     

Regional and local drivers of macroinvertebrate assemblages in boreal springs

Aim To identify the most important environmental drivers of benthic macroinvertebrate assemblages in boreal springs at different spatial scales, and to assess how well benthic assemblages correspond to terrestrially derived ecoregions. Location Finland. Methods Benthic invertebrates were sampled from 153 springs across four boreal ecoregions of Finland, and these data were used to analyse patterns in assemblage variation in relation to environmental factors. Species data were classified using hierarchical divisive clustering (twinspan ) and ordinated using non‐metric multidimensional scaling. The prediction success of the species and environmental data into a priori (ecoregions) and a posteriori (twinspan ) groups was compared using discriminant function analysis. Indicator species analysis was used to identify indicator taxa for both a priori and a posteriori assemblage types. Results The main patterns in assemblage clusters were related to large‐scale geographical variation in temperature. A secondary gradient in species data reflected variation in local habitat structure, particularly abundance of minerogenic spring brooks. Water chemistry variables were only weakly related to assemblage variation. Several indicator species representing southern faunistic elements in boreal springs were identified. Discriminant function analysis showed poorer success in classifying sites into ecoregions based on environmental than on species data. Similarly, when classifying springs into the twinspan groups, classification based on species data vastly outperformed that based on environmental data. Main conclusions A latitudinal zonation pattern of spring assemblages driven by regional thermal conditions is documented, closely paralleling corresponding latitudinal patterns in both terrestrial and freshwater assemblages in Fennoscandia. The importance of local‐scale environmental variables increased with decreasing spatial extent. Ecoregions provide an initial stratification scheme for the bioassessment of benthic macroinvertebrates of North European springs. Our results imply that climate warming, landscape disturbance and degradation of spring habitat pose serious threats to spring biodiversity in northern Europe, especially to its already threatened southern faunistic elements.     

A study of the environmental determinants of malaria and schistosomiasis in the Philippines using Remote Sensing and Geographic Information Systems

Malaria and schistosomiasis are two water-related parasitic diseases affecting millions of people worldwide particularly tropical and subtropical countries. In the Philippines, malaria is found in 72 out of 78 provinces while schistosomiasis is endemic in 24 provinces. The Anopheles mosquito and the Oncomelania snail involved in the transmission of these diseases depend on certain environmental determinants that support mosquito and snail populations. This study, done for the first time in the Philippines, successfully showed how Remote Sensing (RS) and Geographical Information Systems (GIS) can be effectively used in showing how these environmental factors affect the spatial distribution of these two diseases. The study sites, i.e. the municipalities of Asuncion and Kapalong, are known endemic sites for both malaria and schistosomiasis. Georeferenced data enabled visualization of prevalence data in relation to physical maps thus facilitating assessment of disease situation in the two municipalities. RS and GIS data proved that other factors aside from climate influence the epidemiology of the diseases in the two sites. Topography and slope as main physical factors influence the vegetation cover, land use and soil type prevailing in particular areas. In addition, water sources especially irrigation networks differed in various places in the study sites in turn affecting the magnitude and distribution of malaria and schistosomiasis. Significant correlations found between the diseases and the environmental variables formed the basis for development of models to predict the disease prevalence in the two municipalities. Proximity to snail breeding sites and irrigation networks and the highly agricultural nature of the barangays were identified as the most common factors that define the high prevalence areas for schistosomiasis confirming the fact that conditions that support the snail populations will in turn favor the presence of the disease. For malaria, the predictive models included temperature, humidity, soil type, predominance of reproduction brush, presence of cultivated areas, distance from deep wells and distance from conventional water source which are in turn influenced by the factor of elevation.     

Cross-sectional survey of ticks (Acari: Ixodidae) in sheep from an area of the southern Italian Apennines

A cross-sectional survey of ticks was conducted on 197 ovine farms with animals pasturing in an area (3971 km2) of the southern Italian Apennines. The farms were selected to be uniformly distributed throughout the study area using Geographical Information System (GIS). Ticks were collected from 309 (31.4%) out of the 985 sheep sampled, belonging to 92 (46.7%) out of the 197 farms included in the study. The following tick species were found (farm prevalence): Dermacentor marginatus (37.6%), Haemaphysalis punctata (29.4%), H. sulcata (2.5%), H. parva (2.0%). H. inermis (0.5%), Ixodes gibbosus (2.0%), I. ricinus (0.5%), Rhipicephalus sanguineus group (1.0%), and R. bursa (0.5%). A point distribution map (PDM) was drawn by GIS in order to display the distribution of each tick genus in the study area. The general trends of the PDM show that Dermacentor marginatus and Haemaphysalis spp. were widely and homogeneously spread throughout the study area, whereas Rhipicephalus spp. and Ixodes spp. were present only in a few concentrated zones of the study area in accordance to their biological and ecological characteristics.     

Tsetse Fly (G.f. fuscipes) Distribution in the Lake Victoria Basin of Uganda

Tsetse flies transmit trypanosomes, the causative agent of human and animal African trypanosomiasis. The tsetse vector is extensively distributed across sub-Saharan Africa. Trypanosomiasis maintenance is determined by the interrelationship of three elements: vertebrate host, parasite and the vector responsible for transmission. Mapping the distribution and abundance of tsetse flies assists in predicting trypanosomiasis distributions and developing rational strategies for disease and vector control. Given scarce resources to carry out regular full scale field tsetse surveys to up-date existing tsetse maps, there is a need to devise inexpensive means for regularly obtaining dependable area-wide tsetse data to guide control activities. In this study we used spatial epidemiological modelling techniques (logistic regression) involving 5000 field-based tsetse-data (G. f. fuscipes) points over an area of 40,000 km², with satellite-derived environmental surrogates composed of precipitation, temperature, land cover, normalised difference vegetation index (NDVI) and elevation at the sub-national level. We used these extensive tsetse data to analyse the relationships between presence of tsetse (G. f. fuscipes) and environmental variables. The strength of the results was enhanced through the application of a spatial autologistic regression model (SARM). Using the SARM we showed that the probability of tsetse presence increased with proportion of forest cover and riverine vegetation. The key outputs are a predictive tsetse distribution map for the Lake Victoria basin of Uganda and an improved understanding of the association between tsetse presence and environmental variables. The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control.     

基于RS和GIS的杭州城市生态环境质量综合评价技术

针对生态环境质量传统评价技术的不足,开展中小尺度区域RS和GIS相结合的评价技术研究.将研究区域和评价单元网格化,由RS和GIS技术获取生态环境空间数据,选取自然环境条件、环境质量、自然景观格局和城市化影响4大类共11个指标为评价指标,并利用GIS空间分析技术,将环境污染常规监测数据和社会经济统计数据同化到小网格评价单元进行综合评价,并与城市热岛效应对比,分级评价结果基本符合杭州市区生态环境质量现状.     

The Chironomid Communities of Woodland Springs and Spring Brooks, Severely Endangered and Impacted Ecosystems in a Lowland Region of Eastern Germany (Diptera: Chironomidae)

The distribution of chironomid species from four springs and twelve spring brooks in a region heavily affected by industrial activity in eastern Germany was studied. The aims were (1) to document the chironomid taxa communities at the species level, as far as possible, and the most important environmental factors of representative springs and spring brooks of the region, (2) to analyse the distribution of the ecological groups within these small ecosystems and (3) to emphasize the importance of the protection of spring areas and spring brooks in this woodland area shown by the chironomid fauna. There was high degree of abiotic variation among the water bodies, with pH ranging from 2.79 to 6.89. While diversity did not correlate with pH nor with conductivity, significant differences existed between the spring mouth and the reaches some metres downstream with respect to several abiotic parameters and the distribution of the chironomids: oxygen concentrations and taxonomic diversities were higher in spring brooks (2.18–8.98mgO₂/l; 5–28 taxa) than in the spring areas (0.13–2.95mgO₂/l; 0–7 taxa). A total of 74 chironomid taxa were recorded. The chironomid communities are characterized by the presence of rheophilic, cold-stenothermic, crenophilic and sometimes tyrphophilic elements in each site. The data show that each of the spring–spring brook systems surveyed is unique both in biotic and abiotic respects. As the spring system is sensitive to changes in landscape functions (e.g. groundwater levels), the fauna can serve as an indicator of landscape health. Therefore, these small ecosystems should be conserved as a reference.     

Benthic macrocrustacean and insect assemblages in relation to spring habitat characteristics: patterns in abundance and diversity

We studied variation in benthic macrocrustacean and insect assemblages in relation to spring habitat characteristics in six springs located in a single groundwater area in south-west Finland. We defined five habitat types in the studied springs according to water flow and benthic substrate characteristicsminerogenic brooks, organogenic brooks, helocrenes, floating moss carpets and limnocrene pools. Most studied invertebrate orders, as well as individual taxa, showed differences in relative abundances between the habitat types, but the most common taxa occurred in all springs and habitat types. The studied macroinvertebrates were most abundant in the moss carpet sites and least abundant in the pool sites, but the difference was not statistically significant. We did not observe significant differences in mean taxonomic richness per sample between habitat classes. The observed taxonomic richness in pooled samples of habitat classes was highest in moss carpet habitat and lowest in pool habitat, and the rarefied richness estimate was lowest in pool habitat. Benthic macrocrustacean and insect assemblages varied more between habitat types than between individual springs. In an Nonmetric Multidimensional Scaling ordination analysis, spring brook sites were separated from the moss carpet and pool sites, whereas helocrene sites were widely scattered among sites in other habitat classes. The strongest ecological gradients were related to water flow and the presence of minerogenic substrate, separating lentic and lotic habitats. Abundances of moss and coarse detritus accounted for most of the within-class variation. We identified several indicator species for minerogenic and organogenic brooks and for moss carpet and pool habitats, but none for the helocrenes. We found several occurrences of two crenobiont insect species considered threatened in Finland. We suggest that combined studies on macroinvertebrate and bryophyte assemblages would be a powerful approach in assessing the biodiversity of springs.     

Biotic factors and occurrence of Lutzomyia longipalpis in endemic area of visceral leishmaniasis, Mato Grosso do Sul, Brazil

The relationships between environmental exposure to risk agents and health conditions have been studied with the aid of remote sensing imagery, a tool particularly useful in the study of vegetation cover. This study aims to evaluate the influence of environmental variables on the spatial distribution of the abundance of Lutzomyia longipalpis and the reported canine and human visceral leishmaniasis (VL) cases at an urban area of Campo Grande, state of Mato Grosso do Sul. The sandfly captures were performed in 13 residences that were selected by raffle considering four residences or collection station for buffer. These buffers were generated from the central house with about 50, 100 and 200 m from it in an endemic area of VL. The abundance of sandflies and human and canine cases were georreferenced using the GIS software PCI Geomatica. The normalized difference vegetation index (NDVI) and percentage of land covered by vegetation were the environmental variables extracted from a remote sensing IKONOS-2 image. The average NDVI was considered as the complexity of habitat and the standard deviation as the heterogeneity of habitat. One thousand three hundred sixty-seven specimens were collected during the catch. We found a significant positive linear correlation between the abundance of sandflies and the percentage of vegetation cover and average NDVI. However, there was no significant association between habitat heterogeneity and the abundance of these flies.     

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R² (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R²: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the ‘upland model’ was able to more accurately predict SOC compared with the ‘upland & wetland model’. However, the separately calibrated ‘upland and wetland model’ did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM).