A new approach for crop identification with wavelet variance and JM distance

This paper develops a new crop mapping method through combined utilization of both time and frequency information based on wavelet variance and Jeffries–Matusita (JM) distance (CIWJ for short). A two-dimensional wavelet spectrum was obtained from datasets of daily continuous vegetation indices through a continuous wavelet transform using the Mexican hat and the Morlet mother wavelets. The time-average wavelet variance (TAWV) and the scale-average wavelet variance (SAWV) were then calculated based on the wavelet spectrum of the Mexican hat and the Morlet wavelet, respectively. The class separability based on the JM distance was evaluated to discriminate the proper period or scale range applied. Finally, a procedure for criteria quantification was developed using the TAWV and SAWV as the major metrics, and the similarity between unclassified pixels and established land use/cover types was calculated. The proposed CIWJ method was applied to the middle Hexi Corridor in northwest China using 250-m 8-day composite moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) time series datasets in 2012. The CIWJ method was shown to be efficient in crop field mapping, with an overall accuracy of 83.6 % and kappa coefficient of 0.7009, assessed with 30 m Chinese Environmental Disaster Reduction Satellite (HJ-1)-derived data. Compared with methods utilizing information on either frequency or time, the CIWJ method demonstrates tremendous potential for efficient crop mapping and for further applications. This method could be applied to either coarse or high spatial resolution images for agricultural crop identification, as well as other more general or specific land use classifications.     

Alterations in the breeding habitats for two endangered raptor species along the Sava River basin, Croatia

Changes in habitat suitable for breeding of two sympatric raptor species (Haliaeetus albicilla and Aquila pomarina) were analysed along one of the most important breeding sites in Croatia for both species. The habitat suitability modelling was used to assess the influence of forestry practice during 2000-2006 using the known data on nesting places along research area. The four most important variables for lesser spotted eagle were elevation, distance from the nearest pasture, vertical distance to the nearest channel network and broadleaved forest placement (second axis from the principal component analysis of the enhanced vegetation index (EVI) index of MODIS images; November-March). The variables where white-tailed eagles showed greatest shift from overall habitat characteristics in the research area were broadleaved forest (second axis from the principal component analysis of the EVI index), height above the sea level, distance from the small settlements, vertical distance to channel network - all with negative loadings. The results clearly reveal the disproportion of suitable forests for raptors that were cut down in comparison to maturation of suitable forests.     

Measuring forest structure along productivity gradients in the Canadian boreal with small-footprint Lidar

The structure and productivity of boreal forests are key components of the global carbon cycle and impact the resources and habitats available for species. With this research, we characterized the relationship between measurements of forest structure and satellite-derived estimates of gross primary production (GPP) over the Canadian boreal. We acquired stand level indicators of canopy cover, canopy height, and structural complexity from nearly 25,000 km of small-footprint discrete return Light Detection and Ranging (Lidar) data and compared these attributes to GPP estimates derived from the MODerate resolution Imaging Spectroradiometer (MODIS). While limited in our capacity to control for stand age, we removed recently disturbed and managed forests using information on fire history, roads, and anthropogenic change. We found that MODIS GPP was strongly linked to Lidar-derived canopy cover (r?=?0.74, p?<?0.01), however was only weakly related to Lidar-derived canopy height and structural complexity as these attributes are largely a function of stand age. A relationship was apparent between MODIS GPP and the maximum sampled heights derived from Lidar as growth rates and resource availability likely limit tree height in the prolonged absence of disturbance. The most structurally complex stands, as measured by the coefficient of variation of Lidar return heights, occurred where MODIS GPP was highest as productive boreal stands are expected to contain a wider range of tree heights and transition to uneven-aged structures faster than less productive stands. While MODIS GPP related near-linearly to Lidar-derived canopy cover, the weaker relationships to Lidar-derived canopy height and structural complexity highlight the importance of stand age in determining the structure of boreal forests. We conclude that an improved quantification of how both productivity and disturbance shape stand structure is needed to better understand the current state of boreal forests in Canada and how these forests are changing in response to changing climate and disturbance regimes.     

Drought impact assessment from monitoring the seasonality of vegetation condition using long-term time-series satellite images: a case study of Mt. Kenya region

Drought-induced anomalies in vegetation condition over wide areas can be observed by using time-series satellite remote sensing data. Previous methods to assess the anomalies may include limitations in considering (1) the seasonality in terms of each vegetation-cover type, (2) cumulative damage during the drought event, and (3) the application to various types of land cover. This study proposed an improved methodology to assess drought impact from the annual vegetation responses, and discussed the result in terms of diverse landscape mosaics in the Mt. Kenya region (0.4° N 35.8° E?~?1.6° S 38.4° E). From the 30-year annual rainfall records at the six meteorological stations in the study area, we identified 2000 as the drought year and 2001, 2004, and 2007 as the normal precipitation years. The time-series profiles of vegetation condition in the drought and normal precipitation years were obtained from the values of Enhanced Vegetation Index (EVI; Huete et al. 2002), which were acquired from Terra MODIS remote sensing dataset (MOD13Q1) taken every 16 days at the scale of 250-m spatial resolution. The drought impact was determined by integrating the annual differences in EVI profiles between drought and normal conditions, per pixel based on nearly same day of year. As a result, we successfully described the distribution of landscape vulnerability to drought, considering the seasonality of each vegetation-cover type at every MODIS pixel. This result will contribute to the large-scale landscape management of Mt. Kenya region. Future study should improve this method by considering land-use change occurred during the long-term monitoring period.     

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.     

基于RS和GIS技术的贵州省植被生态环境监测分析

为阐明贵州省植被生态环境变化的整体状况,基于RS和GIS技术,应用美国国家航空航天局最新的全球植被指数变化研究数据（GIMMS）,通过计算月归一化植被指数（NDVI）变化率,并对研究区一元线性回归模拟,分析了贵州省1982年-2003年的地表植被覆盖。结果表明：22年来,研究区植被覆盖呈增加趋势,表明贵州省植被生态环境向好的方向发展;贵州省平均植被覆盖在春季和秋季呈上升趋势,夏季和冬季呈下降趋势,其中春季对植被覆盖总变化量的贡献最大;植被覆盖程度增减因区域不同而异,变化程度呈增加的区域主要位于贵,ki-I省的中部地区;变化程度呈减小的区域分布在贵州省的四周边缘。     

Variable-source flood pulsing in a semi-arid transboundary watershed: the Chobe River, Botswana and Namibia

The Chobe River, characterized by an unusual flood pulsing regime and shared between Botswana and Namibia, lies at the heart of the world’s largest transfrontier conservation area (the Kavango–Zambezi Transfrontier Conservation Area). Significant ecological changes and vegetation conversions are occurring along its floodplains. Various scenarios for agricultural and urban water use are currently being proposed by the government of Botswana. However, the understanding of the river’s annual flow regime and timing of the relative contributions of water from three different sources is relatively poor. In light of past and future climate change and variability, this means that allocating water between ecological flows and economic and domestic uses will become increasingly challenging. We reconstruct the inundation history in this basin to help ease this challenge. This paper presents a spatiotemporal approach to estimate the contribution of water from various sources and the magnitude of changes in the flooding extent in the basin between 1985 and 2010. We used time series analysis of bimonthly NOAA AVHRR and NASA MODIS data and climatologic and hydrologic records to determine the flooding timing and extent. The results indicate that between 12 and 62 % of the basin is flooded on an annual basis and that the spatial extent of the flooding varies throughout the year as a function of the timing of peak discharge in two larger basins. A 30-year trend analysis indicates a consistent decline in the average monthly flooded area in the basin. The results may prove useful in future water utilization feasibility studies, in determining measures for protecting ecological flows and levels, and in ecosystem dynamics studies in the context of current and future climate change and variability.     

The development of stream temperature model in a mountainous river of Taiwan

Formosan landlocked salmon is an endangered species and is very sensitive to stream temperature change. This study attempts to improve a former stream temperature model (STM) which was developed for the salmon’s habitat to simulate stream temperature more realistically. Two modules, solar radiation modification (SRM) and surface/subsurface runoff mixing (RM), were incorporated to overcome the limitation of STM designed only for clear-sky conditions. It was found that daily temperature difference is related to cloud cover and can be used to adjust the effects of cloud cover on incident solar radiation to the ground level. The modified model (STM + SRM) improved the simulation during a baseflow period in both winter and summer with the Nash-Sutcliffe efficiency coefficient improved from 0.37 (by STM only) to 0.71 for the winter and from ?0.18 to 0.70 for the summer. On the days with surface/subsurface runoff, the incorporation of the two new modules together (STM + SRM + RM) improved the Nash-Sutcliffe efficiency coefficient from 0.00 to 0.65 and from 0.29 to 0.83 in the winter and the summer, respectively. Meanwhile, the contributions of major thermal sources to stream temperature changes were identified. Groundwater is a major controlling factor for regulating seasonal changes of stream temperature while solar radiation is the primary factor controlling daily stream temperature variations. This study advanced our understanding on short-term stream temperature variation, which could be useful for the authorities to restore the salmon’s habitat.     

Recent trends of plutonium fallout observed in Japan: plutonium as a proxy for desertification

Plutonium in monthly deposition samples collected in Tsukuba (the Meteorological Research Institute), Japan from 1990 to end of 2001 is reported, together with monthly plutonium deposition in Nagasaki and Yonaguni in 2000. The annual deposition of (239,240)Pu during the period from 1990 to 2001 shows no systematic interannual variation. However, monthly (239,240)Pu depositions show a typical seasonal variation with a maximum in spring season (March to April), which corresponds to seasonal cycle of soil dusts originating from the East Asian arid area. Plutonium isotopic ratios in the deposition samples suggest that significant amounts of the recent (239,240)Pu deposition observed in Japan are attributed to the resuspension of plutonium-bearing surface soil particles; resuspended plutonium originates from the East Asian arid areas. The recent increased tendency of (239,240)Pu content in residues in deposition samples may reflect desertification in the East Asian continent.     

Large and mesoscale meteo-oceanographic patterns in local responses of biogeochemical concentrations

Investigations surrounding the variability of productivity in upwelling regions are necessary for a better understanding the physical-biological coupling in these regions by monitoring systems of environmental impacts according to the needs of the regional coastal management. Using a spatial and temporal database from National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric (NCAR) Research reanalysis, Quick Scatterometer vector wind, and surface stations from the Southeast coast of Brazil, we investigate the meteorological influences due to the large-scale systems in the variability of the nutrient and larvae concentration, and chlorophyll a, describing statistically relationships between them in upwelling regions. In addition, we used multivariate analysis, such as PCA and clustering to verify spatial and temporal variances and describe more clear the structure and composition of the ecosystem. Correlation matrix analyses were applied for different water masses present in the study area to identify the relations between physical and biogeochemical parameters in a region, where frequently upwelling occur. Statistical approaches and seasonal variability show that the period of November to March is more sensitive to nutrients (1.20?mg/m(3) for chlorophyll a, 2.20?μmol/l for total nitrogen and 5.5?ml/l for DO) and larvae concentrations (120 org/m(3) for most of the larvae, except for cirripedia that presented values around 370 org/m(3)) relating to the influence of large and mesoescale meteorological patterns. The spatial and temporal variables analyzed with multivariate approach show meaningful seasonality variance of the physical and biological samples, characterizing the principal components responsible for this variance in spring and summer (upwelling period), emphasizing the monitoring of species as crustaceans and mussels that are present in the local economy. Then, the spring and summer season are characterized by high productivity due to the occurrence of upwelling in this period.     

Detecting vegetation cover change on the summit of Cadillac Mountain using multi-temporal remote sensing datasets: 1979, 2001, and 2007

This study examines the efficacy of management strategies implemented in 2000 to reduce visitor-induced vegetation impact and enhance vegetation recovery at the summit loop trail on Cadillac Mountain at Acadia National Park, Maine. Using single-spectral high-resolution remote sensing datasets captured in 1979, 2001, and 2007, pre-classification change detection analysis techniques were applied to measure fractional vegetation cover changes between the time periods. This popular sub-alpine summit with low-lying vegetation and attractive granite outcroppings experiences dispersed visitor use away from the designated trail, so three pre-defined spatial scales (small, 0-30 m; medium, 0-60 m; and large, 0-90 m) were examined in the vicinity of the summit loop trail with visitor use (experimental site) and a site chosen nearby in a relatively pristine undisturbed area (control site) with similar spatial scales. Results reveal significant changes in terms of rates of vegetation impact between 1979 and 2001 extending out to 90 m from the summit loop trail with no management at the site. No significant differences were detected among three spatial zones (inner, 0-30 m; middle, 30-60 m; and outer, 60-90 m) at the experimental site, but all were significantly higher rates of impact compared to similar spatial scales at the control site (all p?< 0.001). In contrast, significant changes in rates of recovery between 2001 and 2007 were observed in the medium and large spatial scales at the experimental site under management as compared to the control site (all p?< 0.05). Also during this later period a higher rate of recovery was observed in the outer zone as compared to the inner zone at the experimental site (p?< 0.05). The overall study results suggest a trend in the desired direction for the site and visitor management strategies designed to reduce vegetation impact and enhance vegetation recovery at the summit loop trail of Cadillac Mountain since 2000. However, the vegetation recovery has been rather minimal and did not reach the level of cover observed during the 1979 time period. In addition, the advantages and some limitations of using remote sensing technologies are discussed in detecting vegetation change in this setting and potential application to other recreation settings.     

西藏拉萨市热岛效应及其影响因子分析

采用2001年、2004年以及2007年三年的EOS/MODIS遥感信息反演的地面温度以及多年常规气象观测资料,讨论了拉萨市热岛现象及其可能影响因子。结果表明:(1)热岛强度的年、季节变化呈现逐渐增强的趋势,其中,冬季的热岛强度最强,其次是春季,秋季和夏季的热岛效应较弱;高温区基本位于城市中心或者县城所在地及其周围,低温区主要集中在各县的郊区;近年来拉萨地区的城市高温区域逐渐扩大,有些高温中心可能向某些区域偏移;遥感资料所获取的地表温度与平均气温之间存在一定的正相关性。(2)无论是年变化,还是季节变化,热岛强度都与风速呈正相关,与日照时数呈负相关,与蒸发量的相关在夏季和冬季分别呈正相关、负相关的相反状况;地表温度与植被分布具有较好的负相关关系,即在城区存在较高的地表温度分布和较小的NDVI,过渡到郊区具有温度减小、NDVI增加的特征;随着城市化进程的加剧,建筑面积不断扩大,人类活动明显增加,排放至大气的人为热增加,这些因素都可能导致热岛强度的增强。     

Assessing differences in macrofaunal assemblages as a factor of sieve mesh size,distance between samples,and time of sampling

With increasing cascading effects of climate change on the marine environment, as well as pollution and anthropogenic utilization of the seafloor, there is increasing interest in tracking changes to benthic communities. Macrofaunal surveys are traditionally conducted as part of pre-incident environmental assessment studies and post-incident monitoring studies when there is a potential impact to the seafloor. These surveys usually characterize the structure and/or spatiotemporal distribution of macrofaunal assemblages collected with sediment cores; however, many different sampling protocols have been used. An assessment of the comparability of past and current survey methods was in need to facilitate future surveys and comparisons. This was the aim of the present study, conducted off the Oregon coast in waters 25–35 m deep. Our results show that the use of a sieve with a 1.0-mm mesh size gives results for community structure comparable to results obtained from a 0.5-mm mesh size, which allows reliable comparisons of recent and past spatiotemporal surveys of macroinfauna. In addition to our primary objective of comparing methods, we also found interacting effects of seasons and depths of collection. Seasonal differences (summer and fall) were seen in infaunal assemblages in the wave-induced sediment motion zone but not deeper. Thus, studies where wave-induced sediment motion can structure the benthic communities, especially during the winter months, should consider this effect when making temporal comparisons. In addition, some macrofauna taxa-like polychaetes and amphipods show high interannual variabilities, so spatiotemporal studies should make sure to cover several years before drawing any conclusions.     

Evaluating the utility and seasonality of NDVI values for assessing post-disturbance recovery in a subalpine forest

Forest disturbances around the world have the potential to alter forest type and cover, with impacts on diversity, carbon storage, and landscape composition. These disturbances, especially fire, are common and often large, making ground investigation of forest recovery difficult. Remote sensing offers a means to monitor forest recovery in real time, over the entire landscape. Typically, recovery monitoring via remote sensing consists of measuring vegetation indices (e.g., NDVI) or index-derived metrics, with the assumption that recovery in NDVI (for example) is a meaningful measure of ecosystem recovery. This study tests that assumption using MODIS 16-day imagery from 2000 to 2010 in the area of the Colorado’s Routt National Forest Hinman burn (2002) and seedling density counts taken in the same area. Results indicate that NDVI is rarely correlated with forest recovery, and is dominated by annual and perennial forb cover, although topography complicates analysis. Utility of NDVI as a means to delineate areas of recovery or non-recovery are in doubt, as bootstrapped analysis indicates distinguishing power only slightly better than random. NDVI in revegetation analyses should carefully consider the ecology and seasonal patterns of the system in question.     

Temporal scale-induced uncertainty in load duration curves for instream-dissolved oxygen

Load duration curves were developed using the Hydrological Simulation Program FORTRAN (HSPF) for dissolved oxygen (DO) for the Amite River in Louisiana, USA. The concept of ‘dissolved oxygen reserve’, defined as the total quantity of DO, is introduced. The effect of temporal resolution on duration curves of DO reserve was examined using duration curves developed based on daily, weekly, biweekly, and monthly average data. Duration curves for DO exhibited high variability in the load estimated using daily data as compared to those based on biweekly and monthly data. A seasonal analysis revealed the trend in the DO reserve. The daily DO reserve for the Amite River at Port Vincent was 44,049.31 kg when daily summer data were used and 74,255.15 kg for daily annual data. A surplus of 10,691 kg of DO reserve was shown in the monthly data during critical summer months. The coefficient of variation (CV), used to define the temporal scale-induced uncertainty, was found to be linearly and inversely correlated with the logarithm of the time scale. Regression equations were developed to extrapolate near real-time flow and water quality data, greatly simplifying flow and water quality monitoring and reducing the cost involved in flow and water quality monitoring.     

“十三五”甘肃省降尘时空变化趋势及影响因素

通过分析"十三五"期间甘肃省降尘及相关数据,对甘肃省降尘时空变化情况进行研究,对其变化趋势和影响因素进行分析。"十三五"期间,甘肃省降尘总体呈下降趋势,下降幅度达24.30%,全省植被覆盖指数上升2.03%,降尘与植被覆盖指数负相关性显著。自然来源中,沙尘天气是影响甘肃省降尘的主要因素。城市精细化管理水平的提高可减少降尘人为来源。     

A new multiscale approach for monitoring vegetation using remote sensing-based indicators in laboratory, field, and landscape

Remote sensing is an important tool for studying patterns in surface processes on different spatiotemporal scales. However, differences in the spatiospectral and temporal resolution of remote sensing data as well as sensor-specific surveying characteristics very often hinder comparative analyses and effective up- and downscaling analyses. This paper presents a new methodical framework for combining hyperspectral remote sensing data on different spatial and temporal scales. We demonstrate the potential of using the “One Sensor at Different Scales” (OSADIS) approach for the laboratory (plot), field (local), and landscape (regional) scales. By implementing the OSADIS approach, we are able (1) to develop suitable stress-controlled vegetation indices for selected variables such as the Leaf Area Index (LAI), chlorophyll, photosynthesis, water content, nutrient content, etc. over a whole vegetation period. Focused laboratory monitoring can help to document additive and counteractive factors and processes of the vegetation and to correctly interpret their spectral response; (2) to transfer the models obtained to the landscape level; (3) to record imaging hyperspectral information on different spatial scales, achieving a true comparison of the structure and process results; (4) to minimize existing errors from geometrical, spectral, and temporal effects due to sensor- and time-specific differences; and (5) to carry out a realistic top- and downscaling by determining scale-dependent correction factors and transfer functions. The first results of OSADIS experiments are provided by controlled whole vegetation experiments on barley under water stress on the plot scale to model LAI using the vegetation indices Normalized Difference Vegetation Index (NDVI) and green NDVI (GNDVI). The regression model ascertained from imaging hyperspectral AISA-EAGLE/HAWK (DUAL) data was used to model LAI. This was done by using the vegetation index GNDVI with an R ² of 0.83, which was transferred to airborne hyperspectral data on the local and regional scales. For this purpose, hyperspectral imagery was collected at three altitudes over a land cover gradient of 25 km within a timeframe of a few minutes, yielding a spatial resolution from 1 to 3 m. For all recorded spatial scales, both the LAI and the NDVI were determined. The spatial properties of LAI and NDVI of all recorded hyperspectral images were compared using semivariance metrics derived from the variogram. The first results show spatial differences in the heterogeneity of LAI and NDVI from 1 to 3 m with the recorded hyperspectral data. That means that differently recorded data on different scales might not sufficiently maintain the spatial properties of high spatial resolution hyperspectral images.     

Variations and trends of ground-level ozone and AOT40 in the rural areas of Lithuania

The analysis of data of the ground-level ozone concentration and accumulated ozone exposure over a threshold of 40 ppb (AOT40) in the rural areas of Lithuania is presented. Trends in the annual ozone mean, 95{th} and 25{th} percentiles were determined as statistically not significant at Preila and Rugsteliskes sites during the 1994hbox{–}2004 period. Trends in the ozone concentration and its percentiles in the air masses arriving to Preila station in “polluted” and “unpolluted” sectors have been examined. Statistically significant changes in the ozone annual mean and 25th percentile were found in air masses in both “polluted” and “unpolluted” sectors in the 1988hbox{–}2002 period. The trend analysis in the ozone monthly mean and percentiles for each month of the year revealed the main changes in the ozone level in both sectors during January-May. Insignificant downward trends in monthly 95th percentile in “unpolluted” sector and upward trends in “polluted” sector were found during summer months. Values of AOT40 for the protection of forests as well as crops and semi-natural vegetation were determined during the 1994–2004 period. The estimated AOT40 values for the protection of forests were lower than the critical level at Lithuanian rural sites but AOT40 values for the protection of crops and semi-natural vegetation were found to be higher than the critical level at both sites.     

Atmospheric arsenic (As) study at five characteristic sampling sites in Taiwan

The main purpose for this study is to observe the seasonal and monthly variations for arsenic (As) in total suspended particulates (TSP) concentration and dry deposition at five characteristic sampling sites during the years 2009 and 2010 in central Taiwan. The results show that the highest and lowest monthly average As concentrations in TSP occurred in January and May at Bei-shi (suburban/coastal) and Quan-xing (industrial) sampling sites. In addition, the results show that the highest and lowest monthly average As dry deposition occurred in October and May at Chang-hua (downtown) and Gao-mei (wetland) sampling sites. This study reflected that the mean highest As concentrations in TSP and mean highest As dry deposition occurred at Quan-xing (industrial). However, the mean lowest As concentrations in TSP and mean lowest As dry deposition also occurred at Gao-mei (wetland). Regarding seasonal variation, the results show that the As average seasonal concentration order in TSP was winter > spring > fall > summer, respectively, at Chang-hua (downtown) and He-mei (residential) sampling sites. Finally, the order of As average seasonal dry deposition was fall > winter > spring > summer, respectively, at Chang-hua (downtown), He-mei (residential), and Gao-mei (wetland) sampling sites.