Issues in monitoring wilderness lake chemistry: A case study in the Sawtooth Mountains,Idaho

A probability-based sample of 48 of the 152 lakes in the Sawtooth Wilderness, Idaho was conducted in summer 1988. Results from this sample were compared to the Environmental Protection Agency's 1985 probability survey of lakes throughout the western United States, which included 17 lakes in the Sawtooth Wilderness. Although methods differed in several respects, including year, season, sampling location within the lakes, holding times, and sample size, general characterization of lake chemistry for the population of lakes in the wilderness based on the two surveys was very similar. The results indicate that general lake characterization in difficult-to-access wilderness areas of the West can be achieved with a modest investment in resources with the use of volunteers. However, accurate measurement of some non-conservative and low-level analytes such as NO ₃ ^– ,NH ₄ ⁺ , total P, and aluminiun in the lakes probably requires more rigorous attention to sampling protocols and holding times. A two-stage sampling strategy employing extensive use of conductivity on a large number of lakes and intensive detailed chemical characterization on a smaller number of lakes offers an alternative design for describing large populations of wilderness lakes. The relatively high concentrations of fluoride and sulfate in many of the study lakes reflect the weathering of minerals not usually identified on geologic maps. These natural sources of acid anions violate the assumptions in commonly employed empirical models of acidification.     

Water quality monitoring and assessment of an urban Mediterranean lake facilitated by remote sensing applications

Degradation of water quality is a major problem worldwide and often leads to serious environmental impacts and concerns about public health. In this study, the water quality monitoring and assessment of the Koumoundourou Lake, a brackish urban shallow lake located in the northeastern part of Elefsis Bay (Greece), were evaluated. A number of water quality parameters (pH, temperature, dissolved oxygen concentration, electrical conductivity, turbidity, nutrients, and chlorophyll-a concentration) were analyzed in water samples collected bimonthly over a 1-year period from five stations throughout the lake. Moreover, biological quality elements were analysed seasonally over the 1-year period (benthic fauna). Statistical analysis was performed in order to evaluate the water quality of the lake and distinguish sources of variation measured in the samples. Furthermore, the chemical and trophic status of the lake was evaluated according to the most widely applicable classification schemes. Satellite images of Landsat 5 Thematic Mapper were used in order for algorithms to be developed and calculate the concentration of chlorophyll-a (Chl-a). The trophic status of the lake was characterized as oligotrophic based on phosphorus and as mesotrophic–eutrophic based on Chl-a concentrations. The results of the remote sensing application indicated a relatively high coefficient of determination (R ²) among point sampling results and the remotely sensed data, which implies that the selected algorithm is reliable and could be used for the monitoring of Chl-a concentration in the particular water body when no field data are available.     

Application of remote sensing to exposure monitoring

Although exposure assessments cannot be completed remotely, remote sensing techniques provide an invaluable adjunct in exposure monitoring programs. Exposure can be defined as the summation over time, in all media, of the amount of a pollutant available at the exchange boundaries of the receptor during a specified period. This paper describes a few remote monitoring techniques that provide direct measurement input into an exposure assessment and several that furnish quantitative or qualitative information leading to decisions regarding how to monitor, such that the source-exposure-dose relationships can be fully defined. Two general classes of remote sensing systems are included in this discussion-passive and active. Passive systems depend on a measurement of the energy reflected or emitted by a target and active systems use an energy source, e.g., a laser to perform the environmental interrogation. Airborne as well as ground-based remote monitoring measurements or systems are also considered in this paper.     

On applications of remote sensing for environmental monitoring

Modern airborne and satellite remote sensing techniques offer attractive opportunities to coastal monitoring systems. Improvements of the evaluation of larger scales phenomena and processes due to the synopticity of the remote sensing data are of particular interest. However, some uncertainties and limitations about remote sensing must be considered. Microwave, infrared and visible radiation methods and their applications are briefly discussed and some applications are demonstrated. Special attention is paid to the remote sensing of various pollutants in the sea, in particular with respect to oil pollution.Promising developments of the remote sensing methods for coastal monitoring are to be expected from the European remote sensing satellite missions ERS 1 and ERS 2.Combination of these observations with simultaneous in situ measurements from ships (sea truth) appears to be most advantageous for the interpretation of the collected data.     

The global troposphere: Biogeochemical cycles,chemistry, and remote sensing

The chemical composition of the troposphere is controlled by various biogeochemical cycles that couple the atmosphere with the oceans, the solid Earth and the biosphere, and by atmospheric photochemical/chemical reactions. These cycles and reactions are discussed and a number of key questions concerning tropospheric composition and chemistry for the carbon, nitrogen, oxygen and sulfur species are identified. Next, we review various remote sensing techniques and instruments capable of measuring and monitoring tropospheric species from the ground, aircraft and space to address some of these key questions. We also consider future thrusts in remote sensing of the troposphere.     

Large scale remote sensing for environmental monitoring of infrastructure

Recent developments in wireless sensor technology afford the opportunity to rapidly and easily deploy large-scale, low-cost, and low-power sensor networks across relatively sizeable environmental regions. Furthermore, the advancement of increasingly smaller and less expensive wireless hardware is further complemented by the rapid development of open-source software components. These software protocols allow for interfacing with the hardware to program and configure the onboard processing and communication settings. In general, a wireless sensor network topology consists of an array of microprocessor boards, referred to as motes, which can engage in two-way communication among each other as well as with a base station that relays the mote data to a host computer. The information can then be either logged and displayed on the local host or directed to an http server for network monitoring remote from the site. A number of wireless sensor products are available that offer off-the-shelf network hardware as well as sensor solutions for environmental monitoring that are compatible with the TinyOS open-source software platform. This paper presents an introduction to wireless sensing and to the use of external antennas for increasing the antenna radiation intensity and shaping signal directivity for monitoring applications requiring larger mote-to-mote communication distances.     

遥感技术在大气环境监测中的应用综述

综合论述了近20多年来国内外对大气环境遥感监测的研究现状,介绍了应用于大气环境遥感监测的多种方法并着重阐述了被动式空基遥感和主动式地基遥感在大气环境遥感中的应用以及探测气溶胶的卫星传感器的发展历程和特点。最后,对我国大气环境遥感研究中存在问题和发展前景进行了讨论。     

内陆水环境污染监测的多时相遥感信息模型

介绍了遥感水质监测的基本原理,对遥感技术在水质监测领域的国内外发展现状进行了归纳分析,并论述了建立多时相、通用型内陆水环境污染遥感监测模型的可行性,最后以湘江长沙段为研究区域,创建了适用于DO、CODCr、CODMn、BOD和TN的水污染遥感因子和相应的多时相遥感信息模型。     

Water quality monitoring of Al-Habbaniyah Lake using remote sensing and in situ measurements

Environmental Monitoring and Assessment - A good quality drinking water is essential for human survival. However, a large percentage of the populations in most developing countries (Nigeria...     

遥感在生态与环境监测中的主要应用领域

遥感是一种以物理手段、数学方法和地学分析为基础的综合应用技术 ,具有宏观、综合、动态和快速的特点。在解决宏观尺度的环境问题时 ,卫星遥感可重复获取多种空间、不同时相和不同波谱分辨率的地球信息 ,是适宜于调查和研究这些主题的唯一的、最有效的工具。本文通过对遥感在环境与生态监测的主要应用领域进行概要阐述 ,旨在抛砖引玉 ,推动遥感在环境与生态监测中的广泛应用。     

卫星遥感环境业务化监测应用平台建设

从中国的卫星遥感技术现状出发,提出了中国的环境遥感应用不能只停留在研究水平,应根据我国环境监测的实际需要,与地面环境监测相结合,建立一套卫星遥感环境业务化监测应用平台,使遥感技术进入环境保护领域的实用化阶段。文章指出卫星遥感环境业务化监测应用平台建设主要包括卫星遥感环境业务化监测指标与监测、运行技术规范体系的建立、卫星遥感环境监测目标的确定、卫星遥感环境业务化监测目标的波谱数据库的建立、卫星遥感环境业务监测应用平台的业务内容、关键技术研究等内容,深化了我国的卫星遥感在环境领域中的应用,具有很高的实用价值。     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve,India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004–2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km². There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km² (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km² is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km²) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.     

Integrating biophysical and socioeconomic information for prioritizing watersheds in a Kashmir Himalayan lake: a remote sensing and GIS approach

Dal Lake, a cradle of Kashmiri civilization has strong linkage with socioeconomics of the state of Jammu and Kashmir. During last few decades, anthropogenic pressures in Dal Lake Catchment have caused environmental deterioration impairing, inter-alia, sustained biotic communities and water quality. The present research was an integrated impact analysis of socioeconomic and biophysical processes at the watershed level on the current status of Dal Lake using multi-sensor and multi-temporal satellite data, simulation modelling together with field data verification. Thirteen watersheds (designated as ‘W1–W13’) were identified and investigated for land use/land cover change detection, quantification of erosion and sediment loads and socioeconomic analysis (total population, total households, literacy rate and economic development status). All the data for the respective watersheds was integrated into the GIS environment based upon multi-criteria analysis and knowledge-based weightage system was adopted for watershed prioritization based on its factors and after carefully observing the field situation. The land use/land cover change detection revealed significant changes with a uniform trend of decreased vegetation and increased impervious surface cover. Increased erosion and sediment loadings were recorded for the watersheds corresponding to their changing land systems, with bare and agriculture lands being the major contributors. The prioritization analysis revealed that W5?>?W2?>?W6?>?W8?>?W1 ranked highest in priority and W13?>?W3?>?W4?>?W11?>?W7 under medium priority. W12?>?W9?>?W10 belonged to low-priority category. The integration of the biophysical and the socioeconomic environment at the watershed level using modern geospatial tools would be of vital importance for the conservation and management strategies of Dal Lake ecosystem.     

Land desertification monitoring and assessment in Yulin of Northwest China using remote sensing and geographic information systems (GIS)

The objective of this study is to develop techniques for assessing and analysing land desertification in Yulin of Northwest China, as a typical monitoring region through the use of remotely sensed data and geographic information systems (GIS). The methodology included the use of Landsat TM data from 1987, 1996 and 2006, supplemented by aerial photos in 1960, topographic maps, field work and use of other existing data. From this, land cover, the Normalised Difference Vegetation Index (NDVI), farmland, woodland and grassland maps at 1:100,000 were prepared for land desertification monitoring in the area. In the study, all data was entered into a GIS using ILWIS software to perform land desertification monitoring. The results indicate that land desertification in the area has been developing rapidly during the past 40 years. Although land desertification has to some extent been controlled in the area by planting grasses and trees, the issue of land desertification is still serious. The study also demonstrates an example of why the integration of remote sensing with GIS is critical for the monitoring of environmental changes in arid and semi-arid regions, e.g. in land desertification monitoring in the Yulin pilot area. However, land desertification monitoring using remote sensing and GIS still needs to be continued and also refined for the purpose of long-term monitoring and the management of fragile ecosystems in the area.     

Seagrass resource assessment using remote sensing methods in St. Joseph Sound and Clearwater Harbor,Florida, USA

In the event of a natural or anthropogenic disturbance, environmental resource managers require a reliable tool to quickly assess the spatial extent of potential damage to the seagrass resource. The temporal availability of the Landsat 5 Thematic Mapper (TM) imagery provided a suitable option to detect and assess damage of the submerged aquatic vegetation (SAV). This study examined Landsat TM imagery classification techniques to create two-class (SAV presence/absence) and three-class (SAV estimated coverage) SAV maps of the seagrass resource. The Mahalanobis Distance method achieved the highest overall accuracy (86%) and validation accuracy (68%) for delineating the seagrass resource (two-class SAV map). The Maximum Likelihood method achieved the highest overall accuracy (74%) and validation accuracy (70%) for delineating the seagrass resource three-class SAV map. The Landsat 5 TM imagery classification provided a seagrass resource map product with similar accuracy to the aerial photointerpretation maps (validation accuracy 71%). The results support the application of remote sensing methods to analyze the spatial extent of the seagrass resource.     

The potential of remote sensing for monitoring land cover changes and effects on physical geography in the area of Kayisdagi Mountain and its surroundings (Istanbul)

The effect of land cover change, from natural to anthropogenic, on physical geography conditions has been studied in Kayisdagi Mountain. Land degradation is the most important environmental issue involved in this study. Most forms of land degradation are natural processes accelerated by human activity. Land degradation is a human induced or natural process that negatively affects the ability of land to function effectively within an ecosystem. Environmental degradation from human pressure and land use has become a major problem in the study area because of high population growth, urbanization rate, and the associated rapid depletion of natural resources. When studying the cost of land degradation, it is not possible to ignore the role of urbanization. In particular, a major cause of deforestation is conversion to urban land. The paper reviews the principles of current remote sensing techniques considered particularly suitable for monitoring Kayisdagi Mountain and its surrounding land cover changes and their effects on physical geography conditions. In addition, this paper addresses the problem of how spatially explicit information about degradation processes in the study area rangelands can be derived from different time series of satellite data. The monitoring approach comprises the time period between 1990 and 2005. Satellite remote sensing techniques have proven to be cost effective in widespread land cover changes. Physical geography and particularly natural geomorphologic processes like erosion, mass movement, physical weathering, and chemical weathering features etc. have faced significant unnatural variation.     

Barriers to the use of remote sensing in providing environmental information

Remote sensing from aircraft and earth-observing satellites is an essential source of environmental information and, at regional and global scales, remote sensing from satellites is often the only way in which some information can be collected. Naturally there are technical limitations, such as low resolution and the inability of optical sensors to see through clouds that restrict the use of satellite data, but technology is moving rapidly and major advances can be expected during the current decade, especially from radar satellites.The main barriers to the use of environmental information provided by remote sensing are not technological, but include cost and a need for training and transfer of technology, and a requirement for users to depart from traditional methods where new technology offers distinct advantages. Perhaps the most important contributions that users of remote sensing data can make to breaking down the barriers to the use of environmental data is to provide very clear statements of their information requirements so that technology can develop to meet these requirements.     

Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing

The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems.