An introduction to digital methods in remote sensing of forested ecosystems: Focus on the Pacific Northwest,USA

Aerial photography has been routinely used for several decades by natural resource scientists and managers to map and monitor the condition of forested landscapes. Recently, along with the emergence of concepts in managing forests as ecosystems, has come a significant shift in emphasis from smaller to larger spatial scales and the widespread use of geographic information systems. These developments have precipitated an increasing need for vegetation information derived from other remote sensing imagery, especially digital data acquired from high-elevation aircraft and satellite platforms. This paper introduces fundamental concepts in digital remote sensing and describes numerous applications of the technology. The intent is to provide a balanced, nontechnical view, discussing the shortcomings, successes, and future potential for digital remote sensing of forested ecosystems.     

Propagation of uncertainties in soil and pesticide properties to pesticide leaching

In the new Dutch decision tree for the evaluation of pesticide leaching to groundwater, spatially distributed soil data are used by the GeoPEARL model to calculate the 90th percentile of the spatial cumulative distribution function of the leaching concentration in the area of potential usage (SP90). Until now it was not known to what extent uncertainties in soil and pesticide properties propagate to spatially aggregated parameters like the SP90. A study was performed to quantify the uncertainties in soil and pesticide properties and to analyze their contribution to the uncertainty in SP90. First, uncertainties in the soil and pesticide properties were quantified. Next, a regular grid sample of points covering the whole of the agricultural area in the Netherlands was randomly selected. At the grid nodes, realizations from the probability distributions of the uncertain inputs were generated and used as input to a Monte Carlo uncertainty propagation analysis. The analysis showed that the uncertainty concerning the SP90 is 10 times smaller than the uncertainty about the leaching concentration at individual point locations. The parameters that contribute most to the uncertainty about the SP90 are, however, the same as the parameters that contribute most to uncertainty about the leaching concentration at individual point locations (e.g., the transformation half-life in soil and the coefficient of sorption on organic matter). Taking uncertainties in soil and pesticide properties into account further leads to a systematic increase of the predicted SP90. The important implication for pesticide regulation is that the leaching concentration is systematically underestimated when these uncertainties are ignored.     

Combination of multispectral remote sensing, variable rate technology and environmental modeling for citrus pest management

The Lower Rio Grande Valley (LRGV) of south Texas is an agriculturally rich area supporting intensive production of vegetables, fruits, grain sorghum, and cotton. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yields. Intensive agricultural activities in past decades might have caused potential contamination of soil, surface water, and groundwater due to leaching of pesticides in the vadose zone. In an effort to promote precision farming in citrus production, this paper aims at developing an airborne multispectral technique for identifying tree health problems in a citrus grove that can be combined with variable rate technology (VRT) for required pesticide application and environmental modeling for assessment of pollution prevention. An unsupervised linear unmixing method was applied to classify the image for the grove and quantify the symptom severity for appropriate infection control. The PRZM-3 model was used to estimate environmental impacts that contribute to nonpoint source pollution with and without the use of multispectral remote sensing and VRT. Research findings using site-specific environmental assessment clearly indicate that combination of remote sensing and VRT may result in benefit to the environment by reducing the nonpoint source pollution by 92.15%. Overall, this study demonstrates the potential of precision farming for citrus production in the nexus of industrial ecology and agricultural sustainability.     

ASSESSMENT OF REMOTE SENSING INPUT TO HYDROLOGIC MODELS1

Remotely sensed variables such as land cover type and snow-cover extent can currently be used directly and effectively in a few specific hydrologic models. Regression models can also be developed using physiographic and snow-cover data to permit estimation of discharge characteristics over extended periods such as a season or year. Most models, however, are not of an appropriate design to readily accept as input the various types of remote sensing parameters that can be obtained now or in the future. Because this new technology has the potential for producing hydrologic data that has significant information content on an areal basis, both inexpensively and repetitively, effort should be devoted now to either modifying existing models or developing new models that can use these data. Minor modifications would at least allow the remote sensing data to be used in an ancillary way to update the model state variables, whereas major structural modifications or new models would permit direct input of the data through remote sensing compatible algorithms. Although current remote sensing inputs to hydrologic models employ only visible and near infrared data, model modification or development should accommodate microwave and thermal infrared data that will be more widely available in the future.     

QuickBird影像融合最佳波段选择及不同融合方法质量评价研究

分析了QuickBird多光谱遥感影像各个波段的光谱特征,并进行了定量评价。根据信息量的大小和波段相关性得到最佳波段组合,在最佳组合波段下利用遥感影像处理软件ERDAS9.2选择或利用建模模块建立不同的影像融合模型对QuikBird多光谱数据与全色遥感影像进行融合,按照定性及定量指标对融合前后的遥感影像进行色彩、分辨率及信息量评价,得到QuikBird影像数据最佳融合方法。     

SATELLITE REMOTE SENSING OF NATURAL RESOURCES: SOME ISSUES TO BE RESOLVED

Satellite remote sensing has emerged as a tool which is highly appropriate to the development process. Its applications already are numerous, ranging from the monitoring of catastrophic or geophysical phenomena at the global scale to the delineation of local mineral resources. The author reviews the conditions under which these applications are taking place and outlines the major issues and problems which will have to be resolved if the maximum benefit is to be derived from satellite remote sensing. He also examines the current and future role of an international infrastructure within which the debate on management may be continued and the specific applications be made more effective.     

Remote sensing for land management and planning

The primary role of remote sensing in land management and planning has been to provide information concerning the physical characteristics of the land which influence the management of individual land parcels or the allocation of lands to various uses These physical characteristics have typically been assessed through aerial photography, which is used to develop resource maps and to monitor changing environmental conditions These uses are well developed and currently well integrated into the planning infrastructure at local, state, and federal levels in the United States.Many newly emerging uses of remote sensing involve digital images which are collected, stored, and processed automatically by electromechanical scanning devices and electronic computers Some scanning devices operate from aircraft or spacecraft to scan ground scenes directly; others scan conventional aerial transparencies to yield digital images. Digital imagery offers the potential for computer-based automated map production, a process that can significantly increase the amount and timeliness of information available to land managers and planners.Future uses of remote sensing in land planning and management will involve geographic information systems, which store resource information in a geocoded format. Geographic information systems allow the automated integration of disparate types of resource data through various types of spatial models so that with accompanying sample ground data, information in the form of thematic maps and/ or aerially aggregated statistics can be produced Key issues confronting the development and integration of geographic information systems into planning pathways are restoration and rectification of digital images, automated techniques for combining both quantitative and qualitative types of data in information-extracting procedures, and the compatibility of alternative data storage modes     

SELECTING RECONNAISSANCE STRATEGIES FOR FLOODPLAIN SURVEYS1

ABSTRACT: Multispectral aircraft and satellite data over the West Branch of the Susquehanna River were analyzed to evaluate potential contributions of remote sensing to floodplain surveys. Multispectral digital classifications of land cover features indicative of floodplain areas were used by interpreters to locate various floodprone area boundaries. The boundaries thus obtained were found to be more striking and continuous in the Landsat data than in the low altitude aircraft data. The digital approach permitted satellite results to be displayed at 1:24,000 scale and aircraft results at even larger scales. Results indicate that remote sensing techniques can delineate floodprone areas more easily in agricultural and limited development areas than in areas covered by a heavy forest canopy. At this time it appears that the remote sensing data would be best used as a form of preliminary planning information or as an internal check on previous or ongoing floodplain studies. In addition, the remote sensing techniques can assist in effectively monitoring floodplain activities after a community enters into the National Flood Insurance Program.     

REMOTE SENSING OF RIPARIAN BUFFERS: PAST PROGRESS AND FUTURE PROSPECTS1

Riparian buffer zone management is an area of increasing relevance as human modification of the landscape continues unabated. Land and water resource managers are continually challenged to maintain stream ecosystem integrity and water quality in the context of rapidly changing land use, which often offsets management gains. Approaches are needed not only to map vegetation cover in riparian zones, but also to monitor the changes taking place, target restoration activities, and assess the success of previous management actions. To date, these objectives have been difficult to meet using traditional techniques based on aerial photos and field visits, particularly over large areas. Recent advances in remote sensing have the potential to substantially aid buffer zone management. Very high resolution imagery is now available that allows detailed mapping and monitoring of buffer zone vegetation and provides a basis for consistent assessments using moderately high resolution remote sensing (e.g., Landsat). Laser‐based remote sensing is another advance that permits even more detailed information on buffer zone properties, such as refined topographic derivatives and multidimensional vegetation structure. These sources of image data and map information are reviewed in this paper, examples of their application to riparian buffer mapping and stream health assessment are provided, and future prospects for improved buffer monitoring are discussed.     

浅谈水质在线监控中遥感技术的应用

空间信息技术以及计算机技术的发展，给环境监控提供了先进、快速和科学的方法。其中，遥感技术由于能够快速、宏观地获得所监控区域的数据，近年来已逐渐成为环境监控系统中的重要技术手段。遥感信息是被控区域的电磁辐射能量及其结构特征与时空状态在遥感图像上的表现。今后，遥感技术、在线监控系统和地理信息系统等多种信息处理工具的结合将是环境信息监控系统发展的主要方向。     

遥感技术在灾害监测中的应用

介绍总结了近年来遥感技术在灾害监测中的应用与进展，以若干应用实例阐明了遥感技术在实现对自然灾害进行宏观、实时、动态、连续监测中不可替代的作用；在对我国灾害遥感的应用现状进行了分析之后，发现灾前预测工作有所不足；指出遥感技术将进一步同地理信息系统技术和全球定位系统技术相结合，在防灾减灾工作中发挥愈来愈重要的作用。     

Surveying and mapping of natural resources by remote sensing

Sustainable economic development requires detailed knowledge of the natural resources of any nation. Acquiring the needed information by conventional means may require a large investment in time, personnel, and therefore, in cost. A viable alternative is space-age technology which provides the necessary tools to conduct surveys of natural resources in a timely manner. Such technologies can obtain the required data by means of digital sensors, radar imaging systems and stereo cameras. These data can be utilized to map structures that may contain oil and gas deposits, recognize high concentrations of economic minerals, and discover regions with fertile soils and good potential for groundwater. Those applications warrant greater use of remote sensing methods and techniques by the international scientific community, particularly for the development of natural resources in the Third World. This paper represents a general review of the available, and easily interpretable, space-borne data that are useful in the mapping of natural resources.     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.     

Monitoring Forest Carbon Sequestration with Remote Sensing and Carbon Cycle Modeling

Sources and sinks of carbon associated with forests depend strongly on the management regime and spatial patterns in potential productivity. Satellite remote sensing can provide spatially explicit information on land cover, stand-age class, and harvesting. Carbon-cycle process models coupled to regional climate databases can provide information on potential rates of production and related rates of decomposition. The integration of remote sensing and modeling thus produces spatially explicit information on carbon storage and flux. This integrated approach was employed to compare carbon flux for the period 1992–1997 over two 165-km² areas in western Oregon. The Coast Range study area was predominately private land managed for timber production, whereas the West Cascades study area was predominantly public land that was less productive but experienced little harvesting in the 1990s. In the Coast Range area, 17% of the land base was harvested between 1991 and 2000. Much of the area was in relatively young, productive-age classes that simulations indicate are a carbon sink. Mean annual harvest removals from the Coast Range were greater than mean annual net ecosystem production. On the West Cascades study area, a relatively small proportion (< 1%) of the land was harvested and the area as a whole was accumulating carbon. The spatially and temporally explicit nature of this approach permits identification of mechanisms underlying land base carbon flux. Published online     

高分辨率遥感影像在城市绿地信息提取中的应用研究

高分辨率卫星遥感图像数据量大、空间分辨率高、结构信息复杂、地物同物异谱现象更为突出等特征给专题信息提取技术带来了新的挑战。基于植被的光谱特征,利用监督分类、植被指数分类和目视解译等方法对QuickBird高分辨率卫星遥感影像的绿地信息进行提取,并对分类精度作了比对分析。研究结果表明,监督分类方法不能得到令人满意的结果,运用植被指数分类方法则有明显改善,其中归一化植被指数(NDVI)精度最高,因此NDVI能有效地对植被进行分类与识别。     

基于信息量的ALI影像最佳波段选择及融合研究

分析了EO-1 ALI多光谱遥感影像各个波段的信息特征,根据信息量大小和波段间的相关性,联合偏度—峰度指数JSKF,提出针对ALI图像新的最佳波段组合方法。在最佳波段组合下对ALI多光谱数据与全色数据分别进行IHS、HPF、PCA和Wavelet变换融合,从信息量角度出发,按照定量指标对融合前后的遥感影像进行评价,并对融合前后影像进行分类应用。     

A geostatistical and probabilistic spectral image processing methodology for monitoring potential CO2 leakages on the surface

Remote sensing has demonstrated success in various environmental applications over the past three decades. This is largely attributed to its ability for good areal coverage and continued development in sensor technologies. Carbon dioxide Capture and Storage (CCS) is an emerging climate change mitigation technology where monitoring is vital for its sustainability. This research investigates the use of spectral remote sensing imagery in detecting potential CO₂ occurrences at the surface, should a leakage occur from subsurface reservoirs where CO₂ is stored. Currently, there are no known leakages of CO₂ at industrial storage sites, therefore, this research was carried out at the Latera natural analogue site in Italy, in order to develop the methodology described. This paper describes the use of a popular probabilistic information fusion theory, referred to as the Dempster–Shafer theory of evidence, to analyse outlier pixels (anomalies). Outlier pixels are first determined using a new geostatistical image filtering methodology based on Intrinsic Random Function (IRF), Independent Component Analysis (ICA), and the industry standard parametric Reed–Xiaoli (RX) anomaly detection. Information fusion of detected outlier pixels and indirect surface effects of CO₂ leakage over time, such as stressed vegetation or mineral alterations, assigns a confidence measure per outlier pixel in order to identify potential leakage points. After visual validation using direct field measurements, it was demonstrated that the proposed methodology is able to detect majority of the seepage points at Latera, and holds promise as a new unsupervised CO₂ monitoring methodology.     

Emergence of Indigenous Vegetation Classifications Through Integration of Traditional Ecological Knowledge and Remote Sensing Analyses

Traditional ecological knowledge (TEK) can play an important role in the understanding of ecological systems. Although TEK has complemented scientific and managerial programs in a variety of contexts, its formal incorporation into remote sensing exercises has to date been limited. Here, we show that the vegetation classifications of the Ache, an indigenous hunter-gatherer tribe of the Mbaracayu Forest Reserve in Paraguay, are reflected in a supervised classification of satellite imagery of the reserve. Accuracy of classification was toward the low end of the range of published values, but was reasonable given the difficult nature of separating forest classes from satellite images. Comparison of the resultant map with a more traditionally elaborated vegetation map highlights differences between the two approaches and the gain in information obtained by considering TEK classifications. We suggest that integration of TEK and remote sensing may provide alternative insights into the ecology of vegetation communities and land cover, particularly in remote and densely forested areas where ecological field research is often limited by roads and/or trail systems.     

Modeling Protected Species Habitat and Assigning Risk to Inform Regulatory Decisions

In the United States, environmental regulatory agencies are required to use “best available” scientific information when making decisions on a variety of issues. However, agencies are often hindered by coarse or incomplete data, particularly as it pertains to threatened and endangered species protection. Stakeholders often agree that more resolute and integrated processes for decision-making are desirable. We demonstrate a process that uses species occurrence data for a federally endangered insect (Karner blue butterfly), a readily available habitat modeling tool, and spatially explicit information about an important Michigan commodity (tart cherries). This case study has characteristics of many protected species regulatory decisions in that species occurrence data were sparse and unequally distributed; regulatory decisions (on pesticide use) were required with potentially significant impacts on a viable agricultural industry; and stakeholder relations were diverse, misinformed, and, in some situations, unjustly contentious. Results from our process include a large-scale, empirically derived habitat suitability map for the focal species and a risk ranking of tart cherry orchards with risk based on the likelihood that pesticide applications will influence the focal protected species. Although the majority (77%) of pesticide-influence zones overlapped Karner blue butterfly habitat, risk scores associated with each orchard were low. Through our process we demonstrated that spatially explicit models can help stakeholders visualize and quantify potential protected species effects. In addition, model outputs can serve to guide field activities (e.g., species surveys and implementation of pesticide buffer zones) that help minimize future effects.     

Geomorphological and geophysical approach for locating favorable groundwater zones in granitic terrain, Andhra Pradesh, India

The increasing demand for fresh water has necessitated the exploration for new sources of groundwater, particularly in hard rock terrain, where groundwater is a vital source of fresh water. A fast, cost effective and economical way of exploration is to study and analyze remote sensing data. Interpreted remote sensing data was used to select sites for carrying out surface geophysical investigations. Various geomorphologic units were demarcated and the lineaments were identified by interpretation of remote sensing satellite images. The potential for occurrence of groundwater in the watershed areas was classified as very good, good, moderate and poor by interpreting the images. Sub-surface geophysical investigations, namely vertical electrical soundings, were carried out to delineate potential water-bearing zones. Integrated studies of interpretation of geomorphologic and geophysical data were used to prepare a groundwater potential map. The studies reveal that the groundwater potential of shallow aquifers is due to geomorphologic features and the potential of deeper aquifers is determined by lineaments such as faults and joints.