Remote Sensing and GIS Technologies as Tools to Support Sustainable Management of Areas Devastated by Landslides

IKONOS panchromatic images from a single year were used to characterise the effects of an extreme rainstorm event on six mountain catchment areas in Venezuela. Image registrations were accomplished using topographic base maps at 1 : 5000 scale giving a mapping accuracy between 37 and 40 m. It was used an 8-bit channel for correction, rectification, filteration and tone enhancements.Landsliding was discerned in the affected watersheds using morphometric criteria, including the shape of the slope failure and its position, exposure bedrock in the scar and deposition of debris down-slope. This study is restricted to the impact analysis of the distribution of landslide erosion scars and the depositional processes on the valley floor. Remote sensing data were combined into a geographic information system (GIS) with planimetric data, contour lines, hydrology and vegetation types to evaluate the distribution of the scars and their effects on the highly populated areas located on the alluvial fans. Hillslope mass wasting induced mass movements, logging and increased the mud and silt in floodwaters affecting settlement down-slope.     

Applying Satellite Imagery to Triage Assessment of Ecosystem Health

Considerable evidence documents that certain changes in vegetation and soils result in irreversibly degraded rangeland ecosystems. We used Advanced Very High Resolution Radiometer (AVHRR) imagery to develop calibration patterns of change in the Normalized Difference Vegetation Index (NDVI) over the growing season for selected sites for which we had ground data and historical data characterizing these sites as irreversibly degraded. We used the NDVI curves for these training sites to classify and map the irreversibly degraded rangelands in southern New Mexico. We composited images into four year blocks: 1988–1991, 1989–1992, and 1990–1993. The overlap in pixels classified as irreversibly degraded ranged from 42.6% to 84.3% in year block comparisons. Quantitative data on vegetation composition and cover were collected at 13 sites within a small portion of the study area. Wide coverage reconnaissance of boundaries between vegetation types was also conducted for comparisons with year block maps. The year block 1988–1991 provided the most accurate delineation of degraded areas. The rangelands of southern New Mexico experienced above average precipitation from 1990–1993. The above average precipitation resulted in spatially variable productivity of ephemeral weedy plants on the training sites and degraded rangelands which resulted in much smaller areas classified as irreversibly degraded. We selected imagery for a single year, 1989, which was characterized by the absence of spring annual plant production in order to eliminate the confounding effect of reflectance from annual weeds. That image analysis classified more than 20% of the rangelands as irreversibly degraded because areas with shrub-grass mosaic were included in the degraded classification. The single year image included more than double the area classified as irreversibly degraded by the year blocks. AVHRR imagery can be used to make triage assessments of irreversibly degraded rangeland but such assessment requires understanding productivity patterns and variability across the landscapes of the region and careful selection of the years from which imagery is chosen.     

Mapping giant salvinia with satellite imagery and image analysis

QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands), normal color (blue, green and red bands), and four-band composite (blue, green, red, and near-infrared bands) images were studied. Unsupervised image analysis was used to classify the imagery. Accuracy assessments performed on the classification maps of the three composite images had producer’s and user’s accuracies for giant salvinia ranging from 87.8 to 93.5%. Color-infrared, normal color, and four-band satellite imagery were excellent for distinguishing giant salvinia in a complex field habitat.     

Distribution of Selected Soil and Water Conservation Practices in the U.S. as Identified with Google Earth

The proper representation of conservation practices on agricultural lands is an important factor in large‐scale assessments of water quality in the United States. Unfortunately, there are few publicly available data sources at the local level and even fewer at the national scale. In this research, randomly selected points within agricultural lands were examined for selected conservation practices using Google Earth aerial imagery by a team of interpreters. In total, 13,530 points had field boundaries digitized, and were subsequently examined and classified. The presence of terraces, grassed waterways, contour farming, center pivot irrigation, strip cropping, ponds, riparian vegetation, filter strips, and land cover were noted. Subjectivity among interpreters was evaluated using duplicate samples and was found to be similar to image misclassification rates in other research. Conservation practice adoption rates for selected major river basins compared favorably with data collected by the Conservation Effects Assessment Project. The frequency of occurrence of each conservation practice was summarized and presented by ecoregion. To facilitate future research, point level data and software source code developed in this research are available via the web at http://nlet.brc.tamus.edu/Conservation . Aerial imagery was found to be a powerful, inexpensive, and easily accessible tool to assess large‐scale conservation practice implementation for certain conservation practices.     

GIS支持的卫星图像土地利用现状分类和制图

应用卫星图像提取专题要素，综合利用多元地理信息，是克服多光谱数据在解像力和分辨率上所存在的局限性的有效途径。ＧＩＳ技术则提供多种处理功能将图像与地理信息复合，提高分类精度。分类图像数据与地形基础要素数据复合，通过彩色扫描绘图机直接绘制高质量的土地利用现状专题地图。     

OPERATIONAL APPLICATIONS OF SATELLITE SNOW COVER OBSERVATIONS1

ABSTRACT: Several federal and state water resources agencies and NASA have recently completed an Applications Systems Verification and Transfer (ASVT) project on the operational applications of satellite snow cover observations. When satellite snow cover data were tested in both empirical seasonal runoff estimation and short term modeling approaches, a definite potential for reducing forecast error was evident. Three years of testing in California resulted in reduction of seasonal stream flow forecast error was evident. Three years of testing in California resulted in reduction of seasonal stream flow forecast error from 15 percent to 10 percent on three study basins; and modeling studies on the Boise River basin in Idaho indicated that satellite snow cover could be used to reduce short term forecast error by up to 9.6 percent (5 day forecast). Potential benefits from improved satellite snow cover based predictions across the 11 western states total 10 million dollars for hydropower and 28 million dollars for irrigation annually. The truly operational application of the new technology in the West, however, will only be possible when the turnaround time for all data is reduced to 72 hours, and the water management agencies can be assured of a continuing supply of operational snow cover data from space.     

Examining Landscape Dynamics at a Watershed Scale Using Landsat TM Imagery for Detection of Wintering Hooded Crane Decline in Yashiro,Japan

It is usually inappropriate to define rectangular land areas or administrative units as the extent for quantifying landscapes that possess hierarchical structure. As a functional unit established by geophysical relationships, the watershed is one of many natural scales in the hierarchical landscape. We examined the dynamics of the Yashiro watershed of Japan at the landscape level using pattern metrics based on Landsat thematic mapper (TM) imagery from 1985 to 1998. This watershed provides important habitats for the hooded crane (Grus monachus), a vulnerable species. While its world population has remained stable, the number wintering at Yashiro has declined in recent years. Changes in landscape metrics reveal that the spatial pattern within the watershed underwent homogenization due to depopulation of local people and shifts in local energy requirements and forest management policy at Yashiro. Specific changes include: a decrease in bare land area from 6.2% to 1.0% of the landscape, increased forest cover from 69.2% to 76.1%, reduction in patch number from 1194 to 616 and enlarged mean patch size, and a decrease in total edge from 223,740 m to 158,040 m. The rate of change in landscape metrics indicates a rapid change towards homogeneity in the landscape since 1990. The temporal changes in hooded crane populations corresponded to the changes in landscape. An alternative explanation has been proposed that decline of the species is influenced by landscape dynamics affecting both habitat selection and food resources. Conservation at the watershed scale is suggested to be complementary to the current conservation measures of the species.     

The application of geographic information systems and global positioning systems in humanitarian emergencies: lessons learned,programme implications and future research

Geographic information systems (GIS), global positioning systems and remote sensing have been increasingly used in public health settings since the 1990s, but application of these methods in humanitarian emergencies has been less documented. Recent areas of application of GIS methods in humanitarian emergencies include hazard, vulnerability, and risk assessments; rapid assessment and survey methods; disease distribution and outbreak investigations; planning and implementation of health information systems; data and programme integration; and programme monitoring and evaluation. The main use of GIS in these areas is to provide maps for decision-making and advocacy, which allow overlaying types of information that may not normally be linked. GIS is also used to improve data collection in the field (for example, for rapid health assessments or mortality surveys). Development of GIS methods requires further research. Although GIS methods may save resources and reduce error, initial investment in equipment and capacity building may be substantial. Especially in humanitarian emergencies, equipment and methodologies must be practical and appropriate for field use. Add-on software to process GIS data needs to be developed and modified. As equipment becomes more user-friendly and costs decrease, GIS will become more of a routine tool for humanitarian aid organisations in humanitarian emergencies, and new and innovative uses will evolve.     

Spectrally Driven Classification of High Spatial Resolution,Hyperspectral Imagery: A Tool for Mapping In-Stream Habitat

Streams represent an essential component of functional ecosystems and serve as sensitive indicators of disturbance. Accurate mapping and monitoring of these features is therefore critical, and this study explored the potential to characterize aquatic habitat with remotely sensed data. High spatial resolution, hyperspectral imagery of the Lamar River, Wyoming, USA, was used to examine the relationship between spectrally defined classes and field-mapped habitats. Advantages of this approach included enhanced depiction of fine-scale heterogeneity and improved portrayal of gradational zones between adjacent features. Certain habitat types delineated in the field were strongly associated with specific image classes, but most included areas of diverse spectral character; spatially buffering the field map polygons strengthened this association. Canonical discriminant analysis (CDA) indicated that the ratio of the variability among groups to that within a group was an order of magnitude greater for spectrally defined image classes (20.84) than for field-mapped habitat types (1.82), suggesting that unsupervised image classification might more effectively categorize the fluvial environment. CDA results also suggested that shortwave-infrared wavelengths were valuable for distinguishing various in-stream habitats. Although hyperspectral stream classification seemed capable of identifying more features than previously recognized, the technique also suggested that the intrinsic complexity of the Lamar River would preclude its subdivision into a discrete number of classes. Establishing physically based linkages between observed spectral patterns and ecologically relevant channel characteristics will require additional research, but hyperspectral stream classification could provide novel insight into fluvial systems while emerging as a potentially powerful tool for resource management.     

Evaluation of a fire behavior information integration system for southern California chaparral wildlands

Close contact between arid, fire-vulnerable chaparral wildlands and urban development in southern California results in conflagrations that have burned 200,000 ha, destroyed 700 structures, and claimed 16 lives in a single year. In 1972, the U.S. Congress established FIRESCOPE to assist southern California fire and emergency agencies and to develop computer methods for the simulation of wildland fire behavior.