Multiscale Indicators of Land Degradation in the Patagonian Monte,Argentina

Depletion of vegetation by overgrazing in arid environments has long-lasting effects on the environmental quality over extended geographic areas. An adequate inspection of habitat changes requires scaled up procedures that would allow assessing end-points of environmental status in broad areas that would be based on processes occurring at the plant canopy level. Our purpose was to find indicators of land degradation–conservation status for use in land monitoring programs and in planning management practices that would be amenable to further up-scaling for use with remotely sensed imagery. In several sites of the Patagonian Monte differing in the impact of grazing management, we evaluated vegetation attributes at three spatial scales. At the population scale, we found that the severity of grazing impact was characterized by the reduction of the palatable grass, P. ligularis, outside and inside shrub canopies. At the vegetation patch scale, we found that land degradation by domestic herbivore impact was characterized by changes in attributes of patch shape (radius, height, internal canopy cover) and patch abundance. At the plant community scale, we found that the structure of the plant canopy as described using Fourier analysis of cover data changed after long-term grazing impact consistently with the modifications in plant population and patch structures. We present a conceptual multiscale scenario of structural changes triggered by domestic herbivore impact, and quantitative indicators of plant structure and processes useful to develop management strategies of the Patagonian-Monte that would conserve its natural habitats. The developed end-points are also amenable for use in land conservation assessment through remotely sensed imagery.     

A multi-scale remote sensing approach for monitoring northern peatland hydrology: present possibilities and future challenges

Remote sensing has the potential to provide quantitative spatially explicit hydrological information across northern peatland complexes. This paper details a multi-scale remote sensing approach for assessing the use of Sphagnum mosses as proxy indicators of near-surface hydrology. Several spectral indices developed from the near infra-red (NIR) and shortwave infra-red (SWIR) liquid water absorption bands, as well as a biophysical index can be correlated with measures of near-surface moisture in the laboratory, in the field and from airborne imagery. Data from all platforms revealed similar patterns in the spectral indices in relation to changes in moisture although the strength of correlations was reduced as the spatial scale increased. The rapid collection of temporally and spatially explicit hydrological data means that the technique has potential practical application for environmental managers and peatland scientists at the local scale. The task of up-scaling the technique for use in operational peatland hydrological monitoring to the global scale is challenging but achievable, and requires further investigation into the heterogeneity of near-surface moisture across Sphagnum patches and the application of novel image processing techniques to improve the spatial resolution of currently available satellite imagery.     

Classifying environmentally significant urban land uses with satellite imagery

We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.     

SATELLITE DETECTION OF SEICHES IN GREAT SALT LAKE,UTAH1

ABSTRACT: On June 15, 1977, an unusual brightness anomaly was detected in the north arm of Great Salt Lake, Utah, on NOAA-5 Very High Resolution Radiometer (VHRR) visible band imagery and on Landsat-2 multispectral visual band imagery. Retrospective inspection of NOAA-3, 4, and 5 satellite imagery from 1974–77 revealed 12 previous cases of the anomaly, whereas post monitoring documented nine other cases through May 1978. Comparison of lake levels in the north arm with meteorological parameters leads to the conclusion that the anomalous brightness is associated with wind induced seiches in the north arm. Apparently the wind induces a lower water depth, turbulence, and mixing throughout the water column in the western third of the north arm, thus increasing the brightness of the surface waters chiefly from sediment resuspension.     

Remotely Sensed Data for Ecosystem Analyses: Combining Hierarchy Theory and Scene Models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost–benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.     

Comparing the Use of Indigenous Knowledge with Classification and Ordination Techniques for Assessing the Species Composition and Structure of Vegetation in a Tropical Forest

dentification of groups that are similar in their floristic composition and structure (habitat types) is essential for conservation and forest managers to allocate high priority areas and to designate areas for reserves, refuges, and other protected areas. In this study, the use of indigenous knowledge for the identification of habitat types in the field was compared against an ecological characterization of habitat types, including their species composition obtained by using classification and ordination techniques for a tropical landscape mosaic in a rural Mayan area of Quintana Roo, Mexico. Plant diversity data calculated from 141 sampled sites chosen randomly on a vegetation class’s thematic map obtained by multispectral satellite image classification were used for this propose. Results indicated high similarity in the categorization of vegetation types between the Mayan classification and those obtained by cluster and detrended correspondence analysis. This suggests that indigenous knowledge has a practical use and can be comparable to that obtained by using science-based methods. Finally, identification and mapping of vegetation classes (habitat types) using satellite image classification allowed us to discriminate significantly different species compositions, in such a way that they can provide a useful mechanism for interpolating diversity values over the entire landscape.     

Management Relevance of Benthic Biogeography at Multiple Scales in Coastal Waters of the Northeast U.S.

Continuing pressures from human activities have harmed the health of ocean ecosystems, particularly those near the coast. Current management practices that operate on one sector at a time have not resulted in healthy oceans that can sustainably provide the ecosystem services humans want and need. Now, adoption of ecosystem-based management (EBM) and coastal and marine spatial planning (CMSP) as foundational principles for ocean management in the United States should result in a more holistic approach. Recent marine biogeographical studies and benthic habitat mapping using satellite imagery, large-scale monitoring programs, ocean observation systems, acoustic and video techniques, landscape ecology, geographic information systems, integrated databases, and ecological modeling provide information that can support EBM, make CMSP ecologically meaningful, and contribute to planning for marine biodiversity conservation. Examples from coastal waters along the northeast coast of the United States from Delaware Bay to Passamaquoddy Bay, Maine, illustrate how benthic biogeography and bottom seascape diversity information is a useful lens through which to view EBM and CMSP in nearshore waters. The focus is on benthic communities, which are widely used in monitoring programs and are sensitive to many stresses from human activities.     

Monitoring Contrasting Land Management in the Savanna Landscapes of Northern Australia

We compared measures of ecosystem state across six adjacent land-tenure groups in the intact tropical savanna landscapes of northern Australia. Tenure groups include two managed by Aboriginal owners, two national parks, a cluster of pastoral leases, and a military training area. This information is of relevance to the debate about the role of indigenous lands in the Australian conservation estate. The timing and frequency of fire was determined by satellite imagery; the biomass and composition of the herb-layer and the abundance of large feral herbivores by field surveys; and weediness by analysis of a Herbarium database. European tenures varied greatly in fire frequencies but were consistently burnt earlier in the dry season than the two Aboriginal tenures, the latter having intermediate fire frequencies. Weeds were more frequent in the European tenures, whilst feral animals were most abundant in the Aboriginal tenures. This variation strongly implies a signature of current management and/or recent environmental history. We identify indices suitable for monitoring of management outcomes in an extensive and sparsely populated landscape. Aboriginal land offers a unique opportunity for the conservation of biodiversity through the maintenance of traditional fire regimes. However, without financial support, traditional practices may prove unsustainable both economically and because exotic weeds and feral animals will alter fire regimes. An additional return on investment in Aboriginal land management is likely to be improved livelihoods and health outcomes for these disadvantaged communities.     

Soil erosion and non-point source pollution impacts assessment with the aid of multi-temporal remote sensing images

Soil erosion associated with non-point source pollution is viewed as a process of land degradation in many terrestrial environments. Careful monitoring and assessment of land use variations with different temporal and spatial scales would reveal a fluctuating interface, punctuated by changes in rainfall and runoff, movement of people, perturbation from environmental disasters, and shifts in agricultural activities and cropping patterns. The use of multi-temporal remote sensing images in support of environmental modeling analysis in a geographic information system (GIS) environment leading to identification of a variety of long-term interactions between land, resources, and the built environment has been a highly promising approach in recent years. This paper started with a series of supervised land use classifications, using SPOT satellite imagery as a means, in the Kao-Ping River Basin, South Taiwan. Then, it was designed to differentiate the variations of eight land use patterns in the past decade, including orchard, farmland, sugarcane field, forest, grassland, barren, community, and water body. Final accuracy was confirmed based on interpretation of available aerial photographs and global positioning system (GPS) measurements. Finally, a numerical simulation model (General Watershed Loading Function, GWLF) was used to relate soil erosion to non-point source pollution impacts in the coupled land and river water systems. Research findings indicate that while the decadal increase in orchards poses a significant threat to water quality, the continual decrease in forested land exhibits a potential impact on water quality management. Non-point source pollution, contributing to part of the downstream water quality deterioration of the Kao-Ping River system in the last decade, has resulted in an irreversible impact on land integrity from a long-term perspective.     

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.     

Monitoring the effect of restoration measures in Indonesian peatlands by radar satellite imagery

In the context of the ongoing climate change discussions the importance of peatlands as carbon stores is increasingly recognised in the public. Drainage, deforestation and peat fires are the main reasons for the release of huge amounts of carbon from peatlands. Successful restoration of degraded tropical peatlands is of high interest due to their huge carbon store and sequestration potential. The blocking of drainage canals by dam building has become one of the most important measures to restore the hydrology and the ecological function of the peat domes. This study investigates the capability of using multitemporal radar remote sensing imagery for monitoring the hydrological effects of these measures. The study area is the former Mega Rice Project area in Central Kalimantan, Indonesia, where peat drainage and forest degradation is especially intense. Restoration measures started in July 2004 by building 30 large dams until June 2008. We applied change detection analysis with more than 80 ENVISAT ASAR and ALOS PALSAR images, acquired between 2004 and 2009. Radar signal increases of up to 1.36 dB show that high frequency multitemporal radar satellite imagery can be used to detect an increase in peat soil moisture after dam construction, especially in deforested areas with a high density of dams. Furthermore, a strong correlation between cross-polarised radar backscatter coefficients and groundwater levels above -50 cm was found. Monitoring peatland rewetting and quantifying groundwater level variations is important information for vegetation re-establishment, fire hazard warning and making carbon emission mitigation tradable under the voluntary carbon market or REDD (Reducing Emissions from Deforestation and Degradation) mechanism.     

Remote Sensing of Landscape-Level Coastal Environmental Indicators

Advances in technology and decreases in cost are making remote sensing (RS) and geographic information systems (GIS) practical and attractive for use in coastal resource management. They are also allowing researchers and managers to take a broader view of ecological patterns and processes. Landscape-level environmental indicators that can be detected by Landsat Thematic Mapper (TM) and other remote sensors are available to provide quantitative estimates of coastal and estuarine habitat conditions and trends. Such indicators include watershed land cover, riparian buffers, shoreline and wetland changes, among others. With the launch of Landsat 7, the cost of TM imagery has dropped by nearly a factor of 10, decreasing the cost of monitoring large coastal areas and estuaries. New satellites, carrying sensors with much finer spatial (1-5 m) and spectral (200 narrow bands) resolutions are being launched, providing a capability to more accurately detect changes in coastal habitat and wetland health. Advances in the application of GIS help incorporate ancillary data layers to improve the accuracy of satellite land-cover classification. When these techniques for generating, organizing, storing, and analyzing spatial information are combined with mathematical models, coastal planners and managers have a means for assessing the impacts of alternative management practices.     

FLOOD INUNDATION IN THE SOUTHEASTERN UNITED STATES FROM AIRCRAFT AND SATELLITE IMAGERY1

ABSTRACT: Panchromatic black and white, color, and color infrared photographs and thermal infrared imagery are compared for a capability to show flood boundaries. In open agricultural and urban areas, these boundaries are easily delineated on all types of am. Boundaries are more difficult to see in wooded areas. In March, hardwood trees are dormant, but black and white photographs and color photographs show only the tops of these trees. Color infrared photographs in January and March have a distinctive color or tone in inundated woods; the limit of this tone is the flood boundary. Daytime thermal infrared imagery in March shows that inundated woods are cooler than dry land but warmer than open water. After about April 1, both color infrared photography and thermal infrared imagery show only the top of the tree canopy and do not reflect underlying flood water. Inundated areas can be delineated easily on ERTS satellite imagery from December through March. On imagery from May 4–5, 1973, however, most inundation boundaries had to be drawn as dashed lines; the tree canopy obscures flood waters in wooded areas. Despite this problem, the results of mapping flood boundaries on May imagery are believed to be reasonable for the scale of the imagery.     

Visual interpretation of satellite imagery for monitoring floods in Bangladesh

This article presents the methods and results of visual interpretation of NOAA AVHRR imagery for mapping flood areas in Bangladesh. Color composites of channels 1 and 2 for 18 August 1987 and 10, 15, and 24 September 1988 were interpreted visually for delineating flood boundaries. On such imagery flood areas appear in dark tones and are separated from land (light tones) owing to the absorption of near infrared by water and its reflectance by land and non-waterbodies. Visual interpretation was aided by the use of ground information, such as physiographic and river maps, previous flood maps, newspaper reports, and other published and unpublished documents on the 1987 and 1988 floods. Interpreted flood areas on selected images ranged from 31% to 43% of the total area of Bangladesh. Visual interpretation overestimated flood areas by 5%–10%, compared to the digitally analyzed data. The main advantage of visual analysis lies in the cost effectiveness of AVHRR photographic products, which make them more accessible than the digital image analysis of computer-compatible tapes.     

EXTRACTION AND UTILIZATION OF SPACE ACQUIRED PHYSIOGRAPHIC DATA FOR WATER RESOURCES DEVELOPMENT1

ABSTRACT: ERTS-1 satellite imagery has been evaluated as a means of providing useful watershed physiography information. From these data physiographic parameters such as drainage basin area and shape, drainage density, stream length and sinuosity, and the percentage of a watershed occupied by major land use types were obtained in three study areas. The study areas were: (1) Southwestern Wisconsin; (2) Eastern Colorado; and (3) portions of the Middle Atlantic States Using ERTS-1 imagery at 1:250,000 and 1:100,000 scales it was found that drainage basin area and shape and stream sinuosity were comparable (within 10%) in all study areas to physiographic measurements derived from conventional topographic maps at the same scales Land use information can be usefully extracted for watersheds as small as 30 mi²(78 km²) in area. Improved drainage network and density information is obtained from ERTS-1 imagery in dissected areas such as Southwestern Wisconsin, but in heavily vegetated areas (Middle Atlantic States) or areas with little physical relief (Eastern Colorado) low order streams are difficult to detect and the derived drainage densities are significantly smaller than those obtained from standard maps. It is concluded that ERTS-1 imagery can be employed to advantage in mean annual runoff prediction techniques and in providing or maintaining land use information used in the calibration and operation of watershed models.     

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。     

USE OF HEMISPHERIC IMAGERY FOR ESTIMATING STREAM SOLAR EXPOSURE1

ABSTRACT: Solar exposure profoundly affects stream processes and species composition. Despite this, prominent stream monitoring protocols focus on canopy closure (obstruction of the sky as a whole) rather than on measures of solar exposure or shading. We identify a candidate set of solar exposure metrics that can be derived from hemispheric images. These metrics enable a more mechanistic evaluation of solar exposure than can be achieved with canopy closure metrics. Data collected from 31 stream reaches in eastern Oregon enable us to quantify and compare metrics of solar exposure from hemispheric images and a metric of canopy closure with a concave densiometer. Repeatability of hemispheric metrics is generally as good as or better than the densiometer closure metric, and variation in the analysis of hemispheric images attributable to differences between analysts is negligibly small. Metrics from the hemispheric images and the densiometer are typically strongly correlated, at the scale of an individual observation and for 150 m stream reaches, but not always in a linear fashion. We quantify the character of the uncertainty in the relationship between the densiometer and the hemispheric metrics. Hemispheric imagery produces repeatable metrics representing an important ecological attribute; thus those researching the effects of solar exposure on stream ecosystems should consider the use of hemispheric imagery.     

基于GIS油田环境监测信息管理系统的研究和应用

以大庆油田为例,通过在区域环境安全信息管理与建筑物环境安全信息管理系统中采用环境地理信息系统(EGIS),构建大庆油田环境地理信息系统(DOFESIMS),并阐述了其技术结构、数学模型、功能及功能扩展,为区域环境安全信息管理的规划与实现提供科学依据。在实现对油田环境有效管理的基础上,对大庆油田污染物排放进行了预测与分析,并将结果进行空间可视化展示,以此证明环境地理信息系统可有效解决区域环境安全的信息管理。     

Tropical Timber Rush in Peruvian Amazonia: Spatial Allocation of Forest Concessions in an Uninventoried Frontier

Land-use allocation has important implications for the conservation and management of tropical forests. Peru’s forestry regime has recently been reformed and more than 7 million ha has been assigned as forest concessions. This potentially has a drastic impact on the land-use practices and species composition of the assigned areas. Nevertheless, the environmental variation found within the concessions and the process applied to delimit them are poorly studied and documented. Thus, it is difficult to estimate the biological impacts of forestry activities in concessions or plan them sustainably. This paper reveals the characteristics of the current concession allocation in Loreto, Peruvian Amazonia, using environmental and access-related variables and compares the concessions to other major land-use assignments. The work draws on a number of data sets describing land-use, ecosystem diversity, and fluvial network in the region. According to our data, certain environment types such as relatively fertile Pebas soils are overrepresented in the concessions, while others, like floodplain forests, are underrepresented in comparison to other land-use assignments. Concessions also have less anthropogenic disturbance than other areas. Furthermore, concessions are located on average further from the river network than the other land-use assignments studied. We claim that forest classification based on productivity, soil fertility, accessibility, and biodiversity patterns is an achievable long-term goal for forest authorities in Peru, and in many other tropical countries. We present a rough design of a geographic information system incorporating environmental, logging, and access-related data that could be applied to approach this goal in Peru.