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1.
Landscape characterization gives an overall information on the status of Land Use and Land Cover(LULC),changes in its composition and the impact of natural and human influences operating at different spatial and temporal scales.This information can be used to monitor changes in natural forest resources and protected areas,delineate potential conservation areas and can serve in effective management of ecologically fragile landscapes.In the present study,geo-spatial tools were used to characterize the landscape of Sariska National Park and its surroundings.Satellite data was used to prepare LULC maps for 1989 and 2000,change detection analysis and computation of landscape metrics.Climatic data,field records and modeling tools were used to map the po-tential spread of two invasive species,Prosopis juliflora and Adhatoda vasica.The results show that the forest area increased from 1989 to 2000,indicating better management practices.Landscape metrics(PAFRAC,PLADJ and AI)also support this argument.Improvements in the degraded forest can further enhance this effect.The entire reserve however is suitable for the invasion of P.juliflora and A.vasica but is more pronounced in Boswellia serrata and Anogeissus pendula-Acacia catechu(open)forests.A detailed landscape characterization map can help forest managers to make important policy decisions concerning issues such as in-vasive species.  相似文献   

2.
The spatial distribution of different C3 and C4 grass species in tropical montane areas is commonly influenced by a number of factors that include site-specific topography. Hence, the distribution of these grasses across topographic gradients can vary significantly. In this study, we investigate the influence of topographic factors (elevation, slope and aspect) on the spatial distribution of Festuca grass species in a commonage area, comprising agro-biodiversity conservation land use. Integration of the topographic variables using GIS and binary logistic regression (LR) modelling showed that C3, Festuca grass species distribution can be predicted or mapped with an accuracy of 80% in the landscape under study. The study contributes to understanding the spatial distribution of C3 grass species and provides valuable information for designing and optimizing rangeland conservation in the subtropical montane landscapes.  相似文献   

3.
Spatial information of the dominant species of submerged aquatic vegetation (SAV) is essential for restoration projects in eutrophic lakes, especially eutrophic Taihu Lake, China. Mapping the distribution of SAV species is very challenging and difficult using only multispectral satellite remote sensing. In this study, we proposed an approach to map the distribution of seven dominant species of SAV in Taihu Lake. Our approach involved information on the life histories of the seven SAV species and eight distribution maps of SAV from February to October. The life history information of the dominant SAV species was summarized from the literature and field surveys. Eight distribution maps of the SAV were extracted from eight 30 m HJ-CCD images from February to October in 2013 based on the classification tree models, and the overall classification accuracies for the SAV were greater than 80%. Finally, the spatial distribution of the SAV species in Taihu in 2013 was mapped using multilayer erasing approach. Based on validation, the overall classification accuracy for the seven species was 68.4%, and kappa was 0.6306, which suggests that larger differences in life histories between species can produce higher identification accuracies. The classification results show that Potamogeton malaianus was the most widely distributed species in Taihu Lake, followed by Myriophyllum spicatum, Potamogeton maackianus, Potamogeton crispus, Elodea nuttallii, Ceratophyllum demersum and Vallisneria spiralis. The information is useful for planning shallow-water habitat restoration projects.  相似文献   

4.
Landscape ecology, inter alia, addresses the question as to how altered landscape patterns affect the distribution, persistence, and abundance of a species. Landscape ecology plays an important role in integrating the different scales of biodiversity from habitat patch to biome level. Satellite remote sensing technology with multi-sensor capabilities offers multi-scale information on landscape composition and configuration. Advances in geospatial analytical tools and spatial statistics have improved the capability to quantify spatial heterogeneity. Globally, landscape level characterization of biodiversity has become an important discipline of science. Considering the vast extent, heterogeneity, and ecological and economic importance of forest landscapes, significant efforts have been made in India during the past decade to strengthen landscape level biodiversity characterization. The generic frame work of studies comprises preparation of national databases providing information on composition and configuration of different landscapes using multi-scale remote sensing techniques, understanding the landscape patterns using geospatial models to elicit disturbance and diversity patterns and application of this information for bioprospecting and conservation purposes. Studies on hierarchical linkage of multi-scale information to study the processes of change, landscape function, dynamics of habitat fragmentation, invasion, development of network of conservation areas based on the understanding of multi-species responses to landscape mosaics, macro-ecological studies to understand environment and species richness, habitat and species transitions and losses, landscape level solutions to adaptation and mitigation strategies to climate change are a few of the future challenges. The paper presents the current experiences and, analyses in conjunction with international scenario and identifies future challenges of Indian landscape level biodiversity studies.  相似文献   

5.
The study explores the use of multiple criteria decision techniques in predicting spatial niche of Brown oak (also known as Kharsu oak, Quercus semecarpifolia Sm.) formation in midaltitude (2,400–3,500 meter amsl) Kumaun Himalaya. Predictive models using various climatic and topographical factors influencing Brown oak’s growth and survival were developed to define its current ecological niche. Analytical Hierarchical Process (AHP) method involving Saaty’s pair-wise comparison was performed to rank the explanatory powers of each compared variable. Variables were suitably weighted using fuzzy factor standardization scheme to reflect their relative importance in defining species niche. An optimum indicator was then chosen for deriving a site suitability map of brown oak. This study establishes the role of aspect in the current distribution of the species along with known influence of altitude. Future niches of oak has been tracked in the projected climate change scenario of +1°C and +2°C rise in temperature and 20 mm in precipitation. The results show that on predicted +1°C and +2°C increase in temperature, present habitat of brown oak distribution may be reduced by 40 per cent and 76 per cent respectively.  相似文献   

6.
The sustainable management and monitoring of urban forests is an important activity in the urbanized world, and operational approaches require information about the status of urban trees to determine the best strategy. One limitation in urban forest studies is the detection and discrimination of tree species using limited training data. Thus, this study focuses on developing generic rule sets from high-resolution WorldView-2 imagery in conjunction with spectral, spatial, colour and textural information for automated urban tree species detection. The object-based image analysis and its combination with statistical analysis of object features is utilized for this purpose. Results of attribute selection indicated that from 55 attributes, only 26 were useful to discriminate urban tree species, namely Messua ferrea L., Samanea saman and Casuarina sumatrana. Finally, the high overall accuracy, approximately 86.87% with kappa of 0.75 confirmed the transferability of the generic model.  相似文献   

7.
Land managers responsible for invasive species removal in the USA require tools to prevent the Asian longhorned beetle (Anoplophora glabripennis) (ALB) from decimating the maple-dominant hardwood forests of Massachusetts and New England. Species distribution models (SDMs) and spread models have been applied individually to predict the invasion distribution and rate of spread, but the combination of both models can increase the accuracy of predictions of species spread over time when habitat suitability is heterogeneous across landscapes. First, a SDM was fit to 2008 ALB presence-only locations. Then, a stratified spread model was generated to measure the probability of spread due to natural and human causes. Finally, the SDM and spread models were combined to evaluate the risk of ALB spread in Central Massachusetts in 2008–2009. The SDM predicted many urban locations in Central Massachusetts as having suitable environments for species establishment. The combined model shows the greatest risk of spread and establishment in suitable locations immediately surrounding the epicentre of the ALB outbreak in Northern Worcester with lower risk areas in suitable locations only accessible through long-range dispersal from access to human transportation networks. The risk map achieved an accuracy of 67% using 2009 ALB locations for model validation. This model framework can effectively provide risk managers with valuable information concerning the timing and spatial extent of spread/establishment risk of ALB and potential strategies needed for effective future risk management efforts.  相似文献   

8.
Application of GIS to estimate soil erosion using RUSLE   总被引：9，自引：0，他引：9  
This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE).Calculations are be done by using capabilities available.This study start with a digital elevation model(DEM) of Shaanxi,which was created by digitizing contour and spot heights from the topographic map on 1:250000 scale and grid themes for the USLE K and C factors.It is note worthy that USLE K can be obtained by adding the K factor as an attribute to a soil theme‘s table.The C can be obtained from tables or using the information about land use and management given by USLE program.A land use theme can be used to add the C factors as an attribute field.The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework.  相似文献   

9.
The objective of this study was to understand the factors that explain the spatial distribution of elephant poaching activities in the areas of the mid-Zambezi Valley, Zimbabwe using geographic information system (GIS) and remotely sensed data integrated with spatial logistic regression. The results showed that significant (α = 0.05) elephant poaching hot spots are located closer to wildlife protected areas. Results further demonstrated that resource availability (water and forage) are the main factors explaining elephant poaching activities in the mid-Zambezi Valley. For example, the majority of poaching activities were found to occur in areas with high vegetation fractional cover (high forage) and close to waterholes. The results also showed that poaching incidences were more prevalent during the dry season. The findings of this study highlight the significance of integrating GIS, remotely sensed data and spatial logistic regression tools for understanding and monitoring elephant poaching activities. This information is critical if poaching activities are to be minimized and it is also important for planning, monitoring and mitigation of poaching activities in similar protected areas across the sub-Saharan Africa.  相似文献   

10.
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11.
Species distribution modeling (SDM) at fine spatial resolutions requires species occurrence data of high positional accuracy to achieve good model performance. However, wildlife occurrences recorded by patrols in ranger‐based monitoring programs suffer from positional errors, because recorded locations represent the positions of the ranger and differ from the actual occurrence locations of wildlife (hereinafter referred to as positional errors in patrol data). This study presented an evaluation of the impact of such positional errors in patrol data on SDM and developed a heuristic‐based approach to mitigating the positional errors. The approach derives probable wildlife occurrence locations from ranger positions, utilizing heuristics based on species preferred habitat and the observer's field of view. The evaluations were conducted through a case study of SDM using patrol records of the black‐and‐white snub‐nosed monkey (Rhinopithecus bieti) in Yunnan, China. The performance of the approach was also compared against alternative sampling methods. The results showed that the positional errors in R. bieti patrol data had an adverse effect on SDM performance, and that the proposed approach can effectively mitigate the impact of the positional errors to greatly improve SDM performance.  相似文献   

12.
Geospatial tools and techniques are playing important roles in determining the location and spatial extents of invasive species infestations and in evaluating the performances of various management activities aimed at controlling their spread. In this study, hyperspectral image processing techniques were used to map purple loosestrife and to assess the effectiveness of biological control agents in controlling its infestations along the Niobrara River in Nebraska. Validation based on field survey showed an overall map accuracy of 82.1% and comparison with in situ data on biocontrol release indicated that biocontrol agents were effective in the areas where they were released.  相似文献   

13.
Abstract

Biodiversity is the variety and variability of flora and fauna in an ecosystem. Articulated into genes, species, and ecosystem, it provides the biological plasticity needed by life on the earth to adapt changes. As we approach towards the forthcoming century, the earth's diversity of life is increasingly at risk through a combination of mostly human induced factors leading to erosion of genetic resources, extinction of species and collapse of ecological systems. Insitu conservation, biotechnology tools for conservation and prospecting, species habitat relationship and following evolutionary process of speciation are some of the challenges. India being one of the mega biodiversity centers of the world is also known for its traditional knowledge of conservation. The varied regions of the country, with unique floristic and faunal richness, their vastness, endemism, heterogeneity and also inaccessibility of large areas have necessitated creation of authentic baseline database on biodiversity. With the advent of Internet based Geographic Information System technology an effort is being made to harness the power of these technologies to facilitate biodiversity conservation.

The information system organizes the data base generated under the project on “Biodiversity Characterization at landscape level using remote sensing and Geographic Information System in North East India” of the Department of Biotechnology and Department of Space, Government of India. The entire database is organized in object oriented relational database using Oracle as Backend and Visual Basic, ASP as front end. The web enabling part comes through uploading the entire spatial and non‐spatial data at a common platform using ArcSDE and ArcIMS The spatial characterization of landscape structures and its linkages with attribute information on the floristic composition, economic valuation, endemism are presented in Biodiversity Information System on a sharable environment. It is a step to evolve with new a mechanism to conserve biological diversity at local, regional and national level.  相似文献   

14.
Quantitative measures of polygon shapes and orientation are important elements of geospatial analysis. These kinds of measures are particularly valuable in the case of lakes, where shape and orientation patterns can help identifying the geomorphological agents behind lake formation and evolution. However, the lack of built-in tools in commercial geographic information system (GIS) software packages designed for this kind of analysis has meant that many researchers often must rely on tools and workarounds that are not always accurate. Here, an easy-to-use method to measure rectangularity R, ellipticity E, and orientation O is developed. In addition, a new rectangularity vs. ellipticity index, REi, is defined. Following a step-by-step process, it is shown how these measures and index can be easily calculated using a combination of GIS built-in functions. The identification of shapes and estimation of orientations performed by this method is applied to the case study of the geometric and oriented lakes of the Llanos de Moxos, in the Bolivian Amazon, where shape and orientation have been the two most important elements studied to infer possible formation mechanisms. It is shown that, thanks to these new indexes, shape and orientation patterns are unveiled, which would have been hard to identify otherwise.  相似文献   

15.
The paper presents a method of estimating parameters in two competitive functional models. The models considered here are concerned with the same observation set and are based on the assumption that an observation may result from a realization of either of two different random variables. These variables differ from one another at least in the main characteristic (for example, outliers can be realizations of one variable). A quantity that describes the opportunity of identifying a single observation with one random variable is assumed to be known. That quantity, called the elementary split potential, is strictly referred to the amount of information that an observation can provide about two competitive assumptions concerning the observation distribution. Parameter assessments that maximize the global elementary split potential (concerning all observations), are called M split estimators. A generalization of M split estimation presented in the paper refers to the theoretical foundation of M-estimation. An erratum to this article can be found at  相似文献   

16.
A current research project is addressing the problem of finding appropriate geographical information by developing a (geo)information realization resource based upon the concepts of the Literate Traveller. It has as its main goal to provide tools for geographical knowledge building and exploration, by providing conventional spatial information plus geographical interpretation and appreciation artifacts. These artifacts are delivered in an interactive multimedia environment. This research examines the formulation of an initial prototype component to assist in providing geographical knowledge. The prototype is based on a study site in Townsville, Australia, and is being used as a vehicle to explore enhanced spatial information provision through the use of rich media. The research examines new ways to prospect for, discover and disseminate spatial knowledge within an intelligence‐briefing context. The paper reports on the concepts behind the design of the application developed for the test site, and presents initial findings from the early evaluation of the prototype.  相似文献   

17.
Least-squares collocation may be used for the estimation of spherical harmonic coefficients and their error and error correlations from GOCE data. Due to the extremely large number of data, this requires the use of the so-called method of Fast Spherical Collocation (FSC) which requires that data is gridded equidistantly on each parallel and have the same uncorrelated noise on the parallel. A consequence of this is that error-covariances will be zero except between coefficients of the same signed order (i.e., the same order and the same coefficient type C–C or S–S). If the data distribution and the characteristics of the data noise are symmetric with respect to the equator, then, within a given order and coefficient type, the error-covariances amongst coefficients whose degrees are of different parity also vanish. The deviation from this “ideal” pattern has been studied using data-sets of second order radial derivatives of the anomalous potential. A total number of points below 17,000 were used having an equi-angular or an equal area distribution or being associated with points on a realistic GOCE orbit but close to the nodes of a grid. Also the data were considered having a correlated or an uncorrelated noise and three different signal covariance functions. Grids including data or not including data in the polar areas were used. Using the functionals associated with the data, error estimates of coefficients and error-correlations between coefficients were calculated up to a maximal degree and order equal to 90. As expected, for the data-distributions with no data in the polar areas the error-estimates were found to be larger than when the polar areas contained data. In all cases it was found that only the error-correlations between coefficients of the same order were significantly different from zero (up to 88%). Error-correlations were significantly larger when data had been regarded as having non-zero error-correlations. Also the error-correlations were largest when the covariance function with the largest signal covariance distance was used. The main finding of this study was that the correlated noise has more pronounced impact on gridded data than on data distributed on a realistic GOCE orbit. This is useful information for methods using gridded data, such as FSC.  相似文献   

18.
决策树结合混合像元分解的中国竹林遥感信息提取   总被引：1，自引：0，他引：1  
竹林是中国亚热带地区特殊而重要的森林资源,现有方法难以实现全国范围竹林时空分布信息快速准确提取。针对此问题,本研究利用2003年、2008年、2014年MODIS NDVI、反射率产品数据和省域Landsat分类数据,提出了基于决策树结合混合像元分解的全国竹林信息提取方法。首先,通过最大似然法获取中国林地分布信息;然后,在林地信息的基础上,构建决策树模型提取中国竹林分布信息;最后,采用线性最小二乘法混合像元分解得到中国竹林丰度图,并计算竹林面积。研究结果表明:(1)最大似然法提取的3个时期中国林地信息的生产者与用户精度均在90%以上,Kappa系数均值为0.93,为竹林信息提取奠定了基础。(2)C5.0算法构建的决策树模型能够很好的提取中国竹林时空分布信息,3个时期竹林分类精度均在80%左右。(3)在混合像元分解的基础上,统计得到的全国各省竹林估算面积与清查面积具有较高的相关性,R~2分别为0.98、0.97和0.95,RMSE范围为3.92万—9.58万ha,说明估算得到全国竹林面积与实际情况较为吻合。本研究所提出基于MODIS遥感数据运用C5.0算法决策树结合混合像元分解的方法,实现了全国竹林时空分布信息的准确提取,为全国竹林资源信息动态监测及管理提供了技术手段和数据支撑。  相似文献   

19.
Coastal wetlands are among the most productive ecosystems globally but have experienced dramatic degradation and loss within the past several decades. Vegetation biomass of coastal wetlands is not only the key component of blue carbon storage but also plays an important role in vertical accretion, important for maintaining these habitats under relative sea-level rise. Remote sensing offers a cost-effective approach to study vegetation biomass at a broad spatial scale. We developed statistical models to predict peak aboveground green biomass of Spartina alterniflora and Juncus roemerianus, two dominant species of salt marshes using WorldView-2 satellite imagery at the Grand Bay National Estuarine Research Reserve (NERR) on the Mississippi coast in the northern Gulf of Mexico. The model accounted for nested data structures in the sampled biomass, assimilated uncertainties from data, parameters and model structures, and helped determine the best vegetation index among a variety of commonly-used indices to predict aboveground green biomass. We developed a series of mixed-effects models, which included different combinations of fixed effect(s), random intercept, and random slope(s). The fixed effects were species and one of the 60 vegetation indices derived from a WorldView-2 image obtained on 6 October 2012. The random effect used was site. We implemented the models in a Bayesian framework and selected the best model structure and vegetation index based on minimum posterior predictive loss and deviance information criterion. The results showed that the best vegetation index to predict peak green biomass was the green chlorophyll index derived from the reflectance values of band 8 (near-infrared) and band 3 (green), and its effect on biomass prediction varied among sites. The inclusion of species as a fixed effect improved the model prediction. The study demonstrated the need to account for spatial dependence of data in developing a robust model, and the importance of the second WorldView-2 near-infrared band (860–1040 nm) in predicting aboveground green biomass for the Grand Bay NERR. The analysis using mixed-effects modeling in Bayesian inference which coherently combined field and WorldView-2 data with uncertainties accounted for provides a robust and nondestructive tool for resource managers to monitor the status of coastal wetlands at a high spatial resolution in a timely manner. Through this study, we hope to emphasize the importance of appropriately accounting for nested data structures using mixed-effects models and promote wider application of Bayesian inference to facilitate assimilation of uncertainties in remote sensing applications.  相似文献   

20.
One of the fundamental issues of geographical information science is to design GIS interfaces and functionalities in a way that is easy to understand, teach, and use. Unfortunately, current geographical information systems (including ArcGIS) remains very difficult to use as spatial analysis tools, because they organize and expose functionalities according to GIS data structures and processing algorithms. As a result, GIS interfaces are conceptually confusing, cognitively complex, and semantically disconnected from the way human reason about spatial analytical activities. In this article, we propose an approach that structures GIS analytical functions based on the notion of “analytical intent”. We describe an experiment that replaces ArcGIS desktop interface with a conversational interface, to enable mixed‐initiative user‐system interactions at the level of analytical intentions. We initially focus on the subset of GIS functions that are relevant to “finding what's inside” as described by Mitchell, but the general principles apply to other types of spatial analysis. This work demonstrates the feasibility of delegating some spatial thinking tasks to computational agents, and also raises future research questions that are key to building a better theory of spatial thinking with GIS.  相似文献   

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