Vegetation mapping of the Mond Protected Area of Bushehr Province (south-west Iran).

Science.gov (United States)

Mehrabian, Ahmadreza; Naqinezhad, Alireza; Mahiny, Abdolrassoul Salman; Mostafavi, Hossein; Liaghati, Homan; Kouchekzadeh, Mohsen

2009-03-01

Arid regions of the world occupy up to 35% of the earth's surface, the basis of various definitions of climatic conditions, vegetation types or potential for food production. Due to their high ecological value, monitoring of arid regions is necessary and modern vegetation studies can help in the conservation and management of these areas. The use of remote sensing for mapping of desert vegetation is difficult due to mixing of the spectral reflectance of bright desert soils with the weak spectral response of sparse vegetation. We studied the vegetation types in the semiarid to arid region of Mond Protected Area, south-west Iran, based on unsupervised classification of the Spot XS bands and then produced updated maps. Sixteen map units covering 12 vegetation types were recognized in the area based on both field works and satellite mapping. Halocnemum strobilaceum and Suaeda fruticosa vegetation types were the dominant types and Ephedra foliata, Salicornia europaea-Suaeda heterophylla vegetation types were the smallest. Vegetation coverage decreased sharply with the increase in salinity towards the coastal areas of the Persian Gulf. The highest vegetation coverage belonged to the riparian vegetation along the Mond River, which represents the northern boundary of the protected area. The location of vegetation types was studied on the separate soil and habitat diversity maps of the study area, which helped in final refinements of the vegetation map produced.

Vegetation Water Content Mapping for Agricultural Regions in SMAPVEX16

Science.gov (United States)

White, W. A.; Cosh, M. H.; McKee, L.; Berg, A. A.; McNairn, H.; Hornbuckle, B. K.; Colliander, A.; Jackson, T. J.

2017-12-01

Vegetation water content impacts the ability of L-band radiometers to measure surface soil moisture. Therefore it is necessary to quantify the amount of water held in surface vegetation for an accurate soil moisture remote sensing retrieval. A methodology is presented for generating agricultural vegetation water content maps using Landsat 8 scenes for agricultural fields of Iowa and Manitoba for the Soil Moisture Active Passive Validation Experiments in 2016 (SMAPVEX16). Manitoba has a variety of row crops across the region, and the study period encompasses the time frame from emergence to reproduction, as well as a forested region. The Iowa study site is dominated by corn and soybeans, presenting an easier challenge. Ground collection of vegetation biomass and water content were also collected to provide a ground truth data source. Errors for the resulting vegetation water content maps ranged depending upon crop type, but generally were less than 15% of the total plant water content per crop type. Interpolation is done between Landsat overpasses to produce daily vegetation water content maps for the summer of 2016 at a 30 meter resolution.

Demonstration of wetland vegetation mapping in Florida from computer-processed satellite and aircraft multispectral scanner data

Science.gov (United States)

Butera, M. K.

1979-01-01

The success of remotely mapping wetland vegetation of the southwestern coast of Florida is examined. A computerized technique to process aircraft and LANDSAT multispectral scanner data into vegetation classification maps was used. The cost effectiveness of this mapping technique was evaluated in terms of user requirements, accuracy, and cost. Results indicate that mangrove communities are classified most cost effectively by the LANDSAT technique, with an accuracy of approximately 87 percent and with a cost of approximately 3 cent per hectare compared to $46.50 per hectare for conventional ground survey methods.

Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and northern Mexico

Science.gov (United States)

Dye, Dennis G.; Middleton, Barry R.; Vogel, John M.; Wu, Zhuoting; Velasco, Miguel G.

2016-01-01

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

Possibilities and methods for mapping air pollution

Energy Technology Data Exchange (ETDEWEB)

LeBlanc, F

1971-01-01

For various reasons lichens seem to be much more sensitive to air pollution than flowering plants. Various methods to map the long-range effect of phytotoxicants on epiphytic lichens and mosses have been proposed. This paper outlines a few of these and proposes a new method. In Sudbury, Ontario, vegetation has been greatly affected by sulfur dioxide emanating from three huge smelters. The author shows that his map based on the response of lichens matches quite well with another map from the same area based on continuous SO/sub 2/ monitoring. The advantage of the biological map is that it took two weeks to accumulate the data required while the other one took ten years.

LBA-ECO LC-15 Aerodynamic Roughness Maps of Vegetation Canopies, Amazon Basin: 2000

Data.gov (United States)

National Aeronautics and Space Administration — This data set, LBA-ECO LC-15 Aerodynamic Roughness Maps of Vegetation Canopies, Amazon Basin: 2000, provides physical roughness maps of vegetation canopies in the...

High-resolution mapping of wetland vegetation biomass and distribution with L-band radar in southeastern coastal Louisiana

Science.gov (United States)

Thomas, N. M.; Simard, M.; Byrd, K. B.; Windham-Myers, L.; Castaneda, E.; Twilley, R.; Bevington, A. E.; Christensen, A.

2017-12-01

Louisiana coastal wetlands account for approximately one third (37%) of the estuarine wetland vegetation in the conterminous United States, yet the spatial distribution of their extent and aboveground biomass (AGB) is not well defined. This knowledge is critical for the accurate completion of national greenhouse gas (GHG) inventories. We generated high-resolution baselines maps of wetland vegetation extent and biomass at the Atchafalaya and Terrebonne basins in coastal Louisiana using a multi-sensor approach. Optical satellite data was used within an object-oriented machine learning approach to classify the structure of wetland vegetation types, offering increased detail over currently available land cover maps that do not distinguish between wetland vegetation types nor account for non-permanent seasonal changes in extent. We mapped 1871 km2 of wetlands during a period of peak biomass in September 2015 comprised of flooded forested wetlands and leaf, grass and emergent herbaceous marshes. The distribution of aboveground biomass (AGB) was mapped using JPL L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). Relationships between time-series radar imagery and field data collected in May 2015 and September 2016 were derived to estimate AGB at the Wax Lake and Atchafalaya deltas. Differences in seasonal biomass estimates reflect the increased AGB in September over May, concurrent with periods of peak biomass and the onset of the vegetation growing season, respectively. This method provides a tractable means of mapping and monitoring biomass of wetland vegetation types with L-band radar, in a region threatened with wetland loss under projections of increasing sea-level rise and terrestrial subsidence. Through this, we demonstrate a method that is able to satisfy the IPCC 2013 Wetlands Supplement requirement for Tier 2/Tier 3 reporting of coastal wetland GHG inventories.

USING OF THERMAL STRUCTURE MAPS FOR VEGETATION MAPPING (CASE OF ALTACHEYSKY WILDLIFE AREA

Directory of Open Access Journals (Sweden)

L. A. Abramova

2014-01-01

Full Text Available Thermal infrared imagery contains considerable amount of qualitative information about ground objects and landscapes. In spite of it, this type of data is often used to derive quantitative information such as land or sea surface temperatures. This paper describes the examination of Altacheysky wildlife area situated in the southern part of Buryatia Republic, Mukhorshibirsky district based on Landsat imagery and ground observations. Ground observations were led to study the vegetation cover of the area. Landsat imagery were used to make multitemporal thermal infrared image combined of 7 ETM+ scenes and to make multispectral image combined of different zones of a OLI scene. Both images were classified. The multitemporal thermal infrared classification result was used to compose thermal structure map of the wildlife area. Comparison of the map, multispectral image classification result and ground observations data reveals that thermal structure map describes better the particularities of Altacheysky wildlife area vegetation cover.

Airborne Lidar: Advances in Discrete Return Technology for 3D Vegetation Mapping

Directory of Open Access Journals (Sweden)

Valerie Ussyshkin

2011-02-01

Full Text Available Conventional discrete return airborne lidar systems, used in the commercial sector for efficient generation of high quality spatial data, have been considered for the past decade to be an ideal choice for various mapping applications. Unlike two-dimensional aerial imagery, the elevation component of airborne lidar data provides the ability to represent vertical structure details with very high precision, which is an advantage for many lidar applications focusing on the analysis of elevated features such as 3D vegetation mapping. However, the use of conventional airborne discrete return lidar systems for some of these applications has often been limited, mostly due to relatively coarse vertical resolution and insufficient number of multiple measurements in vertical domain. For this reason, full waveform airborne sensors providing more detailed representation of target vertical structure have often been considered as a preferable choice in some areas of 3D vegetation mapping application, such as forestry research. This paper presents an overview of the specific features of airborne lidar technology concerning 3D mapping applications, particularly vegetation mapping. Certain key performance characteristics of lidar sensors important for the quality of vegetation mapping are discussed and illustrated by the advanced capabilities of the ALTM-Orion, a new discrete return sensor manufactured by Optech Incorporated. It is demonstrated that advanced discrete return sensors with enhanced 3D mapping capabilities can produce data of enhanced quality, which can represent complex structures of vegetation targets at the level of details equivalent in some aspects to the content of full waveform data. It is also shown that recent advances in conventional airborne lidar technology bear the potential to create a new application niche, where high quality dense point clouds, enhanced by fully recorded intensity for multiple returns, may provide sufficient

Mapping coastal vegetation using an expert system and hyperspectral imagery

NARCIS (Netherlands)

Schmidt, K.S.; Skidmore, A.K.; Kloosterman, E.H.; Oosten, van H.; Kumar, L.; Janssen, J.A.M.

2004-01-01

Mapping and monitoring salt marshes in the Netherlands are important activities of the Ministry of Public Works (Rijkswaterstaat). The Survey Department (Meetkundige Dienst) produces vegetation maps using aerial photographs. However, it is a time-consuming and expensive activity. The accuracy of the

Integrating field sampling, geostatistics and remote sensing to map wetland vegetation in the Pantanal, Brazil

Directory of Open Access Journals (Sweden)

J. Arieira

2011-03-01

Full Text Available Development of efficient methodologies for mapping wetland vegetation is of key importance to wetland conservation. Here we propose the integration of a number of statistical techniques, in particular cluster analysis, universal kriging and error propagation modelling, to integrate observations from remote sensing and field sampling for mapping vegetation communities and estimating uncertainty. The approach results in seven vegetation communities with a known floral composition that can be mapped over large areas using remotely sensed data. The relationship between remotely sensed data and vegetation patterns, captured in four factorial axes, were described using multiple linear regression models. There were then used in a universal kriging procedure to reduce the mapping uncertainty. Cross-validation procedures and Monte Carlo simulations were used to quantify the uncertainty in the resulting map. Cross-validation showed that accuracy in classification varies according with the community type, as a result of sampling density and configuration. A map of uncertainty derived from Monte Carlo simulations revealed significant spatial variation in classification, but this had little impact on the proportion and arrangement of the communities observed. These results suggested that mapping improvement could be achieved by increasing the number of field observations of those communities with a scattered and small patch size distribution; or by including a larger number of digital images as explanatory variables in the model. Comparison of the resulting plant community map with a flood duration map, revealed that flooding duration is an important driver of vegetation zonation. This mapping approach is able to integrate field point data and high-resolution remote-sensing images, providing a new basis to map wetland vegetation and allow its future application in habitat management, conservation assessment and long-term ecological monitoring in wetland

Approaches to vegetation mapping and ecophysiological hypothesis testing using combined information from TIMS, AVIRIS, and AIRSAR

Science.gov (United States)

Oren, R.; Vane, G.; Zimmermann, R.; Carrere, V.; Realmuto, V.; Zebker, Howard A.; Schoeneberger, P.; Schoeneberger, M.

1991-01-01

The Tropical Rainforest Ecology Experiment (TREE) had two primary objectives: (1) to design a method for mapping vegetation in tropical regions using remote sensing and determine whether the result improves on available vegetation maps; and (2) to test a specific hypothesis on plant/water relations. Both objectives were thought achievable with the combined information from the Thermal Infrared Multispectral Scanner (TIMS), Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and Airborne Synthetic Aperture Radar (AIRSAR). Implicitly, two additional objectives were: (1) to ascertain that the range within each variable potentially measurable with the three instruments is large enough in the site, relative to the sensitivity of the instruments, so that differences between ecological groups may be detectable; and (2) to determine the ability of the three systems to quantify different variables and sensitivities. We found that the ranges in values of foliar nitrogen concentration, water availability, stand structure and species composition, and plant/water relations were large, even within the upland broadleaf vegetation type. The range was larger when other vegetation types were considered. Unfortunately, cloud cover and navigation errors compromised the utility of the TIMS and AVIRIS data. Nevertheless, the AIRSAR data alone appear to have improved on the available vegetation map for the study area. An example from an area converted to a farm is given to demonstrate how the combined information from AIRSAR, TIMS, and AVIRIS can uniquely identify distinct classes of land use. The example alludes to the potential utility of the three instruments for identifying vegetation at an ecological scale finer than vegetation types.

Vegetation Mapping - Tecolote Canyon, San Diego Co. [ds656

Data.gov (United States)

California Natural Resource Agency — Vegetation mapping has been conducted at various City of San Diego Park and Recreation Open Space lands in support of natural resource management objectives and the...

MAPPING ALPINE VEGETATION LOCATION PROPERTIES BY DENSE MATCHING

Directory of Open Access Journals (Sweden)

R. Niederheiser

2016-06-01

Full Text Available Highly accurate 3D micro topographic mapping in mountain research demands for light equipment and low cost solutions. Recent developments in structure from motion and dense matching techniques provide promising tools for such applications. In the following, the feasibility of terrestrial photogrammetry for mapping topographic location properties of sparsely vegetated areas in selected European mountain regions is investigated. Changes in species composition at alpine vegetation locations are indicators of climate change consequences, such as the pronounced rise of average temperatures in mountains compared to the global average. Better understanding of climate change effects on plants demand for investigations on a micro-topographic scale. We use professional and consumer grade digital single-lens reflex cameras mapping 288 plots each 3 x 3 m on 18 summits in the Alps and Mediterranean Mountains within the GLORIA (GLobal Observation Research Initiative in Alpine environments network. Image matching tests result in accuracies that are in the order of millimetres in the XY-plane and below 0.5 mm in Z-direction at the second image pyramid level. Reconstructing vegetation proves to be a challenge due to its fine and small structured architecture and its permanent movement by wind during image acquisition, which is omnipresent on mountain summits. The produced 3D point clouds are gridded to 6 mm resolution from which topographic parameters such as slope, aspect and roughness are derived. At a later project stage these parameters will be statistically linked to botanical reference data in order to conclude on relations between specific location properties and species compositions.

An evaluation of rapid methods for monitoring vegetation characteristics of wetland bird habitat

Science.gov (United States)

Tavernia, Brian G.; Lyons, James E.; Loges, Brian W.; Wilson, Andrew; Collazo, Jaime A.; Runge, Michael C.

2016-01-01

Wetland managers benefit from monitoring data of sufficient precision and accuracy to assess wildlife habitat conditions and to evaluate and learn from past management decisions. For large-scale monitoring programs focused on waterbirds (waterfowl, wading birds, secretive marsh birds, and shorebirds), precision and accuracy of habitat measurements must be balanced with fiscal and logistic constraints. We evaluated a set of protocols for rapid, visual estimates of key waterbird habitat characteristics made from the wetland perimeter against estimates from (1) plots sampled within wetlands, and (2) cover maps made from aerial photographs. Estimated percent cover of annuals and perennials using a perimeter-based protocol fell within 10 percent of plot-based estimates, and percent cover estimates for seven vegetation height classes were within 20 % of plot-based estimates. Perimeter-based estimates of total emergent vegetation cover did not differ significantly from cover map estimates. Post-hoc analyses revealed evidence for observer effects in estimates of annual and perennial covers and vegetation height. Median time required to complete perimeter-based methods was less than 7 percent of the time needed for intensive plot-based methods. Our results show that rapid, perimeter-based assessments, which increase sample size and efficiency, provide vegetation estimates comparable to more intensive methods.

Remote sensing and vegetation mapping in South Africa

Directory of Open Access Journals (Sweden)

M. L. Jarman

1983-12-01

Full Text Available The kinds of imagery, types of data and general relationships between scale of study, scale of mapping and scale of remote sensing products that are appropriate to the South African situation for visual and digital analysis are presented. The type of remote sensing product and processing, the type of field exercise appropriate to each, and the purpose of producing maps at each scale are discussed. Lack of repetitive imagery to date has not allowed for the full investigation of monitoring potential and careful planning at national level is needed to ensure availability of imagery for monitoring purposes. Map production processes which are rapid and accurate should be utilized. An integrated approach to vegetation mapping and surveying, which incorporates the best features of both visual and digital processing, is recommended for use.

Evaluating the Use of an Object-Based Approach to Lithological Mapping in Vegetated Terrain

Directory of Open Access Journals (Sweden)

Stephen Grebby

2016-10-01

Full Text Available Remote sensing-based approaches to lithological mapping are traditionally pixel-oriented, with classification performed on either a per-pixel or sub-pixel basis with complete disregard for contextual information about neighbouring pixels. However, intra-class variability due to heterogeneous surface cover (i.e., vegetation and soil or regional variations in mineralogy and chemical composition can result in the generation of unrealistic, generalised lithological maps that exhibit the “salt-and-pepper” artefact of spurious pixel classifications, as well as poorly defined contacts. In this study, an object-based image analysis (OBIA approach to lithological mapping is evaluated with respect to its ability to overcome these issues by instead classifying groups of contiguous pixels (i.e., objects. Due to significant vegetation cover in the study area, the OBIA approach incorporates airborne multispectral and LiDAR data to indirectly map lithologies by exploiting associations with both topography and vegetation type. The resulting lithological maps were assessed both in terms of their thematic accuracy and ability to accurately delineate lithological contacts. The OBIA approach is found to be capable of generating maps with an overall accuracy of 73.5% through integrating spectral and topographic input variables. When compared to equivalent per-pixel classifications, the OBIA approach achieved thematic accuracy increases of up to 13.1%, whilst also reducing the “salt-and-pepper” artefact to produce more realistic maps. Furthermore, the OBIA approach was also generally capable of mapping lithological contacts more accurately. The importance of optimising the segmentation stage of the OBIA approach is also highlighted. Overall, this study clearly demonstrates the potential of OBIA for lithological mapping applications, particularly in significantly vegetated and heterogeneous terrain.

Estimating fractional vegetation cover and the vegetation index of bare soil and highly dense vegetation with a physically based method

Science.gov (United States)

Song, Wanjuan; Mu, Xihan; Ruan, Gaiyan; Gao, Zhan; Li, Linyuan; Yan, Guangjian

2017-06-01

Normalized difference vegetation index (NDVI) of highly dense vegetation (NDVIv) and bare soil (NDVIs), identified as the key parameters for Fractional Vegetation Cover (FVC) estimation, are usually obtained with empirical statistical methods However, it is often difficult to obtain reasonable values of NDVIv and NDVIs at a coarse resolution (e.g., 1 km), or in arid, semiarid, and evergreen areas. The uncertainty of estimated NDVIs and NDVIv can cause substantial errors in FVC estimations when a simple linear mixture model is used. To address this problem, this paper proposes a physically based method. The leaf area index (LAI) and directional NDVI are introduced in a gap fraction model and a linear mixture model for FVC estimation to calculate NDVIv and NDVIs. The model incorporates the Moderate Resolution Imaging Spectroradiometer (MODIS) Bidirectional Reflectance Distribution Function (BRDF) model parameters product (MCD43B1) and LAI product, which are convenient to acquire. Two types of evaluation experiments are designed 1) with data simulated by a canopy radiative transfer model and 2) with satellite observations. The root-mean-square deviation (RMSD) for simulated data is less than 0.117, depending on the type of noise added on the data. In the real data experiment, the RMSD for cropland is 0.127, for grassland is 0.075, and for forest is 0.107. The experimental areas respectively lack fully vegetated and non-vegetated pixels at 1 km resolution. Consequently, a relatively large uncertainty is found while using the statistical methods and the RMSD ranges from 0.110 to 0.363 based on the real data. The proposed method is convenient to produce NDVIv and NDVIs maps for FVC estimation on regional and global scales.

Vegetation Mapping of the Mond Protected Area of Bushehr Provice (SW Iran)

OpenAIRE

Mehrabian, Ahmadreza; Mahiny, Abdolrassoul Salman; Mostafavi, Hossein; Liaghati, Homan

2010-01-01

The current study is a new approach to vegetation mapping in Iran using remote sensing (RS) and the geographic information system (GIS). One of the most important problems in remote sensing of desert vegetation is that the reflectance from soil and rocks is often much greater than that of sparse vegetation and this makes it difficult to separate out the vegetation signal (Gates et al. 1965); and there is spectral variability within shrubs of the same species (Duncant et al., 1993). These prop...

Selection of vegetation indices for mapping the sugarcane condition around the oil and gas field of North West Java Basin, Indonesia

Science.gov (United States)

Muji Susantoro, Tri; Wikantika, Ketut; Saepuloh, Asep; Handoyo Harsolumakso, Agus

2018-05-01

Selection of vegetation indices in plant mapping is needed to provide the best information of plant conditions. The methods used in this research are the standard deviation and the linear regression. This research tried to determine the vegetation indices used for mapping the sugarcane conditions around oil and gas fields. The data used in this study is Landsat 8 OLI/TIRS. The standard deviation analysis on the 23 vegetation indices with 27 samples has resulted in the six highest standard deviations of vegetation indices, termed as GRVI, SR, NLI, SIPI, GEMI and LAI. The standard deviation values are 0.47; 0.43; 0.30; 0.17; 0.16 and 0.13. Regression correlation analysis on the 23 vegetation indices with 280 samples has resulted in the six vegetation indices, termed as NDVI, ENDVI, GDVI, VARI, LAI and SIPI. This was performed based on regression correlation with the lowest value R2 than 0,8. The combined analysis of the standard deviation and the regression correlation has obtained the five vegetation indices, termed as NDVI, ENDVI, GDVI, LAI and SIPI. The results of the analysis of both methods show that a combination of two methods needs to be done to produce a good analysis of sugarcane conditions. It has been clarified through field surveys and showed good results for the prediction of microseepages.

Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

Science.gov (United States)

Nelson, P.; Paradis, D. P.

2017-12-01

The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined

Vegetation mapping from high-resolution satellite images in the heterogeneous arid environments of Socotra Island (Yemen)

Science.gov (United States)

Malatesta, Luca; Attorre, Fabio; Altobelli, Alfredo; Adeeb, Ahmed; De Sanctis, Michele; Taleb, Nadim M.; Scholte, Paul T.; Vitale, Marcello

2013-01-01

Socotra Island (Yemen), a global biodiversity hotspot, is characterized by high geomorphological and biological diversity. In this study, we present a high-resolution vegetation map of the island based on combining vegetation analysis and classification with remote sensing. Two different image classification approaches were tested to assess the most accurate one in mapping the vegetation mosaic of Socotra. Spectral signatures of the vegetation classes were obtained through a Gaussian mixture distribution model, and a sequential maximum a posteriori (SMAP) classification was applied to account for the heterogeneity and the complex spatial pattern of the arid vegetation. This approach was compared to the traditional maximum likelihood (ML) classification. Satellite data were represented by a RapidEye image with 5 m pixel resolution and five spectral bands. Classified vegetation relevés were used to obtain the training and evaluation sets for the main plant communities. Postclassification sorting was performed to adjust the classification through various rule-based operations. Twenty-eight classes were mapped, and SMAP, with an accuracy of 87%, proved to be more effective than ML (accuracy: 66%). The resulting map will represent an important instrument for the elaboration of conservation strategies and the sustainable use of natural resources in the island.

Association between mapped vegetation and Quaternary geology on Santa Rosa Island, California

Science.gov (United States)

Cronkite-Ratcliff, C.; Corbett, S.; Schmidt, K. M.

2017-12-01

Vegetation and surficial geology are closely connected through the interface generally referred to as the critical zone. Not only do they influence each other, but they also provide clues into the effects of climate, topography, and hydrology on the earth's surface. This presentation describes quantitative analyses of the association between the recently compiled, independently generated vegetation and geologic map units on Santa Rosa Island, part of the Channel Islands National Park in Southern California. Santa Rosa Island was heavily grazed by sheep and cattle ranching for over one hundred years prior to its acquisition by the National Park Service. During this period, the island experienced significant erosion and spatial reduction and diversity of native plant species. Understanding the relationship between geology and vegetation is necessary for monitoring the recovery of native plant species, enhancing the viability of restoration sites, and understanding hydrologic conditions favorable for plant growth. Differences in grain size distribution and soil depth between geologic units support different plant communities through their influence on soil moisture, while differences in unit age reflect different degrees of pedogenic maturity. We find that unsupervised machine learning methods provide more informative insight into vegetation-geology associations than traditional measures such as Cramer's V and Goodman and Kruskal's lambda. Correspondence analysis shows that unique vegetation-geology patterns associated with beach/dune, grassland, hillslope/colluvial, and fluvial/wetland environments can be discerned from the data. By combining geology and vegetation with topographic variables, mixture models can be used to partition the landscape into multiple representative types, which then be compared with conceptual models of plant growth and succession over different landforms. Using this collection of methods, we show various ways that that Quaternary geology

Digital soil mapping using remote sensing indices, terrain attributes, and vegetation features in the rangelands of northeastern Iran.

Science.gov (United States)

Mahmoudabadi, Ebrahim; Karimi, Alireza; Haghnia, Gholam Hosain; Sepehr, Adel

2017-09-11

Digital soil mapping has been introduced as a viable alternative to the traditional mapping methods due to being fast and cost-effective. The objective of the present study was to investigate the capability of the vegetation features and spectral indices as auxiliary variables in digital soil mapping models to predict soil properties. A region with an area of 1225 ha located in Bajgiran rangelands, Khorasan Razavi province, northeastern Iran, was chosen. A total of 137 sampling sites, each containing 3-5 plots with 10-m interval distance along a transect established based on randomized-systematic method, were investigated. In each plot, plant species names and numbers as well as vegetation cover percentage (VCP) were recorded, and finally one composite soil sample was taken from each transect at each site (137 soil samples in total). Terrain attributes were derived from a digital elevation model, different bands and spectral indices were obtained from the Landsat7 ETM+ images, and vegetation features were calculated in the plots, all of which were used as auxiliary variables to predict soil properties using artificial neural network, gene expression programming, and multivariate linear regression models. According to R 2 RMSE and MBE values, artificial neutral network was obtained as the most accurate soil properties prediction function used in scorpan model. Vegetation features and indices were more effective than remotely sensed data and terrain attributes in predicting soil properties including calcium carbonate equivalent, clay, bulk density, total nitrogen, carbon, sand, silt, and saturated moisture capacity. It was also shown that vegetation indices including NDVI, SAVI, MSAVI, SARVI, RDVI, and DVI were more effective in estimating the majority of soil properties compared to separate bands and even some soil spectral indices.

Vegetation map and plant checklist of Ol Ari Nyiro ranch and the ...

African Journals Online (AJOL)

Ol Ari Nyiro is a 360 km2 ranch of the Laikipia Plateau, in a semi-arid part of Kenya. The vegetation of the ranch and nearby Mukutan Gorge was mapped, and a preliminary check-list of fungi and vascular plants compiled. The vegetation was classified in 16 different types. A total of 708 species and subspecies were ...

A Study on Remote Probing Method for Drawing Ecology/Nature Map and the Application (III) - Drawing the Swamp Classification Map around River

Energy Technology Data Exchange (ETDEWEB)

Jeon, Seong Woo; Cho, Jeong Keon; Jeong, Hwi Chol [Korea Environment Institute, Seoul (Korea)

2000-12-01

The map of ecology/nature in the amended Natural Environment Conservation Act is the necessary data, which is drawn through assessing the national land with ecological factors, to execute the Korea's environmental policy. Such important ecology/nature map should be continuously revised and improved the reliability with adding several new factors. In this point of view, this study has the significance in presenting the improvement scheme of ecology/nature map. 'A Study on Remote Probing Method for Drawing Ecology/Nature Map and the Application' that has been performed for 3 years since 1998 has researched the drawing method of subject maps that could be built in a short time - a land-covering classification map, a vegetation classification map, and a swamp classification map around river - and the promoting principles hereafter. This study also presented the possibility and limit of classification by several satellite image data, so it would be a big help to build the subject map in the Government level. The land-covering classification map, a result of the first year, has been already being built by Ministry of Environment as a national project, and the improvement scheme of the vegetation map that was presented as a result of second year has been used in building the basic ecology/nature map. We hope that the results from this study will be applied as basic data to draw an ecology/nature map and contribute to expanding the understanding on the usefulness of the several ecosystem analysis methods with applying an ecology/nature map and a remote probe. 55 refs., 38 figs., 24 tabs.

Pre-LBA CABARE Mapped Land Surface and Vegetation Characteristics, Rondonia, Brazil

Data.gov (United States)

National Aeronautics and Space Administration — ABSTRACT: Surface parameter digital maps of vegetation, soil, and topography were obtained for Rondonia, Brazil, covering the 5x5 degree region bounded by 13-8...

Vegetation Water Content Mapping in a Diverse Agricultural Landscape: National Airborne Field Experiment 2006

Science.gov (United States)

Cosh, Michael H.; Jing Tao; Jackson, Thomas J.; McKee, Lynn; O'Neill, Peggy

2011-01-01

Mapping land cover and vegetation characteristics on a regional scale is critical to soil moisture retrieval using microwave remote sensing. In aircraft-based experiments such as the National Airborne Field Experiment 2006 (NAFE 06), it is challenging to provide accurate high resolution vegetation information, especially on a daily basis. A technique proposed in previous studies was adapted here to the heterogenous conditions encountered in NAFE 06, which included a hydrologically complex landscape consisting of both irrigated and dryland agriculture. Using field vegetation sampling and ground-based reflectance measurements, the knowledge base for relating the Normalized Difference Water Index (NDWI) and the vegetation water content was extended to a greater diversity of agricultural crops, which included dryland and irrigated wheat, alfalfa, and canola. Critical to the generation of vegetation water content maps, the land cover for this region was determined from satellite visible/infrared imagery and ground surveys with an accuracy of 95.5% and a kappa coefficient of 0.95. The vegetation water content was estimated with a root mean square error of 0.33 kg/sq m. The results of this investigation contribute to a more robust database of global vegetation water content observations and demonstrate that the approach can be applied with high accuracy. Keywords: Vegetation, field experimentation, thematic mapper, NDWI, agriculture.

Accuracy assessment of vegetation community maps generated by aerial photography interpretation: perspective from the tropical savanna, Australia

Science.gov (United States)

Lewis, Donna L.; Phinn, Stuart

2011-01-01

Aerial photography interpretation is the most common mapping technique in the world. However, unlike an algorithm-based classification of satellite imagery, accuracy of aerial photography interpretation generated maps is rarely assessed. Vegetation communities covering an area of 530 km2 on Bullo River Station, Northern Territory, Australia, were mapped using an interpretation of 1:50,000 color aerial photography. Manual stereoscopic line-work was delineated at 1:10,000 and thematic maps generated at 1:25,000 and 1:100,000. Multivariate and intuitive analysis techniques were employed to identify 22 vegetation communities within the study area. The accuracy assessment was based on 50% of a field dataset collected over a 4 year period (2006 to 2009) and the remaining 50% of sites were used for map attribution. The overall accuracy and Kappa coefficient for both thematic maps was 66.67% and 0.63, respectively, calculated from standard error matrices. Our findings highlight the need for appropriate scales of mapping and accuracy assessment of aerial photography interpretation generated vegetation community maps.

Comparison of saturated areas mapping methods in the Jizera Mountains, Czech Republic

Czech Academy of Sciences Publication Activity Database

Kulasová, A.; Beven, K. J.; Blažková, Š. D.; Řezáčová, Daniela; Cajthaml, J.

2014-01-01

Roč. 62, č. 2 (2014), s. 160-168 ISSN 0042-790X R&D Projects: GA ČR(CZ) GAP209/11/2045 Institutional support: RVO:68378289 Keywords : mapping variable source areas * boot method * piezometers * vegetation mapping Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 1.486, year: 2014 http://147.213.145.2/vc_articles/2014_62_2_Kulasova_160.pdf

Pre-LBA CABARE Mapped Land Surface and Vegetation Characteristics, Rondonia, Brazil

Data.gov (United States)

National Aeronautics and Space Administration — Surface parameter digital maps of vegetation, soil, and topography were obtained for Rondonia, Brazil, covering the 5x5 degree region bounded by 13-8 degrees S and...

[Application of biotope mapping model integrated with vegetation cover continuity attributes in urban biodiversity conservation].

Science.gov (United States)

Gao, Tian; Qiu, Ling; Chen, Cun-gen

2010-09-01

Based on the biotope classification system with vegetation structure as the framework, a modified biotope mapping model integrated with vegetation cover continuity attributes was developed, and applied to the study of the greenbelts in Helsingborg in southern Sweden. An evaluation of the vegetation cover continuity in the greenbelts was carried out by the comparisons of the vascular plant species richness in long- and short-continuity forests, based on the identification of woodland continuity by using ancient woodland indicator species (AWIS). In the test greenbelts, long-continuity woodlands had more AWIS. Among the forests where the dominant trees were more than 30-year-old, the long-continuity ones had a higher biodiversity of vascular plants, compared with the short-continuity ones with the similar vegetation structure. The modified biotope mapping model integrated with the continuity features of vegetation cover could be an important tool in investigating urban biodiversity, and provide corresponding strategies for future urban biodiversity conservation.

A temperature and vegetation adjusted NTL urban index for urban area mapping and analysis

Science.gov (United States)

Zhang, Xiya; Li, Peijun

2018-01-01

Accurate and timely information regarding the extent and spatial distribution of urban areas on regional and global scales is crucially important for both scientific and policy-making communities. Stable nighttime light (NTL) data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) provides a unique proxy of human settlement and activity, which has been used in the mapping and analysis of urban areas and urbanization dynamics. However, blooming and saturation effects of DMSP/OLS NTL data are two unresolved problems in regional urban area mapping and analysis. This study proposed a new urban index termed the Temperature and Vegetation Adjusted NTL Urban Index (TVANUI). It is intended to reduce blooming and saturation effects and to enhance urban features by combining DMSP/OLS NTL data with Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer onboard the Terra satellite. The proposed index was evaluated in two study areas by comparison with established urban indices. The results demonstrated the proposed TVANUI was effective in enhancing the variation of DMSP/OLS light in urban areas and in reducing blooming and saturation effects, showing better performance than three established urban indices. The TVANUI also significantly outperformed the established urban indices in urban area mapping using both the global-fixed threshold and the local-optimal threshold methods. Thus, the proposed TVANUI provides a useful variable for urban area mapping and analysis on regional scale, as well as for urbanization dynamics using time-series DMSP/OLS and related satellite data.

Cloud-based computation for accelerating vegetation mapping and change detection at regional to national scales

Science.gov (United States)

Matthew J. Gregory; Zhiqiang Yang; David M. Bell; Warren B. Cohen; Sean Healey; Janet L. Ohmann; Heather M. Roberts

2015-01-01

Mapping vegetation and landscape change at fine spatial scales is needed to inform natural resource and conservation planning, but such maps are expensive and time-consuming to produce. For Landsat-based methodologies, mapping efforts are hampered by the daunting task of manipulating multivariate data for millions to billions of pixels. The advent of cloud-based...

Model of Peatland Vegetation Species using HyMap Image and Machine Learning

Science.gov (United States)

Dayuf Jusuf, Muhammad; Danoedoro, Projo; Muljo Sukojo, Bangun; Hartono

2017-12-01

Species Tumih / Parepat (Combretocarpus-rotundatus Mig. Dancer) family Anisophylleaceae and Meranti (Shorea Belangerang, Shorea Teysmanniana Dyer ex Brandis) family Dipterocarpaceae is a group of vegetation species distribution model. Species pioneer is predicted as an indicator of the succession of ecosystem restoration of tropical peatland characteristics and extremely fragile (unique) in the endemic hot spot of Sundaland. Climate change projections and conservation planning are hot topics of current discussion, analysis of alternative approaches and the development of combinations of species projection modelling algorithms through geospatial information systems technology. Approach model to find out the research problem of vegetation level based on the machine learning hybrid method, wavelet and artificial neural networks. Field data are used as a reference collection of natural resource field sample objects and biodiversity assessment. The testing and training ANN data set iterations times 28, achieve a performance value of 0.0867 MSE value is smaller than the ANN training data, above 50%, and spectral accuracy 82.1 %. Identify the location of the sample point position of the Tumih / Parepat vegetation species using HyMap Image is good enough, at least the modelling, design of the species distribution can reach the target in this study. The computation validation rate above 90% proves the calculation can be considered.

Mapping Aquatic Vegetation in a Large, Shallow Eutrophic Lake: A Frequency-Based Approach Using Multiple Years of MODIS Data

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Xiaohan Liu

2015-08-01

Full Text Available Aquatic vegetation serves many important ecological and socioeconomic functions in lake ecosystems. The presence of floating algae poses difficulties for accurately estimating the distribution of aquatic vegetation in eutrophic lakes. We present an approach to map the distribution of aquatic vegetation in Lake Taihu (a large, shallow eutrophic lake in China and reduce the influence of floating algae on aquatic vegetation mapping. Our approach involved a frequency analysis over a 2003–2013 time series of the floating algal index (FAI based on moderate-resolution imaging spectroradiometer (MODIS data. Three phenological periods were defined based on the vegetation presence frequency (VPF and the growth of algae and aquatic vegetation: December and January composed the period of wintering aquatic vegetation; February and March composed the period of prolonged coexistence of algal blooms and wintering aquatic vegetation; and June to October was the peak period of the coexistence of algal blooms and aquatic vegetation. By comparing and analyzing the satellite-derived aquatic vegetation distribution and 244 in situ measurements made in 2013, we established a FAI threshold of −0.025 and VPF thresholds of 0.55, 0.45 and 0.85 for the three phenological periods. We validated the accuracy of our approach by comparing the results between the satellite-derived maps and the in situ results obtained from 2008–2012. The overall classification accuracy was 87%, 81%, 77%, 88% and 73% in the five years from 2008–2012, respectively. We then applied the approach to the MODIS images from 2003–2013 and obtained the total area of the aquatic vegetation, which varied from 265.94 km2 in 2007 to 503.38 km2 in 2008, with an average area of 359.62 ± 69.20 km2 over the 11 years. Our findings suggest that (1 the proposed approach can be used to map the distribution of aquatic vegetation in eutrophic algae-rich waters and (2 dramatic changes occurred in the

Mapping agroecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images

Science.gov (United States)

Menenti, M.; Azzali, S.; Verhoef, W.; Van Swol, R.

1993-01-01

Examples are presented of applications of a fast Fourier transform algorithm to analyze time series of images of Normalized Difference Vegetation Index values. The results obtained for a case study on Zambia indicated that differences in vegetation development among map units of an existing agroclimatic map were not significant, while reliable differences were observed among the map units obtained using the Fourier analysis.

Rescuing and Sharing Historical Vegetation Data for Ecological Analysis: The California Vegetation Type Mapping Project

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Maggi Kelly

2016-10-01

Full Text Available Research efforts that synthesize historical and contemporary ecological data with modeling approaches improve our understanding of the complex response of species, communities, and landscapes to changing biophysical conditions through time and in space. Historical ecological data are particularly important in this respect. There are remaining barriers that limit such data synthesis, and technological improvements that make multiple diverse datasets more readily available for integration and synthesis are needed. This paper presents one case study of the Wieslander Vegetation Type Mapping project in California and highlights the importance of rescuing, digitizing and sharing historical datasets. We review the varied ecological uses of the historical collection: the vegetation maps have been used to understand legacies of land use change and plan for the future; the plot data have been used to examine changes to chaparral and forest communities around the state and to predict community structure and shifts under a changing climate; the photographs have been used to understand changing vegetation structure; and the voucher specimens in combination with other specimen collections have been used for large scale distribution modeling efforts. The digitization and sharing of the data via the web has broadened the scope and scale of the types of analysis performed. Yet, additional research avenues can be pursued using multiple types of VTM data, and by linking VTM data with contemporary data. The digital VTM collection is an example of a data infrastructure that expands the potential of large scale research through the integration and synthesis of data drawn from numerous data sources; its journey from analog to digital is a cautionary tale of the importance of finding historical data, digitizing it with best practices, linking it with other datasets, and sharing it with the research community.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

Science.gov (United States)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Predictive Mapping of Dwarf Shrub Vegetation in an Arid High Mountain Ecosystem Using Remote Sensing and Random Forests

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Kim André Vanselow

2014-07-01

Full Text Available In many arid mountains, dwarf shrubs represent the most important fodder and firewood resources; therefore, they are intensely used. For the Eastern Pamirs (Tajikistan, they are assumed to be overused. However, empirical evidence on this issue is lacking. We aim to provide a method capable of mapping vegetation in this mountain desert. We used random forest models based on remote sensing data (RapidEye, ASTER GDEM and 359 plots to predictively map total vegetative cover and the distribution of the most important firewood plants, K. ceratoides and A. leucotricha. These species were mapped as present in 33.8% of the study area (accuracy 90.6%. The total cover of the dwarf shrub communities ranged from 0.5% to 51% (per pixel. Areas with very low cover were limited to the vicinity of roads and settlements. The model could explain 80.2% of the total variance. The most important predictor across the models was MSAVI2 (a spectral vegetation index particularly invented for low-cover areas. We conclude that the combination of statistical models and remote sensing data worked well to map vegetation in an arid mountainous environment. With this approach, we were able to provide tangible data on dwarf shrub resources in the Eastern Pamirs and to relativize previous reports about their extensive depletion.

Mapping vegetation patterns in arable land using the models STICS and DAISY

Science.gov (United States)

Heuer, Antje; Casper, Markus

2010-05-01

Several statistical methods exist to detect spatial and / or temporal variability with regard to ecological data-analysis: Semivariance-analysis, Trend surface analysis, Kriging, Voronoi polygons, Moran's I and Mantel-test, to mention just some of them. In this contribution, we concentrate on spatial vegetation patterns within the soil-vegetation-atmosphere (SVAT) system. Using variography, spatial analysis with a geographic information system and self-organizing maps, spatial patterns of yield have been isolated in an agro-ecosystem (see poster contribution EGU 2009, EGU2009-8948). Data were derived from two agricultural plots, each about 5 hectare, in the area of Newel, located in Western Palatinate, Germany. The plots have been conventionally cultivated with a crop rotation of winter rape, winter wheat and spring barley. The aim of the present study is to find out if the existing natural spatial patterns can be mapped by means of SVAT models. If so, the discretization of a landscape according to its spatial patterns could be the basis for parameterization of SVAT models in order to model soil-vegetation-atmosphere interaction over a large area, that is for up-scaling. For this purpose the SVAT models STICS (developed by INRA, France) and DAISY (developed at Tåstrup University, Denmark) are applied. After a wide sensitivity analysis both models are parameterized with field data according to the given situation of each of the detected spatial patterns. The results of the simulation per representative location of a pattern are validated first with field data concerning yield, soil water content and soil nitrogen; besides, above ground dry matter, root depth and specific stress indices are used for validation. The conclusions that can be made with regard to up-scaling are discussed in detail. In a second step the results of the STICS model are compared with those of the DAISY model to analyse the models' behaviour, to get further knowledge about the inner structure

Vegetation - Napa County and Blue Ridge Berryessa [ds201

Data.gov (United States)

California Department of Resources — In 1995, the Manual of California Vegetation (MCV) introduced a quantitatively based method for classifying and mapping vegetation in California. In 2002 Department...

Vegetation - Napa County and Blue Ridge Berryessa [ds201

Data.gov (United States)

California Natural Resource Agency — In 1995, the Manual of California Vegetation (MCV) introduced a quantitatively based method for classifying and mapping vegetation in California. In 2002 Department...

The integration of GPS, vegetation mapping and GIS in ecological and behavioural studies

Directory of Open Access Journals (Sweden)

Steven Mark Rutter

2007-07-01

Full Text Available Global Positioning System (GPS satellite navigation receivers are increasingly being used in ecological and behavioural studies to track the movements of animals in relation to the environments in which they live and forage. Concurrent recording of the animal's foraging behaviour (e.g. from jaw movement recording allows foraging locations to be determined. By combining the animal GPS movement and foraging data with habitat and vegetation maps using a Geographical Information System (GIS it is possible to relate animal movement and foraging location to landscape and habitat features and vegetation types. This powerful approach is opening up new opportunities to study the spatial aspects of animal behaviour, especially foraging behaviour, with far greater precision and objectivity than before. Advances in GPS technology now mean that sub-metre precision systems can be used to track animals, extending the range of application of this technology from landscape and habitat scale to paddock and patch scale studies. As well as allowing ecological hypotheses to be empirically tested at the patch scale, the improvements in precision are also leading to the approach being increasing extended from large scale ecological studies to smaller (paddock scale agricultural studies. The use of sub-metre systems brings both new scientific opportunities and new technological challenges. For example, fitting all of the animals in a group with sub-metre precision GPS receivers allows their relative inter-individual distances to be precisely calculated, and their relative orientations can be derived from data from a digital compass fitted to each receiver. These data, analyzed using GIS, could give new insights into the social behaviour of animals. However, the improvements in precision with which the animals are being tracked also needs equivalent improvements in the precision with which habitat and vegetation are mapped. This needs some degree of automation, as

A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates

Directory of Open Access Journals (Sweden)

Ying Cai

2012-09-01

Full Text Available In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT, the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%–93.3% and overall (92.0%–93.1% accuracies. Our

National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio

Science.gov (United States)

Hop, Kevin D.; Drake, J.; Strassman, Andrew C.; Hoy, Erin E.; Menard, Shannon; Jakusz, J.W.; Dieck, J.J.

2013-01-01

information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type.A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha.Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent.A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval.The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table

The Importance of Temporal and Spatial Vegetation Structure Information in Biotope Mapping Schemes: A Case Study in Helsingborg, Sweden

Science.gov (United States)

Gao, Tian; Qiu, Ling; Hammer, Mårten; Gunnarsson, Allan

2012-02-01

Temporal and spatial vegetation structure has impact on biodiversity qualities. Yet, current schemes of biotope mapping do only to a limited extend incorporate these factors in the mapping. The purpose of this study is to evaluate the application of a modified biotope mapping scheme that includes temporal and spatial vegetation structure. A refined scheme was developed based on a biotope classification, and applied to a green structure system in Helsingborg city in southern Sweden. It includes four parameters of vegetation structure: continuity of forest cover, age of dominant trees, horizontal structure, and vertical structure. The major green structure sites were determined by interpretation of panchromatic aerial photographs assisted with a field survey. A set of biotope maps was constructed on the basis of each level of modified classification. An evaluation of the scheme included two aspects in particular: comparison of species richness between long-continuity and short-continuity forests based on identification of woodland continuity using ancient woodland indicators (AWI) species and related historical documents, and spatial distribution of animals in the green space in relation to vegetation structure. The results indicate that (1) the relationship between forest continuity: according to verification of historical documents, the richness of AWI species was higher in long-continuity forests; Simpson's diversity was significantly different between long- and short-continuity forests; the total species richness and Shannon's diversity were much higher in long-continuity forests shown a very significant difference. (2) The spatial vegetation structure and age of stands influence the richness and abundance of the avian fauna and rabbits, and distance to the nearest tree and shrub was a strong determinant of presence for these animal groups. It is concluded that continuity of forest cover, age of dominant trees, horizontal and vertical structures of vegetation

Vegetation - Suisun Marsh 2000 [ds161

Data.gov (United States)

California Natural Resource Agency — This vegetation mapping project of Suisun Marsh blends ground-based classification, aerial photo interpretation, and GIS editing and processing. The method is based...

Vegetation - Suisun Marsh 1999 [ds160

Data.gov (United States)

California Natural Resource Agency — This vegetation mapping project of Suisun Marsh blends ground-based classification, aerial photo interpretation, and GIS editing and processing. The method is based...

Vegetation - Suisun Marsh 2003 [ds162

Data.gov (United States)

California Natural Resource Agency — This vegetation mapping project of Suisun Marsh blends ground-based classification, aerial photo interpretation, and GIS editing and processing. The method is based...

SACRIFICING THE ECOLOGICAL RESOLUTION OF VEGETATION MAPS AT THE ALTAR OF THEMATIC ACCURACY: ASSESSED MAP ACCURACIES FOR HIERARCHICAL VEGETATION CLASSIFICATIONS IN THE EASTERN GREAT BASIN OF THE SOUTHWEST REGIONAL GAP ANALYSIS PROJECT (SW REGAP)

Science.gov (United States)

The Southwest Regional Gap Analysis Project (SW ReGAP) improves upon previous GAP projects conducted in Arizona, Colorado, Nevada, New Mexico, and Utah to provide a consistent, seamless vegetation map for this large and ecologically diverse geographic region. Nevada's compone...

A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data

Science.gov (United States)

Stibig, H.-J.; Belward, A.S.; Roy, P.S.; Rosalina-Wasrin, U.; Agrawal, S.; Joshi, P.K.; ,; Beuchle, R.; Fritz, S.; Mubareka, S.; Giri, C.

2007-01-01

Aim  Our aim was to produce a uniform ‘regional’ land-cover map of South and Southeast Asia based on ‘sub-regional’ mapping results generated in the context of the Global Land Cover 2000 project.Location  The ‘region’ of tropical and sub-tropical South and Southeast Asia stretches from the Himalayas and the southern border of China in the north, to Sri Lanka and Indonesia in the south, and from Pakistan in the west to the islands of New Guinea in the far east.Methods  The regional land-cover map is based on sub-regional digital mapping results derived from SPOT-VEGETATION satellite data for the years 1998–2000. Image processing, digital classification and thematic mapping were performed separately for the three sub-regions of South Asia, continental Southeast Asia, and insular Southeast Asia. Landsat TM images, field data and existing national maps served as references. We used the FAO (Food and Agriculture Organization) Land Cover Classification System (LCCS) for coding the sub-regional land-cover classes and for aggregating the latter to a uniform regional legend. A validation was performed based on a systematic grid of sample points, referring to visual interpretation from high-resolution Landsat imagery. Regional land-cover area estimates were obtained and compared with FAO statistics for the categories ‘forest’ and ‘cropland’.Results  The regional map displays 26 land-cover classes. The LCCS coding provided a standardized class description, independent from local class names; it also allowed us to maintain the link to the detailed sub-regional land-cover classes. The validation of the map displayed a mapping accuracy of 72% for the dominant classes of ‘forest’ and ‘cropland’; regional area estimates for these classes correspond reasonably well to existing regional statistics.Main conclusions  The land-cover map of South and Southeast Asia provides a synoptic view of the distribution of land cover of tropical and sub

Mapping vegetation communities of the Karkonosze National Park using APEX hyperspectral data and Support Vector Machines

OpenAIRE

Marcinkowska Adriana; Zagajewski Bogdan; Ochtyra Adrian; Jarocińska Anna; Raczko Edwin; Kupková Lucie; Stych Premysl; Meuleman Koen

2014-01-01

This research aims to discover the potential of hyperspectral remote sensing data for mapping mountain vegetation ecosystems. First, the importance of mountain ecosystems to the global system should be stressed due to mountainous ecosystems forming a very sensitive indicator of global climate change. Furthermore, a variety of biotic and abiotic factors influence the spatial distribution of vegetation in the mountains, producing a diverse mosaic leading to high biodiversity.

Wieslander Vegetation

Data.gov (United States)

California Natural Resource Agency — Digital version of the 1945 California Vegetation Type Maps by A. E. Wieslander of the U.S. Forest Service. Source scale of maps are 1:100,000. These compiled maps...

Pattern Analysis of Vegetation and Structure Mapping of Yard Plant in Gatak District, Sukoharjo

Directory of Open Access Journals (Sweden)

Sofyan Anif

2004-01-01

Full Text Available Target of research is to know 1 level of type variety (diversitas and mount the closeness (densitas of lawn crop which conducting in region of District of Gatak of Sub Province Sukoharjo; 2 pattern of mapping of lawn crop which conducting in region District of Gatak of Sub Province Sukoharjo of pursuant to variety level and its closeness. This research is field survey done with the method of multi stage that is stratified purposive of sampling and random sampling. Focus the survey is does the stocktaking of lawn crop which conducting in house lawn. To know the structure of vegetate data processed by using formula Cox (1989 to know the closeness level, while to know the level of species variety, data analyzed to use the index of diversities Simpson. Pursuant to result of inferential solution and research 1 result analyze the structure of vegetate of lawn crop indicate that (a District Gatak have the level of high diversities lawn crop, with the index diversities of equal to 0,84159 and index predominate equal to 0,15841, and also highest PIE 0,20657 and PIE lowerest of equal to 0,00032. Species of lawn crop having high domination that is melinjo (Gnetum gnemon, (b closeness of lawn crop at every countryside in District Gatak of included in category very meeting of because  relied on by a closeness value of every countryside more than 75%. Crop found in research are having high closeness level for example: melinjo, banana, mango, rambutan, papaya, tapioca, and coconut, while crop having low closeness level for example: jambu mete, tapak doro, flower pukul empat; and 2 mapping of lawn crop cover the function value and amount of lawn crop found by a number of 57 type of lawn crop found in researh area, can be grouped to become 5 faction that is drug crop, vegetable faction, fruit crop, decorative crop, and protector crop.

An analysis on vegetation pattern of ecotone in North China

Energy Technology Data Exchange (ETDEWEB)

Jia, J.C.; Zhang, H.Y. [North China Electric Power Univ., Beijing (China). Energy and Environmental Research Center

2008-07-01

Vegetation pattern is influenced by several natural factors, including climatic elements, elevation factors and soil conditions. Since soil formation and soil types are influenced by water-temperature conditions, much can be learned about vegetation distribution patterns by studying the relationship between water-temperature conditions and vegetation distribution. This paper presented the results of a study whose purpose was to provide scientific evidence for exploiting natural resources, planting trees, and restoring grassland from cropland. A warmth index (WI ) and humidity index (HI) were used to examine the relation between the distribution of vegetation and the water-temperature condition in North China's ecotone, the transition area between two adjacent but different plant communities, including steppe, bush and forest ecosystems. A vegetation map of the study site was digitized and then converted into a vegetation grid map from which 17 different vegetation types were chosen as the study object. A monthly mean temperature grid map and precipitation grid map of the study site were made based on the method of spatial interpolation, by using 119 meteorological data for 50 years during the period from 1951 to 2000. The thermal distribution curves and humidity distribution curves of 17 vegetation types in North China, determined the whole range and optimum range of WI and HI of 17 vegetation types. The relative proportion of each vegetation type distributed in the optimum range of WI and HI were calculated. The vegetation pattern was analyzed according to the WI and HI standard, and was described by species and their relative amount. 10 refs., 5 tabs., 3 figs.

REMOTE SENSING METHODS FOR PHYTOMASS ESTIMATION AND MAPPING OF TUNDRA VEGETATION

Directory of Open Access Journals (Sweden)

Elena Golubeva

2010-01-01

Full Text Available Mapping of above-ground phytomass provides a baseline for monitoring climate-induced changes, especially in the northern regions. This is important for practical applications, such as assessing quality of pastures and defining reindeer migration routes. Use of very high resolution (1 m and better aerial and satellite images is of particular interest, because changes at the level of individual trees can be monitored over comparatively large areas. The goals of this study were to: i establish relations between phytomass values and structure and spectral reflectance derived from ground research and ii upscale from ground data to QuickBird satellite imagery to compile maps of above-ground phytomass for key sites. As a result, the study has produced a preliminary map of the above-ground phytomass of lichens for a test site in the Tuliok Valley, Khibiny Mountains, central Kola Peninsula, Russia, with phytomass values well in line with fieldwork data.

Mapping and conservation importance rating of the South African coastal vegetation as an aid to development planning

CSIR Research Space (South Africa)

Raal, PA

1996-05-01

Full Text Available ELSEVIER Landscape and Urban Planning 34 (1996) 389-400 Mapping and conservation importance rating of the South African coastal vegetation as an aid to development planning P.A. Raal *, M.E.R. Bums Division of Earth, Marine...-incide with the local authority administrative boundaries. Areas which have not yet been mapped are also shown. P.A. Raal, M.E.R. Burns/ Landscape and Urban Planning 34 (1996) 389-400 391 a botanical map series which can be used...

Evaluation of ALOS PALSAR Data for High-Resolution Mapping of Vegetated Wetlands in Alaska

Directory of Open Access Journals (Sweden)

Daniel Clewley

2015-06-01

Full Text Available As the largest natural source of methane, wetlands play an important role in the carbon cycle. High-resolution maps of wetland type and extent are required to quantify wetland responses to climate change. Mapping northern wetlands is particularly important because of a disproportionate increase in temperatures at higher latitudes. Synthetic aperture radar data from a spaceborne platform can be used to map wetland types and dynamics over large areas. Following from earlier work by Whitcomb et al. (2009 using Japanese Earth Resources Satellite (JERS-1 data, we applied the “random forests” classification algorithm to variables from L-band ALOS PALSAR data for 2007, topographic data (e.g., slope, elevation and locational information (latitude, longitude to derive a map of vegetated wetlands in Alaska, with a spatial resolution of 50 m. We used the National Wetlands Inventory and National Land Cover Database (for upland areas to select training and validation data and further validated classification results with an independent dataset that we created. A number of improvements were made to the method of Whitcomb et al. (2009: (1 more consistent training data in upland areas; (2 better distribution of training data across all classes by taking a stratified random sample of all available training pixels; and (3 a more efficient implementation, which allowed classification of the entire state as a single entity (rather than in separate tiles, which eliminated discontinuities at tile boundaries. The overall accuracy for discriminating wetland from upland was 95%, and the accuracy at the level of wetland classes was 85%. The total area of wetlands mapped was 0.59 million km2, or 36% of the total land area of the state of Alaska. The map will be made available to download from NASA’s wetland monitoring website.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

Science.gov (United States)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Kuchler Vegetation

Data.gov (United States)

California Natural Resource Agency — Digital version of potential natural plant communites as compiled and published on 'Map of the Natural Vegetation of California' by A. W. Kuchler, 1976. Source map...

Cost-Effectiveness of Seven Approaches to Map Vegetation Communities — A Case Study from Northern Australia’s Tropical Savannas

Directory of Open Access Journals (Sweden)

Stuart Phinn

2013-01-01

Full Text Available Vegetation communities are traditionally mapped from aerial photography interpretation. Other semi-automated methods include pixel- and object-based image analysis. While these methods have been used for decades, there is a lack of comparative research. We evaluated the cost-effectiveness of seven approaches to map vegetation communities in a northern Australia’s tropical savanna environment. The seven approaches included: (1. aerial photography interpretation, (2. pixel-based image-only classification (Maximum Likelihood Classifier, (3. pixel-based integrated classification (Maximum Likelihood Classifier, (4. object-based image-only classification (nearest neighbor classifier, (5. object-based integrated classification (nearest neighbor classifier, (6. object-based image-only classification (step-wise ruleset, and (7. object-based integrated classification (step-wise ruleset. Approach 1 was applied to 1:50,000 aerial photography and approaches 2–7 were applied to SPOT5 and Landsat5 TM multispectral data. The integrated approaches (3, 5 and 7 included ancillary data (a digital elevation model, slope model, normalized difference vegetation index and hydrology information. The cost-effectiveness was assessed taking into consideration the accuracy and costs associated with each classification approach and image dataset. Accuracy was assessed in terms of overall accuracy and the costs were evaluated using four main components: field data acquisition and preparation, image data acquisition and preparation, image classification and accuracy assessment. Overall accuracy ranged from 28%, for the image-only pixel-based approach, to 67% for the aerial photography interpretation, while total costs ranged from AU$338,000 to AU$388,180 (Australian dollars, for the pixel-based image-only classification and aerial photography interpretation respectively. The most labor-intensive component was field data acquisition and preparation, followed by image data

Application of Cocktail method in vegetation classification

Directory of Open Access Journals (Sweden)

Hamed Asadi

2016-09-01

Full Text Available This study intends to assess the application of Cocktail method in the classification of large vegetation databases. For this purpose, Buxus hyrcana dataset consisted of 442 relevés with 89 species were used and by the modified TWINSPAN. For running the Cocktail method, first primarily classification was done by modified TWINSPAN, and by performing phi analysis in the groups resulted five species were selected which had the highest fidelity value. Then sociological species groups were formed by examining co-occurrence of these 5 species with other species in the database. 21 plant communities belongs to 6 variant, 17 sub associations, 11 associations, 4 alliance, 1 order and 1 class were recognized by assigning 379 releves to the sociological species groups by using logical formulas. Also, 63 releves by the logical formula were not assigned to any sociological species groups, by FPFI index were assigned to the sociological species groups which had the most index value. According to 91% classification agreement with Brown-Blanquet classification and Cocktail classification, we suggest Cocktail method to vegetation scientists as an efficient alternative of Braun-Blanquet method to classify large vegetation databases.

Mapping Mixed Methods Research: Methods, Measures, and Meaning

Science.gov (United States)

Wheeldon, J.

2010-01-01

This article explores how concept maps and mind maps can be used as data collection tools in mixed methods research to combine the clarity of quantitative counts with the nuance of qualitative reflections. Based on more traditional mixed methods approaches, this article details how the use of pre/post concept maps can be used to design qualitative…

Mapping the Wetland Vegetation Communities of the Australian Great Artesian Basin Springs Using SAM, Mtmf and Spectrally Segmented PCA Hyperspectral Analyses

Science.gov (United States)

White, D. C.; Lewis, M. M.

2012-07-01

The Australian Great Artesian Basin (GAB) supports a unique and diverse range of groundwater dependent wetland ecosystems termed GAB springs. In recent decades the ecological sustainability of the springs has become uncertain as demands on this iconic groundwater resource increase. The impacts of existing water extractions for mining and pastoral activities are unknown. This situation is compounded by the likelihood of future increasing demand for extractions. Hyperspectral remote sensing provides the necessary spectral and spatial detail to discriminate wetland vegetation communities. Therefore the objectives of this paper are to discriminate the spatial extent and distribution of key spring wetland vegetation communities associated with the GAB springs evaluating three hyperspectral techniques: Spectral Angle Mapper (SAM), Mixture Tuned Matched Filtering (MTMF) and Spectrally Segmented PCA. In addition, to determine if the hyperspectral techniques developed can be applied at a number of sites representative of the range of spring formations and geomorphic settings and at two temporal intervals. Two epochs of HyMap airborne hyperspectral imagery were captured for this research in March 2009 and April 2011 at a number of sites representative of the floristic and geomorphic diversity of GAB spring groups/complexes within South Australia. Colour digital aerial photography at 30 cm GSD was acquired concurrently with the HyMap imagery. The image acquisition coincided with a field campaign of spectroradiometry measurements and a botanical survey. To identify key wavebands which have the greatest capability to discriminate vegetation communities of the GAB springs and surrounding area three hyperspectral data reduction techniques were employed: (i) Spectrally Segmented PCA (SSPCA); (ii) the Minimum Noise Transform (MNF); and (iii) the Pixel Purity Index (PPI). SSPCA was applied to NDVI-masked vegetation portions of the HyMap imagery with wavelength regions spectrally

Development of a high-resolution binational vegetation map of the Santa Cruz River riparian corridor and surrounding watershed, southern Arizona and northern Sonora, Mexico

Science.gov (United States)

Wallace, Cynthia S.A.; Villarreal, Miguel L.; Norman, Laura M.

2011-01-01

This report summarizes the development of a binational vegetation map developed for the Santa Cruz Watershed, which straddles the southern border of Arizona and the northern border of Sonora, Mexico. The map was created as an environmental input to the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM) that is being created by the U.S. Geological Survey for the watershed. The SCWEPM is a map-based multicriteria evaluation tool that allows stakeholders to explore tradeoffs between valued ecosystem services at multiple scales within a participatory decision-making process. Maps related to vegetation type and are needed for use in modeling wildlife habitat and other ecosystem services. Although detailed vegetation maps existed for the U.S. side of the border, there was a lack of consistent data for the Santa Cruz Watershed in Mexico. We produced a binational vegetation classification of the Santa Cruz River riparian habitat and watershed vegetation based on NatureServe Terrestrial Ecological Systems (TES) units using Classification And Regression Tree (CART) modeling. Environmental layers used as predictor data were derived from a seasonal set of Landsat Thematic Mapper (TM) images (spring, summer, and fall) and from a 30-meter digital-elevation-model (DEM) grid. Because both sources of environmental data are seamless across the international border, they are particularly suited to this binational modeling effort. Training data were compiled from existing field data for the riparian corridor and data collected by the NM-GAP (New Mexico Gap Analysis Project) team for the original Southwest Regional Gap Analysis Project (SWReGAP) modeling effort. Additional training data were collected from core areas of the SWReGAP classification itself, allowing the extrapolation of the SWReGAP mapping into the Mexican portion of the watershed without collecting additional training data.

Mapping post-fire forest regeneration and vegetation recovery using a combination of very high spatial resolution and hyperspectral satellite imagery

Science.gov (United States)

Mitri, George H.; Gitas, Ioannis Z.

2013-02-01

Careful evaluation of forest regeneration and vegetation recovery after a fire event provides vital information useful in land management. The use of remotely sensed data is considered to be especially suitable for monitoring ecosystem dynamics after fire. The aim of this work was to map post-fire forest regeneration and vegetation recovery on the Mediterranean island of Thasos by using a combination of very high spatial (VHS) resolution (QuickBird) and hyperspectral (EO-1 Hyperion) imagery and by employing object-based image analysis. More specifically, the work focused on (1) the separation and mapping of three major post-fire classes (forest regeneration, other vegetation recovery, unburned vegetation) existing within the fire perimeter, and (2) the differentiation and mapping of the two main forest regeneration classes, namely, Pinus brutia regeneration, and Pinus nigra regeneration. The data used in this study consisted of satellite images and field observations of homogeneous regenerated and revegetated areas. The methodology followed two main steps: a three-level image segmentation, and, a classification of the segmented images. The process resulted in the separation of classes related to the aforementioned objectives. The overall accuracy assessment revealed very promising results (approximately 83.7% overall accuracy, with a Kappa Index of Agreement of 0.79). The achieved accuracy was 8% higher when compared to the results reported in a previous work in which only the EO-1 Hyperion image was employed in order to map the same classes. Some classification confusions involving the classes of P. brutia regeneration and P. nigra regeneration were observed. This could be attributed to the absence of large and dense homogeneous areas of regenerated pine trees in the study area.

Vegetation - Suisun Marsh, Change 1999 to 2000 [ds163

Data.gov (United States)

California Natural Resource Agency — This vegetation mapping project of Suisun Marsh blends ground-based classification, aerial photo interpretation, and GIS editing and processing. The method is based...

Vegetation - Suisun Marsh, Change 1999 to 2003 [ds164

Data.gov (United States)

California Natural Resource Agency — This vegetation mapping project of Suisun Marsh blends ground-based classification, aerial photo interpretation, and GIS editing and processing. The method is based...

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

Science.gov (United States)

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2015-08-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

Method of producing vegetable puree

DEFF Research Database (Denmark)

2004-01-01

A process for producing a vegetable puree, comprising the sequential steps of: a)crushing, chopping or slicing the vegetable into pieces of 1 to 30 mm; b) blanching the vegetable pieces at a temperature of 60 to 90°C; c) contacted the blanched vegetable pieces with a macerating enzyme activity; d......) blending the macerated vegetable pieces and obtaining a puree....

Soil Erosion Risk Map based on irregularity of the vegetative activity

Science.gov (United States)

Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

2016-04-01

Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified

Mapping Congo Basin vegetation types from 300 m and 1 km multi-sensor time series for carbon stocks and forest areas estimation

Directory of Open Access Journals (Sweden)

A. Verhegghen

2012-12-01

Full Text Available This study aims to contribute to the understanding of the Congo Basin forests by delivering a detailed map of vegetation types with an improved spatial discrimination and coherence for the whole Congo Basin region. A total of 20 land cover classes were described with the standardized Land Cover Classification System (LCCS developed by the FAO. Based on a semi-automatic processing chain, the Congo Basin vegetation types map was produced by combining 19 months of observations from the Envisat MERIS full resolution products (300 m and 8 yr of daily SPOT VEGETATION (VGT reflectances (1 km. Four zones (north, south and two central were delineated and processed separately according to their seasonal and cloud cover specificities. The discrimination between different vegetation types (e.g. forest and savannas was significantly improved thanks to the MERIS sharp spatial resolution. A better discrimination was achieved in cloudy areas by taking advantage of the temporal consistency of the SPOT VGT observations. This resulted in a precise delineation of the spatial extent of the rural complex in the countries situated along the Atlantic coast. Based on this new map, more accurate estimates of the surface areas of forest types were produced for each country of the Congo Basin. Carbon stocks of the Basin were evaluated to a total of 49 360 million metric tons. The regional scale of the map was an opportunity to investigate what could be an appropriate tree cover threshold for a forest class definition in the Congo Basin countries. A 30% tree cover threshold was suggested. Furthermore, the phenology of the different vegetation types was illustrated systematically with EVI temporal profiles. This Congo Basin forest types map reached a satisfactory overall accuracy of 71.5% and even 78.9% when some classes are aggregated. The values of the Cohen's kappa coefficient, respectively 0.64 and 0.76 indicates a result significantly better than random.

Mapping gains and losses in woody vegetation across global tropical drylands

DEFF Research Database (Denmark)

Tian, Feng; Brandt, Martin Stefan; Liu, Yi Y

2017-01-01

MODerate resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data to remove the interannual fluctuations of the woody leaf component. We revealed significant trends (P ... trend in the leaf component (VODleaf modeled from NDVI), indicating pronounced gradual growth/decline in woody vegetation not captured by traditional assessments. The method is validated using a unique record of ground measurements from the semiarid Sahel and shows a strong agreement between changes...

A method for climate and vegetation reconstruction through the inversion of a dynamic vegetation model

Energy Technology Data Exchange (ETDEWEB)

Garreta, Vincent; Guiot, Joel; Hely, Christelle [CEREGE, UMR 6635, CNRS, Universite Aix-Marseille, Europole de l' Arbois, Aix-en-Provence (France); Miller, Paul A.; Sykes, Martin T. [Lund University, Department of Physical Geography and Ecosystems Analysis, Geobiosphere Science Centre, Lund (Sweden); Brewer, Simon [Universite de Liege, Institut d' Astrophysique et de Geophysique, Liege (Belgium); Litt, Thomas [University of Bonn, Paleontological Institute, Bonn (Germany)

2010-08-15

Climate reconstructions from data sensitive to past climates provide estimates of what these climates were like. Comparing these reconstructions with simulations from climate models allows to validate the models used for future climate prediction. It has been shown that for fossil pollen data, gaining estimates by inverting a vegetation model allows inclusion of past changes in carbon dioxide values. As a new generation of dynamic vegetation model is available we have developed an inversion method for one model, LPJ-GUESS. When this novel method is used with high-resolution sediment it allows us to bypass the classic assumptions of (1) climate and pollen independence between samples and (2) equilibrium between the vegetation, represented as pollen, and climate. Our dynamic inversion method is based on a statistical model to describe the links among climate, simulated vegetation and pollen samples. The inversion is realised thanks to a particle filter algorithm. We perform a validation on 30 modern European sites and then apply the method to the sediment core of Meerfelder Maar (Germany), which covers the Holocene at a temporal resolution of approximately one sample per 30 years. We demonstrate that reconstructed temperatures are constrained. The reconstructed precipitation is less well constrained, due to the dimension considered (one precipitation by season), and the low sensitivity of LPJ-GUESS to precipitation changes. (orig.)

A comparison of two different approaches for mapping potential ozone damage to vegetation. A model study

International Nuclear Information System (INIS)

Simpson, D.; Ashmore, M.R.; Emberson, L.; Tuovinen, J.-P.

2007-01-01

Two very different types of approaches are currently in use today for indicating risk of ozone damage to vegetation in Europe. One approach is the so-called AOTX (accumulated exposure over threshold of X ppb) index, which is based upon ozone concentrations only. The second type of approach entails an estimate of the amount of ozone entering via the stomates of vegetation, the AFstY approach (accumulated stomatal flux over threshold of Y nmol m -2 s -1 ). The EMEP chemical transport model is used to map these different indicators of ozone damage across Europe, for two illustrative vegetation types, wheat and beech forests. The results show that exceedences of critical levels for either type of indicator are widespread, but that the indicators give very different spatial patterns across Europe. Model simulations for year 2020 scenarios suggest reductions in risks of vegetation damage whichever indicator is used, but suggest that AOT40 is much more sensitive to emission control than AFstY values. - Model calculations of AOT40 and AFstY show very different spatial variations in the risks of ozone damage to vegetation

Fuel loads and fuel type mapping

Science.gov (United States)

Chuvieco, Emilio; Riaño, David; Van Wagtendonk, Jan W.; Morsdof, Felix; Chuvieco, Emilio

2003-01-01

Correct description of fuel properties is critical to improve fire danger assessment and fire behaviour modeling, since they guide both fire ignition and fire propagation. This chapter deals with properties of fuel that can be considered static in short periods of time: biomass loads, plant geometry, compactness, etc. Mapping these properties require a detail knowledge of vegetation vertical and horizontal structure. Several systems to classify the great diversity of vegetation characteristics in few fuel types are described, as well as methods for mapping them with special emphasis on those based on remote sensing images.

A NEW HABITAT CLASSIFICATION AND MANUAL FOR STANDARDIZED HABITAT MAPPING

Directory of Open Access Journals (Sweden)

A. KUN

2007-01-01

Full Text Available Today the documentation of natural heritage with scientific methods but for conservation practice – like mapping of actual vegetation – becomes more and more important. For this purpose mapping guides containing only the names and descriptions of vegetation types are not sufficient. Instead, new, mapping-oriented vegetation classification systems and handbooks are needed. There are different standardised systems fitted to the characteristics of a region already published and used successfully for surveying large territories. However, detailed documentation of the aims and steps of their elaboration is still missing. Here we present a habitat-classification method developed specifically for mapping and the steps of its development. Habitat categories and descriptions reflect site conditions, physiognomy and species composition as well. However, for species composition much lower role was given deliberately than in the phytosociological systems. Recognition and mapping of vegetation types in the field is highly supported by a definition, list of subtypes and list of ‘types not belonging to this habitat category’. Our system is two-dimensional: the first dimension is habitat type, the other is naturalness based habitat quality. The development of the system was conducted in two steps, over 200 mappers already tested it over 7000 field days in different projects.

Reproducibility of crop surface maps extracted from Unmanned Aerial Vehicle (UAV) derived digital surface maps

KAUST Repository

Parkes, Stephen

2016-10-25

Crop height measured from UAVs fitted with commercially available RGB cameras provide an affordable alternative to retrieve field scale high resolution estimates. The study presents an assessment of between flight reproducibility of Crop Surface Maps (CSM) extracted from Digital Surface Maps (DSM) generated by Structure from Motion (SfM) algorithms. Flights were conducted over a centre pivot irrigation system covered with an alfalfa crop. An important step in calculating the absolute crop height from the UAV derived DSM is determining the height of the underlying terrain. Here we use automatic thresholding techniques applied to RGB vegetation index maps to classify vegetated and soil pixels. From interpolation of classified soil pixels, a terrain map is calculated and subtracted from the DSM. The influence of three different thresholding techniques on CSMs are investigated. Median Alfalfa crop heights determined with the different thresholding methods varied from 18cm for K means thresholding to 13cm for Otsu thresholding methods. Otsu thresholding also gave the smallest range of crop heights and K means thresholding the largest. Reproducibility of median crop heights between flight surveys was 4-6cm for all thresholding techniques. For the flight conducted later in the afternoon shadowing caused soil pixels to be classified as vegetation in key locations around the domain, leading to lower crop height estimates. The range of crop heights was similar for both flights using K means thresholding (35-36cm), local minimum thresholding depended on whether raw or normalised RGB intensities were used to calculate vegetation indices (30-35cm), while Otsu thresholding had a smaller range of heights and varied most between flights (26-30cm). This study showed that crop heights from multiple survey flights are comparable, however, they were dependent on the thresholding method applied to classify soil pixels and the time of day the flight was conducted.

Reproducibility of crop surface maps extracted from Unmanned Aerial Vehicle (UAV) derived digital surface maps

KAUST Repository

Parkes, Stephen; McCabe, Matthew; Al-Mashhawari, Samir K.; Rosas, Jorge

2016-01-01

Crop height measured from UAVs fitted with commercially available RGB cameras provide an affordable alternative to retrieve field scale high resolution estimates. The study presents an assessment of between flight reproducibility of Crop Surface Maps (CSM) extracted from Digital Surface Maps (DSM) generated by Structure from Motion (SfM) algorithms. Flights were conducted over a centre pivot irrigation system covered with an alfalfa crop. An important step in calculating the absolute crop height from the UAV derived DSM is determining the height of the underlying terrain. Here we use automatic thresholding techniques applied to RGB vegetation index maps to classify vegetated and soil pixels. From interpolation of classified soil pixels, a terrain map is calculated and subtracted from the DSM. The influence of three different thresholding techniques on CSMs are investigated. Median Alfalfa crop heights determined with the different thresholding methods varied from 18cm for K means thresholding to 13cm for Otsu thresholding methods. Otsu thresholding also gave the smallest range of crop heights and K means thresholding the largest. Reproducibility of median crop heights between flight surveys was 4-6cm for all thresholding techniques. For the flight conducted later in the afternoon shadowing caused soil pixels to be classified as vegetation in key locations around the domain, leading to lower crop height estimates. The range of crop heights was similar for both flights using K means thresholding (35-36cm), local minimum thresholding depended on whether raw or normalised RGB intensities were used to calculate vegetation indices (30-35cm), while Otsu thresholding had a smaller range of heights and varied most between flights (26-30cm). This study showed that crop heights from multiple survey flights are comparable, however, they were dependent on the thresholding method applied to classify soil pixels and the time of day the flight was conducted.

Crestridge Vegetation Map [ds211

Data.gov (United States)

California Natural Resource Agency — This layer represents vegetation communities in the Department of Fish and Game's Crestridge Ecological Reserve. The County of San Diego, the Conservation Biology...

Remote sensing analysis of vegetation at the San Carlos Apache Reservation, Arizona and surrounding area

Science.gov (United States)

Norman, Laura M.; Middleton, Barry R.; Wilson, Natalie R.

2018-01-01

Mapping of vegetation types is of great importance to the San Carlos Apache Tribe and their management of forestry and fire fuels. Various remote sensing techniques were applied to classify multitemporal Landsat 8 satellite data, vegetation index, and digital elevation model data. A multitiered unsupervised classification generated over 900 classes that were then recoded to one of the 16 generalized vegetation/land cover classes using the Southwest Regional Gap Analysis Project (SWReGAP) map as a guide. A supervised classification was also run using field data collected in the SWReGAP project and our field campaign. Field data were gathered and accuracy assessments were generated to compare outputs. Our hypothesis was that a resulting map would update and potentially improve upon the vegetation/land cover class distributions of the older SWReGAP map over the 24,000  km2 study area. The estimated overall accuracies ranged between 43% and 75%, depending on which method and field dataset were used. The findings demonstrate the complexity of vegetation mapping, the importance of recent, high-quality-field data, and the potential for misleading results when insufficient field data are collected.

Golden Gate National Recreation Area Vegetation Inventory Project

Data.gov (United States)

California Natural Resource Agency — High resolution vegetation polygons mapped by the National Park Service. The vegetation units of this map were determined through stereoscopic interpretation of...

Vegetation Change in Interior Alaska Over the Last Four Decades

Science.gov (United States)

Huhman, H.; Dewitz, J.; Cristobal, J.; Prakash, A.

2017-12-01

The Arctic has become a generally warmer place over the past decades leading to earlier snowmelt, permafrost degradation and changing plant communities. One area in particular, vegetation change, is responding relatively rapidly to climate change, impacting the surrounding environment with changes to forest fire regime, forest type, forest resiliency, habitat availability for subsistence flora and fauna, hydrology, among others. To quantify changes in vegetation in the interior Alaska boreal forest over the last four decades, this study uses the National Land Cover Database (NLCD) decision-tree based classification methods, using both C5 and ERDAS Imagine software, to classify Landsat Surface Reflectance Images into the following NLCD-consistent vegetation classes: planted, herbaceous, shrubland, and forest (deciduous, evergreen and mixed). The results of this process are a total of four vegetation cover maps, that are freely accessible to the public, one for each decade in the 1980's, 1990's, 2000's, and a current map for 2017. These maps focus on Fairbanks, Alaska and the surrounding area covering approximately 36,140 square miles. The maps are validated with over 4,000 ground truth points collected through organizations such as the Landfire Project and the Long Term Ecological Research Network, as well as vegetation and soil spectra collected from the study area concurrent with the Landsat satellite over-passes with a Spectral Evolution PSR+ 3500 spectro-radiometer (0.35 - 2.5 μm). We anticipate these maps to be viewed by a wide user-community and may aid in preparing the residents of Alaska for changes in their subsistence food sources and will contribute to the scientific community in understanding the variety of changes that can occur in response to changing vegetation.

Vegetation - Anza-Borrego Desert State Park [ds165

Data.gov (United States)

California Natural Resource Agency — The Anza Borrego Desert State Park (ABDSP) Vegetation Map depicts vegetation within the Park and its surrounding environment. The map was prepared by the Department...

Mineral and Vegetation Maps of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada, Generated from ASTER Satellite Data

Science.gov (United States)

Rockwell, Barnaby W.

2010-01-01

Multispectral remote sensing data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were analyzed to identify and map minerals, vegetation groups, and volatiles (water and snow) in support of geologic studies of the Bodie Hills, Sweetwater Mountains, and Wassuk Range, California/Nevada. Digital mineral and vegetation mapping results are presented in both portable document format (PDF) and ERDAS Imagine format (.img). The ERDAS-format files are suitable for integration with other geospatial data in Geographic Information Systems (GIS) such as ArcGIS. The ERDAS files showing occurrence of 1) iron-bearing minerals, vegetation, and water, and 2) clay, sulfate, mica, carbonate, Mg-OH, and hydrous quartz minerals have been attributed according to identified material, so that the material detected in a pixel can be queried with the interactive attribute identification tools of GIS and image processing software packages (for example, the Identify Tool of ArcMap and the Inquire Cursor Tool of ERDAS Imagine). All raster data have been orthorectified to the Universal Transverse Mercator (UTM) projection using a projective transform with ground-control points selected from orthorectified Landsat Thematic Mapper data and a digital elevation model from the U.S. Geological Survey (USGS) National Elevation Dataset (1/3 arc second, 10 m resolution). Metadata compliant with Federal Geographic Data Committee (FGDC) standards for all ERDAS-format files have been included, and contain important information regarding geographic coordinate systems, attributes, and cross-references. Documentation regarding spectral analysis methodologies employed to make the maps is included in these cross-references.

Assessment of vegetation trends in drylands from time series of earth observation data

NARCIS (Netherlands)

Fensholt, R.; Horion, S.; Tagesson, T.; Ehammer, A.; Grogan, K.; Tian, F.; Huber, S.; Verbesselt, J.; Prince, S.D.; Tucker, C.J.; Rasmussen, K.

2015-01-01

This chapter summarizes approaches to the detection of dryland vegetation change and methods for observing spatio-temporal trends from space. An overview of suitable long-term Earth Observation (EO) based datasets for assessment of global dryland vegetation trends is provided and a status map of

Mapping Submerged Aquatic Vegetation Using RapidEye Satellite Data: The Example of Lake Kummerow (Germany

Directory of Open Access Journals (Sweden)

Christine Fritz

2017-07-01

Full Text Available Submersed aquatic vegetation (SAV is sensitive to changes in environmental conditions and plays an important role as a long-term indictor for the trophic state of freshwater lakes. Variations in water level height, nutrient condition, light availability and water temperature affect the growth and species composition of SAV. Detailed information about seasonal variations in littoral bottom coverage are still unknown, although these effects are expected to mask climate change-related long-term changes, as derived by snapshots of standard monitoring methods included in the European Water Framework Directive. Remote sensing offers concepts to map SAV quickly, within large areas, and at short intervals. This study analyses the potential of a semi-empirical method to map littoral bottom coverage by a multi-seasonal approach. Depth-invariant indices were calculated for four Atmospheric & Topographic Correction (ATCOR2 atmospheric corrected RapidEye data sets acquired at Lake Kummerow, Germany, between June and August 2015. RapidEye data evaluation was supported by in situ measurements of the diffuse attenuation coefficient of the water column and bottom reflectance. The processing chain was able to differentiate between SAV and sandy sediment. The successive increase of SAV coverage from June to August was correctly monitored. Comparisons with in situ and Google Earth imagery revealed medium accuracies (kappa coefficient = 0.61, overall accuracy = 72.2%. The analysed time series further revealed how water constituents and temporary surface phenomena such as sun glint or algal blooms influence the identification success of lake bottom substrates. An abundant algal bloom biased the interpretability of shallow water substrate such that a differentiation of sediments and SAV patches failed completely. Despite the documented limitations, mapping of SAV using RapidEye seems possible, even in eutrophic lakes.

Development of a Dynamic Web Mapping Service for Vegetation Productivity Using Earth Observation and in situ Sensors in a Sensor Web Based Approach

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Sytze de Bruin

2009-03-01

Full Text Available This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS. A prototype has been developed which provides daily maps of vegetation productivity for the Netherlands with a spatial resolution of 250 m. Daily available MODIS surface reflectance products and meteorological parameters obtained through a Sensor Observation Service (SOS were used as input for a vegetation productivity model. This paper presents the vegetation productivity model, the sensor data sources and the implementation of the automated processing facility. Finally, an evaluation is made of the opportunities and limitations of sensor web based approaches for the development of web services which combine both satellite and in situ sensor sources.

On the potential of long wavelength imaging radars for mapping vegetation types and woody biomass in tropical rain forests

Science.gov (United States)

Rignot, Eric J.; Zimmermann, Reiner; Oren, Ram

1995-01-01

In the tropical rain forests of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 100 kg/sq m in old, undisturbed floodplain stands, the P-band polarimetric radar data gathered in June of 1993 by the AIRSAR (Airborne Synthetic Aperture Radar) instrument separate most major vegetation formations and also perform better than expected in estimating woody biomass. The worldwide need for large scale, updated biomass estimates, achieved with a uniformly applied method, as well as reliable maps of land cover, justifies a more in-depth exploration of long wavelength imaging radar applications for tropical forests inventories.

Classification and mapping of rangeland vegetation physiognomic ...

African Journals Online (AJOL)

Plot vegetation species growth form, cover and height data were collected from 450 sampling sites based on eight spectral strata generated using unsupervised image classification. Field data were grouped at four levels of seven, six, three and two vegetation physiognomic classes which were subjected to both ML and ...

Large-Scale Mapping and Predictive Modeling of Submerged Aquatic Vegetation in a Shallow Eutrophic Lake

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Karl E. Havens

2002-01-01

Full Text Available A spatially intensive sampling program was developed for mapping the submerged aquatic vegetation (SAV over an area of approximately 20,000 ha in a large, shallow lake in Florida, U.S. The sampling program integrates Geographic Information System (GIS technology with traditional field sampling of SAV and has the capability of producing robust vegetation maps under a wide range of conditions, including high turbidity, variable depth (0 to 2 m, and variable sediment types. Based on sampling carried out in AugustœSeptember 2000, we measured 1,050 to 4,300 ha of vascular SAV species and approximately 14,000 ha of the macroalga Chara spp. The results were similar to those reported in the early 1990s, when the last large-scale SAV sampling occurred. Occurrence of Chara was strongly associated with peat sediments, and maximal depths of occurrence varied between sediment types (mud, sand, rock, and peat. A simple model of Chara occurrence, based only on water depth, had an accuracy of 55%. It predicted occurrence of Chara over large areas where the plant actually was not found. A model based on sediment type and depth had an accuracy of 75% and produced a spatial map very similar to that based on observations. While this approach needs to be validated with independent data in order to test its general utility, we believe it may have application elsewhere. The simple modeling approach could serve as a coarse-scale tool for evaluating effects of water level management on Chara populations.

Large-scale mapping and predictive modeling of submerged aquatic vegetation in a shallow eutrophic lake.

Science.gov (United States)

Havens, Karl E; Harwell, Matthew C; Brady, Mark A; Sharfstein, Bruce; East, Therese L; Rodusky, Andrew J; Anson, Daniel; Maki, Ryan P

2002-04-09

A spatially intensive sampling program was developed for mapping the submerged aquatic vegetation (SAV) over an area of approximately 20,000 ha in a large, shallow lake in Florida, U.S. The sampling program integrates Geographic Information System (GIS) technology with traditional field sampling of SAV and has the capability of producing robust vegetation maps under a wide range of conditions, including high turbidity, variable depth (0 to 2 m), and variable sediment types. Based on sampling carried out in August-September 2000, we measured 1,050 to 4,300 ha of vascular SAV species and approximately 14,000 ha of the macroalga Chara spp. The results were similar to those reported in the early 1990s, when the last large-scale SAV sampling occurred. Occurrence of Chara was strongly associated with peat sediments, and maximal depths of occurrence varied between sediment types (mud, sand, rock, and peat). A simple model of Chara occurrence, based only on water depth, had an accuracy of 55%. It predicted occurrence of Chara over large areas where the plant actually was not found. A model based on sediment type and depth had an accuracy of 75% and produced a spatial map very similar to that based on observations. While this approach needs to be validated with independent data in order to test its general utility, we believe it may have application elsewhere. The simple modeling approach could serve as a coarse-scale tool for evaluating effects of water level management on Chara populations.

Pattern Decomposition Method and a New Vegetation Index for Hyper-Multispectral Satellite Data Analysis

Science.gov (United States)

Muramatsu, K.; Furumi, S.; Hayashi, A.; Shiono, Y.; Ono, A.; Fujiwara, N.; Daigo, M.; Ochiai, F.

We have developed the ``pattern decomposition method'' based on linear spectral mixing of ground objects for n-dimensional satellite data. In this method, spectral response patterns for each pixel in an image are decomposed into three components using three standard spectral shape patterns determined from the image data. Applying this method to AMSS (Airborne Multi-Spectral Scanner) data, eighteen-dimensional data are successfully transformed into three-dimensional data. Using the three components, we have developed a new vegetation index in which all the multispectral data are reflected. We consider that the index should be linear to the amount of vegetation and vegetation vigor. To validate the index, its relations to vegetation types, vegetation cover ratio, and chlorophyll contents of a leaf were studied using spectral reflectance data measured in the field with a spectrometer. The index was sensitive to vegetation types and vegetation vigor. This method and index are very useful for assessment of vegetation vigor, classifying land cover types and monitoring vegetation changes

To what extent can vegetation change and plant stress be surveyed by remote sensing?

Energy Technology Data Exchange (ETDEWEB)

Toemmervik, Hans

1998-12-31

Air pollution from the nickel processing industry in the Kola region of Russia accounts for a large part of the environmental problems in the north-eastern parts of Norway and Finland. The objectives of this thesis were to examine if vegetation damage and plant stress can be surveyed by remote sensing and to assess the use of chlorophyll fluorescence measurements to detect plant stress in the field. The study was carried out in the border area between Norway and Russia. Two spaceborne and one airborne sensors were used. Changes in vegetation cover could be monitored with a degree of accuracy varying from 75 to 83%. A hybrid classification method monitored changes in both lichen dominated vegetation and in vegetation cover types dominated by dwarf shrubs and green plants, which were significantly associated with the differences in SO{sub 2} emission during the period from 1973 to 1994. Vegetation indices, change detection maps and prediction maps provided information on biomass and coverage of green vegetation. This was associated with the differences in the SO{sub 2} emissions during the same period. The vegetation and land cover types with the greatest stress and damage had the largest modelled SO{sub 2} concentration levels in the ground air layer while the vegetation cover types with the lowest degree of stress had the lowest. Comparison of the airborne casi map with the previously processed Landsat TM map from the same area showed that the casi map separated the complete vegetation cover into more detail than the Landsat TM map. The casi images indicated a red-edge shift for the medium to heavily damaged vegetation cover types. Problems with using airborne remote sensing by casi include variable clouds, lack of synoptic view, and cost. The variation in chlorophyll fluorescence of 11 plant species at 16 sites was most influenced by precipitation, temperature and continentality. 373 refs., 49 figs., 37 tabs.

Mapping caribou habitat north of the 51st parallel in Québec using Landsat imagery

Directory of Open Access Journals (Sweden)

Stéphanie Chalifoux

2003-04-01

Full Text Available A methodology using Landsat Thematic Mapper (TM images and vegetation typology, based on lichens as the principal component of caribou winter diet, was developed to map caribou habitat over a large and diversified area of Northern Québec. This approach includes field validation by aerial surveys (helicopter, classification of vegetation types, image enhancement, visual interpretation and computer assisted mapping. Measurements from more than 1500 field sites collected over six field campaigns from 1989 to 1996 represented the data analysed in this study. As the study progressed, 14 vegetation classes were defined and retained for analyses. Vegetation classes denoting important caribou habitat included six classes of upland lichen communities (Lichen, Lichen-Shrub, Shrub-Lichen, Lichen-Graminoid-Shrub, Lichen-Woodland, Lichen-Shrub-Woodland. Two classes (Burnt-over area, Regenerating burnt-over area are related to forest fire, and as they develop towards lichen communities, will become important for caribou. The last six classes are retained to depict remaining vegetation cover types. A total of 37 Landsat TM scenes were geocoded and enhanced using two methods: the Taylor method and the false colour composite method (bands combination and stretching. Visual inter¬pretation was chosen as the most efficient and reliable method to map vegetation types related to caribou habitat. The 43 maps produced at the scale of 1:250 000 and the synthesis map (1:2 000 000 provide a regional perspective of caribou habitat over 1200 000 km2 covering the entire range of the George river herd. The numerical nature of the data allows rapid spatial analysis and map updating.

Mapping the recovery of the burnt vegetation by classifying pre- and post-fire spectral indices

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M. A Peña

2017-12-01

Full Text Available This study analyzed the state of recovery of the burnt vegetation in the National Park of Torres del Paine between December, 2011 and March, 2012. The calculation and comparison of the NVDI (normalized difference vegetation index of the burnt area throughout a time series of 24 Landsat images acquired before, during and after the fire (2009- 2015, showed the temporal variation in the biomass levels of the burnt vegetation. The subsequent classification and comparison of the spectral indices: NDVI, NBR (normalized burnt ratio and NDWI (normalized difference water index on a full-data available and phenologically matched pre- and post-fire image pair (acquired in October 2009 and 2014, enabled to analyze and mapping the state of recovery of the burnt vegetation. The results show that the area of the lowest classes of all the spectral indices of the pre-fire date became the most dominant on the post-fire date. The pre- and post- fire NDVI class crossing by a confusion matrix showed that the highest and most prevailing pre-fire NDVI classes, mostly corresponding to hydromorphic forests and Andean scrubs, turned into the lowest class in 2014. The remaining area, comprising Patagonian steppe, reestablished its biomass levels in 2014, mostly exhibiting the same pre-fire NDVI classes. These results may provide guidelines to monitor and manage the regeneration of the vegetation impacted by this fire.

Rapid Vegetative Propagation Method for Carob

OpenAIRE

Hamide GUBBUK; Esma GUNES; Tomas AYALA-SILVA; Sezai ERCISLI

2011-01-01

Most of fruit species are propagated by vegetative methods such as budding, grafting, cutting, suckering, layering etc. to avoid heterozygocity. Carob trees (Ceratonia siliqua L.) are of highly economical value and are among the most difficult to propagate fruit species. In the study, air-layering propagation method was investigated first time to compare wild and cultivated (�Sisam�) carob types. In the experiment, one year old carob limbs were air-layered on coco peat medium by wrapping with...

Deep Learning of Post-Wildfire Vegetation Loss using Bitemporal Synthetic Aperture Radar Images

Science.gov (United States)

Chen, Z.; Glasscoe, M. T.; Parker, J. W.

2017-12-01

Wildfire events followed by heavy precipitation have been proven causally related to breakouts of mudflow or debris flow, which, can demand rapid evacuation and threaten residential communities and civil infrastructure. For example, in the case of the city of Glendora, California, it was first afflicted by a severe wildfire in 1968 and then the flooding caused mudslides and debris flow in 1969 killed 34 people. Therefore, burn area or vegetation loss mapping due to wildfire is critical to agencies for preparing for secondary hazards, particularly flooding and flooding induced mudflow. However, rapid post-wildfire mapping of vegetation loss mapping is not readily obtained by regular remote sensing methods, e.g. various optical methods, due to the presence of smoke, haze, and rainy/cloudy conditions that often follow a wildfire event. In this paper, we will introduce and develop a deep learning-based framework that uses Synthetic Aperture Radar images collected prior to and after a wildfire event. A convolutional neural network (CNN) approach will be used that replaces traditional principle component analysis (PCA) based differencing for non-supervised change feature extraction. Using a small sample of human-labeled burned vegetation, normal vegetation, and urban built-up pixels, we will compare the performance of deep learning and PCA-based feature extraction. The 2014 Coby Fire event, which affected the downstream city of Glendora, was used to evaluate the proposed framework. The NASA's UAVSAR data (https://uavsar.jpl.nasa.gov/) will be utilized for mapping the vegetation damage due to the Coby Fire event.

Development of a dynamic web mapping service for vegetation productivity using earth observation and in situ sensors in a sensor web based approach

NARCIS (Netherlands)

Kooistra, L.; Bergsma, A.R.; Chuma, B.; Bruin, de S.

2009-01-01

This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS). A prototype has been developed which provides daily maps of vegetation productivity for the

Islands of biogeodiversity in arid lands on a polygons map study: Detecting scale invariance patterns from natural resources maps.

Science.gov (United States)

Ibáñez, J J; Pérez-Gómez, R; Brevik, Eric C; Cerdà, A

2016-12-15

Many maps (geology, hydrology, soil, vegetation, etc.) are created to inventory natural resources. Each of these resources is mapped using a unique set of criteria, including scales and taxonomies. Past research indicates that comparing results of related maps (e.g., soil and geology maps) may aid in identifying mapping deficiencies. Therefore, this study was undertaken in Almeria Province, Spain to (i) compare the underlying map structures of soil and vegetation maps and (ii) investigate if a vegetation map can provide useful soil information that was not shown on a soil map. Soil and vegetation maps were imported into ArcGIS 10.1 for spatial analysis, and results then exported to Microsoft Excel worksheets for statistical analyses to evaluate fits to linear and power law regression models. Vegetative units were grouped according to the driving forces that determined their presence or absence: (i) climatophilous (ii) lithologic-climate; and (iii) edaphophylous. The rank abundance plots for both the soil and vegetation maps conformed to Willis or Hollow Curves, meaning the underlying structures of both maps were the same. Edaphophylous map units, which represent 58.5% of the vegetation units in the study area, did not show a good correlation with the soil map. Further investigation revealed that 87% of the edaphohygrophilous units were found in ramblas, ephemeral riverbeds that are not typically classified and mapped as soils in modern systems, even though they meet the definition of soil given by the most commonly used and most modern soil taxonomic systems. Furthermore, these edaphophylous map units tend to be islands of biodiversity that are threatened by anthropogenic activity in the region. Therefore, this study revealed areas that need to be revisited and studied pedologically. The vegetation mapped in these areas and the soils that support it are key components of the earth's critical zone that must be studied, understood, and preserved. Copyright © 2016

Continental Scale Vegetation Structure Mapping Using Field Calibrated Landsat, ALOS Palsar And GLAS ICESat

Science.gov (United States)

Scarth, P.; Phinn, S. R.; Armston, J.; Lucas, R.

2015-12-01

Vertical plant profiles are important descriptors of canopy structure and are used to inform models of biomass, biodiversity and fire risk. In Australia, an approach has been developed to produce large area maps of vertical plant profiles by extrapolating waveform lidar estimates of vertical plant profiles from ICESat/GLAS using large area segmentation of ALOS PALSAR and Landsat satellite image products. The main assumption of this approach is that the vegetation height profiles are consistent across the segments defined from ALOS PALSAR and Landsat image products. More than 1500 field sites were used to develop an index of fractional cover using Landsat data. A time series of the green fraction was used to calculate the persistent green fraction continuously across the landscape. This was fused with ALOS PALSAR L-band Fine Beam Dual polarisation 25m data and used to segment the Australian landscapes. K-means clustering then grouped the segments with similar cover and backscatter into approximately 1000 clusters. Where GLAS-ICESat footprints intersected these clusters, canopy profiles were extracted and aggregated to produce a mean vertical vegetation profile for each cluster that was used to derive mean canopy and understorey height, depth and density. Due to the large number of returns, these retrievals are near continuous across the landscape, enabling them to be used for inventory and modelling applications. To validate this product, a radiative transfer model was adapted to map directional gap probability from airborne waveform lidar datasets to retrieve vertical plant profiles Comparison over several test sites show excellent agreement and work is underway to extend the analysis to improve national biomass mapping. The integration of the three datasets provide options for future operational monitoring of structure and AGB across large areas for quantifying carbon dynamics, structural change and biodiversity.

Improving automated disturbance maps using snow-covered landsat time series stacks

Science.gov (United States)

Kirk M. Stueve; Ian W. Housman; Patrick L. Zimmerman; Mark D. Nelson; Jeremy Webb; Charles H. Perry; Robert A. Chastain; Dale D. Gormanson; Chengquan Huang; Sean P. Healey; Warren B. Cohen

2012-01-01

Snow-covered winter Landsat time series stacks are used to develop a nonforest mask to enhance automated disturbance maps produced by the Vegetation Change Tracker (VCT). This method exploits the enhanced spectral separability between forested and nonforested areas that occurs with sufficient snow cover. This method resulted in significant improvements in Vegetation...

A Continuation Method for Weakly Kannan Maps

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Ariza-Ruiz David

2010-01-01

Full Text Available The first continuation method for contractive maps in the setting of a metric space was given by Granas. Later, Frigon extended Granas theorem to the class of weakly contractive maps, and recently Agarwal and O'Regan have given the corresponding result for a certain type of quasicontractions which includes maps of Kannan type. In this note we introduce the concept of weakly Kannan maps and give a fixed point theorem, and then a continuation method, for this class of maps.

Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest

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Zhihui Wang

2016-06-01

Full Text Available Hyperspectral remote sensing serves as an effective tool for estimating foliar nitrogen using a variety of techniques. Vegetation indices (VIs are a simple means of retrieving foliar nitrogen. Despite their popularity, few studies have been conducted to examine the utility of VIs for mapping canopy foliar nitrogen in a mixed forest context. In this study, we assessed the performance of 32 vegetation indices derived from HySpex airborne hyperspectral images for estimating canopy mass-based foliar nitrogen concentration (%N in the Bavarian Forest National Park. The partial least squares regression (PLSR was performed for comparison. These vegetation indices were classified into three categories that are mostly correlated to nitrogen, chlorophyll, and structural properties such as leaf area index (LAI. %N was destructively measured in 26 broadleaf, needle leaf, and mixed stand plots to represent the different species and canopy structure. The canopy foliar %N is defined as the plot-level mean foliar %N of all species weighted by species canopy foliar mass fraction. Our results showed that the variance of canopy foliar %N is mainly explained by functional type and species composition. The normalized difference nitrogen index (NDNI produced the most accurate estimation of %N (R2CV = 0.79, RMSECV = 0.26. A comparable estimation of %N was obtained by the chlorophyll index Boochs2 (R2CV = 0.76, RMSECV = 0.27. In addition, the mean NIR reflectance (800–850 nm, representing canopy structural properties, also achieved a good accuracy in %N estimation (R2CV = 0.73, RMSECV = 0.30. The PLSR model provided a less accurate estimation of %N (R2CV = 0.69, RMSECV = 0.32. We argue that the good performance of all three categories of vegetation indices in %N estimation can be attributed to the synergy among plant traits (i.e., canopy structure, leaf chemical and optical properties while these traits may converge across plant species for evolutionary reasons. Our

Laser Sensing of Vegetation Based on Dual Spectrum Measurements of Reflection Coefficients

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M. L. Belov

2017-01-01

Full Text Available Currently, a promising trend in remote sensing of environment is to monitor the vegetative cover: evaluate the productivity of agricultural crops; evaluate the moisture content of soils and the state of ecosystems; provide mapping the sites of bogging, desertification, drought, etc.; control the phases of vegetation of crops, etc.Development of monitoring systems for remote detection of vegetation sites being under unfavorable conditions (low or high temperature, excess or lack of water, soil salinity, disease, etc. is of relevance. Optical methods are the most effective for this task. These methods are based on the physical features of reflection spectra in the visible and near infrared spectral range for vegetation under unfavorable conditions and vegetation under normal conditions.One of the options of optoelectronic equipment for monitoring vegetation condition is laser equipment that allows remote sensing of vegetation from the aircraft and mapping of vegetation sites with abnormal (inactive periods of vegetation reflection spectra with a high degree of spatial resolution.The paper deals with development of a promising dual-spectrum method for laser remote sensing of vegetation. Using the experimentally measured reflection spectra of different vegetation types, mathematical modeling of probability for appropriate detection and false alarms to solve a problem of detecting the vegetation under unfavorable conditions (with abnormal reflection spectra is performed based on the results of dual-spectrum measurements of the reflection coefficient.In mathematical modeling, the lidar system was supposed to provide sensing at wavelengths of 0.532 μm and 0.85 μm. The noise of the measurement was supposed to be normal with zero mean value and mean-square value of 1% -10%.It is shown that the method of laser sensing of vegetation condition based on the results of dual-spectrum measurement of the reflection coefficient at wavelengths of 0.532 μm and 0

Mapping and exploring variation in post-fire vegetation recovery following mixed severity wildfire using airborne LiDAR.

Science.gov (United States)

Gordon, Christopher E; Price, Owen F; Tasker, Elizabeth M

2017-07-01

There is a public perception that large high-severity wildfires decrease biodiversity and increase fire hazard by homogenizing vegetation composition and increasing the cover of mid-story vegetation. But a growing literature suggests that vegetation responses are nuanced. LiDAR technology provides a promising remote sensing tool to test hypotheses about post-fire vegetation regrowth because vegetation cover can be quantified within different height strata at fine scales over large areas. We assess the usefulness of airborne LiDAR data for measuring post-fire mid-story vegetation regrowth over a range of spatial resolutions (10 × 10 m, 30 × 30 m, 50 × 50 m, 100 × 100 m cell size) and investigate the effect of fire severity on regrowth amount and spatial pattern following a mixed severity wildfire in Warrumbungle National Park, Australia. We predicted that recovery would be more vigorous in areas of high fire severity, because park managers observed dense post-fire regrowth in these areas. Moderate to strong positive associations were observed between LiDAR and field surveys of mid-story vegetation cover between 0.5-3.0 m. Thus our LiDAR survey was an apt representation of on-ground vegetation cover. LiDAR-derived mid-story vegetation cover was 22-40% lower in areas of low and moderate than high fire severity. Linear mixed-effects models showed that fire severity was among the strongest biophysical predictors of mid-story vegetation cover irrespective of spatial resolution. However much of the variance associated with these models was unexplained, presumably because soil seed banks varied at finer scales than our LiDAR maps. Dense patches of mid-story vegetation regrowth were small (median size 0.01 ha) and evenly distributed between areas of low, moderate and high fire severity, demonstrating that high-severity fires do not homogenize vegetation cover. Our results are relevant for ecosystem conservation and fire management because they: indicate

Integration of singularity and zonality methods for prospectivity map of blind mineralization

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samaneh safari

2016-12-01

Full Text Available Singularity based on fractal and multifractal is a technique for detection of depletion and enrichment for geochemical exploration, while the index of vertical geochemical zonality (Vz of Pb.Zn/Cu.Ag is a practical method for exploration of blind porphyry copper mineralization. In this study, these methods are combined for recognition, delineation, and enrichment of Vz in Jebal- Barez in the south of Iran. The studied area is located in the Shar-E-Babak–Bam ore field in the southern part of the Central Iranian volcano–plutonic magmatic arc. The region has a semiarid climate, mountainous topography, and poor vegetation cover. Seven hundreds samples of stream sedimentary were taken from the region. Geochemical data subset represent a total drainage basin area. Samples are analyzed for Cu, Zn, Ag, Pb, Au, W, As, Hg, Ba, Bi by atomic absorption method. Prospectivity map for blind mineralization is represented in this area. The results are in agreement with previous studies which have been focused in this region. Kerver is detected as the main blind mineralization in Jebal- Barz which had been previously intersected by drilled borehole for exploration purposes. In this research, it has been demonstrated that employing the singularity of geochemical zonality anomalies method, as opposed to using singularity of elements, improves mapping of mineral prospectivity.

Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation

Science.gov (United States)

Nguyen, Uyen

Index (NDVI) average values in the adjacent uplands also decreased over thirty years and were correlated with the previous year's annual precipitation. Hence an increase in ET in the uplands did not appear to be responsible for the decrease in river flows in this study, leaving increased regional groundwater pumping as a feasible alternative explanation for decreased flows and deterioration of the riparian forest. The second research objective was to develop a new method of classification using very high-resolution aerial photo to map riparian vegetation at the species level in the Colorado River Ecosystem, Grand Canyon area, Arizona. Ground surveys have showed an obvious trend in which non-native saltcedar (Tamarix spp.) has replaced native vegetation over time. Our goal was to develop a quantitative mapping procedure to detect changes in vegetation as the ecosystem continues to respond to hydrological and climate changes. Vegetation mapping for the Colorado River Ecosystem needed an updated database map of the area covered by riparian vegetation and an indicator of species composition in the river corridor. The objective of this research was to generate a new riparian vegetation map at species level using a supervised image classification technique for the purpose of patch and landscape change detection. A new classification approach using multispectral images allowed us to successfully identify and map riparian species coverage the over whole Colorado River Ecosystem, Grand Canyon area. The new map was an improvement over the initial 2002 map since it reduced fragmentation from mixed riparian vegetation areas. The most dominant tree species in the study areas is saltcedar (Tamarix spp.). The overall accuracy is 93.48% and the kappa coefficient is 0.88. The reference initial inventory map was created using 2002 images to compare and detect changes through 2009. The third objective of my research focused on using multiplatform of remote sensing and ground calibration

Evaluation of vegetation cover using the normalized difference vegetation index (NDVI

Directory of Open Access Journals (Sweden)

Gabriela Camargos Lima

2013-08-01

Full Text Available Soil loss by water erosion is the main cause of soil degradation in Brazil. However, erosion can be reduced by the presence of vegetation. The Normalized Difference Vegetation Index (NDVI makes it possible to identify the vegetative vigor of crops or natural vegetation which facilities the identification of areas with vegetation covers. This information is very important in identifying the phenomena which might be occurring in a particular area, especially those related to soil degradation by water erosion. Thus, the aim of this work was to assess the canopy cover by using NDVI, checking the image accuracy using the Coverage Index (CI based on the Stocking method, in the Sub-basin of Posses, which belongs to the Cantareira System, located in the Extrema municipality, Minas Gerais, Brazil. Landsat-5 TM images were used. The sub-basin of Posses was very altered in comparison to the surrounding areas. The NDVI technique proved to be a suitable tool to assess the uses that occur in the sub-basin of Posses, as validated by the Stocking methodology. The map derived from NDVI allowed the geographic distribution of different land uses to be observed and allowed for the identification of critical areas in relation to vegetation cover as well. This finding can be used to optimize efforts to recover and protect soil in areas with bare soil and degraded pasture, in order to reduce environmental degradation. The CI has not exceeded 40% for land use classes that occur in the majority of the sub-basin (91%, except in areas of woody vegetation.

Vegetation - McKenzie Preserve [ds703

Data.gov (United States)

California Natural Resource Agency — The California Native Plant Society (CNPS) Vegetation Program produced a vegetation map and classification for approximately 11,600 acres primarily within Millerton...

Object-based vegetation classification with high resolution remote sensing imagery

Science.gov (United States)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions

Phytosociological studies on vegetation change caused by road construction in natural park. III

Energy Technology Data Exchange (ETDEWEB)

Kameyama, A

1975-06-01

An attempt has been made to explain how forests have been destroyed by road construction in a natural park in Japan. The author discussed the methods of analyzing the problem, as well as the impact of the construction on various developmental stages in plants. A survey of the plant community was taken and a vegetation map on a scale of 1:3,000 was made. According to the map, vegetation was affected in an area 10-20m from the road, sometimes 50 m, by exhaust fumes from the traffic.

VEGETATION COVER ANALYSIS OF HAZARDOUS WASTE SITES IN UTAH AND ARIZONA USING HYPERSPECTRAL REMOTE SENSING

Energy Technology Data Exchange (ETDEWEB)

Serrato, M.; Jungho, I.; Jensen, J.; Jensen, R.; Gladden, J.; Waugh, J.

2012-01-17

Remote sensing technology can provide a cost-effective tool for monitoring hazardous waste sites. This study investigated the usability of HyMap airborne hyperspectral remote sensing data (126 bands at 2.3 x 2.3 m spatial resolution) to characterize the vegetation at U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. Regression trees resulted in the best calibration performance of LAI estimation (R{sup 2} > 0.80). The use of REPs failed to accurately predict LAI (R{sup 2} < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of 1 higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (< 1m) found on the sites.

Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing

Directory of Open Access Journals (Sweden)

Mike Serrato

2012-01-01

Full Text Available This study investigated the usability of hyperspectral remote sensing for characterizing vegetation at hazardous waste sites. The specific objectives of this study were to: (1 estimate leaf-area-index (LAI of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP, and machine learning regression trees, and (2 map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF-derived metrics and vegetation indices. HyMap airborne data (126 bands at 2.3 × 2.3 m spatial resolution, collected over the U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona, were used. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. Regression trees resulted in the best calibration performance of LAI estimation (R2 > 0.80. The use of REPs failed to accurately predict LAI (R2 < 0.2. The use of the MTMF-derived metrics (matched filter scores and infeasibility and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches ( < 1 m found on the sites.

Vegetation Cover Analysis Of Hazardous Waste Sites In Utah And Arizona Using Hyperspectral Remote Sensing

International Nuclear Information System (INIS)

Serrato, M.; Jungho, I.; Jensen, J.; Jensen, R.; Gladden, J.; Waugh, J.

2012-01-01

Remote sensing technology can provide a cost-effective tool for monitoring hazardous waste sites. This study investigated the usability of HyMap airborne hyperspectral remote sensing data (126 bands at 2.3 x 2.3 m spatial resolution) to characterize the vegetation at U.S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. Regression trees resulted in the best calibration performance of LAI estimation (R 2 > 0.80). The use of REPs failed to accurately predict LAI (R 2 < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of 1 higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (< 1m) found on the sites.

EVALUATION AND MAPPING OF RANGELANDS DEGRADATION USING REMOTELY SENSED DATA

Directory of Open Access Journals (Sweden)

Majid Ajorlo

2005-05-01

Full Text Available The empirical and scientifically documents prove that misuse of natural resource causes degradation in it. So natural resources conservation is important in approaching sustainable development aims. In current study, Landsat Thematic Mapper images and grazing gradient method have been used to map the extent and degree of rangeland degradation. In during ground-based data measuring, factors such as vegetation cover, litter, plant diversity, bare soil, and stone & gravels were estimated as biophysical indicators of degradation. The next stage, after geometric correction and doing some necessary pre-processing practices on the study area’s images; the best and suitable vegetation index has been selected to map rangeland degradation among the Normalized Difference Vegetation Index (NDVI, Soil Adjusted Vegetation Index (SAVI, and Perpendicular Vegetation Index (PVI. Then using suitable vegetation index and distance parameter was produced the rangelands degradation map. The results of ground-based data analysis reveal that there is a significant relation between increasing distance from critical points and plant diversity and also percentage of litter. Also there is significant relation between vegetation cover percent and distance from village, i.e. the vegetation cover percent increases by increasing distance from villages, while it wasn’t the same around the stock watering points. The result of analysis about bare soil and distance from critical point was the same to vegetation cover changes manner. Also there wasn’t significant relation between stones & gravels index and distance from critical points. The results of image processing show that, NDVI appears to be sensitive to vegetation changes along the grazing gradient and it can be suitable vegetation index to map rangeland degradation. The degradation map shows that there is high degradation around the critical points. These areas need urgent attention for soil conservation. Generally, it

A hierarchical approach of hybrid image classification for land use and land cover mapping

Directory of Open Access Journals (Sweden)

Rahdari Vahid

2018-01-01

Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

Classification of High-Mountain Vegetation Communities within a Diverse Giant Mountains Ecosystem Using Airborne APEX Hyperspectral Imagery

Directory of Open Access Journals (Sweden)

Adriana Marcinkowska-Ochtyra

2018-04-01

Full Text Available Mapping plant communities is a difficult and time consuming endeavor. Methods relying on field surveys deliver high quality data but are usually limited to relatively small areas. In this paper we apply airborne hyperspectral data to vegetation mapping in remote and hard to reach areas. We classified 22 vegetation communities in the Giant Mountains on 3.12-m Airborne Prism Experiment (APEX hyperspectral images, registered in 288 spectral bands (10 September 2012. As the classification algorithm, Support Vector Machines (SVM was used. APEX data were corrected geometrically and atmospherically, and three dimensionality reduction methods were performed to select the best dataset. As reference we used a non-forest vegetation map containing vegetation communities of Polish Karkonosze National Park from 2002, orthophotomap and field surveys data from 2013 to 2014. We obtained the post-classification maps of 22 vegetation communities, lakes and areas without any vegetation. Iterative accuracy assessment repeated 100 times was used to obtain the most objective results for individual communities. The median value of overall accuracy (OA was 84%. Fourteen out of twenty-four classes were classified of more than 80% of producer accuracy (PA and sixteen out of twenty-four of user accuracy (UA. APEX data and SVM with the use of iterative accuracy assessment are useful for the mountain communities classification. This can support both Polish and Czech national parks management by giving the information about diversity of communities in the whole transboundary area, helping with identification especially in changing environment caused by humans.

The "Set Map" Method of Navigation.

Science.gov (United States)

Tippett, Julian

1998-01-01

Explains the "set map" method of using the baseplate compass to solve walkers' navigational needs as opposed to the 1-2-3 method for taking a bearing. The map, with the compass permanently clipped to it, is rotated to the position in which its features have the same orientation as their counterparts on the ground. Includes directions and…

The spatial distribution of vegetation types in the Serengeti ecosystem : the influence of rainfall and topographic relief on vegetation patch characteristics

NARCIS (Netherlands)

Reed, D. N.; Anderson, T. M.; Dempewolf, J.; Metzger, K.; Serneels, S.

The aim of this study is to introduce a structural vegetation map of the Serengeti ecosystem and, based on the map, to test the relative influences of landscape factors on the spatial heterogeneity of vegetation in the ecosystem. This study was conducted in the Serengeti-Maasai Mara ecosystem in

Sampling and Mapping Soil Erosion Cover Factor for Fort Richardson, Alaska. Integrating Stratification and an Up-Scaling Method

National Research Council Canada - National Science Library

Wang, Guangxing; Gertner, George; Anderson, Alan B; Howard, Heidi

2006-01-01

When a ground and vegetation cover factor related to soil erosion is mapped with the aid of remotely sensed data, a cost-efficient sample design to collect ground data and obtain an accurate map is required...

Vegetation of the Hantam-Tanqua-Roggeveld subregion, South Africa Part 2: Succulent Karoo Biome related vegetation

Directory of Open Access Journals (Sweden)

Helga van der Merwe

2009-03-01

Full Text Available The Hantam-Tanqua-Roggeveld subregion lies within the Succulent Karoo Hotspot that stretches along the western side of the Republic of South Africa and Namibia. This project, carried out to document the botanical diversity in the Hantam-Tanqua-Roggeveld subregion, was part of a project identified as a priority during the SKEP (Succulent Karoo Ecosystem Programme initiative in this Hotspot. Botanical surveys were conducted in an area covering over three million hectares. Satellite images of the area and topocadastral, land type and geology maps were used to stratify the area into relatively homogeneous units. An analysis of the floristic data of 390 sample plots identified two major floristic units, i.e. the Fynbos Biome related vegetation and the Succulent Karoo Biome related vegetation. A description of the vegetation related to the Succulent Karoo Biome is presented in this article. Seven associations, 16 subassociations and several mosaic vegetation units, consisting of more than one vegetation unit, were identified and mapped. Various threats to the vegetation in the region were identified during the survey and are briefly discussed.

Using Intervention Mapping for Systematic Development of Two School-Based Interventions Aimed at Increasing Children's Fruit and Vegetable Intake

Science.gov (United States)

Reinaerts, E.; De Nooijer, J.; De Vries, N. K.

2008-01-01

Purpose: The purpose of this paper is to show how the intervention mapping (IM) protocol could be applied to the development of two school-based interventions. It provides an extensive description of the development, implementation and evaluation of two interventions which aimed to increase fruit and vegetable (F&V) consumption among primary…

Landslide susceptibility mapping by comparing weight of evidence, fuzzy logic, and frequency ratio methods

Directory of Open Access Journals (Sweden)

V. Vakhshoori

2016-09-01

Full Text Available A regional scale basin susceptible to landslide located in Qaemshahr area in northern Iran was chosen for comparing the reliability of weight of evidence (WofE, fuzzy logic, and frequency ratio (FR methods for landslide susceptibility mapping. The locations of 157 landslides were identified using Google Earth® or extracted from archived data, from which, 22 rockslides were eliminated from the data-set due to their different conditions. The 135 remaining landslides were randomly divided into two groups of modelling (70% and validation (30% data-sets. Elevation, slope degree, slope aspect, lithology, land use/cover, normalized difference vegetation index, rainfall, distance to drainage network, roads, and faults were considered as landslide causative factors. The landslide susceptibility maps were prepared using the three mentioned methods. The validation process was measured by the success and prediction rates calculated by area under receiver operating characteristic curve. The ‘OR’, ‘AND’, ‘SUM’, and ‘PRODUCT’ operators of the fuzzy logic method were unacceptable because these operators classify the target area into either very high or very low susceptible zones that are inconsistent with the physical conditions of the study area. The results of fuzzy ‘GAMMA’ operators were relatively reliable while, FR and WofE methods showed results that are more reliable.

Extraction and determination of arsenic species in leafy vegetables: Method development and application.

Science.gov (United States)

Ma, Li; Yang, Zhaoguang; Kong, Qian; Wang, Lin

2017-02-15

Extraction of arsenic (As) species in leafy vegetables was investigated by different combinations of methods and extractants. The extracted As species were separated and determined by HPLC-ICP-MS method. The microwave assisted method using 1% HNO3 as the extractant exhibited satisfactory efficiency (>90%) at 90°C for 1.5h. The proposed method was applied for extracting As species from real leafy vegetables. Thirteen cultivars of leafy vegetables were collected and analyzed. The predominant species in all the investigated vegetable samples were As(III) and As(V). Moreover, both As(III) and As(V) concentrations were positive significant (p<0.01) correlated with total As (tAs) concentration. However, the percentage of As(V) reduced with tAs concentration increasing probably due to the conversion and transformation of As(V) to As(III) after uptake. The hazard quotient results indicated no particular risk to 94.6% of local consumers. Considerably carcinogenic risk by consumption of the leafy vegetables was observed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Vegetation - San Felipe Valley [ds172

Data.gov (United States)

California Natural Resource Agency — This Vegetation Map of the San Felipe Valley Wildlife Area in San Diego County, California is based on vegetation samples collected in the field in 2002 and 2005 and...

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

Science.gov (United States)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation

Hyperspectral remote sensing of vegetation

Science.gov (United States)

Thenkabail, Prasad S.; Lyon, John G.; Huete, Alfredo

2011-01-01

Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research.

Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

NARCIS (Netherlands)

Ali, A.; de Bie, C.A.J.M.; Skidmore, A.K.; Scarrott, R.G.; Hamad, A.A.; Venus, V.; Lymberakis, P.

2013-01-01

The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but

A method to correct coordinate distortion in EBSD maps

International Nuclear Information System (INIS)

Zhang, Y.B.; Elbrønd, A.; Lin, F.X.

2014-01-01

Drift during electron backscatter diffraction mapping leads to coordinate distortions in resulting orientation maps, which affects, in some cases significantly, the accuracy of analysis. A method, thin plate spline, is introduced and tested to correct such coordinate distortions in the maps after the electron backscatter diffraction measurements. The accuracy of the correction as well as theoretical and practical aspects of using the thin plate spline method is discussed in detail. By comparing with other correction methods, it is shown that the thin plate spline method is most efficient to correct different local distortions in the electron backscatter diffraction maps. - Highlights: • A new method is suggested to correct nonlinear spatial distortion in EBSD maps. • The method corrects EBSD maps more precisely than presently available methods. • Errors less than 1–2 pixels are typically obtained. • Direct quantitative analysis of dynamic data are available after this correction

CrowdMapping: A Crowdsourcing-Based Terminology Mapping Method for Medical Data Standardization.

Science.gov (United States)

Mao, Huajian; Chi, Chenyang; Huang, Boyu; Meng, Haibin; Yu, Jinghui; Zhao, Dongsheng

2017-01-01

Standardized terminology is the prerequisite of data exchange in analysis of clinical processes. However, data from different electronic health record systems are based on idiosyncratic terminology systems, especially when the data is from different hospitals and healthcare organizations. Terminology standardization is necessary for the medical data analysis. We propose a crowdsourcing-based terminology mapping method, CrowdMapping, to standardize the terminology in medical data. CrowdMapping uses a confidential model to determine how terminologies are mapped to a standard system, like ICD-10. The model uses mappings from different health care organizations and evaluates the diversity of the mapping to determine a more sophisticated mapping rule. Further, the CrowdMapping model enables users to rate the mapping result and interact with the model evaluation. CrowdMapping is a work-in-progress system, we present initial results mapping terminologies.

A comparative study on the landslide susceptibility mapping using ...

Indian Academy of Sciences (India)

from faults, lithology, normalized difference vegetation index (NDVI), sediment transport index (STI), stream power ... economic losses and creating high maintenance costs, are ..... evidence method to landslide susceptibility map- ping using ...

(abstract) Studies of Interferometric Penetration into Vegetation Canopies using Multifrequency Interferometry Data at JPL

Science.gov (United States)

Hensley, Scott; Rodriguez, Ernesto; Truhafft, Bob; van Zyl, Jakob; Rosen, Paul; Werner, Charles; Madsen, Sren; Chapin, Elaine

1997-01-01

Radar interferometric observations both from spaceborne and airborne platforms have been used to generate accurate topographic maps, measure milimeter level displacements from earthquakes and volcanoes, and for making land cover classification and land cover change maps. Interferometric observations have two basic measurements, interferometric phase, which depends upon the path difference between the two antennas and the correlation. One of the key questions concerning interferometric observations of vegetated regions is where in the canopy does the interferometric phase measure the height. Results for two methods of extracting tree heights and other vegetation parameters based upon the amount of volumetric decorrelation will be presented.

The pro children intervention: applying the intervention mapping protocol to develop a school-based fruit and vegetable promotion programme.

Science.gov (United States)

Pérez-Rodrigo, Carmen; Wind, Marianne; Hildonen, Christina; Bjelland, Mona; Aranceta, Javier; Klepp, Knut-Inge; Brug, Johannes

2005-01-01

The importance of careful theory-based intervention planning is recognized for fruit and vegetable promotion. This paper describes the application of the Intervention Mapping (IM) protocol to develop the Pro Children intervention to promote consumption of fruit and vegetable among 10- to 13-year-old schoolchildren. Based on a needs assessment, promotion of intake of fruit and vegetable was split into performance objectives and related personal, social and environmental determinants. Crossing the performance objectives with related important and changeable determinants resulted in a matrix of learning and change objectives for which appropriate educational strategies were identified. Theoretically similar but culturally relevant interventions were designed, implemented and evaluated in Norway, the Netherlands and Spain during 2 school years. Programme activities included provision of fruits and vegetables in the schools, guided classroom activities, computer-tailored feedback and advice for children, and activities to be completed at home with the family. Additionally, optional intervention components for community reinforcement included incorporation of mass media, school health services or grocery stores. School project committees were supported. The Pro Children intervention was carefully developed based on the IM protocol that resulted in a comprehensive school-based fruit and vegetable promotion programme, but culturally sensible and locally relevant. (c) 2005 S. Karger AG, Basel

Seasonal comparison of two spatially distributed evapotranspiration mapping methods

Science.gov (United States)

Kisfaludi, Balázs; Csáki, Péter; Péterfalvi, József; Primusz, Péter

2017-04-01

More rainfall is disposed of through evapotranspiration (ET) on a global scale than through runoff and storage combined. In Hungary, about 90% of the precipitation evapotranspirates from the land and only 10% goes to surface runoff and groundwater recharge. Therefore, evapotranspiration is a very important element of the water balance, so it is a suitable parameter for the calibration of hydrological models. Monthly ET values of two MODIS-data based ET products were compared for the area of Hungary and for the vegetation period of the year 2008. The differences were assessed by land cover types and by elevation zones. One ET map was the MOD16, aiming at global coverage and provided by the MODIS Global Evaporation Project. The other method is called CREMAP, it was developed at the Budapest University of Technology and Economics for regional scale ET mapping. CREMAP was validated for the area of Hungary with good results, but ET maps were produced only for the period of 2000-2008. The aim of this research was to evaluate the performance of the MOD16 product compared to the CREMAP method. The average difference between the two products was the highest during summer, CREMAP estimating higher ET values by about 25 mm/month. In the spring and autumn, MOD16 ET values were higher by an average of 6 mm/month. The differences by land cover types showed a similar seasonal pattern to the average differences, and they correlated strongly with each other. Practically the same difference values could be calculated for arable lands and forests that together cover nearly 75% of the area of the country. Therefore, it can be said that the seasonal changes had the same effect on the two method's ET estimations in each land cover type areas. The analysis by elevation zones showed that on elevations lower than 200 m AMSL the trends of the difference values were similar to the average differences. The correlation between the values of these elevation zones was also strong. However weaker

Mapcurves: a quantitative method for comparing categorical maps.

Science.gov (United States)

William W. Hargrove; M. Hoffman Forrest; Paul F. Hessburg

2006-01-01

We present Mapcurves, a quantitative goodness-of-fit (GOF) method that unambiguously shows the degree of spatial concordance between two or more categorical maps. Mapcurves graphically and quantitatively evaluate the degree of fit among any number of maps and quantify a GOF for each polygon, as well as the entire map. The Mapcurve method indicates a perfect fit even if...

Mapping species of submerged aquatic vegetation with multi-seasonal satellite images and considering life history information

Science.gov (United States)

Luo, Juhua; Duan, Hongtao; Ma, Ronghua; Jin, Xiuliang; Li, Fei; Hu, Weiping; Shi, Kun; Huang, Wenjiang

2017-05-01

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.

Mapping of fluoride endemic area and assessment of F(-1) accumulation in soil and vegetation.

Science.gov (United States)

Saini, Poonam; Khan, Suphiya; Baunthiyal, Mamta; Sharma, Vinay

2013-02-01

The prevalence of fluorosis is mainly due to the consumption of more fluoride (F(-1)) through drinking water, vegetables, and crops. The objective of the study was mapping of F(-1) endemic area of Newai Tehsil, Tonk district, Rajasthan, India. For the present study, water, soil (0-45 cm), and vegetation samples were collected from 17 villages. Fluoride concentration in water samples ranged from 0.3 to 9.8 mg/l. Out of 17 villages studied, the amounts of F(-1) content of eight villages were found to exceed the permissible limits. Labile F(-1) content and total F(-1) content in soil samples ranges 11.00-70.05 mg/l and 50.3-179.63 μg g(-1), respectively. F(-1) content in tree species was found in this order Azadirachta indica 47.32-55.76 μg g(-1) > Prosopis juliflora 40.16-49.63 μg g(-1) > Acacia tortilis 34.39-43.60 μg g(-1). While in case of leafy vegetables, F(-1) content order was Chenopodium album 54.23-98.42 μg g(-1) > Spinacea oleracea 30.41-64.09 μg g(-1) > Mentha arvensis 35.48-51.97 μg g(-1). The order of F(-1) content in crops was found as 41.04 μg g(-1) Pennisetum glaucum > 13.61 μg g(-1) Brassica juncea > 7.98 μg g(-1) Triticum sativum in Krishi Vigyan Kendra (KVK) farms. Among vegetation, the leafy vegetables have more F(-1) content. From the results, it is suggested that the people of KVK farms should avoid the use of highly F(-1) containing water for irrigation and drinking purpose. It has been recommended to the government authority to take serious steps to supply drinking water with low F(-1) concentration for the fluorosis affected villages. Further, grow more F(-1) hyperaccumulator plants in F(-1) endemic areas to lower the F(-1) content of the soils.

A time-delayed method for controlling chaotic maps

International Nuclear Information System (INIS)

Chen Maoyin; Zhou Donghua; Shang Yun

2005-01-01

Combining the repetitive learning strategy and the optimality principle, this Letter proposes a time-delayed method to control chaotic maps. This method can effectively stabilize unstable periodic orbits within chaotic attractors in the sense of least mean square. Numerical simulations of some chaotic maps verify the effectiveness of this method

Unsupervised classification of lidar-based vegetation structure metrics at Jean Lafitte National Historical Park and Preserve

Science.gov (United States)

Kranenburg, Christine J.; Palaseanu-Lovejoy, Monica; Nayegandhi, Amar; Brock, John; Woodman, Robert

2012-01-01

Traditional vegetation maps capture the horizontal distribution of various vegetation properties, for example, type, species and age/senescence, across a landscape. Ecologists have long known, however, that many important forest properties, for example, interior microclimate, carbon capacity, biomass and habitat suitability, are also dependent on the vertical arrangement of branches and leaves within tree canopies. The objective of this study was to use a digital elevation model (DEM) along with tree canopy-structure metrics derived from a lidar survey conducted using the Experimental Advanced Airborne Research Lidar (EAARL) to capture a three-dimensional view of vegetation communities in the Barataria Preserve unit of Jean Lafitte National Historical Park and Preserve, Louisiana. The EAARL instrument is a raster-scanning, full waveform-resolving, small-footprint, green-wavelength (532-nanometer) lidar system designed to map coastal bathymetry, topography and vegetation structure simultaneously. An unsupervised clustering procedure was then applied to the 3-dimensional-based metrics and DEM to produce a vegetation map based on the vertical structure of the park's vegetation, which includes a flotant marsh, scrub-shrub wetland, bottomland hardwood forest, and baldcypress-tupelo swamp forest. This study was completed in collaboration with the National Park Service Inventory and Monitoring Program's Gulf Coast Network. The methods presented herein are intended to be used as part of a cost-effective monitoring tool to capture change in park resources.

Northern Everglades, Florida, satellite image map

Science.gov (United States)

Thomas, Jean-Claude; Jones, John W.

2002-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program with support from the Everglades National Park. The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

Method and system for a network mapping service

Science.gov (United States)

Bynum, Leo

2017-10-17

A method and system of publishing a map includes providing access to a plurality of map data files or mapping services between at least one publisher and at least one subscriber; defining a map in a map context comprising parameters and descriptors to substantially duplicate a map by reference to mutually accessible data or mapping services, publishing a map to a channel in a table file on server; accessing the channel by at least one subscriber, transmitting the mapping context from the server to the at least one subscriber, executing the map context by the at least one subscriber, and generating the map on a display software associated with the at least one subscriber by reconstituting the map from the references and other data in the mapping context.

PROBLEMS IN VEGETATION MONITORING IN NATURE MANAGEMENT PRACTICE: TWO CASE STUDIES

Directory of Open Access Journals (Sweden)

I. DE RONDE

2007-04-01

Full Text Available One of the major requirements of the monitoring of vegetation is the comparability of data between years. Therefore, a proper sampling scheme is essential. However, through the years, in nature management practice lots of data collected without a primary monitoring goal. Afterwards, it often seems very valuable to include these older data in the analysis for several reasons. In two examples from military ranges in the Netherlands, two of the problems which can be met with in comparing unequivalent or biased data in monitoring are shown. In the first example, the frequency of grassland species in two sets of relevés is examined. A solution is presented for the overrepresentation of relevés from one or more vegetation types from the first year, based on the area of the vegetation types on the vegetation map of this same year. In the second example, two sequential vegetation maps are compared. A major problem is often the thematic incongruence of sequential vegetation maps. Afterwards, this can only be resolved by upscaling one or both maps. It is concluded that the use of old data for monitoring purposes can be very valuable, but that this often calls for creative data handling, in which GIS and modern computer programmes are very helpful.

Vegetation Change in Blue Oak Woodlands in California

Science.gov (United States)

Barbara A. Holzman; Barbara H. Allen-Diaz

1991-01-01

A preliminary report of a statewide project investigating vegetation change in blue oak (Quercus douglasii) woodlands in California is presented. Vegetation plots taken in the 1930s, as part of a statewide vegetation mapping project, were relocated and surveyed. Species composition, cover and tree stand structure data from the earlier study were...

A Vegetation Database for the Colorado River Ecosystem from Glen Canyon Dam to the Western Boundary of Grand Canyon National Park, Arizona

Science.gov (United States)

Ralston, Barbara E.; Davis, Philip A.; Weber, Robert M.; Rundall, Jill M.

2008-01-01

supervised classification determined that accuracies varied among vegetation classes from 90% to 49%. Causes for low accuracies were similar spectral signatures among vegetation classes. Fuzzy accuracy assessment improved classification accuracies such that Federal mapping standards of 80% accuracies for all classes were met. The scale used to quantify vegetation adequately meets the needs of the stakeholder group. Increasing the scale to meet the U.S. Geological Survey (USGS)-National Park Service (NPS)National Mapping Program's minimum mapping unit of 0.5 ha is unwarranted because this scale would reduce the resolution of some classes (e.g., seep willow/coyote willow would likely be combined with tamarisk). While this would undoubtedly improve classification accuracies, it would not provide the community-level information about vegetation change that would benefit stakeholders. The identification of vegetation classes should follow NPS mapping approaches to complement the national effort and should incorporate the alternative analysis for community identification that is being incorporated into newer NPS mapping efforts. National Vegetation Classification is followed in this report for association- to formation-level categories. Accuracies could be improved by including more environmental variables such as stage elevation in the classification process and incorporating object-based classification methods. Another approach that may address the heterogeneous species issue and classification is to use spectral mixing analysis to estimate the fractional cover of species within each pixel and better quantify the cover of individual species that compose a cover class. Varying flights to capture vegetation at different times of the year might also help separate some vegetation classes, though the cost may be prohibitive. Lastly, photointerpretation instead of automated mapping could be tried. Photointerpretation would likely not improve accuracies in this case, howev

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

Directory of Open Access Journals (Sweden)

Frank Canters

2008-06-01

Full Text Available Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city’s inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing.

Moment methods for nonlinear maps

International Nuclear Information System (INIS)

Pusch, G.D.; Atomic Energy of Canada Ltd., Chalk River, ON

1993-01-01

It is shown that Differential Algebra (DA) may be used to push moments of distributions through a map, at a computational cost per moment comparable to pushing a single particle. The algorithm is independent of order, and whether or not the map is symplectic. Starting from the known result that moment-vectors transform linearly - like a tensor - even under a nonlinear map, I suggest that the form of the moment transformation rule indicates that the moment-vectors are elements of the dual to DA-vector space. I propose several methods of manipulating moments and constructing invariants using DA. I close with speculations on how DA might be used to ''close the circle'' to solve the inverse moment problem, yielding an entirely DA-and-moment-based space-charge code. (Author)

Radiation Source Mapping with Bayesian Inverse Methods

Science.gov (United States)

Hykes, Joshua Michael

We present a method to map the spectral and spatial distributions of radioactive sources using a small number of detectors. Locating and identifying radioactive materials is important for border monitoring, accounting for special nuclear material in processing facilities, and in clean-up operations. Most methods to analyze these problems make restrictive assumptions about the distribution of the source. In contrast, the source-mapping method presented here allows an arbitrary three-dimensional distribution in space and a flexible group and gamma peak distribution in energy. To apply the method, the system's geometry and materials must be known. A probabilistic Bayesian approach is used to solve the resulting inverse problem (IP) since the system of equations is ill-posed. The probabilistic approach also provides estimates of the confidence in the final source map prediction. A set of adjoint flux, discrete ordinates solutions, obtained in this work by the Denovo code, are required to efficiently compute detector responses from a candidate source distribution. These adjoint fluxes are then used to form the linear model to map the state space to the response space. The test for the method is simultaneously locating a set of 137Cs and 60Co gamma sources in an empty room. This test problem is solved using synthetic measurements generated by a Monte Carlo (MCNP) model and using experimental measurements that we collected for this purpose. With the synthetic data, the predicted source distributions identified the locations of the sources to within tens of centimeters, in a room with an approximately four-by-four meter floor plan. Most of the predicted source intensities were within a factor of ten of their true value. The chi-square value of the predicted source was within a factor of five from the expected value based on the number of measurements employed. With a favorable uniform initial guess, the predicted source map was nearly identical to the true distribution

Using multi-spectral sensors for vegetation mapping

CSIR Research Space (South Africa)

Van Deventer, Heidi

2016-07-01

Full Text Available Wetland and estuarine vegetation is often difficult to detect and separate from adjacent land covers with multispectral sensors for a number of reasons. The spatial resolution of space-borne sensors is often insufficient for these features which...

Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska

Science.gov (United States)

Lara, Mark J.; Nitze, Ingmar; Grosse, Guido; McGuire, A. David

2018-01-01

Arctic tundra landscapes are composed of a complex mosaic of patterned ground features, varying in soil moisture, vegetation composition, and surface hydrology over small spatial scales (10–100 m). The importance of microtopography and associated geomorphic landforms in influencing ecosystem structure and function is well founded, however, spatial data products describing local to regional scale distribution of patterned ground or polygonal tundra geomorphology are largely unavailable. Thus, our understanding of local impacts on regional scale processes (e.g., carbon dynamics) may be limited. We produced two key spatiotemporal datasets spanning the Arctic Coastal Plain of northern Alaska (~60,000 km2) to evaluate climate-geomorphological controls on arctic tundra productivity change, using (1) a novel 30 m classification of polygonal tundra geomorphology and (2) decadal-trends in surface greenness using the Landsat archive (1999–2014). These datasets can be easily integrated and adapted in an array of local to regional applications such as (1) upscaling plot-level measurements (e.g., carbon/energy fluxes), (2) mapping of soils, vegetation, or permafrost, and/or (3) initializing ecosystem biogeochemistry, hydrology, and/or habitat modeling.

SENTINEL-1 and SENTINEL-2 Data Fusion for Wetlands Mapping: Balikdami, Turkey

Science.gov (United States)

Kaplan, G.; Avdan, U.

2018-04-01

Wetlands provide a number of environmental and socio-economic benefits such as their ability to store floodwaters and improve water quality, providing habitats for wildlife and supporting biodiversity, as well as aesthetic values. Remote sensing technology has proven to be a useful and frequent application in monitoring and mapping wetlands. Combining optical and microwave satellite data can help with mapping and monitoring the biophysical characteristics of wetlands and wetlands` vegetation. Also, fusing radar and optical remote sensing data can increase the wetland classification accuracy. In this paper, data from the fine spatial resolution optical satellite, Sentinel-2 and the Synthetic Aperture Radar Satellite, Sentinel-1, were fused for mapping wetlands. Both Sentinel-1 and Sentinel-2 images were pre-processed. After the pre-processing, vegetation indices were calculated using the Sentinel-2 bands and the results were included in the fusion data set. For the classification of the fused data, three different classification approaches were used and compared. The results showed significant improvement in the wetland classification using both multispectral and microwave data. Also, the presence of the red edge bands and the vegetation indices used in the data set showed significant improvement in the discrimination between wetlands and other vegetated areas. The statistical results of the fusion of the optical and radar data showed high wetland mapping accuracy, showing an overall classification accuracy of approximately 90 % in the object-based classification method. For future research, we recommend multi-temporal image use, terrain data collection, as well as a comparison of the used method with the traditional image fusion techniques.

Comparison of vitamin losses in vegetables due to various cooking methods.

Science.gov (United States)

Rumm-Kreuter, D; Demmel, I

1990-01-01

Preparing vegetables with heat the contents of their constituents will change to a various extent. Particularly the water-soluble and the heat-sensitive vitamins are affected. At an early stage the vitamin C losses were investigated, because of vitamin C's indicating function for oxidation and leaching-out processes (1, 2, 7, 11-13, 15, 17). The degree of vitamin losses is influenced by various factors, for example the type of food, variety of vegetables, the way of cutting, preparation, duration and method of cooking. The influence of the various cooking methods with regard to the losses of certain water-soluble vitamins will be discussed.

Linear Algebraic Method for Non-Linear Map Analysis

International Nuclear Information System (INIS)

Yu, L.; Nash, B.

2009-01-01

We present a newly developed method to analyze some non-linear dynamics problems such as the Henon map using a matrix analysis method from linear algebra. Choosing the Henon map as an example, we analyze the spectral structure, the tune-amplitude dependence, the variation of tune and amplitude during the particle motion, etc., using the method of Jordan decomposition which is widely used in conventional linear algebra.

A method to correct coordinate distortion in EBSD maps

DEFF Research Database (Denmark)

Zhang, Yubin; Elbrønd, Andreas Benjamin; Lin, Fengxiang

2014-01-01

Drift during electron backscatter diffraction mapping leads to coordinate distortions in resulting orientation maps, which affects, in some cases significantly, the accuracy of analysis. A method, thin plate spline, is introduced and tested to correct such coordinate distortions in the maps after...... the electron backscatter diffraction measurements. The accuracy of the correction as well as theoretical and practical aspects of using the thin plate spline method is discussed in detail. By comparing with other correction methods, it is shown that the thin plate spline method is most efficient to correct...

A method for determination of 90Sr in vegetation

International Nuclear Information System (INIS)

Nygren, U.

1998-12-01

This report describes a method for determination of 90 Sr in vegetation. The method consists of wet-ashing the samples and separating Sr from the sample matrix by oxalate precipitation and extraction chromatography. 90 Y ingrowth is awaited after which Y is separated from Sr and 90 Y measured in a proportional counter. The method has been applied on two reference materials and the 90 Sr results agree well with the recommended values. The method has also been used on 20 samples of blueberry twigs and the mean recovery of Sr was 74%

A HYBRID METHOD IN VEGETATION HEIGHT ESTIMATION USING POLINSAR IMAGES OF CAMPAIGN BIOSAR

Directory of Open Access Journals (Sweden)

S. Dehnavi

2015-12-01

Full Text Available Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy. Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar

Science.gov (United States)

Dehnavi, S.; Maghsoudi, Y.

2015-12-01

Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

Weed map generation from UAV image mosaics based on crop row detection

DEFF Research Database (Denmark)

Midtiby, Henrik Skov

To control weed in a field effectively with a minimum of herbicides, knowledge about the weed patches is required. Based on images acquired by Unmanned Aerial Vehicles (UAVs), a vegetation map of the entire field can be generated. Manual analysis, which is often required, to detect weed patches...... is used as input for the method. Issues related to perspective distortion are reduced by using an orthomosaic, which is a high resolution image of the entire field, built from hundreds of images taken by a UAV. A vegetation map is generated from the orthomosaic by calculating the excess green color index...

Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

Science.gov (United States)

Varlamova, Eugenia V.; Solovyev, Vladimir S.

2017-11-01

Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

An empirical study on the utility of BRDF model parameters and topographic parameters for mapping vegetation in a semi-arid region with MISR imagery

Science.gov (United States)

Multi-angle remote sensing has been proved useful for mapping vegetation community types in desert regions. Based on Multi-angle Imaging Spectro-Radiometer (MISR) multi-angular images, this study compares roles played by Bidirectional Reflectance Distribution Function (BRDF) model parameters with th...

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

Science.gov (United States)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

South Florida Everglades: satellite image map

Science.gov (United States)

Jones, John W.; Thomas, Jean-Claude; Desmond, G.B.

2001-01-01

These satellite image maps are one product of the USGS Land Characteristics from Remote Sensing project, funded through the USGS Place-Based Studies Program (http://access.usgs.gov/) with support from the Everglades National Park (http://www.nps.gov/ever/). The objective of this project is to develop and apply innovative remote sensing and geographic information system techniques to map the distribution of vegetation, vegetation characteristics, and related hydrologic variables through space and over time. The mapping and description of vegetation characteristics and their variations are necessary to accurately simulate surface hydrology and other surface processes in South Florida and to monitor land surface changes. As part of this research, data from many airborne and satellite imaging systems have been georeferenced and processed to facilitate data fusion and analysis. These image maps were created using image fusion techniques developed as part of this project.

A multi-scale method of mapping urban influence

Science.gov (United States)

Timothy G. Wade; James D. Wickham; Nicola Zacarelli; Kurt H. Riitters

2009-01-01

Urban development can impact environmental quality and ecosystem services well beyond urban extent. Many methods to map urban areas have been developed and used in the past, but most have simply tried to map existing extent of urban development, and all have been single-scale techniques. The method presented here uses a clustering approach to look beyond the extant...

Evaluation of identification methods of irradiated spices and dehydrated vegetables in Brazil

International Nuclear Information System (INIS)

Bernardes, D.M.L.; Del Mastro, N.L.

1998-01-01

Complete text of publication follows. This paper deals with the use of analytical methods to determine whether imported or for export Brazilian spices and dehydrated vegetables were irradiated. Viscosimetry, thermoluminescence (TL) and electron spin resonance (ESR) were used for the identification of some irradiated products: black pepper, white pepper, cinnamon, nutmeg, garlic, cumin, oregano, celery, paprika and coriander. Viscosimetry was performed in suspensions of irradiated spices and dehydrated vegetables which had been gellified by heat. Thermoluminescence (TL) is based on the transference of electrons to an excited state by radiation with emission of light when the electrons are thermally stimulated. The thermoluminescent signal of spices can be explained by the presence of mineral grains adhering on the surface of the samples. Free radicals produced by irradiation of spices were analyzed by electron spin resonance (EPR) signals. The results of this study lead to the conclusion that viscosimetry, thermoluminescence and electron spin resonance are analytical methods that can be use to detect whether spices and dehydrated vegetables were irradiated, specially when a combination of different methods was used

A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series

OpenAIRE

David Helman; Itamar M. Lensky; Naama Tessler; Yagil Osem

2015-01-01

We present an efficient method for monitoring woody (i.e., evergreen) and herbaceous (i.e., ephemeral) vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI) time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI ...

Vegetation - Lassen Foothills [ds564

Data.gov (United States)

California Natural Resource Agency — In 2007 Aerial Information Systems, Inc. (AIS) was contracted by the California Native Plant Society (CNPS) to produce a vegetation map for approximately 100,000...

Habitat mapping using hyperspectral images in the vicinity of Hekla volcano in Iceland

Science.gov (United States)

Vilmundardóttir, Olga K.; Sigurmundsson, Friðþór S.; Pedersen, Gro B. M.; Falco, Nicola; Rustowicz, Rose; Gísladóttir, Guðrún; Benediktsson, Jón A.

2016-04-01

Hekla, one of the most active volcanoes in Iceland, has created a diverse volcanic landscape with lava flows, hyaloclastite and tephra fields. The variety of geological formations and different times of formation create diverse vegetation within Hekla's vicinity. The region is subjected to extensive loss of vegetation cover and soil erosion due to human utilization of woodlands and ongoing sheep grazing. The eolian activity and frequent tephra deposition has created vast areas of sparse vegetation cover. Over the 20th century, many activities have centered on preventing further loss of vegetated land and restoring ecosystems. The benefit of these activities is now noticeable in the increased vegetation and woodland cover although erosion is still active within the area. For mapping and monitoring this highly dynamic environment remote sensing techniques are extremely useful. One of the principal goals of the project 'Environmental Mapping and Monitoring of Iceland with Remote Sensing' (EMMIRS) is to use hyperspectral images and LiDAR data to classify and map the vegetation within the Hekla area. The data was collected in an aerial survey in summer 2015 by the Natural Environment Research Council (NERC), UK. The habitat type classification, currently being developed at the Icelandic Institute of Natural History and follows the structure of the EUNIS classification system, will be used for classifying the vegetation. The habitat map created by this new technique's outcome will be compared to the existent vegetation maps made by the conventional vegetation mapping method and the multispectral image classification techniques. In the field, vegetation cover, soil properties and spectral reflectance were measured within different habitat types. Special emphasis was on collecting data on vegetation and soil in the historical lavas from Hekla for assessing habitats forming over the millennia. A lava-chronosequence was established by measuring vegetation and soil in lavas

Further results for crack-edge mappings by ray methods

International Nuclear Information System (INIS)

Norris, A.N.; Achenbach, J.D.; Ahlberg, L.; Tittman, B.R.

1984-01-01

This chapter discusses further extensions of the local edge mapping method to the pulse-echo case and to configurations of water-immersed specimens and transducers. Crack edges are mapped by the use of arrival times of edge-diffracted signals. Topics considered include local edge mapping in a homogeneous medium, local edge mapping algorithms, local edge mapping through an interface, and edge mapping through an interface using synthetic data. Local edge mapping is iterative, with two or three iterations required for convergence

Mapping rice extent map with crop intensity in south China through integration of optical and microwave images based on google earth engine

Science.gov (United States)

Zhang, X.; Wu, B.; Zhang, M.; Zeng, H.

2017-12-01

Rice is one of the main staple foods in East Asia and Southeast Asia, which has occupied more than half of the world's population with 11% of cultivated land. Study on rice can provide direct or indirect information on food security and water source management. Remote sensing has proven to be the most effective method to monitoring the cropland in large scale by using temporary and spectral information. There are two main kinds of satellite have been used to mapping rice including microwave and optical. Rice, as the main crop of paddy fields, the main feature different from other crops is flooding phenomenon at planning stage (Figure 1). Microwave satellites can penetrate through clouds and efficiency on monitoring flooding phenomenon. Meanwhile, the vegetation index based on optical satellite can well distinguish rice from other vegetation. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for processing very large geospatial datasets. Google has collected large number of remote sensing satellite data around the world, which providing researchers with the possibility of doing application by using multi-source remote sensing data in a large area. In this work, we map rice planting area in south China through integration of Landsat-8 OLI, Sentienl-2, and Sentinel-1 Synthetic Aperture Radar (SAR) images. The flowchart is shown in figure 2. First, a threshold method the VH polarized backscatter from SAR sensor and vegetation index including normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) from optical sensor were used the classify the rice extent map. The forest and water surface extent map provided by earth engine were used to mask forest and water. To overcome the problem of the "salt and pepper effect" by Pixel-based classification when the spatial resolution increased, we segment the optical image and use the pixel- based classification results to merge the object

USING IMAGE PROCESSING METHODS WITH RASTER EDITING TOOLS FOR MAPPING EELGRASS DISTRIBUTIONS IN PACIFIC NORHWEST ESTUARIES

Science.gov (United States)

False-color near-infrared (CIR) aerial photography of seven Oregon estuaries was acquired at extreme low tides and digitally orthorectified with a ground pixel resolution of 25 cm to provide data for intertidal vegetation mapping. Exposed, semi-exposed and some submerged eelgras...

Atlas of the potential vegetation of Ethiopia

DEFF Research Database (Denmark)

Friis, Ib; Demissew, Sebsebe; van Breugel, Paulo

Based on many years of field work by the two senior authors (Ib Friis and Sebsebe Demissew) and with the application of GIS analyses (by P. van Breugel) 15 major vegetation types in Ethiopia are described and mapped. The book descibes the structure and floristic composition of the vegetation types...

Mapeamento da antiga cobertura vegetal de várzea do Baixo Amazonas a partir de imagens históricas (1975-1981 do Sensor MSS-Landsat Mapping ancient vegetation cover of the Amazon floodplain using historical MSS/Landsat images (1975-1981

Directory of Open Access Journals (Sweden)

Vivian Fróes Renó

2011-03-01

Full Text Available Este estudo apresenta um mapa da cobertura vegetal da planície de inundação do Rio Amazonas entre as cidades de Parintins (AM e Almeirim (PA, com base em imagens Landsat-MSS adquiridas entre 1975 e 1981. O processamento digital dessas imagens envolveu a transformação para imagens-fração de vegetação, solo e água escura (sombra, seguido da aplicação de técnicas de segmentação e classificação por região. O mapa resultante da classificação foi organizado em quatro classes de cobertura do solo: floresta de várzea, vegetação não-florestal de várzea, solo exposto e água aberta. A precisão do mapa foi estimada a partir de dois tipos de informações coletadas em campo: 1 pontos de descrição: para validação das classes de cobertura não sujeitas a grandes alterações, como é o caso dos corpos d'água permanentes, e identificação de indicadores dos tipos de cobertura original presentes na paisagem na ocasião da obtenção das imagens (72 pontos; 2 entrevistas com moradores antigos para a recuperação da memória sobre a cobertura vegetal existente há 30 anos (44 questionários. Ao todo foram coletadas informações em 116 pontos distribuídos ao longo da área de estudo. Esses pontos foram utilizados para calcular o Índice Kappa de concordância entre os dados de campo e o mapa resultante da classificação automática, cujo valor (0,78 indica a boa qualidade do mapa de cobertura vegetal da várzea. Os resultados mostram que a região possuía uma cobertura florestal de várzea de aproximadamente 8.650 km2 no período de aquisição das imagens.This study presents a vegetation map of the Amazon River floodplain between the towns of Parintins (AM and Almeirim (PA, based on Landsat-MSS scenes from 1975 to 1981. Digital processing involved the transformation of multispectral images into fraction-images of vegetation, soil and dark water (shadow, followed by the application of segmentation and region

On the suitability of MODIS time series metrics to map vegetation types in dry savanna ecosystems: A case study in the Kalahari of NE Namibia

NARCIS (Netherlands)

Hüttich, C.; Gessner, U.; Herold, M.; Strohbach, B.; Schmidt, M.; Keil, M.; Dech, S.

2009-01-01

The characterization and evaluation of the recent status of biodiversity in Southern Africa’s Savannas is a major prerequisite for suitable and sustainable land management and conservation purposes. This paper presents an integrated concept for vegetation type mapping in a dry savanna ecosystem

Climate change and spatial distribution of vegetation in Colombia

Directory of Open Access Journals (Sweden)

Juan Carlos Alarcon Hincapie

2013-12-01

Full Text Available Vegetation change under two climate change scenarios in different periods of the 21st Century are modeled for Colombia. Vegetation for the years 1970 to 2000 was reproduced using the Holdridge model with climate data with a spatial resolution of 900 meters. The vegetation types that occupied the most territory were sub-humid tropical forest, tropical dry forest and Andean wet forest. These results were validated by comparing with the Colombian ecosystem map (SINA, 2007, which confirmed a high degree of similarity between the modeled spatial vegetation patterns and modern ecosystem distributions. Future vegetation maps were simulated using data generated by a regional climate model under two scenarios (A2 and B2; IPCC, 2007 for the periods 2011-2040 and 2070-2100. Based on our predictions high altitude vegetation will convert to that of lower altitudes and drier provinces with the most dramatic change occurring in the A2 scenario from 2070-2100. The most affected areas are the páramo and other high Andean vegetation types, which in the timeframe of the explored scenarios will disappear by the middle of the 21st Century.

A Progressive Buffering Method for Road Map Update Using OpenStreetMap Data

Directory of Open Access Journals (Sweden)

Changyong Liu

2015-07-01

Full Text Available Web 2.0 enables a two-way interaction between servers and clients. GPS receivers become available to more citizens and are commonly found in vehicles and smart phones, enabling individuals to record and share their trajectory data on the Internet and edit them online. OpenStreetMap (OSM makes it possible for citizens to contribute to the acquisition of geographic information. This paper studies the use of OSM data to find newly mapped or built roads that do not exist in a reference road map and create its updated version. For this purpose, we propose a progressive buffering method for determining an optimal buffer radius to detect the new roads in the OSM data. In the next step, the detected new roads are merged into the reference road maps geometrically, topologically, and semantically. Experiments with OSM data and reference road maps over an area of 8494 km2 in the city of Wuhan, China and five of its 5 km × 5 km areas are conducted to demonstrate the feasibility and effectiveness of the method. It is shown that the OSM data can add 11.96% or a total of 2008.6 km of new roads to the reference road maps with an average precision of 96.49% and an average recall of 97.63%.

Simple saponification method for the quantitative determination of carotenoids in green vegetables.

Science.gov (United States)

Larsen, Erik; Christensen, Lars P

2005-08-24

A simple, reliable, and gentle saponification method for the quantitative determination of carotenoids in green vegetables was developed. The method involves an extraction procedure with acetone and the selective removal of the chlorophylls and esterified fatty acids from the organic phase using a strongly basic resin (Ambersep 900 OH). Extracts from common green vegetables (beans, broccoli, green bell pepper, chive, lettuce, parsley, peas, and spinach) were analyzed by high-performance liquid chromatography (HPLC) for their content of major carotenoids before and after action of Ambersep 900 OH. The mean recovery percentages for most carotenoids [(all-E)-violaxanthin, (all-E)-lutein epoxide, (all-E)-lutein, neolutein A, and (all-E)-beta-carotene] after saponification of the vegetable extracts with Ambersep 900 OH were close to 100% (99-104%), while the mean recovery percentages of (9'Z)-neoxanthin increased to 119% and that of (all-E)-neoxanthin and neolutein B decreased to 90% and 72%, respectively.

Mapping critical levels of ozone, sulfur dioxide and nitrogen oxide for crops, forests and natural vegetation in the United States

International Nuclear Information System (INIS)

Rosenbaum, B.J.; Strickland, T.C.; McDowell, M.K.

1994-01-01

Air pollution abatement strategies for controlling nitrogen dioxide, sulfur dioxide, and ozone emissions in the United States focus on a 'standards-based' approach. This approach places limits on air pollution by maintaining a baseline value for air quality, no matter what the ecosystem can or cannot withstand. This paper, presents example critical levels maps for the conterminous U.S. developed using the 'effects-based' mapping approach as defined by the United Nations Economic Commission for Europe's Convention on Long-Range Transboundary Air Pollution, Task Force on Mapping. This approach emphasizes the pollution level or load capacity an ecosystem can accommodate before degradation occurs, and allows for analysis of cumulative effects. Presents the first stage of an analysis that reports the distribution of exceedances of critical levels for NO 2 , SO 2 , and O 3 in sensitive forest, crop, and natural vegetation ecosystems in the contiguous United States. It is concluded that extrapolation to surrounding geographic areas requires the analysis of diverse and compounding factors that preclude simple extrapolation methods. Pollutant data depicted in this analysis are limited to locationally specific data, and would be enhanced by utilizing spatial statistics, along with converging associated anthropogenic and climatological factors. Values used for critical levels were derived from current scientific knowledge. While not intended to be a definitive value, adjustments will occur as the scientific community gains new insight to pollutant/receptor relationships. We recommend future analysis to include a refinement of sensitive receptor data coverages and to report relative proportions of exceedances at varying grid scales. 27 refs., 4 figs., 1 tab

An integrated pan-tropical biomass map using multiple reference datasets.

Science.gov (United States)

Avitabile, Valerio; Herold, Martin; Heuvelink, Gerard B M; Lewis, Simon L; Phillips, Oliver L; Asner, Gregory P; Armston, John; Ashton, Peter S; Banin, Lindsay; Bayol, Nicolas; Berry, Nicholas J; Boeckx, Pascal; de Jong, Bernardus H J; DeVries, Ben; Girardin, Cecile A J; Kearsley, Elizabeth; Lindsell, Jeremy A; Lopez-Gonzalez, Gabriela; Lucas, Richard; Malhi, Yadvinder; Morel, Alexandra; Mitchard, Edward T A; Nagy, Laszlo; Qie, Lan; Quinones, Marcela J; Ryan, Casey M; Ferry, Slik J W; Sunderland, Terry; Laurin, Gaia Vaglio; Gatti, Roberto Cazzolla; Valentini, Riccardo; Verbeeck, Hans; Wijaya, Arief; Willcock, Simon

2016-04-01

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets. © 2015 John Wiley & Sons Ltd.

Depth Estimation of Submerged Aquatic Vegetation in Clear Water Streams Using Low-Altitude Optical Remote Sensing.

Science.gov (United States)

Visser, Fleur; Buis, Kerst; Verschoren, Veerle; Meire, Patrick

2015-09-30

UAVs and other low-altitude remote sensing platforms are proving very useful tools for remote sensing of river systems. Currently consumer grade cameras are still the most commonly used sensors for this purpose. In particular, progress is being made to obtain river bathymetry from the optical image data collected with such cameras, using the strong attenuation of light in water. No studies have yet applied this method to map submergence depth of aquatic vegetation, which has rather different reflectance characteristics from river bed substrate. This study therefore looked at the possibilities to use the optical image data to map submerged aquatic vegetation (SAV) depth in shallow clear water streams. We first applied the Optimal Band Ratio Analysis method (OBRA) of Legleiter et al. (2009) to a dataset of spectral signatures from three macrophyte species in a clear water stream. The results showed that for each species the ratio of certain wavelengths were strongly associated with depth. A combined assessment of all species resulted in equally strong associations, indicating that the effect of spectral variation in vegetation is subsidiary to spectral variation due to depth changes. Strongest associations (R²-values ranging from 0.67 to 0.90 for different species) were found for combinations including one band in the near infrared (NIR) region between 825 and 925 nm and one band in the visible light region. Currently data of both high spatial and spectral resolution is not commonly available to apply the OBRA results directly to image data for SAV depth mapping. Instead a novel, low-cost data acquisition method was used to obtain six-band high spatial resolution image composites using a NIR sensitive DSLR camera. A field dataset of SAV submergence depths was used to develop regression models for the mapping of submergence depth from image pixel values. Band (combinations) providing the best performing models (R²-values up to 0.77) corresponded with the OBRA

Non- chemical methods of seed treatment for control of seed- borne pathogens on vegetables

NARCIS (Netherlands)

Amein, T.; Wright, S.A.I.; Wickstrom, M.; Schmitt, A.; Koch, E.; Wolf, van der J.M.; Groot, S.P.C.; Werner, S.; Jahn, M.

2006-01-01

The aim of EU-project "Seed Treatments for Organic Vegetable Production" (STOVE) was to evaluate non-chemical methods for control of seed-borne pathogens in organic vegetable production. Physical (hot air, hot water and electron) and biologi-cal (microorganisms and different agents of natural

What is an evidence map? A systematic review of published evidence maps and their definitions, methods, and products.

Science.gov (United States)

Miake-Lye, Isomi M; Hempel, Susanne; Shanman, Roberta; Shekelle, Paul G

2016-02-10

The need for systematic methods for reviewing evidence is continuously increasing. Evidence mapping is one emerging method. There are no authoritative recommendations for what constitutes an evidence map or what methods should be used, and anecdotal evidence suggests heterogeneity in both. Our objectives are to identify published evidence maps and to compare and contrast the presented definitions of evidence mapping, the domains used to classify data in evidence maps, and the form the evidence map takes. We conducted a systematic review of publications that presented results with a process termed "evidence mapping" or included a figure called an "evidence map." We identified publications from searches of ten databases through 8/21/2015, reference mining, and consulting topic experts. We abstracted the research question, the unit of analysis, the search methods and search period covered, and the country of origin. Data were narratively synthesized. Thirty-nine publications met inclusion criteria. Published evidence maps varied in their definition and the form of the evidence map. Of the 31 definitions provided, 67 % described the purpose as identification of gaps and 58 % referenced a stakeholder engagement process or user-friendly product. All evidence maps explicitly used a systematic approach to evidence synthesis. Twenty-six publications referred to a figure or table explicitly called an "evidence map," eight referred to an online database as the evidence map, and five stated they used a mapping methodology but did not present a visual depiction of the evidence. The principal conclusion of our evaluation of studies that call themselves "evidence maps" is that the implied definition of what constitutes an evidence map is a systematic search of a broad field to identify gaps in knowledge and/or future research needs that presents results in a user-friendly format, often a visual figure or graph, or a searchable database. Foundational work is needed to better

A Phenology-Based Method for Monitoring Woody and Herbaceous Vegetation in Mediterranean Forests from NDVI Time Series

Directory of Open Access Journals (Sweden)

David Helman

2015-09-01

Full Text Available We present an efficient method for monitoring woody (i.e., evergreen and herbaceous (i.e., ephemeral vegetation in Mediterranean forests at a sub pixel scale from Normalized Difference Vegetation Index (NDVI time series derived from the Moderate Resolution Imaging Spectroradiometer (MODIS. The method is based on the distinct development periods of those vegetation components. In the dry season, herbaceous vegetation is absent or completely dry in Mediterranean forests. Thus the mean NDVI in the dry season was attributed to the woody vegetation (NDVIW. A constant NDVI value was assumed for soil background during this period. In the wet season, changes in NDVI were attributed to the development of ephemeral herbaceous vegetation in the forest floor and its maximum value to the peak green cover (NDVIH. NDVIW and NDVIH agreed well with field estimates of leaf area index and fraction of vegetation cover in two differently structured Mediterranean forests. To further assess the method’s assumptions, understory NDVI was retrieved form MODIS Bidirectional Reflectance Distribution Function (BRDF data and compared with NDVIH. After calibration, leaf area index and woody and herbaceous vegetation covers were assessed for those forests. Applicability for pre- and post-fire monitoring is presented as a potential use of this method for forest management in Mediterranean-climate regions.

Introducing a method for mapping recreational experience

DEFF Research Database (Denmark)

Lindholst, Andrej Christian; Dempsey, Nicola; Burton, Mel

2013-01-01

spaces provide and support a range of recreational experiences. The exploration reported here is based on a short review of the methods background and an application in two test sites in Sheffield, South Yorkshire in early summer 2010. This paper critically appraises the application of rec......-mapping’, an innovative method of analysing and mapping positive recreational experiences in urban green spaces is explored and piloted within the UK planning context. Originating in the Nordic countries, this on-site method can provide urban planners and designers with data about the extent to which specific green......-mapping at smaller spatial scales and recommends further explorations within the UK planning context, as the method adds to existing open space assessment by providing a unique layer of information to analyse more fully the recreational qualities of urban green spaces....

Acoustic methods for cavitation mapping in biomedical applications

Science.gov (United States)

Wan, M.; Xu, S.; Ding, T.; Hu, H.; Liu, R.; Bai, C.; Lu, S.

2015-12-01

In recent years, cavitation is increasingly utilized in a wide range of applications in biomedical field. Monitoring the spatial-temporal evolution of cavitation bubbles is of great significance for efficiency and safety in biomedical applications. In this paper, several acoustic methods for cavitation mapping proposed or modified on the basis of existing work will be presented. The proposed novel ultrasound line-by-line/plane-by-plane method can depict cavitation bubbles distribution with high spatial and temporal resolution and may be developed as a potential standard 2D/3D cavitation field mapping method. The modified ultrafast active cavitation mapping based upon plane wave transmission and reception as well as bubble wavelet and pulse inversion technique can apparently enhance the cavitation to tissue ratio in tissue and further assist in monitoring the cavitation mediated therapy with good spatial and temporal resolution. The methods presented in this paper will be a foundation to promote the research and development of cavitation imaging in non-transparent medium.

Large-Scale Mapping of Carbon Stocks in Riparian Forests with Self-Organizing Maps and the k-Nearest-Neighbor Algorithm

Directory of Open Access Journals (Sweden)

Leonhard Suchenwirth

2014-07-01

Full Text Available Among the machine learning tools being used in recent years for environmental applications such as forestry, self-organizing maps (SOM and the k-nearest neighbor (kNN algorithm have been used successfully. We applied both methods for the mapping of organic carbon (Corg in riparian forests due to their considerably high carbon storage capacity. Despite the importance of floodplains for carbon sequestration, a sufficient scientific foundation for creating large-scale maps showing the spatial Corg distribution is still missing. We estimated organic carbon in a test site in the Danube Floodplain based on RapidEye remote sensing data and additional geodata. Accordingly, carbon distribution maps of vegetation, soil, and total Corg stocks were derived. Results were compared and statistically evaluated with terrestrial survey data for outcomes with pure remote sensing data and for the combination with additional geodata using bias and the Root Mean Square Error (RMSE. Results show that SOM and kNN approaches enable us to reproduce spatial patterns of riparian forest Corg stocks. While vegetation Corg has very high RMSEs, outcomes for soil and total Corg stocks are less biased with a lower RMSE, especially when remote sensing and additional geodata are conjointly applied. SOMs show similar percentages of RMSE to kNN estimations.

Post-fire vegetation recovery in Portugal based on spot/vegetation data

Science.gov (United States)

Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

2010-04-01

A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI), with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation indices.

Mapping tropical dry forest habitats integrating landsat NDVI, Ikonos imagery, and topographic information in the Caribbean island of Mona.

Science.gov (United States)

Martinuzzi, Sebastiáin; Gould, William A; Ramos Gonzalez, Olga M; Martinez Robles, Alma; Calle Maldonado, Paulina; Pérez-Buitrago, Néstor; Fumero Caban, José J

2008-06-01

Assessing the status of tropical dry forest habitats using remote sensing technologies is one of the research priorities for Neotropical forests. We developed a simple method for mapping vegetation and habitats in a tropical dry forest reserve, Mona Island, Puerto Rico, by integrating the Normalized Difference Vegetation Index (NDVI) from Landsat, topographic information, and high-resolution Ikonos imagery. The method was practical for identifying vegetation types in areas with a great variety of plant communities and complex relief, and can be adapted to other dry forest habitats of the Caribbean Islands. NDVI was useful for identifying the distribution of forests, woodlands, and shrubland, providing a natural representation of the vegetation patterns on the island. The use of Ikonos imagery allowed increasing the number of land cover classes. As a result, sixteen land-cover types were mapped over the 5500 ha area, with a kappa coefficient of accuracy equal to 79%. This map is a central piece for modeling vertebrate species distribution and biodiversity patterns by the Puerto Rico Gap Analysis Project, and it is of great value for assisting research and management actions in the island.

Mapped Fourier Methods for stiff problems in toroidal geometry

OpenAIRE

Guillard , Herve

2014-01-01

Fourier spectral or pseudo-spectral methods are usually extremely efficient for periodic problems. However this efficiency is lost if the solutions have zones of rapid variations or internal layers. For these cases, a large number of Fourier modes are required and this makes the Fourier method unpractical in many cases. This work investigates the use of mapped Fourier method as a way to circumvent this problem. Mapped Fourier method uses instead of the usual Fourier interpolant the compositio...

Remote sensing application for delineating coastal vegetation - A case study

Digital Repository Service at National Institute of Oceanography (India)

Kunte, P.D.; Wagle, B.G.

Remote sensing data has been used for mapping coastal vegetation along the Goa Coast, India. The study envisages the use of digital image processing techniques for delineating geomorphic features and associated vegetation, including mangrove, along...

Sensory determinants of stated liking for vegetable names and actual liking for canned vegetables

DEFF Research Database (Denmark)

Dinnella, Caterina; Morizet, David; Masi, Camilla

2016-01-01

tastes (sweet, umami), delicate flavour and bright appealing colour. A second group of highly disliked vegetables consists of cauliflowers and broccoli, characterized by disliked sensations such as bitter taste and objectionable flavour. Internal Preference Maps from actual liking scores indicate...

Investigation on the Patterns of Global Vegetation Change Using a Satellite-Sensed Vegetation Index

Directory of Open Access Journals (Sweden)

Ainong Li

2010-06-01

Full Text Available The pattern of vegetation change in response to global change still remains a controversial issue. A Normalized Difference Vegetation Index (NDVI dataset compiled by the Global Inventory Modeling and Mapping Studies (GIMMS was used for analysis. For the period 1982–2006, GIMMS-NDVI analysis indicated that monthly NDVI changes show homogenous trends in middle and high latitude areas in the northern hemisphere and within, or near, the Tropic of Cancer and Capricorn; with obvious spatio-temporal heterogeneity on a global scale over the past two decades. The former areas featured increasing vegetation activity during growth seasons, and the latter areas experienced an even greater amplitude in places where precipitation is adequate. The discussion suggests that one should be cautious of using the NDVI time-series to analyze local vegetation dynamics because of its coarse resolution and uncertainties.

Santos Basin Geological Structures Mapped by Cross-gradient Method

Science.gov (United States)

Jilinski, P.; Fontes, S. L.

2011-12-01

Introduction We mapped regional-scale geological structures localized in offshore zone Santos Basin, South-East Brazilian Coast. The region is dominated by transition zone from oceanic to continental crust. Our objective was to determine the imprint of deeper crustal structures from correlation between bathymetric, gravity and magnetic anomaly maps. The region is extensively studied for oil and gas deposits including large tectonic sub-salt traps. Our method is based on gradient directions and their magnitudes product. We calculate angular differences and cross-product and access correlation between properties and map structures. Theory and Method We used angular differences and cross-product to determine correlated region between bathymetric, free-air gravity and magnetic anomaly maps. This gradient based method focuses on borders of anomalies and uses its morphological properties to access correlation between their sources. We generated maps of angles and cross-product distribution to locate correlated regions. Regional scale potential fields maps of FA and MA are a reflection of the overlaying and overlapping effects of the adjacent structures. Our interest was in quantifying and characterizing the relation between shapes of magnetic anomalies and gravity anomalies. Results Resulting maps show strong correlation between bathymetry and gravity anomaly and bathymetry and magnetic anomaly for large strictures including Serra do Mar, shelf, continental slope and rise. All maps display the regional dominance of NE-SW geological structures alignment parallel to the shore. Special interest is presented by structures transgressing this tendency. Magnetic, gravity anomaly and bathymetry angles map show large correlated region over the shelf zone and smaller scale NE-SW banded structures over abyssal plane. From our interpretation the large band of inverse correlation adjacent to the shore is generated by the gravity effect of Serra do Mar. Disrupting structures including

A scalable hybrid multi-robot SLAM method for highly detailed maps

NARCIS (Netherlands)

Pfingsthorn, M.; Slamet, B.; Visser, A.

2008-01-01

Recent successful SLAM methods employ hybrid map representations combining the strengths of topological maps and occupancy grids. Such representations often facilitate multi-agent mapping. In this paper, a successful SLAM method is presented, which is inspired by the manifold data structure by

Backtracking Method of Coloring Administrative Maps Considering Visual Perception Rules

Directory of Open Access Journals (Sweden)

WEI Zhiwei

2018-03-01

Full Text Available Color design in administrative maps should incorporate and balance area configuration, color harmony, and users' purposes. Based on visual perceptual rules, this paper quantifies color harmony, color contrast and perceptual balance in coloring administrative maps, and a model is suggested to evaluate the coloring quality after color template is selected. Then a backtracking method based on area balance is proposed to compute colored areas. Experiments show that this method can well meet visual perceptual rules while coloring administrative maps, and can be used for later map design.

Qualitative screening method for pesticide residues detection in fruits and vegetables

Directory of Open Access Journals (Sweden)

Iván Mauricio Huérfano Barco

2018-01-01

Full Text Available Because of the importance of developing methodologies that allow agricultural residues analysis, a rapid screening qualitative method for the determination of pesticides residues in fruits and vegetables was validated. The methodology was based on the European QuEChERS extraction method with an additional cleaning step by gel permeation chromatography (GPC, which helped to reduce the number of matrix components in the final extract. The analysis was carried out by gas chromatography coupled to mass spectrometry with a single quadrupole analyzer. The methodology was appropriate for the qualitative analysis of 31 pesticides at their respective maximum residue limits. Consistent results were obtained with respect to a quantitative routine methodology in the analysis of real samples, hence the methodology was proven to be a good alternative for the fast analysis of these contaminants in fruits and vegetables.

Spatial-temporal development of the mangrove vegetation cover on a hydraulic landfill (Via Expressa Sul, Florianópolis, SC): mapping and interpretation of digital aerophotographs, and quantitative analysis

OpenAIRE

Anderson Tavares de Melo; Eduardo Juan Soriano-Sierra; Luiz Antônio Paulino

2011-01-01

The implementation of a hydraulic landfill along the southern expressway (Via Expressa Sul), in the central-south region of Santa Catarina Island, started in 1995 and was completed in 1997. The landfill provided the mangrove vegetation a new environment to colonize, which has developed rapidly during this short period of time. This study mapped the vegetation cover of this region using aerial photographs from five years (1994, 1997, 2002, 2004 and 2007), which demonstrated the spatial-tempora...

Mapping the environmental and biogeographic complexity of the Amazon basin using remote sensing methods

Science.gov (United States)

Streher, A. S.; Cordeiro, C. L. O.; Silva, T. S. F.

2017-12-01

Mapping environmental envelopes onto geographical space has been classically important for understanding biogeographical patterns. Knowing the biotic and abiotic limits defining these envelopes, we can better understand the requirements limiting species distributions. Most present efforts in this regard have focused on single-species distribution models, but the current breadth and accessibility of quantitative, spatially explicit environmental information can also be explored from an environment-first perspective. We thus used remote sensing to determine the occurrence of environmental discontinuities in the Amazon region and evaluated if such discontinuities may act as barriers to determine species distribution and range limits, forming clear environmental envelopes. We combined data on topography (SRTM), precipitation (CHIRPS), vegetation descriptors (PALSAR-1 backscattering, biomass, NDVI) and temperature (MODIS), using object-based image analysis and unsupervised learning to map environmental envelopes. We identified 14 environmental envelopes for the Amazon sensu latissimo region, mainly delimited by changes in vegetation, topography and precipitation. The resulting envelopes were compared to the distribution of 120 species of Trogonidae, Galbulidae, Bucconidae, Cebidae, Hylidae and Lecythidaceae, amounting to 22,649 occurrence records within the Amazonregion. We determined species prevalence in each envelope by calculating the ratio between species relative frequency per envelope and envelope relative frequency (area) in the complete map. Values closer to 1 indicate a high degree of prevalence. We found strong envelope associations (prevalence > 0.5) for 20 species (17% of analyzed taxa). Although several biogeographical and ecological factors will influence the distribution of a species, our results show that not only geographical barriers, but also modern environmental discontinuities may limit the distribution of some species., and may have also done so

A method for mapping corn using the US Geological Survey 1992 National Land Cover Dataset

Science.gov (United States)

Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.

2006-01-01

Long-term exposure to elevated nitrate levels in community drinking water supplies has been associated with an elevated risk of several cancers including non-Hodgkin's lymphoma, colon cancer, and bladder cancer. To estimate human exposure to nitrate, specific crop type information is needed as fertilizer application rates vary widely by crop type. Corn requires the highest application of nitrogen fertilizer of crops grown in the Midwest US. We developed a method to refine the US Geological Survey National Land Cover Dataset (NLCD) (including map and original Landsat images) to distinguish corn from other crops. Overall average agreement between the resulting corn and other row crops class and ground reference data was 0.79 kappa coefficient with individual Landsat images ranging from 0.46 to 0.93 kappa. The highest accuracies occurred in Regions where corn was the single dominant crop (greater than 80.0%) and the crop vegetation conditions at the time of image acquisition were optimum for separation of corn from all other crops. Factors that resulted in lower accuracies included the accuracy of the NLCD map, accuracy of corn areal estimates, crop mixture, crop condition at the time of Landsat overpass, and Landsat scene anomalies.

Evaluation of DNA extraction methods for PCR-based detection of Listeria monocytogenes from vegetables.

Science.gov (United States)

Vojkovska, H; Kubikova, I; Kralik, P

2015-03-01

Epidemiological data indicate that raw vegetables are associated with outbreaks of Listeria monocytogenes. Therefore, there is a demand for the availability of rapid and sensitive methods, such as PCR assays, for the detection and accurate discrimination of L. monocytogenes. However, the efficiency of PCR methods can be negatively affected by inhibitory compounds commonly found in vegetable matrices that may cause false-negative results. Therefore, the sample processing and DNA isolation steps must be carefully evaluated prior to the introduction of such methods into routine practice. In this study, we compared the ability of three column-based and four magnetic bead-based commercial DNA isolation kits to extract DNA of the model micro-organism L. monocytogenes from raw vegetables. The DNA isolation efficiency of all isolation kits was determined using a triplex real-time qPCR assay designed to specifically detect L. monocytogenes. The kit with best performance, the PowerSoil(™) Microbial DNA Isolation Kit, is suitable for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. Coupled with the triplex real-time qPCR assay, this DNA isolation kit is applicable to the samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. Several recent outbreaks of Listeria monocytogenes have been associated with the consumption of fruits and vegetables. Real-time PCR assays allow fast detection and accurate quantification of microbes. However, the success of real-time PCR is dependent on the success with which template DNA can be extracted. The results of this study suggest that the PowerSoil(™) Microbial DNA Isolation Kit can be used for the extraction of amplifiable DNA from L. monocytogenes cells in vegetable with efficiencies ranging between 29.6 and 70.3%. This method is applicable to samples with bacterial loads of 10(3) bacterial cells per gram of L. monocytogenes. © 2014

Satellite monitoring of different vegetation types by differential optical absorption spectroscopy (DOAS in the red spectral range

Directory of Open Access Journals (Sweden)

T. Wagner

2007-01-01

Full Text Available A new method for the satellite remote sensing of different types of vegetation and ocean colour is presented. In contrast to existing algorithms relying on the strong change of the reflectivity in the red and near infrared spectral region, our method analyses weak narrow-band (few nm reflectance structures (i.e. "fingerprint" structures of vegetation in the red spectral range. It is based on differential optical absorption spectroscopy (DOAS, which is usually applied for the analysis of atmospheric trace gas absorptions. Since the spectra of atmospheric absorption and vegetation reflectance are simultaneously included in the analysis, the effects of atmospheric absorptions are automatically corrected (in contrast to other algorithms. The inclusion of the vegetation spectra also significantly improves the results of the trace gas retrieval. The global maps of the results illustrate the seasonal cycles of different vegetation types. In addition to the vegetation distribution on land, they also show patterns of biological activity in the oceans. Our results indicate that improved sets of vegetation spectra might lead to more accurate and more specific identification of vegetation type in the future.

Increasing the Accuracy of Mapping Urban Forest Carbon Density by Combining Spatial Modeling and Spectral Unmixing Analysis

Directory of Open Access Journals (Sweden)

Hua Sun

2015-11-01

Full Text Available Accurately mapping urban vegetation carbon density is challenging because of complex landscapes and mixed pixels. In this study, a novel methodology was proposed that combines a linear spectral unmixing analysis (LSUA with a linear stepwise regression (LSR, a logistic model-based stepwise regression (LMSR and k-Nearest Neighbors (kNN, to map the forest carbon density of Shenzhen City of China, using Landsat 8 imagery and sample plot data collected in 2014. The independent variables that contributed to statistically significantly improving the fit of a model to data and reducing the sum of squared errors were first selected from a total of 284 spectral variables derived from the image bands. The vegetation fraction from LSUA was then added as an independent variable. The results obtained using cross-validation showed that: (1 Compared to the methods without the vegetation information, adding the vegetation fraction increased the accuracy of mapping carbon density by 1%–9.3%; (2 As the observed values increased, the LSR and kNN residuals showed overestimates and underestimates for the smaller and larger observations, respectively, while LMSR improved the systematical over and underestimations; (3 LSR resulted in illogically negative and unreasonably large estimates, while KNN produced the greatest values of root mean square error (RMSE. The results indicate that combining the spatial modeling method LMSR and the spectral unmixing analysis LUSA, coupled with Landsat imagery, is most promising for increasing the accuracy of urban forest carbon density maps. In addition, this method has considerable potential for accurate, rapid and nondestructive prediction of urban and peri-urban forest carbon stocks with an acceptable level of error and low cost.

A Body of Work Standard-Setting Method with Construct Maps

Science.gov (United States)

Wyse, Adam E.; Bunch, Michael B.; Deville, Craig; Viger, Steven G.

2014-01-01

This article describes a novel variation of the Body of Work method that uses construct maps to overcome problems of transparency, rater inconsistency, and scores gaps commonly occurring with the Body of Work method. The Body of Work method with construct maps was implemented to set cut-scores for two separate K-12 assessment programs in a large…

Analysis of Decadal Vegetation Dynamics Using Multi-Scale Satellite Images

Science.gov (United States)

Chiang, Y.; Chen, K.

2013-12-01

This study aims at quantifying vegetation fractional cover (VFC) by incorporating multi-resolution satellite images, including Formosat-2(RSI), SPOT(HRV/HRG), Landsat (MSS/TM) and Terra/Aqua(MODIS), to investigate long-term and seasonal vegetation dynamics in Taiwan. We used 40-year NDVI records for derivation of VFC, with field campaigns routinely conducted to calibrate the critical NDVI threshold. Given different sensor capabilities in terms of their spatial and spectral properties, translation and infusion of NDVIs was used to assure NDVI coherence and to determine the fraction of vegetation cover at different spatio-temporal scales. Based on the proposed method, a bimodal sequence of intra-annual VFC which corresponds to the dual-cropping agriculture pattern was observed. Compared to seasonal VFC variation (78~90%), decadal VFC reveals moderate oscillations (81~86%), which were strongly linked with landuse changes and several major disturbances. This time-series mapping of VFC can be used to examine vegetation dynamics and its response associated with short-term and long-term anthropogenic/natural events.

Evaluation of sample preparation methods and optimization of nickel determination in vegetable tissues

Directory of Open Access Journals (Sweden)

Rodrigo Fernando dos Santos Salazar

2011-02-01

Full Text Available Nickel, although essential to plants, may be toxic to plants and animals. It is mainly assimilated by food ingestion. However, information about the average levels of elements (including Ni in edible vegetables from different regions is still scarce in Brazil. The objectives of this study were to: (a evaluate and optimize a method for preparation of vegetable tissue samples for Ni determination; (b optimize the analytical procedures for determination by Flame Atomic Absorption Spectrometry (FAAS and by Electrothermal Atomic Absorption (ETAAS in vegetable samples and (c determine the Ni concentration in vegetables consumed in the cities of Lorena and Taubaté in the Vale do Paraíba, State of São Paulo, Brazil. By means of the analytical technique for determination by ETAAS or FAAS, the results were validated by the test of analyte addition and recovery. The most viable method tested for quantification of this element was HClO4-HNO3 wet digestion. All samples but carrot tissue collected in Lorena contained Ni levels above the permitted by the Brazilian Ministry of Health. The most disturbing results, requiring more detailed studies, were the Ni concentrations measured in carrot samples from Taubaté, where levels were five times higher than permitted by Brazilian regulations.

Deriving soil function maps to assess related ecosystem services using imaging spectroscopy in the Lyss agricultural area, Switzerland

Science.gov (United States)

Diek, Sanne; de Jong, Rogier; Braun, Daniela; Böhler, Jonas; Schaepman, Michael

2014-05-01

Soils play an important role in the benefits offered by ecosystems services. In densely populated Switzerland soils are a scarce resource, with high pressure on services ranging from urban expansion to over-utilization. Key change drivers include erosion, soil degradation, land management change and (chemical) pollution, which should be taken into consideration. Therefore there is an emerging need for an integrated, sustainable and efficient system assessing the management of soil and land as a resource. The use of remote sensing can offer spatio-temporal and quantitative information of extended areas. In particular imaging spectroscopy has shown to perfectly complement existing sampling schemes as secondary information for digital soil mapping. Although only the upper-most layer of soil interacts with light when using reflectance spectroscopy, it still can offer valuable information that can be utilized by farmers and decision makers. Fully processed airborne imaging spectrometer data from APEX as well as land cover classification for the agricultural area in Lyss were available. Based on several spectral analysis methods we derived multiple soil properties, including soil organic matter, soil texture, and mineralogy; complemented by vegetation parameters, including leaf area index, chlorophyll content, pigment distribution, and water content. The surface variables were retrieved using a combination of index-based and physically-based retrievals. Soil properties in partly to fully vegetated areas were interpolated using regression kriging based methods. This allowed the continuous assessment of potential soil functions as well as non-contiguous maps of abundances of combined soil and vegetation parameters. Based on a simple regression model we could make a rough estimate of ecosystem services. This provided the opportunity to look at the differences between the interpolated soil function maps and the non-contiguous (but combined) vegetation and soil function maps

PEMETAAN FAKTOR C YANG DITURUNKAN DARI BERBAGAI INDEKS VEGETASI DATA PENGINDERAAN JAUH SEBAGAI MASUKAN PEMODELAN EROSI DI DAS MERAWU (C Factor Mapping Derived from Various Vegetation Indeces of Remotely Sensed Data for Erosion Modeling at Merawu Catchment

Directory of Open Access Journals (Sweden)

Bambang Sulistyo

2011-03-01

Full Text Available ABSTRAK Penelitian ini bertujuan untuk mengkaji berbagai indeks vegetasi yang diturunkan dari data penginderaan jauh dalam pemetaan faktor C sebagai masukan dalam pemodelan erosi USLE (Universal Soil Loss Equation. Metode yang digunakan dalam penelitian ini adalah dengan menganalisis data penginderaan jauh Landsat 7 ETM + sehingga menghasilkan berbagai indeks vegetasi yang kemudian dilakukan analisis korelasi dengan Faktor C yang diukur di lapangan pada 45 lokasi. Dari analisis ini diperoleh suatu model untuk pemetaan faktor C (C model dari berbagai indeks vegetasi. Peta faktor C yang diperoleh kemudian dilakukan validasi pada 48 lokasi sehingga akan diketahui keakuratan hasil pemodelan. Dalam penelitian ini dikaji 11 (sebelas indeks vegetasi yang diturunkan dari data penginderaan jauh, yaitu ARVI, MSAVI, TVI, VIF, NDVI, TSAVI, SAVI, EVI, RVI, DVI, dan PVI. Hasil penelitian menunjukkan bahwa dari 11 indeks vegetasi yang dikaji terdapat 8 indeks vegetasi yang menghasilkan peta faktor C dengan ketelitian yang tinggi, yaitu MSAVI, TVI, VIF, NDVI, TSAVI, SAVI, EVI, dan RVI. Indeks vegetasi yang menggunakan rumus yang lebih kompleks menghasilkan koefisien korelasi yang lebih tinggi dibanding dengan indeks vegetasi yang menggunakan rumus yang sederhana. Indeks vegetasi yang mempertimbangkan latar belakang tanah (MSAVI dan TSAVI mempunyai koefisien korelasi lebih tinggi dibanding dengan koefisien korelasi yang tidak mempertimbangkan latar belakang tanah. ABSTRACT The research was aim at studying C factor mapping derived from various vegetation indices of remotely-sensed data as input for USLE (Universal Soil Loss Equation erosion modeling at Merawu Catchment. Methodology applied was by analyzing remote sensing data of Landsat 7 ETM+ to obtain various vegetation indices for correlation analysis with C Factor measured directly from 45 locations on the field. The analysis resulted models for C factor mapping from various vegetation indices (Cmodel. These

Evaluation of the data of vegetable covering using fraction images and multitemporal vegetation index, derived of orbital data of moderate resolution of the sensor MODIS

International Nuclear Information System (INIS)

Murillo Mejia, Mario Humberto

2006-01-01

The objective was to evaluate the data obtained by sensor MODIS onboard the EOS terra satellite land cover units. The study area is the republic of Colombia in South America. The methodology consisted of analyzing the multitemporal (vegetation, soil and shade-water) fraction images and vegetation indices (NDVI) apply the lineal spectral mixture model to products derived from derived images by sensor MODIS data obtained in years 2001 and 2003. The mosaics of the original and the transformed vegetation (soil and shade-water) bands were generated for the whole study area using SPRING 4. 0 software, developed by INPE then these mosaics were segmented, classified, mapped, and edited to obtain a moderate resolution land cover map. The results derived from MODIS analysis were compared with Landsat ETM+ data acquire for a single test site. The results of the project showed the usefulness of MODIS images for large-scale land cover mapping and monitoring studies

Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado

Science.gov (United States)

Rockwell, Barnaby W.

2013-01-01

Multispectral satellite data acquired by the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 7 Enhanced Thematic Mapper Plus (TM) sensors are being used to populate an online Geographic Information System (GIS) of the spatial occurrence of mineral groups and green vegetation across the western conterminous United States and Alaska. These geospatial data are supporting U.S. Geological Survey national-scale mineral deposit database development and other mineral resource and geoenvironmental research as a means of characterizing mineral exposures related to mined and unmined hydrothermally altered rocks and mine waste. This report introduces a new methodology for the automated analysis of Landsat TM data that has been applied to more than 180 scenes covering the western United States. A map of mineral groups and green vegetation produced using this new methodology that covers the western San Juan Mountains, Colorado, and the Four Corners Region is presented. The map is provided as a layered GeoPDF and in GIS-ready digital format. TM data analysis results from other well-studied and mineralogically characterized areas with strong hydrothermal alteration and (or) supergene weathering of near-surface sulfide minerals are also shown and compared with results derived from ASTER data analysis.

A detection method of vegetable oils in edible blended oil based on three-dimensional fluorescence spectroscopy technique.

Science.gov (United States)

Xu, Jing; Liu, Xiao-Fei; Wang, Yu-Tian

2016-12-01

Edible blended vegetable oils are made from two or more refined oils. Blended oils can provide a wider range of essential fatty acids than single vegetable oils, which helps support good nutrition. Nutritional components in blended oils are related to the type and content of vegetable oils used, and a new, more accurate, method is proposed to identify and quantify the vegetable oils present using cluster analysis and a Quasi-Monte Carlo integral. Three-dimensional fluorescence spectra were obtained at 250-400nm (excitation) and 260-750nm (emission). Mixtures of sunflower, soybean and peanut oils were used as typical examples to validate the effectiveness of the method. Copyright © 2016 Elsevier Ltd. All rights reserved.

A new method to infer vegetation boundary movement from 'snapshot' data

NARCIS (Netherlands)

Eppinga, M.B.; Pucko, C.A.; Baudena, M.; Beckage, B.; Molofsky, J.

2012-01-01

Global change may induce shifts in plant community distributions at multiple spatial scales. At the ecosystem scale, such shifts may result in movement of ecotones or vegetation boundaries. Most indicators for ecosystem change require timeseries data, but here a new method is proposed enabling

Global vegetation change predicted by the modified Budyko model

Energy Technology Data Exchange (ETDEWEB)

Monserud, R.A.; Tchebakova, N.M.; Leemans, R. (US Department of Agriculture, Moscow, ID (United States). Intermountain Research Station, Forest Service)

1993-09-01

A modified Budyko global vegetation model is used to predict changes in global vegetation patterns resulting from climate change (CO[sub 2] doubling). Vegetation patterns are predicted using a model based on a dryness index and potential evaporation determined by solving radiation balance equations. Climate change scenarios are derived from predictions from four General Circulation Models (GCM's) of the atmosphere (GFDL, GISS, OSU, and UKMO). All four GCM scenarios show similar trends in vegetation shifts and in areas that remain stable, although the UKMO scenario predicts greater warming than the others. Climate change maps produced by all four GCM scenarios show good agreement with the current climate vegetation map for the globe as a whole, although over half of the vegetation classes show only poor to fair agreement. The most stable areas are Desert and Ice/Polar Desert. Because most of the predicted warming is concentrated in the Boreal and Temperate zones, vegetation there is predicted to undergo the greatest change. Most vegetation classes in the Subtropics and Tropics are predicted to expand. Any shift in the Tropics favouring either Forest over Savanna, or vice versa, will be determined by the magnitude of the increased precipitation accompanying global warming. Although the model predicts equilibrium conditions to which many plant species cannot adjust (through migration or microevolution) in the 50-100 y needed for CO[sub 2] doubling, it is not clear if projected global warming will result in drastic or benign vegetation change. 72 refs., 3 figs., 3 tabs.

a Mapping Method of Slam Based on Look up Table

Science.gov (United States)

Wang, Z.; Li, J.; Wang, A.; Wang, J.

2017-09-01

In the last years several V-SLAM(Visual Simultaneous Localization and Mapping) approaches have appeared showing impressive reconstructions of the world. However these maps are built with far more than the required information. This limitation comes from the whole process of each key-frame. In this paper we present for the first time a mapping method based on the LOOK UP TABLE(LUT) for visual SLAM that can improve the mapping effectively. As this method relies on extracting features in each cell divided from image, it can get the pose of camera that is more representative of the whole key-frame. The tracking direction of key-frames is obtained by counting the number of parallax directions of feature points. LUT stored all mapping needs the number of cell corresponding to the tracking direction which can reduce the redundant information in the key-frame, and is more efficient to mapping. The result shows that a better map with less noise is build using less than one-third of the time. We believe that the capacity of LUT efficiently building maps makes it a good choice for the community to investigate in the scene reconstruction problems.

METHODS OF SIMULATION ON THE MAP OF ETHNOGEOGRAPHICAL KNOWLEDGE

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A. M. Saraeva

2017-01-01

Full Text Available The article deals with the features of the spatial representation of the location of objects and phenomena on the Earth. One of the types of “cartographic representation” is modeling on the contour map. The advantages of the method are revealed. The application of modeling techniques that allows one to include ethnogeographic data in the content of the characteristics of the territory and reflect them on the contour map. The basis of ethnogeographic modeling is the identification and creation of elements of the material and spiritual culture of peoples by means of conventional signs. Comparison of these elements, their superimposition with respect to each other, as well as their comparison with geographic maps allow us to determine the interrelations and the dependence of the phenomenon. Modeling on contour maps is the basic method of learning in geography. On the one hand, it creates a cartographic image of the studied territory, and on the other hand it facilitates the creation of “visual supports” on the map.Modeling on contour maps, at the beginning students put the basic geographical names, which will serve as the basic knowledge. Then, by purposefully analyzing and comparing the thematic maps of the atlas or textbook, the students reflect specific ethno-geographical knowledge on contour maps. As a result, contour maps acquire “their own face”, and do not become a simple copy of maps of an atlas or textbook.Also, the features of the effect of this technique on the formation of spatial representations about the studied object have been analyzed. Thanks to the cartographic model, one can maintain a constant cognitive interest in the material studied. Modeling on the contour map will allow one to present the structure of the links between the elements of the ethnogeographical material. The basis of ethnogeographic modeling on the contour map is the identification and mapping of elements of the material and spiritual culture of

Impact of economic growth on vegetation health in China based on GIMMS NDVI

NARCIS (Netherlands)

Jin, X.; Wan, L.; Zhang, Y.K.; Schaepman, M.E.

2008-01-01

The negative impact of economic development on vegetation health in China was assessed using gross domestic product (GDP) and the Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data. Five levels of vegetation changes were established based on the

Determination of phenol in locally grown fruits and vegetable by spectrophotometric method

International Nuclear Information System (INIS)

Iqbal, M.; Khan, F.A.; Farooqui, Z.H.; Ifrahim, A.F.K.

2005-01-01

Spectrophotometric method for the determination of phenol in the sample of locally grown fruits apple, pear, sweet orange and vegetable radish of Quetta, Hyderabad and Nawabshah are described juices from these fruits and vegetable were squeezed, filtered and decolorized with charcoal. The antipyrine dye formed by reaction between phenol and 4-aminoantipyrine was analyzed. The calibration graphs were prepared in the range of 0.5 to 4 ppm of phenol. Phenol in apple, pear and sweet orange was found to be in the range of 1-1.2 ppm and in radish was found to be 0.5 ppm. Possible source of organic pollutant were pointed out and were discussed. Limits of detection of the method was investigated and was found to be 0.2 mu g/ml

Progress in Geo-Electrical Methods for Hydrogeological Mapping?

DEFF Research Database (Denmark)

Schrøder, Niels

2014-01-01

In most of the 20th century the geo-electrical methods were primarily used for groundwater exploration and the application of the methods were normally followed by a borehole, and a moment of truth. In this process the use of DC (direct current) soundings have been developed to a high grade...... of excellence. In the last 25 years the geo-electrical methods are more used in connection with groundwater protection and planning, and new methods, as transient electromagnetic (TEM) soundings, have been developed that provide more measurements per hour. In Denmark this change is very explicit, and a paper....... The test area was earlier mapped by DC-soundings, so it is possible to test the methods against each other. It is concluded that well performed DC-soundings with a Schlumberger configuration still provide the best base for hydrogeological mapping...

Delta Vegetation and Land Use [ds292

Data.gov (United States)

California Natural Resource Agency — Vegetation and land use are mapped for the approximately 725,000 acres constituting the Legal Delta portion of the Sacramento and San Joaquin River Delta area....

Barrier island habitat map and vegetation survey—Dauphin Island, Alabama, 2015

Science.gov (United States)

Enwright, Nicholas M.; Borchert, Sinéad M.; Day, Richard H.; Feher, Laura C.; Osland, Michael J.; Wang, Lei; Wang, Hongqing

2017-08-04

Barrier islands are dynamic environments due to their position at the land-sea interface. Storms, waves, tides, currents, and relative sea-level rise are powerful forces that shape barrier island geomorphology and habitats (for example, beach, dune, marsh, and forest). Hurricane Katrina in 2005 and the Deep Water Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Alabama. The latter event prompted a collaborative effort between the U.S. Geological Survey, the U.S. Army Corps of Engineers, and the State of Alabama funded by the National Fish and Wildlife Foundation to investigate viable, sustainable restoration options that protect and restore the natural resources of Dauphin Island, Alabama.In order to understand the feasibility and sustainability of various restoration scenarios, it is important to understand current conditions on Dauphin Island. To further this understanding, a detailed 19-class habitat map for Dauphin Island was produced from 1-foot aerial infrared photography collected on December 4, 2015, and lidar data collected in January 2015. We also conducted a ground survey of habitat types, vegetation community structure, and elevations in November and December 2015. These products provide baseline data regarding the ecological and general geomorphological attributes of the area, which can be compared with observations from other dates for tracking changes over time.

Applying Clustering Methods in Drawing Maps of Science: Case Study of the Map For Urban Management Science

Directory of Open Access Journals (Sweden)

Mohammad Abuei Ardakan

2010-04-01

Full Text Available The present paper offers a basic introduction to data clustering and demonstrates the application of clustering methods in drawing maps of science. All approaches towards classification and clustering of information are briefly discussed. Their application to the process of visualization of conceptual information and drawing of science maps are illustrated by reviewing similar researches in this field. By implementing aggregated hierarchical clustering algorithm, which is an algorithm based on complete-link method, the map for urban management science as an emerging, interdisciplinary scientific field is analyzed and reviewed.

A new method for mapping perceptual biases across visual space.

Science.gov (United States)

Finlayson, Nonie J; Papageorgiou, Andriani; Schwarzkopf, D Samuel

2017-08-01

How we perceive the environment is not stable and seamless. Recent studies found that how a person qualitatively experiences even simple visual stimuli varies dramatically across different locations in the visual field. Here we use a method we developed recently that we call multiple alternatives perceptual search (MAPS) for efficiently mapping such perceptual biases across several locations. This procedure reliably quantifies the spatial pattern of perceptual biases and also of uncertainty and choice. We show that these measurements are strongly correlated with those from traditional psychophysical methods and that exogenous attention can skew biases without affecting overall task performance. Taken together, MAPS is an efficient method to measure how an individual's perceptual experience varies across space.

System and method for image mapping and visual attention

Science.gov (United States)

Peters, II, Richard A. (Inventor)

2011-01-01

A method is described for mapping dense sensory data to a Sensory Ego Sphere (SES). Methods are also described for finding and ranking areas of interest in the images that form a complete visual scene on an SES. Further, attentional processing of image data is best done by performing attentional processing on individual full-size images from the image sequence, mapping each attentional location to the nearest node, and then summing all attentional locations at each node.

Post-fire vegetation recovery in Portugal based ewline on spot/vegetation data

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C. Gouveia

2010-04-01

Full Text Available A procedure is presented that allows identifying large burned scars and the monitoring of vegetation recovery in the years following major fire episodes. The procedure relies on 10-day fields of Maximum Value Composites of Normalized Difference Vegetation Index (MVC-NDVI, with a 1 km×1 km spatial resolution obtained from the VEGETATION instrument. The identification of fire scars during the extremely severe 2003 fire season is performed based on cluster analysis of NDVI anomalies that persist during the vegetative cycle of the year following the fire event. Two regions containing very large burned scars were selected, located in Central and Southwestern Portugal, respectively, and time series of MVC-NDVI analysed before the fire events took place and throughout the post-fire period. It is shown that post-fire vegetation dynamics in the two selected regions may be characterised based on maps of recovery rates as estimated by fitting a monoparametric model of vegetation recovery to MVC-NDVI data over each burned scar. Results indicated that the recovery process in the region located in Central Portugal is mostly related to fire damage rather than to vegetation density before 2003, whereas the latter seems to have a more prominent role than vegetation conditions after the fire episode, e.g. in the case of the region in Southwestern Portugal. These differences are consistent with the respective predominant types of vegetation. The burned area located in Central Portugal is dominated by Pinus Pinaster whose natural regeneration crucially depends on the destruction of seeds present on the soil surface during the fire, whereas the burned scar in Southwestern Portugal was populated by Eucalyptus that may quickly re-sprout from buds after fire. Besides its simplicity, the monoparametric model of vegetation recovery has the advantage of being easily adapted to other low-resolution satellite data, as well as to other types of vegetation

Spatial-temporal development of the mangrove vegetation cover on a hydraulic landfill (Via Expressa Sul, Florianópolis, SC: mapping and interpretation of digital aerophotographs, and quantitative analysis

Directory of Open Access Journals (Sweden)

Anderson Tavares de Melo

2011-12-01

Full Text Available The implementation of a hydraulic landfill along the southern expressway (Via Expressa Sul, in the central-south region of Santa Catarina Island, started in 1995 and was completed in 1997. The landfill provided the mangrove vegetation a new environment to colonize, which has developed rapidly during this short period of time. This study mapped the vegetation cover of this region using aerial photographs from five years (1994, 1997, 2002, 2004 and 2007, which demonstrated the spatial-temporal evolution of the vegetation since the year before the implementation of the landfill (1994 to its recent state (2007. The data from this study allowed changes in the surface of three bands of vegetation, a band of trees (Laguncularia racemosa and Avicennia schaueriana, a band of the seagrass praturá (Spartina alterniflora and a transition band (companions of mangrove species and restinga plants, to be quantified.

SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

Energy Technology Data Exchange (ETDEWEB)

Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

2002-08-01

Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

Enhanced Deforestation Mapping in North Korea using Spatial-temporal Image Fusion Method and Phenology-based Index

Science.gov (United States)

Jin, Y.; Lee, D.

2017-12-01

North Korea (the Democratic People's Republic of Korea, DPRK) is known to have some of the most degraded forest in the world. The characteristics of forest landscape in North Korea is complex and heterogeneous, the major vegetation cover types in the forest are hillside farm, unstocked forest, natural forest, and plateau vegetation. Better classification of types in high spatial resolution of deforested areas could provide essential information for decisions about forest management priorities and restoration of deforested areas. For mapping heterogeneous vegetation covers, the phenology-based indices are helpful to overcome the reflectance value confusion that occurs when using one season images. Coarse spatial resolution images may be acquired with a high repetition rate and it is useful for analyzing phenology characteristics, but may not capture the spatial detail of the land cover mosaic of the region of interest. Previous spatial-temporal fusion methods were only capture the temporal change, or focused on both temporal change and spatial change but with low accuracy in heterogeneous landscapes and small patches. In this study, a new concept for spatial-temporal image fusion method focus on heterogeneous landscape was proposed to produce fine resolution images at both fine spatial and temporal resolution. We classified the three types of pixels between the base image and target image, the first type is only reflectance changed caused by phenology, this type of pixels supply the reflectance, shape and texture information; the second type is both reflectance and spectrum changed in some bands caused by phenology like rice paddy or farmland, this type of pixels only supply shape and texture information; the third type is reflectance and spectrum changed caused by land cover type change, this type of pixels don't provide any information because we can't know how land cover changed in target image; and each type of pixels were applied different prediction methods

EnviroAtlas - Austin, TX - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. Vegetated cover is defined as Trees & Forest and Grass & Herbaceous. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Comparative Assessment of Two Vegetation Fractional Cover Estimating Methods and Their Impacts on Modeling Urban Latent Heat Flux Using Landsat Imagery

Directory of Open Access Journals (Sweden)

Kai Liu

2017-05-01

Full Text Available Quantifying vegetation fractional cover (VFC and assessing its role in heat fluxes modeling using medium resolution remotely sensed data has received less attention than it deserves in heterogeneous urban regions. This study examined two approaches (Normalized Difference Vegetation Index (NDVI-derived and Multiple Endmember Spectral Mixture Analysis (MESMA-derived methods that are commonly used to map VFC based on Landsat imagery, in modeling surface heat fluxes in urban landscape. For this purpose, two different heat flux models, Two-source energy balance (TSEB model and Pixel Component Arranging and Comparing Algorithm (PCACA model, were adopted for model evaluation and analysis. A comparative analysis of the NDVI-derived and MESMA-derived VFCs showed that the latter achieved more accurate estimates in complex urban regions. When the two sources of VFCs were used as inputs to both TSEB and PCACA models, MESMA-derived urban VFC produced more accurate urban heat fluxes (Bowen ratio and latent heat flux relative to NDVI-derived urban VFC. Moreover, our study demonstrated that Landsat imagery-retrieved VFC exhibited greater uncertainty in obtaining urban heat fluxes for the TSEB model than for the PCACA model.

Extending a field-based Sonoran desert vegetation classification to a regional scale using optical and microwave satellite imagery

Science.gov (United States)

Shupe, Scott Marshall

2000-10-01

Vegetation mapping in and regions facilitates ecological studies, land management, and provides a record to which future land changes can be compared. Accurate and representative mapping of desert vegetation requires a sound field sampling program and a methodology to transform the data collected into a representative classification system. Time and cost constraints require that a remote sensing approach be used if such a classification system is to be applied on a regional scale. However, desert vegetation may be sparse and thus difficult to sense at typical satellite resolutions, especially given the problem of soil reflectance. This study was designed to address these concerns by conducting vegetation mapping research using field and satellite data from the US Army Yuma Proving Ground (USYPG) in Southwest Arizona. Line and belt transect data from the Army's Land Condition Trend Analysis (LCTA) Program were transformed into relative cover and relative density classification schemes using cluster analysis. Ordination analysis of the same data produced two and three-dimensional graphs on which the homogeneity of each vegetation class could be examined. It was found that the use of correspondence analysis (CA), detrended correspondence analysis (DCA), and non-metric multidimensional scaling (NMS) ordination methods was superior to the use of any single ordination method for helping to clarify between-class and within-class relationships in vegetation composition. Analysis of these between-class and within-class relationships were of key importance in examining how well relative cover and relative density schemes characterize the USYPG vegetation. Using these two classification schemes as reference data, maximum likelihood and artificial neural net classifications were then performed on a coregistered dataset consisting of a summer Landsat Thematic Mapper (TM) image, one spring and one summer ERS-1 microwave image, and elevation, slope, and aspect layers

Generation and Assessment of Urban Land Cover Maps Using High-Resolution Multispectral Aerial Images

DEFF Research Database (Denmark)

Höhle, Joachim; Höhle, Michael

2013-01-01

a unique method for the automatic generation of urban land cover maps. In the present paper, imagery of a new medium-format aerial camera and advanced geoprocessing software are applied to derive normalized digital surface models and vegetation maps. These two intermediate products then become input...... to a tree structured classifier, which automatically derives land cover maps in 2D or 3D. We investigate the thematic accuracy of the produced land cover map by a class-wise stratified design and provide a method for deriving necessary sample sizes. Corresponding survey adjusted accuracy measures...... and their associated confidence intervals are used to adequately reflect uncertainty in the assessment based on the chosen sample size. Proof of concept for the method is given for an urban area in Switzerland. Here, the produced land cover map with six classes (building, wall and carport, road and parking lot, hedge...

Method II : The energy-momentum map

NARCIS (Netherlands)

Broer, H.; Hoveijn, I.; Lunter, G.; Vegter, G.

2003-01-01

In this chapter we apply the energy–momentum map reduction method to the same class of systems as in Chap. 2, namely two degree-of-freedom systems with optional symmetry, near equilibrium and close to resonance. We calculate the tangent space and nondegeneracy conditions for the 1:2, 1:3 and 1:4

Coupling Analysis of Heat Island Effects, Vegetation Coverage and Urban Flood in Wuhan

Science.gov (United States)

Liu, Y.; Liu, Q.; Fan, W.; Wang, G.

2018-04-01

In this paper, satellite image, remote sensing technique and geographic information system technique are main technical bases. Spectral and other factors comprehensive analysis and visual interpretation are main methods. We use GF-1 and Landsat8 remote sensing satellite image of Wuhan as data source, and from which we extract vegetation distribution, urban heat island relative intensity distribution map and urban flood submergence range. Based on the extracted information, through spatial analysis and regression analysis, we find correlations among heat island effect, vegetation coverage and urban flood. The results show that there is a high degree of overlap between of urban heat island and urban flood. The area of urban heat island has buildings with little vegetation cover, which may be one of the reasons for the local heavy rainstorms. Furthermore, the urban heat island has a negative correlation with vegetation coverage, and the heat island effect can be alleviated by the vegetation to a certain extent. So it is easy to understand that the new industrial zones and commercial areas which under constructions distribute in the city, these land surfaces becoming bare or have low vegetation coverage, can form new heat islands easily.

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

Science.gov (United States)

Sidick, Erkin

2012-01-01

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to

Computational methods for constructing protein structure models from 3D electron microscopy maps.

Science.gov (United States)

Esquivel-Rodríguez, Juan; Kihara, Daisuke

2013-10-01

Protein structure determination by cryo-electron microscopy (EM) has made significant progress in the past decades. Resolutions of EM maps have been improving as evidenced by recently reported structures that are solved at high resolutions close to 3Å. Computational methods play a key role in interpreting EM data. Among many computational procedures applied to an EM map to obtain protein structure information, in this article we focus on reviewing computational methods that model protein three-dimensional (3D) structures from a 3D EM density map that is constructed from two-dimensional (2D) maps. The computational methods we discuss range from de novo methods, which identify structural elements in an EM map, to structure fitting methods, where known high resolution structures are fit into a low-resolution EM map. A list of available computational tools is also provided. Copyright © 2013 Elsevier Inc. All rights reserved.

A Karnaugh-Map based fingerprint minutiae extraction method

Directory of Open Access Journals (Sweden)

Sunil Kumar Singla

2010-07-01

Full Text Available Fingerprint is one of the most promising method among all the biometric techniques and has been used for thepersonal authentication for a long time because of its wide acceptance and reliability. Features (Minutiae are extracted fromthe fingerprint in question and are compared with the features already stored in the database for authentication. Crossingnumber (CN is the most commonly used minutiae extraction method for fingerprints. In this paper, a new Karnaugh-Mapbased fingerprint minutiae extraction method has been proposed and discussed. In the proposed algorithm the 8 neighborsof a pixel in a 33 window are arranged as 8 bits of a byte and corresponding hexadecimal (hex value is calculated. Thesehex values are simplified using standard Karnaugh-Map (K-map technique to obtain the minimized logical expression.Experiments conducted on the FVC2002/Db1_a database reveals that the developed method is better than the crossingnumber (CN method.

Manual herbicide application methods for managing vegetation in Appalachian hardwood forests

Science.gov (United States)

Jeffrey D. Kochenderfer; James N. Kochenderfer; Gary W. Miller

2012-01-01

Four manual herbicide application methods are described for use in Appalachian hardwood forests. Stem injection, basal spray, cut-stump, and foliar spray techniques can be used to control interfering vegetation and promote the development of desirable reproduction and valuable crop trees in hardwood forests. Guidelines are presented to help the user select the...

Plant pigment types, distributions, and influences on shallow water submerged aquatic vegetation mapping

Science.gov (United States)

Hall, Carlton R.; Bostater, Charles R., Jr.; Virnstein, Robert

2004-11-01

Development of robust protocols for use in mapping shallow water habitats using hyperspectral imagery requires knowledge of absorbing and scattering features present in the environment. These include, but are not limited to, water quality parameters, phytoplankton concentrations and species, submerged aquatic vegetation (SAV) species and densities, epiphytic growth on SAV, benthic microalgae and substrate reflectance characteristics. In the Indian River Lagoon, Fl. USA we conceptualize the system as having three possible basic layers, water column and SAV bed above the bottom. Each layer is occupied by plants with their associated light absorbing pigments that occur in varying proportions and concentrations. Phytoplankton communities are composed primarily of diatoms, dinoflagellates, and picoplanktonic cyanobacteria. SAV beds, including flowering plants and green, red, and brown macro-algae exist along density gradients ranging in coverage from 0-100%. SAV beds may be monotypic, or more typically, mixtures of the several species that may or may not be covered in epiphytes. Shallow water benthic substrates are colonized by periphyton communities that include diatoms, dinoflagellates, chlorophytes and cyanobacteria. Inflection spectra created form ASIA hyperspectral data display a combination of features related to water and select plant pigment absorption peaks.

Response of spatial vegetation distribution in China to climate changes since the Last Glacial Maximum (LGM)

Science.gov (United States)

Wang, Siyang; Xu, Xiaoting; Shrestha, Nawal; Zimmermann, Niklaus E.; Tang, Zhiyao; Wang, Zhiheng

2017-01-01

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present. PMID:28426780

Method to map individual electromagnetic field components inside a photonic crystal

NARCIS (Netherlands)

Denis, T.; Reijnders, B.; Lee, J.H.H.; van der Slot, Petrus J.M.; Vos, Willem L.; Boller, Klaus J.

2012-01-01

We present a method to map the absolute electromagnetic field strength inside photonic crystals. We apply the method to map the dominant electric field component Ez of a two-dimensional photonic crystal slab at microwave frequencies. The slab is placed between two mirrors to select Bloch standing

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods.

Science.gov (United States)

Jiménez-Carvelo, Ana M; González-Casado, Antonio; Pérez-Castaño, Estefanía; Cuadros-Rodríguez, Luis

2017-03-01

A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phase LC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis took only 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil were used: one input-class, two input-class, and pseudo two input-class.

Comparison of sampling strategies for object-based classification of urban vegetation from Very High Resolution satellite images

Science.gov (United States)

Rougier, Simon; Puissant, Anne; Stumpf, André; Lachiche, Nicolas

2016-09-01

Vegetation monitoring is becoming a major issue in the urban environment due to the services they procure and necessitates an accurate and up to date mapping. Very High Resolution satellite images enable a detailed mapping of the urban tree and herbaceous vegetation. Several supervised classifications with statistical learning techniques have provided good results for the detection of urban vegetation but necessitate a large amount of training data. In this context, this study proposes to investigate the performances of different sampling strategies in order to reduce the number of examples needed. Two windows based active learning algorithms from state-of-art are compared to a classical stratified random sampling and a third combining active learning and stratified strategies is proposed. The efficiency of these strategies is evaluated on two medium size French cities, Strasbourg and Rennes, associated to different datasets. Results demonstrate that classical stratified random sampling can in some cases be just as effective as active learning methods and that it should be used more frequently to evaluate new active learning methods. Moreover, the active learning strategies proposed in this work enables to reduce the computational runtime by selecting multiple windows at each iteration without increasing the number of windows needed.

Statistical methods in physical mapping

International Nuclear Information System (INIS)

Nelson, D.O.

1995-05-01

One of the great success stories of modern molecular genetics has been the ability of biologists to isolate and characterize the genes responsible for serious inherited diseases like fragile X syndrome, cystic fibrosis and myotonic muscular dystrophy. This dissertation concentrates on constructing high-resolution physical maps. It demonstrates how probabilistic modeling and statistical analysis can aid molecular geneticists in the tasks of planning, execution, and evaluation of physical maps of chromosomes and large chromosomal regions. The dissertation is divided into six chapters. Chapter 1 provides an introduction to the field of physical mapping, describing the role of physical mapping in gene isolation and ill past efforts at mapping chromosomal regions. The next two chapters review and extend known results on predicting progress in large mapping projects. Such predictions help project planners decide between various approaches and tactics for mapping large regions of the human genome. Chapter 2 shows how probability models have been used in the past to predict progress in mapping projects. Chapter 3 presents new results, based on stationary point process theory, for progress measures for mapping projects based on directed mapping strategies. Chapter 4 describes in detail the construction of all initial high-resolution physical map for human chromosome 19. This chapter introduces the probability and statistical models involved in map construction in the context of a large, ongoing physical mapping project. Chapter 5 concentrates on one such model, the trinomial model. This chapter contains new results on the large-sample behavior of this model, including distributional results, asymptotic moments, and detection error rates. In addition, it contains an optimality result concerning experimental procedures based on the trinomial model. The last chapter explores unsolved problems and describes future work

Statistical methods in physical mapping

Energy Technology Data Exchange (ETDEWEB)

Nelson, David O. [Univ. of California, Berkeley, CA (United States)

1995-05-01

One of the great success stories of modern molecular genetics has been the ability of biologists to isolate and characterize the genes responsible for serious inherited diseases like fragile X syndrome, cystic fibrosis and myotonic muscular dystrophy. This dissertation concentrates on constructing high-resolution physical maps. It demonstrates how probabilistic modeling and statistical analysis can aid molecular geneticists in the tasks of planning, execution, and evaluation of physical maps of chromosomes and large chromosomal regions. The dissertation is divided into six chapters. Chapter 1 provides an introduction to the field of physical mapping, describing the role of physical mapping in gene isolation and ill past efforts at mapping chromosomal regions. The next two chapters review and extend known results on predicting progress in large mapping projects. Such predictions help project planners decide between various approaches and tactics for mapping large regions of the human genome. Chapter 2 shows how probability models have been used in the past to predict progress in mapping projects. Chapter 3 presents new results, based on stationary point process theory, for progress measures for mapping projects based on directed mapping strategies. Chapter 4 describes in detail the construction of all initial high-resolution physical map for human chromosome 19. This chapter introduces the probability and statistical models involved in map construction in the context of a large, ongoing physical mapping project. Chapter 5 concentrates on one such model, the trinomial model. This chapter contains new results on the large-sample behavior of this model, including distributional results, asymptotic moments, and detection error rates. In addition, it contains an optimality result concerning experimental procedures based on the trinomial model. The last chapter explores unsolved problems and describes future work.

Vegetation - Carrizo Plain ER, 2005 - 2008 [ds561

Data.gov (United States)

California Natural Resource Agency — The Vegetation Map of the Carrizo Plain Ecological Reserve, San Luis Obispo County, California was created by the California Department of Fish and Game (DFG)...

A novel method of S-box design based on chaotic map and composition method

International Nuclear Information System (INIS)

Lambić, Dragan

2014-01-01

Highlights: • Novel chaotic S-box generation method is presented. • Presented S-box has better cryptographic properties than other examples of chaotic S-boxes. • The advantages of the proposed method are the low complexity and large key space. -- Abstract: An efficient algorithm for obtaining random bijective S-boxes based on chaotic maps and composition method is presented. The proposed method is based on compositions of S-boxes from a fixed starting set. The sequence of the indices of starting S-boxes used is obtained by using chaotic maps. The results of performance test show that the S-box presented in this paper has good cryptographic properties. The advantages of the proposed method are the low complexity and the possibility to achieve large key space

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method (ESQM v5.2)

Science.gov (United States)

Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis

2017-12-01

Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.

Methodical Aspects of Applying Strategy Map in an Organization

Directory of Open Access Journals (Sweden)

Piotr Markiewicz

2013-06-01

Full Text Available One of important aspects of strategic management is the instrumental aspect included in a rich set of methods and techniques used at particular stages of strategic management process. The object of interest in this study is the development of views and the implementation of strategy as an element of strategic management and instruments in the form of methods and techniques. The commonly used method in strategy implementation and measuring progress is Balanced Scorecard (BSC. The method was created as a result of implementing the project “Measuring performance in the Organization of the future” of 1990, completed by a team under the supervision of David Norton (Kaplan, Norton 2002. The developed method was used first of all to evaluate performance by decomposition of a strategy into four perspectives and identification of measures of achievement. In the middle of 1990s the method was improved by enriching it, first of all, with a strategy map, in which the process of transition of intangible assets into tangible financial effects is reflected (Kaplan, Norton 2001. Strategy map enables illustration of cause and effect relationship between processes in all four perspectives and performance indicators at the level of organization. The purpose of the study being prepared is to present methodical conditions of using strategy maps in the strategy implementation process in organizations of different nature.

Regolith-geology mapping with support vector machine: A case study over weathered Ni-bearing peridotites, New Caledonia

Science.gov (United States)

De Boissieu, Florian; Sevin, Brice; Cudahy, Thomas; Mangeas, Morgan; Chevrel, Stéphane; Ong, Cindy; Rodger, Andrew; Maurizot, Pierre; Laukamp, Carsten; Lau, Ian; Touraivane, Touraivane; Cluzel, Dominique; Despinoy, Marc

2018-02-01

Accurate maps of Earth's geology, especially its regolith, are required for managing the sustainable exploration and development of mineral resources. This paper shows how airborne imaging hyperspectral data collected over weathered peridotite rocks in vegetated, mountainous terrane in New Caledonia were processed using a combination of methods to generate a regolith-geology map that could be used for more efficiently targeting Ni exploration. The image processing combined two usual methods, which are spectral feature extraction and support vector machine (SVM). This rationale being the spectral features extraction can rapidly reduce data complexity by both targeting only the diagnostic mineral absorptions and masking those pixels complicated by vegetation, cloud and deep shade. SVM is a supervised classification method able to generate an optimal non-linear classifier with these features that generalises well even with limited training data. Key minerals targeted are serpentine, which is considered as an indicator for hydrolysed peridotitic rock, and iron oxy-hydroxides (hematite and goethite), which are considered as diagnostic of laterite development. The final classified regolith map was assessed against interpreted regolith field sites, which yielded approximately 70% similarity for all unit types, as well as against a regolith-geology map interpreted using traditional datasets (not hyperspectral imagery). Importantly, the hyperspectral derived mineral map provided much greater detail enabling a more precise understanding of the regolith-geological architecture where there are exposed soils and rocks.

LBA-ECO LC-07 Wetland Extent, Vegetation, and Inundation: Lowland Amazon Basin

Data.gov (United States)

National Aeronautics and Space Administration — This data set provides a map of wetland extent, vegetation type, and dual-season flooding state of the entire lowland Amazon basin. The map was derived from mosaics...

Vegetation Fraction Mapping with High Resolution Multispectral Data in the Texas High Plains

Science.gov (United States)

Oshaughnessy, S. A.; Gowda, P. H.; Basu, S.; Colaizzi, P. D.; Howell, T. A.; Schulthess, U.

2010-12-01

Land surface models use vegetation fraction to more accurately partition latent, sensible and soil heat fluxes from a partially vegetated surface as it affects energy and moisture exchanges between the earth’s surface and atmosphere. In recent years, there is interest to integrate vegetation fraction data into intelligent irrigation scheduling systems to avoid false positive signals to irrigate. Remote sensing can facilitate the collection of vegetation fraction information on individual fields over large areas in a timely and cost-effective manner. In this study, we developed and evaluated a set of vegetation fraction models using least square regression and artificial neural network (ANN) techniques using RapidEye satellite data (6.5 m spatial resolution and on-demand temporal resolution). Four images were acquired during the 2010 summer growing season, covering bare soil to full crop cover conditions, over the USDA-ARS-Conservation and Production Research Laboratory in Bushland, Texas [350 11' N, 1020 06' W; 1,170 m elevation MSL]. Spectral signatures were extracted from 25 ground truth locations with geographic coordinates. Vegetation fraction information was derived from digital photos taken at the time of image acquisition using a supervised classification technique. Comparison of performance statistics indicate that ANN performed slightly better than least square regression models.

The Application and Evaluation of Modified Atmosphere Packaging in Selected Minimally Processed Vegetables

OpenAIRE

Greene, Aine, (Thesis)

2003-01-01

The central aim of this study was to optimise the processing and storage of selected vegetable within the parameters of extended shelf life, time/temperature relationships and sensory quality. The vegetables were selected on the basis of the results of a survey of the Irish vegetable industry. The current literature in the field of modified atmosphere packaging (MAP) and the Irish vegetable industry was reviewed. The current state and future requirements of the Irish vegetable industry was in...

Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia.

Science.gov (United States)

Wakie, Tewodros T; Evangelista, Paul H; Jarnevich, Catherine S; Laituri, Melinda

2014-01-01

We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM) were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC) curve (AUC). Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC  = 0.94), while the potential habitat for future infestations is 5,024 km2 (AUC  = 0.95). Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.

Temporal reflectance changes in vegetables

DEFF Research Database (Denmark)

Dissing, Bjørn Skovlund; Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

2009-01-01

Quality control in the food industry is often performed by measuring various chemical compounds of the food involved. We propose an imaging concept for acquiring high quality multispectral images to evaluate changes of carrots and celeriac over a period of 14 days. Properties originating...... in the surface chemistry of vegetables may be captured in an integrating sphere illumination which enables the creation of detailed surface chemistry maps with a good combination of spectral and spatial resolutions. Prior to multispectral image recording, the vegetables were prefried and frozen at -30Â......°C for four months. During the 14 days of image recording, the vegetables were kept at +5°C in refrigeration. In this period, surface changes and thereby reflectance properties were very subtle. To describe this small variation we employed advanced statistical techniques to search a large featurespace...

A novel quantitative analysis method of three-dimensional fluorescence spectra for vegetable oils contents in edible blend oil

Science.gov (United States)

Xu, Jing; Wang, Yu-Tian; Liu, Xiao-Fei

2015-04-01

Edible blend oil is a mixture of vegetable oils. Eligible blend oil can meet the daily need of two essential fatty acids for human to achieve the balanced nutrition. Each vegetable oil has its different composition, so vegetable oils contents in edible blend oil determine nutritional components in blend oil. A high-precision quantitative analysis method to detect the vegetable oils contents in blend oil is necessary to ensure balanced nutrition for human being. Three-dimensional fluorescence technique is high selectivity, high sensitivity, and high-efficiency. Efficiency extraction and full use of information in tree-dimensional fluorescence spectra will improve the accuracy of the measurement. A novel quantitative analysis is proposed based on Quasi-Monte-Carlo integral to improve the measurement sensitivity and reduce the random error. Partial least squares method is used to solve nonlinear equations to avoid the effect of multicollinearity. The recovery rates of blend oil mixed by peanut oil, soybean oil and sunflower are calculated to verify the accuracy of the method, which are increased, compared the linear method used commonly for component concentration measurement.

Wada-test, functional magnetic resonance imaging and direct electrical stimulation - brain mapping methods

International Nuclear Information System (INIS)

Minkin, K.; Tanova, R.; Busarski, A.; Penkov, M.; Penev, L.; Hadjidekov, V.

2009-01-01

Modern neurosurgery requires accurate preoperative and intraoperative localization of brain pathologies but also of brain functions. The presence of individual variations in healthy subjects and the shift of brain functions in brain diseases provoke the introduction of various methods for brain mapping. The aim of this paper was to analyze the most widespread methods for brain mapping: Wada-test, functional magnetic resonance imaging (fMRI) and intraoperative direct electrical stimulation (DES). This study included 4 patients with preoperative brain mapping using Wada-test and fMRI. Intraoperative mapping with DES during awake craniotomy was performed in one case. The histopathological diagnosis was low-grade glioma in 2 cases, cortical dysplasia (1 patient) and arteriovenous malformation (1 patient). The brain mapping permits total lesion resection in three of four patients. There was no new postoperative deficit despite surgery near or within functional brain areas. Brain plasticity provoking shift of eloquent areas from their usual locations was observed in two cases. The brain mapping methods allow surgery in eloquent brain areas recognized in the past as 'forbidden areas'. Each method has advantages and disadvantages. The precise location of brain functions and pathologies frequently requires combination of different brain mapping methods. (authors)

Comparing 511 keV Attenuation Maps Obtained from Different Energy Mapping Methods for CT Based Attenuation Correction of PET Data

Directory of Open Access Journals (Sweden)

Maryam Shirmohammad

2008-06-01

Full Text Available Introduction:  The  advent  of  dual-modality  PET/CT  scanners  has  revolutionized  clinical  oncology  by  improving lesion localization and facilitating treatment planning for radiotherapy. In addition, the use of  CT images for CT-based attenuation correction (CTAC decreases the overall scanning time and creates  a noise-free  attenuation  map  (6map.  CTAC  methods  include  scaling,  segmentation,  hybrid  scaling/segmentation, bilinear and dual energy methods. All CTAC methods require the transformation  of CT Hounsfield units (HU to linear attenuation coefficients (LAC at 511 keV. The aim of this study is  to compare the results of implementing different methods of energy mapping in PET/CT scanners.   Materials and Methods: This study was conducted in 2 phases, the first phase in a phantom and the  second  one  on  patient  data.  To  perform  the  first  phase,  a  cylindrical  phantom  with  different  concentrations of K2HPO4 inserts was CT scanned and energy mapping methods were implemented on  it. For performing the second phase, different energy  mapping  methods  were implemented on several  clinical studies and compared to the transmission (TX image derived using Ga-68 radionuclide source  acquired on the GE Discovery LS PET/CT scanner.   Results: An ROI analysis was performed on different positions of the resultant 6maps and the average  6value of each ROI was compared to the reference value. The results of the 6maps obtained for 511 keV  compared to the theoretical  values showed that in the phantom for low  concentrations  of K 2 HPO 4 all  these  methods  produce  511  keV  attenuation  maps  with  small  relative  difference  compared  to  gold  standard. The relative difference for scaling, segmentation, hybrid, bilinear and dual energy methods was  4.92,  3.21,  4.43,  2.24  and  2.29%,  respectively.  Although  for  high  concentration �

Patterns in woody vegetation structure across African savannas

Science.gov (United States)

Axelsson, Christoffer R.; Hanan, Niall P.

2017-07-01

Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP) modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the level of spatial aggregation among woody plants in the landscape will vary across environmental gradients. A high level of woody plant aggregation is most distinct in periodic vegetation patterns (PVPs), which emerge as a result of ecohydrological processes such as runoff generation and increased infiltration close to plants. Similar, albeit weaker, forces may influence the spatial distribution of woody plants elsewhere in savannas. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. Using high-spatial-resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enabled us to elucidate the effects of rainfall regimes (MAP and seasonality), soil texture, slope, and fire frequency on woody vegetation properties. We found that previously documented increases in woody cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. Along a gradient of mean annual precipitation from the driest (< 200 mm yr-1) to the wettest (1200-1400 mm yr-1) end, mean estimates of crown size, crown density, and woody cover increased by 233, 73, and 491 % respectively. We also found a unimodal relationship between mean crown size and sand content suggesting that maximal

Patterns in woody vegetation structure across African savannas

Directory of Open Access Journals (Sweden)

C. R. Axelsson

2017-07-01

Full Text Available Vegetation structure in water-limited systems is to a large degree controlled by ecohydrological processes, including mean annual precipitation (MAP modulated by the characteristics of precipitation and geomorphology that collectively determine how rainfall is distributed vertically into soils or horizontally in the landscape. We anticipate that woody canopy cover, crown density, crown size, and the level of spatial aggregation among woody plants in the landscape will vary across environmental gradients. A high level of woody plant aggregation is most distinct in periodic vegetation patterns (PVPs, which emerge as a result of ecohydrological processes such as runoff generation and increased infiltration close to plants. Similar, albeit weaker, forces may influence the spatial distribution of woody plants elsewhere in savannas. Exploring these trends can extend our knowledge of how semi-arid vegetation structure is constrained by rainfall regime, soil type, topography, and disturbance processes such as fire. Using high-spatial-resolution imagery, a flexible classification framework, and a crown delineation method, we extracted woody vegetation properties from 876 sites spread over African savannas. At each site, we estimated woody cover, mean crown size, crown density, and the degree of aggregation among woody plants. This enabled us to elucidate the effects of rainfall regimes (MAP and seasonality, soil texture, slope, and fire frequency on woody vegetation properties. We found that previously documented increases in woody cover with rainfall is more consistently a result of increasing crown size than increasing density of woody plants. Along a gradient of mean annual precipitation from the driest (< 200 mm yr−1 to the wettest (1200–1400 mm yr−1 end, mean estimates of crown size, crown density, and woody cover increased by 233, 73, and 491 % respectively. We also found a unimodal relationship between mean crown size and sand

Prompt Proxy Mapping of Flood Damaged Rice Fields Using MODIS-Derived Indices

Directory of Open Access Journals (Sweden)

Youngjoo Kwak

2015-11-01

Full Text Available Flood mapping, particularly hazard and risk mapping, is an imperative process and a fundamental part of emergency response and risk management. This paper aims to produce a flood risk proxy map of damaged rice fields over the whole of Bangladesh, where monsoon river floods are dominant and frequent, affecting over 80% of the total population. This proxy risk map was developed to meet the request of the government on a national level. This study represents a rapid, straightforward methodology for estimating rice-crop damage in flood areas of Bangladesh during the large flood from July to September 2007, despite the lack of primary data. We improved a water detection algorithm to achieve a better discrimination capacity to discern flood areas by using a modified land surface water index (MLSWI. Then, rice fields were estimated utilizing a hybrid rice field map from land-cover classification and MODIS-derived indices, such as the normalized difference vegetation index (NDVI and enhanced vegetation index (EVI. The results showed that the developed method is capable of providing instant, comprehensive, nationwide mapping of flood risks, such as rice field damage. The detected flood areas and damaged rice fields during the 2007 flood were verified by comparing them with the Advanced Land Observing Satellite (ALOS AVNIR-2 images (a 10 m spatial resolution and in situ field survey data with moderate agreement (K = 0.57.

EnviroAtlas - Des Moines, IA - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. Vegetated cover is defined as Trees & Forest and Grass & Herbaceous. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://enviroatlas.epa.gov/EnviroAtlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

Systematic Mapping and Statistical Analyses of Valley Landform and Vegetation Asymmetries Across Hydroclimatic Gradients

Science.gov (United States)

Poulos, M. J.; Pierce, J. L.; McNamara, J. P.; Flores, A. N.; Benner, S. G.

2015-12-01

Terrain aspect alters the spatial distribution of insolation across topography, driving eco-pedo-hydro-geomorphic feedbacks that can alter landform evolution and result in valley asymmetries for a suite of land surface characteristics (e.g. slope length and steepness, vegetation, soil properties, and drainage development). Asymmetric valleys serve as natural laboratories for studying how landscapes respond to climate perturbation. In the semi-arid montane granodioritic terrain of the Idaho batholith, Northern Rocky Mountains, USA, prior works indicate that reduced insolation on northern (pole-facing) aspects prolongs snow pack persistence, and is associated with thicker, finer-grained soils, that retain more water, prolong the growing season, support coniferous forest rather than sagebrush steppe ecosystems, stabilize slopes at steeper angles, and produce sparser drainage networks. We hypothesize that the primary drivers of valley asymmetry development are changes in the pedon-scale water-balance that coalesce to alter catchment-scale runoff and drainage development, and ultimately cause the divide between north and south-facing land surfaces to migrate northward. We explore this conceptual framework by coupling land surface analyses with statistical modeling to assess relationships and the relative importance of land surface characteristics. Throughout the Idaho batholith, we systematically mapped and tabulated various statistical measures of landforms, land cover, and hydroclimate within discrete valley segments (n=~10,000). We developed a random forest based statistical model to predict valley slope asymmetry based upon numerous measures (n>300) of landscape asymmetries. Preliminary results suggest that drainages are tightly coupled with hillslopes throughout the region, with drainage-network slope being one of the strongest predictors of land-surface-averaged slope asymmetry. When slope-related statistics are excluded, due to possible autocorrelation, valley

A Method of Mapping Burned Area Using Chinese FengYun-3 MERSI Satellite Data

Science.gov (United States)

Shan, T.

2017-12-01

Wildfire is a naturally reoccurring global phenomenon which has environmental and ecological consequences such as effects on the global carbon budget, changes to the global carbon cycle and disruption to ecosystem succession. The information of burned area is significant for post disaster assessment, ecosystems protection and restoration. The Medium Resolution Spectral Imager (MERSI) onboard FENGYUN-3C (FY-3C) has shown good ability for fire detection and monitoring but lacks recognition among researchers. In this study, an automated burned area mapping algorithm was proposed based on FY-3C MERSI data. The algorithm is generally divided into two phases: 1) selection of training pixels based on 1000-m resolution MERSI data, which offers more spectral information through the use of more vegetation indices; and 2) classification: first the region growing method is applied to 1000-m MERSI data to calculate the core burned area and then the same classification method is applied to the 250-m MERSI data set by using the core burned area as a seed to obtain results at a finer spatial resolution. An evaluation of the performance of the algorithm was carried out at two study sites in America and Canada. The accuracy assessment and validation were made by comparing our results with reference results derived from Landsat OLI data. The result has a high kappa coefficient and the lower commission error, indicating that this algorithm can improve the burned area mapping accuracy at the two study sites. It may then be possible to use MERSI and other data to fill the gaps in the imaging of burned areas in the future.

Development of iodimetric redox method for routine estimation of ascorbic acid from fresh fruit and vegetables

International Nuclear Information System (INIS)

Munir, M.; Baloch, A. K.; Khan, W. A.; Ahmad, F.; Jamil, M.

2013-01-01

The iodimetric method (Im) is developed for rapid estimation of ascorbic acid from fresh fruit and vegetables. The efficiency of Im was compared with standard with standard dye method (Dm) utilizing a variety of model solutions and aqueous extracts from fresh fruit and vegetables of different colors. The Im presented consistently accurate and precise results from colorless to colored model solutions and from fruit/vegetable extracts with standard deviation (Stdev) in the range of +-0.013 - +-0.405 and +-0.019 - +-0.428 respectively with no significant difference between the replicates. The Dm worked also satisfactorily for colorless model solutions and extracts (Stdev range +-0.235 - +-0.309) while producing unsatisfactory results (+-0.464 - +-3.281) for colored counterparts. Severe discrepancies/ overestimates continued to pileup (52% to 197%) estimating the nutrient from high (3.0 mg/10mL) to low (0.5 mg/10mL) concentration levels, respectively. On the basis of precision and reliability, the Im technique is suggested for adoption in general laboratories for routine estimation of ascorbic acid from fruit and vegetables possessing any shade. (author)

A performance comparison of sampling methods in the assessment of species composition patterns and environment–vegetation relationships in species-rich grasslands

OpenAIRE

Grzegorz Swacha; Zoltán Botta-Dukát; Zygmunt Kącki; Daniel Pruchniewicz; Ludwik Żołnierz

2017-01-01

The influence that different sampling methods have on the results and the interpretation of vegetation analysis has been much debated, but little is yet known about how the spatial arrangement of samples affect patterns of species composition and environment–vegetation relationships within the same vegetation type. We compared three data sets of the same sample size obtained by three standard sampling methods: preferential, random, and systematic. These different sampling methods were applied...

EnviroAtlas - Cleveland, OH - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees & Forest, Grass & Herbaceous, Woody Wetlands, and Emergent Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas ) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

EnviroAtlas - Paterson, NJ - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. EnviroAtlas defines vegetated buffer for this community as trees and forest and grass and herbaceous. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Estimating vegetation vulnerability to detect areas prone to land degradation in the Mediterranean basin

Science.gov (United States)

Imbrenda, Vito; Coluzzi, Rosa; D'Emilio, Mariagrazia; Lanfredi, Maria; Simoniello, Tiziana

2013-04-01

Vegetation is one of the key components to study land degradation vulnerability because of the complex interactions and feedbacks that link it to soil. In the Mediterranean region, degradation phenomena are due to a mix of predisposing factors (thin soil horizons, low soil organic matter, increasing aridity, etc.) and bad management practices (overgrazing, deforestation, intensification of agriculture, tourism development). In particular, in areas threatened by degradation processes but still covered by vegetation, large scale soil condition evaluation is a hard task and the detection of stressed vegetation can be useful to identify on-going soil degradation phenomena and to reduce their impacts through interventions for recovery/rehabilitation. In this context the use of satellite time series can increase the efficacy and completeness of the land degradation assessment, providing precious information to understand vegetation dynamics. In order to estimate vulnerability levels in Basilicata (a Mediterranean region of Southern Italy) in the framework of PRO-LAND project (PO-FESR Basilicata 2007-2013), we crossed information on potential vegetation vulnerability with information on photosynthetic activity dynamics. Potential vegetation vulnerability represents the vulnerability related to the type of present cover in terms of fire risk, erosion protection, drought resistance and plant cover distribution. It was derived from an updated land cover map by separately analyzing each factor, and then by combining them to obtain concise information on the possible degradation exposure. The analysis of photosynthetic activity dynamics provides information on the status of vegetation, that is fundamental to discriminate the different vulnerability levels within the same land cover, i.e. the same potential vulnerability. For such a purpose, we analyzed a time series (2000-2010) of a satellite vegetation index (MODIS NDVI) with 250m resolution, available as 16-day composite

Evaluating a small footprint, waveform-resolving lidar over coastal vegetation communities

Science.gov (United States)

Nayegandhl, A.; Brock, J.C.; Wright, C.W.; O'Connell, M. J.

2006-01-01

NASA's Experimental Advanced Airborne Research Lidar (EAARL) is a raster-scanning, waveform-resolving, green-wavelength (532 nm) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor records the time history of the return waveform within a small footprint (20 cm diameter) for each laser pulse, enabling characterization of vegetation canopy structure and "bare earth" topography under a variety of vegetation types. A collection of individual waveforms combined within a synthesized large footprint was used to define three metrics: canopy height (CH), canopy reflection ratio (CRR), and height of median energy (HOME). Bare Earth Elevation (BEE) metric was derived using the individual small-footprint waveforms. All four metrics were tested for reproducibility, which resulted in an average of 95 percent correspondence within two standard deviations of the mean. CH and BEE values were also tested for accuracy using ground-truth data. The results presented in this paper show that combining several individual small-footprint laser pulses to define a composite "large-footprint" waveform is a possible method to depict the vertical structure of a vegetation canopy. ?? 2006 American Society for Photogrammetry and Remote Sensing.

Flood Hazard Mapping by Applying Fuzzy TOPSIS Method

Science.gov (United States)

Han, K. Y.; Lee, J. Y.; Keum, H.; Kim, B. J.; Kim, T. H.

2017-12-01

There are lots of technical methods to integrate various factors for flood hazard mapping. The purpose of this study is to suggest the methodology of integrated flood hazard mapping using MCDM(Multi Criteria Decision Making). MCDM problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. In this study, to apply MCDM to assessing flood risk, maximum flood depth, maximum velocity, and maximum travel time are considered as criterion, and each applied elements are considered as alternatives. The scheme to find the efficient alternative closest to a ideal value is appropriate way to assess flood risk of a lot of element units(alternatives) based on various flood indices. Therefore, TOPSIS which is most commonly used MCDM scheme is adopted to create flood hazard map. The indices for flood hazard mapping(maximum flood depth, maximum velocity, and maximum travel time) have uncertainty concerning simulation results due to various values according to flood scenario and topographical condition. These kind of ambiguity of indices can cause uncertainty of flood hazard map. To consider ambiguity and uncertainty of criterion, fuzzy logic is introduced which is able to handle ambiguous expression. In this paper, we made Flood Hazard Map according to levee breach overflow using the Fuzzy TOPSIS Technique. We confirmed the areas where the highest grade of hazard was recorded through the drawn-up integrated flood hazard map, and then produced flood hazard map can be compared them with those indicated in the existing flood risk maps. Also, we expect that if we can apply the flood hazard map methodology suggested in this paper even to manufacturing the current flood risk maps, we will be able to make a new flood hazard map to even consider the priorities for hazard areas, including more varied and important information than ever before. Keywords : Flood hazard map; levee break analysis; 2D analysis; MCDM; Fuzzy TOPSIS

A Hybrid Vision-Map Method for Urban Road Detection

Directory of Open Access Journals (Sweden)

Carlos Fernández

2017-01-01

Full Text Available A hybrid vision-map system is presented to solve the road detection problem in urban scenarios. The standardized use of machine learning techniques in classification problems has been merged with digital navigation map information to increase system robustness. The objective of this paper is to create a new environment perception method to detect the road in urban environments, fusing stereo vision with digital maps by detecting road appearance and road limits such as lane markings or curbs. Deep learning approaches make the system hard-coupled to the training set. Even though our approach is based on machine learning techniques, the features are calculated from different sources (GPS, map, curbs, etc., making our system less dependent on the training set.

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method (ESQM v5.2

Directory of Open Access Journals (Sweden)

T. S. Kalra

2017-12-01

Full Text Available Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.

A Method of Generating Indoor Map Spatial Data Automatically from Architectural Plans

Directory of Open Access Journals (Sweden)

SUN Weixin

2016-06-01

Full Text Available Taking architectural plans as data source, we proposed a method which can automatically generate indoor map spatial data. Firstly, referring to the spatial data demands of indoor map, we analyzed the basic characteristics of architectural plans, and introduced concepts of wall segment, adjoining node and adjoining wall segment, based on which basic flow of indoor map spatial data automatic generation was further established. Then, according to the adjoining relation between wall lines at the intersection with column, we constructed a repair method for wall connectivity in relation to the column. Utilizing the method of gradual expansibility and graphic reasoning to judge wall symbol local feature type at both sides of door or window, through update the enclosing rectangle of door or window, we developed a repair method for wall connectivity in relation to the door or window and a method for transform door or window into indoor map point feature. Finally, on the basis of geometric relation between adjoining wall segment median lines, a wall center-line extraction algorithm was presented. Taking one exhibition hall's architectural plan as example, we performed experiment and results show that the proposed methods have preferable applicability to deal with various complex situations, and realized indoor map spatial data automatic extraction effectively.

Concept mapping as a promising method to bring practice into science

NARCIS (Netherlands)

van Bon, M.J.H.; van de Goor, L.A.M.; Holsappel, J.C.; Kuunders, T.J.M.; Jacobs-van der Bruggen, M.A.M.; te Brake, J.H.M.; van Oers, J.A.M.

2014-01-01

Objective Concept mapping is a method for developing a conceptual framework of a complex topic for use as a guide to evaluation or planning. In concept mapping, thoughts and ideas are represented in the form of a picture or map, the content of which is determined by a group of stakeholders. This

Assessment of Atmospheric Algorithms to Retrieve Vegetation in Natural Protected Areas Using Multispectral High Resolution Imagery

Directory of Open Access Journals (Sweden)

Javier Marcello

2016-09-01

Full Text Available The precise mapping of vegetation covers in semi-arid areas is a complex task as this type of environment consists of sparse vegetation mainly composed of small shrubs. The launch of high resolution satellites, with additional spectral bands and the ability to alter the viewing angle, offers a useful technology to focus on this objective. In this context, atmospheric correction is a fundamental step in the pre-processing of such remote sensing imagery and, consequently, different algorithms have been developed for this purpose over the years. They are commonly categorized as imaged-based methods as well as in more advanced physical models based on the radiative transfer theory. Despite the relevance of this topic, a few comparative studies covering several methods have been carried out using high resolution data or which are specifically applied to vegetation covers. In this work, the performance of five representative atmospheric correction algorithms (DOS, QUAC, FLAASH, ATCOR and 6S has been assessed, using high resolution Worldview-2 imagery and field spectroradiometer data collected simultaneously, with the goal of identifying the most appropriate techniques. The study also included a detailed analysis of the parameterization influence on the final results of the correction, the aerosol model and its optical thickness being important parameters to be properly adjusted. The effects of corrections were studied in vegetation and soil sites belonging to different protected semi-arid ecosystems (high mountain and coastal areas. In summary, the superior performance of model-based algorithms, 6S in particular, has been demonstrated, achieving reflectance estimations very close to the in-situ measurements (RMSE of between 2% and 3%. Finally, an example of the importance of the atmospheric correction in the vegetation estimation in these natural areas is presented, allowing the robust mapping of species and the analysis of multitemporal variations

Theory, methods and tools for determining environmental flows for riparian vegetation: Riparian vegetation-flow response guilds

Science.gov (United States)

Merritt, D.M.; Scott, M.L.; Leroy, Poff N.; Auble, G.T.; Lytle, D.A.

2010-01-01

Riparian vegetation composition, structure and abundance are governed to a large degree by river flow regime and flow-mediated fluvial processes. Streamflow regime exerts selective pressures on riparian vegetation, resulting in adaptations (trait syndromes) to specific flow attributes. Widespread modification of flow regimes by humans has resulted in extensive alteration of riparian vegetation communities. Some of the negative effects of altered flow regimes on vegetation may be reversed by restoring components of the natural flow regime. 2. Models have been developed that quantitatively relate components of the flow regime to attributes of riparian vegetation at the individual, population and community levels. Predictive models range from simple statistical relationships, to more complex stochastic matrix population models and dynamic simulation models. Of the dozens of predictive models reviewed here, most treat one or a few species, have many simplifying assumptions such as stable channel form, and do not specify the time-scale of response. In many cases, these models are very effective in developing alternative streamflow management plans for specific river reaches or segments but are not directly transferable to other rivers or other regions. 3. A primary goal in riparian ecology is to develop general frameworks for prediction of vegetation response to changing environmental conditions. The development of riparian vegetation-flow response guilds offers a framework for transferring information from rivers where flow standards have been developed to maintain desirable vegetation attributes, to rivers with little or no existing information. 4. We propose to organise riparian plants into non-phylogenetic groupings of species with shared traits that are related to components of hydrologic regime: life history, reproductive strategy, morphology, adaptations to fluvial disturbance and adaptations to water availability. Plants from any river or region may be grouped

A Subpixel Classification of Multispectral Satellite Imagery for Interpetation of Tundra-Taiga Ecotone Vegetation (Case Study on Tuliok River Valley, Khibiny, Russia)

Science.gov (United States)

Mikheeva, A. I.; Tutubalina, O. V.; Zimin, M. V.; Golubeva, E. I.

2017-12-01

The tundra-taiga ecotone plays significant role in northern ecosystems. Due to global climatic changes, the vegetation of the ecotone is the key object of many remote-sensing studies. The interpretation of vegetation and nonvegetation objects of the tundra-taiga ecotone on satellite imageries of a moderate resolution is complicated by the difficulty of extracting these objects from the spectral and spatial mixtures within a pixel. This article describes a method for the subpixel classification of Terra ASTER satellite image for vegetation mapping of the tundra-taiga ecotone in the Tuliok River, Khibiny Mountains, Russia. It was demonstrated that this method allows to determine the position of the boundaries of ecotone objects and their abundance on the basis of quantitative criteria, which provides a more accurate characteristic of ecotone vegetation when compared to the per-pixel approach of automatic imagery interpretation.

Sensitive spectrophotometric methods for determination of some organophosphorus pesticides in vegetable samples

Directory of Open Access Journals (Sweden)

MAGDA A. AKL

2010-03-01

Full Text Available Three rapid, simple, reproducible and sensitive spectrophotometric methods (A, B and C are described for the determination of two organophosphorus pesticides, (malathion and dimethoate in formulations and vegetable samples. The methods A and B involve the addition of an excess of Ce4+ into sulphuric acid medium and the determination of the unreacted oxidant by decreasing the red color of chromotrope 2R (C2R at a suitable lmax = 528 nm for method A, or a decrease in the orange pink color of rhodamine 6G (Rh6G at a suitable lmax = = 525 nm. The method C is based on the oxidation of malathion or dimethoate with the slight excess of N-bromosuccinimide (NBS and the determination of unreacted oxidant by reacting it with amaranth dye (AM in hydrochloric acid medium at a suitable lmax = 520 nm. A regression analysis of Beer-Lambert plots showed a good correlation in the concentration range of 0.1-4.2 μg mL−1. The apparent molar absorptivity, Sandell sensitivity, the detection and quantification limits were calculated. For more accurate analysis, Ringbom optimum concentration ranges are 0.25-4.0 μg mL−1. The developed methods were successfully applied to the determination of malathion, and dimethoate in their formulations and environmental vegetable samples.

Matching methods to produce maps for pest risk analysis to resources

Directory of Open Access Journals (Sweden)

Richard Baker

2013-09-01

Full Text Available Decision support systems (DSSs for pest risk mapping are invaluable for guiding pest risk analysts seeking to add maps to pest risk analyses (PRAs. Maps can help identify the area of potential establishment, the area at highest risk and the endangered area for alien plant pests. However, the production of detailed pest risk maps may require considerable time and resources and it is important to match the methods employed to the priority, time and detail required. In this paper, we apply PRATIQUE DSSs to Phytophthora austrocedrae, a pathogen of the Cupressaceae, Thaumetopoea pityocampa, the pine processionary moth, Drosophila suzukii, spotted wing Drosophila, and Thaumatotibia leucotreta, the false codling moth. We demonstrate that complex pest risk maps are not always a high priority and suggest that simple methods may be used to determine the geographic variation in relative risks posed by invasive alien species within an area of concern.

Landscape dynamics in the Arctic foothills: Landscape evolution and vegetation succession on disturbances

Energy Technology Data Exchange (ETDEWEB)

Walker, D.A.; Walker, M.D.

1990-10-20

This document contains a summary of research accomplished by the University of Colorado's Institute of Arctic and Alpine Research (INSTAAR) Joint Facility for Regional Ecosystem Analysis (JFREA) for the Department of Energy's R D research program for 1989--1990. Aerial photographs, orthophoto topographic maps, and digital elevation models (DEMs) of the Toolik Lake region site were prepared by Aeromap US at 1:500 and 1:5000 scales. During August 1990, the region surrounding Toolik Lake was mapped at 1:5000 scale, and the intensive research grid was mapped at 1:500 scale. Mapped variables include vegetation, landforms, surface forms, and percentage surface water. Soil data from the Imnavait Creek and Toolik Lake sites are central to the analysis of landscape evolution. Soils were collected from the base of the O horizon at 72 gridpoints on the 1:500-scale map area at Imnavait Creek, and 85 grid points at Toolik Lake. Soils are being analyzed for percentage moisture, pH (saturated paste), electrical conductivity, percentage organic matter, nitrate, nitrogen, phosphorus, potassium, iron, manganese, copper. Soils were also collected from 81 permanent plots (199 horizons) which will be used for vegetation-environmental analyses. Permanent 1 {times} 1-meter point-quadrat plots were established at 85 points of the Toolik Lake grid. Data from the plots will be stratified according to slope position and terrain unit and used to compare vegetation structure and cover on different aged surfaces. Work continued on the study of the effects of road dust on tundra vegetation. 28 figs.

A dataset mapping the potential biophysical effects of vegetation cover change

Science.gov (United States)

Duveiller, Gregory; Hooker, Josh; Cescatti, Alessandro

2018-02-01

Changing the vegetation cover of the Earth has impacts on the biophysical properties of the surface and ultimately on the local climate. Depending on the specific type of vegetation change and on the background climate, the resulting competing biophysical processes can have a net warming or cooling effect, which can further vary both spatially and seasonally. Due to uncertain climate impacts and the lack of robust observations, biophysical effects are not yet considered in land-based climate policies. Here we present a dataset based on satellite remote sensing observations that provides the potential changes i) of the full surface energy balance, ii) at global scale, and iii) for multiple vegetation transitions, as would now be required for the comprehensive evaluation of land based mitigation plans. We anticipate that this dataset will provide valuable information to benchmark Earth system models, to assess future scenarios of land cover change and to develop the monitoring, reporting and verification guidelines required for the implementation of mitigation plans that account for biophysical land processes.

Medium Scale Central Valley Riparian Vegetation and Land Use with Aggregated Delta Veg, 2011 [ds724

Data.gov (United States)

California Natural Resource Agency — Geodatabase (SDE) feature class containing map of vegetation along mainstem rivers and major tributaries (including ancillary natural and semi-natural vegetation)...

Modelling Multi Hazard Mapping in Semarang City Using GIS-Fuzzy Method

Science.gov (United States)

Nugraha, A. L.; Awaluddin, M.; Sasmito, B.

2018-02-01

One important aspect of disaster mitigation planning is hazard mapping. Hazard mapping can provide spatial information on the distribution of locations that are threatened by disaster. Semarang City as the capital of Central Java Province is one of the cities with high natural disaster intensity. Frequent natural disasters Semarang city is tidal flood, floods, landslides, and droughts. Therefore, Semarang City needs spatial information by doing multi hazard mapping to support disaster mitigation planning in Semarang City. Multi Hazards map modelling can be derived from parameters such as slope maps, rainfall, land use, and soil types. This modelling is done by using GIS method with scoring and overlay technique. However, the accuracy of modelling would be better if the GIS method is combined with Fuzzy Logic techniques to provide a good classification in determining disaster threats. The Fuzzy-GIS method will build a multi hazards map of Semarang city can deliver results with good accuracy and with appropriate threat class spread so as to provide disaster information for disaster mitigation planning of Semarang city. from the multi-hazard modelling using GIS-Fuzzy can be known type of membership that has a good accuracy is the type of membership Gauss with RMSE of 0.404 the smallest of the other membership and VAF value of 72.909% of the largest of the other membership.

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

Science.gov (United States)

Ackers, Steven H.; Davis, Raymond J.; Olsen, K.; Dugger, Catherine

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.Recent increases in the use of light detection and ranging (lidar) data, coupled with the need to produce spatially accurate and detailed forest vegetation maps have spurred interest in its use for SDMs and habitat mapping. Instead of modeling predictor variables from remotely sensed spectral data, lidar provides direct measurements of vegetation height for use in SDMs. We expect a SDM habitat map produced from directly measured predictor variables to be more accurate than one produced from modeled predictors.We used maximum entropy (Maxent) SDM modeling software to compare predictive performance and estimates of habitat area between Landsat-based and lidar-based northern spotted owl SDMs and habitat maps. We explored the differences and similarities between these maps, and to a pre-existing aerial photo-interpreted habitat map produced by local wildlife biologists. The lidar-based map had the highest predictive performance based on 10 bootstrapped replicate models (AUC = 0.809 ± 0.011), but the

Groundwater dependant vegetation identified by remote sensing in the Iberian Peninsula

Science.gov (United States)

Gouveia, Célia; Pascoa, Patrícia; Kurz-Besson, Cathy

2017-04-01

Groundwater Dependant Ecosystems (GDEs) are defined as ecosystems whose composition, structure, and function depend on the water supplies from groundwater aquifers. Within GDEs, phreatophytes are terrestrial plants relying on groundwater through deep rooting. They can be found worldwide but are mostly adapted to environments facing scarce water availability or recurrent drought periods mainly in semi-arid to arid climate geographical areas, such as the Mediterranean basin. We present a map of the potential distribution of GDEs over the Iberian Peninsula (IP) obtained by remote sensing and identifying hotspots corresponding to the most vulnerable areas for rainfed vegetation facing the risk of desertification. The characterization of GDEs was assessed by remote sensing (RS), using CORINE land-cover information and the Normalized Difference Vegetation Index (NDVI) from VEGETATION recorded between 1998 and 2014 with a resolution of 1km. The methodology based on Gou et al (2015) relied on three approaches to map GDEs over the IP by: i) Detecting vegetation remaining green during the dry periods, since GDEs are more likely to show high NDVI values during summer of dry years; ii) Spotting vegetation with low seasonal changes since GDEs are more prone to have the lowest NDVI standard deviation along an entire year, and iii) Discriminating vegetation with low inter-annual variability since GDEs areas should provide the lowest NDVI changes between extreme wet and dry years. A geospatial analysis was performed to gather the potential area of GDEs (obtained with NDVI), vegetation land cover types (CORINE land cover) and climatic variables (temperature, precipitation and the Standardized Precipitation-Evapotranspiration Index SPEI). This analysis allowed the identification of hotspots of the most vulnerable areas for rainfed vegetation regarding water scarcity over the Iberian Peninsula, where protection measures should be urgently applied to sustain rainfed ecosystem and agro

Adaptive multiresolution method for MAP reconstruction in electron tomography

Energy Technology Data Exchange (ETDEWEB)

Acar, Erman, E-mail: erman.acar@tut.fi [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland); Peltonen, Sari; Ruotsalainen, Ulla [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland)

2016-11-15

3D image reconstruction with electron tomography holds problems due to the severely limited range of projection angles and low signal to noise ratio of the acquired projection images. The maximum a posteriori (MAP) reconstruction methods have been successful in compensating for the missing information and suppressing noise with their intrinsic regularization techniques. There are two major problems in MAP reconstruction methods: (1) selection of the regularization parameter that controls the balance between the data fidelity and the prior information, and (2) long computation time. One aim of this study is to provide an adaptive solution to the regularization parameter selection problem without having additional knowledge about the imaging environment and the sample. The other aim is to realize the reconstruction using sequences of resolution levels to shorten the computation time. The reconstructions were analyzed in terms of accuracy and computational efficiency using a simulated biological phantom and publically available experimental datasets of electron tomography. The numerical and visual evaluations of the experiments show that the adaptive multiresolution method can provide more accurate results than the weighted back projection (WBP), simultaneous iterative reconstruction technique (SIRT), and sequential MAP expectation maximization (sMAPEM) method. The method is superior to sMAPEM also in terms of computation time and usability since it can reconstruct 3D images significantly faster without requiring any parameter to be set by the user. - Highlights: • An adaptive multiresolution reconstruction method is introduced for electron tomography. • The method provides more accurate results than the conventional reconstruction methods. • The missing wedge and noise problems can be compensated by the method efficiently.

Mapping of Vegetation with the Geoinformation System and Determining of Carrying Capacity of the Pre-Urals Steppe area for a Newly Establishing Population of the Przewalski Horse Equus ferus przewalskii at the Orenburg State Nature Reserve

Science.gov (United States)

Fedorov, N. I.; Mikhailenko, O. I.; Zharkikh, T. L.; Bakirova, R. T.

2018-01-01

Mapping of the vegetation (1:25000) of the Pre-Urals Steppe area at the Orenburg State Nature Reserve was completed in 2016. A map created with the geoinformation system contains 1931 simple and complex polygons for 25 types of vegetation. In a drought year, the average stock of palatable vegetation of the whole area is estimated at 8380 tons dry weight. The estimation is based on the size of areas covered by different types of vegetation, their grass production, the correction coefficients for decreasing of pasture forage stocks in winter and decreasing of production of grass communities in dry years. Based on pasture forage stocks the area could tolerate the maximum population size of 1769 individuals of the Przewalski horse, their average density could be 0.11 horse per ha. Yet, as watering places for animals are limited in Pre-Urals Steppe, grazing pressures on the vegetation next to the water sources may increase in dry years. That is why the above-mentioned calculated maximum population size and density must be reduced at least by half until some additional watering places are established and monitoring of the grazing effect on the vegetation next to the places is carried out regularly. Thus, the maximum size of the population is estimated at 800 to 900 individuals, which is almost 1.5 times more than necessary to establish a self-sustained population of the Przewalski horse.

Vegetation Description, Rare Plant Inventory, and Vegetation Monitoring for Craig Mountain, Idaho.

Energy Technology Data Exchange (ETDEWEB)

Mancuso, Michael; Moseley, Robert

1994-12-01

The Craig Mountain Wildlife Mitigation Area was purchased by Bonneville Power Administration (BPA) as partial mitigation for wildlife losses incurred with the inundation of Dworshak Reservoir on the North Fork Clearwater River. Upon completion of the National Environmental Protection Act (NEPA) process, it is proposed that title to mitigation lands will be given to the Idaho Department of Fish and Game (IDFG). Craig Mountain is located at the northern end of the Hells Canyon Ecosystem. It encompasses the plateau and steep canyon slopes extending from the confluence of the Snake and Salmon rivers, northward to near Waha, south of Lewiston, Idaho. The forested summit of Craig Mountain is characterized by gently rolling terrain. The highlands dramatically break into the canyons of the Snake and Salmon rivers at approximately the 4,700 foot contour. The highly dissected canyons are dominated by grassland slopes containing a mosaic of shrubfield, riparian, and woodland habitats. During the 1993 and 1994 field seasons, wildlife, habitat/vegetation, timber, and other resources were systematically inventoried at Craig Mountain to provide Fish and Game managers with information needed to draft an ecologically-based management plan. The results of the habitat/vegetation portion of the inventory are contained in this report. The responsibilities for the Craig Mountain project included: (1) vegetation data collection, and vegetation classification, to help produce a GIS-generated Craig Mountain vegetation map, (2) to determine the distribution and abundance of rare plants populations and make recommendations concerning their management, and (3) to establish a vegetation monitoring program to evaluate the effects of Fish and Game management actions, and to assess progress towards meeting habitat mitigation goals.

Vegetation description, rare plant inventory, and vegetation monitoring for Craig Mountain, Idaho

International Nuclear Information System (INIS)

Mancuso, M.; Moseley, R.

1994-12-01

The Craig Mountain Wildlife Mitigation Area was purchased by Bonneville Power Administration (BPA) as partial mitigation for wildlife losses incurred with the inundation of Dworshak Reservoir on the North Fork Clearwater River. Upon completion of the National Environmental Protection Act (NEPA) process, it is proposed that title to mitigation lands will be given to the Idaho Department of Fish and Game (IDFG). Craig Mountain is located at the northern end of the Hells Canyon Ecosystem. It encompasses the plateau and steep canyon slopes extending from the confluence of the Snake and Salmon rivers, northward to near Waha, south of Lewiston, Idaho. The forested summit of Craig Mountain is characterized by gently rolling terrain. The highlands dramatically break into the canyons of the Snake and Salmon rivers at approximately the 4,700 foot contour. The highly dissected canyons are dominated by grassland slopes containing a mosaic of shrubfield, riparian, and woodland habitats. During the 1993 and 1994 field seasons, wildlife, habitat/vegetation, timber, and other resources were systematically inventoried at Craig Mountain to provide Fish and Game managers with information needed to draft an ecologically-based management plan. The results of the habitat/vegetation portion of the inventory are contained in this report. The responsibilities for the Craig Mountain project included: (1) vegetation data collection, and vegetation classification, to help produce a GIS-generated Craig Mountain vegetation map, (2) to determine the distribution and abundance of rare plants populations and make recommendations concerning their management, and (3) to establish a vegetation monitoring program to evaluate the effects of Fish and Game management actions, and to assess progress towards meeting habitat mitigation goals

Empirical evaluation of a practical indoor mobile robot navigation method using hybrid maps

DEFF Research Database (Denmark)

Özkil, Ali Gürcan; Fan, Zhun; Xiao, Jizhong

2010-01-01

This video presents a practical navigation scheme for indoor mobile robots using hybrid maps. The method makes use of metric maps for local navigation and a topological map for global path planning. Metric maps are generated as occupancy grids by a laser range finder to represent local information...... about partial areas. The global topological map is used to indicate the connectivity of the ‘places-of-interests’ in the environment and the interconnectivity of the local maps. Visual tags on the ceiling to be detected by the robot provide valuable information and contribute to reliable localization...... that the method is implemented successfully on physical robot in a hospital environment, which provides a practical solution for indoor navigation....

Mapping current and potential distribution of non-native Prosopis juliflora in the Afar region of Ethiopia.

Directory of Open Access Journals (Sweden)

Tewodros T Wakie

Full Text Available We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI and Normalized Difference Vegetation Indices (NDVI with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclimatic products and generated topographic variables from the Shuttle Radar Topography Mission product (SRTM were used to predict potential infestations. We ran Maxent models using non-correlated variables and the 143 species- occurrence points. Maxent generated probability surfaces were converted into binary maps using the 10-percentile logistic threshold values. Performances of models were evaluated using area under the receiver-operating characteristic (ROC curve (AUC. Our results indicate that the extent of P. juliflora invasion is approximately 3,605 km2 in the Afar region (AUC  = 0.94, while the potential habitat for future infestations is 5,024 km2 (AUC  = 0.95. Our analyses demonstrate that time-series of MODIS vegetation indices and species occurrence points can be used with Maxent modeling software to map the current distribution of P. juliflora, while topo-climatic variables are good predictors of potential habitat in Ethiopia. Our results can quantify current and future infestations, and inform management and policy decisions for containing P. juliflora. Our methods can also be replicated for managing invasive species in other East African countries.

Radiation hybrid mapping as one of the main methods of the creation of high resolution maps of human and animal genomes

International Nuclear Information System (INIS)

Sulimova, G.E.; Kompanijtsev, A.A.; Mojsyak, E.V.; Rakhmanaliev, Eh.R.; Klimov, E.A.; Udina, I.G.; Zakharov, I.A.

2000-01-01

Radiation hybrid mapping (RH mapping) is considered as one of the main method of constructing physical maps of mammalian genomes. In introduction, theoretical prerequisites of developing of the RH mapping and statistical methods of data analysis are discussed. Comparative characteristics of universal commercial panels of the radiation hybrid somatic cells (RH panels) are shown. In experimental part of the work, RH mapping is used to localize nucleotide sequences adjacent to Not I sites of human chromosome 3 with the aim to integrate contig map of Nor I clones to comprehensive maps of human genome. Five nucleotide sequences adjacent to the sites of integration of papilloma virus in human genome and expressed in the cells of cervical cancer involved localized. It is demonstrated that the region 13q14.3-q21.1 was enriched with nucleotide sequences involved in the processes of carcinogenesis. RH mapping can be considered as one of the most perspective applications of modern radiation biology in the field of molecular genetics, that is, in constructing physical maps of mammalian genomes with high resolution level [ru

Case studies: Soil mapping using multiple methods

Science.gov (United States)

Petersen, Hauke; Wunderlich, Tina; Hagrey, Said A. Al; Rabbel, Wolfgang; Stümpel, Harald

2010-05-01

Soil is a non-renewable resource with fundamental functions like filtering (e.g. water), storing (e.g. carbon), transforming (e.g. nutrients) and buffering (e.g. contamination). Degradation of soils is meanwhile not only to scientists a well known fact, also decision makers in politics have accepted this as a serious problem for several environmental aspects. National and international authorities have already worked out preservation and restoration strategies for soil degradation, though it is still work of active research how to put these strategies into real practice. But common to all strategies the description of soil state and dynamics is required as a base step. This includes collecting information from soils with methods ranging from direct soil sampling to remote applications. In an intermediate scale mobile geophysical methods are applied with the advantage of fast working progress but disadvantage of site specific calibration and interpretation issues. In the framework of the iSOIL project we present here some case studies for soil mapping performed using multiple geophysical methods. We will present examples of combined field measurements with EMI-, GPR-, magnetic and gammaspectrometric techniques carried out with the mobile multi-sensor-system of Kiel University (GER). Depending on soil type and actual environmental conditions, different methods show a different quality of information. With application of diverse methods we want to figure out, which methods or combination of methods will give the most reliable information concerning soil state and properties. To investigate the influence of varying material we performed mapping campaigns on field sites with sandy, loamy and loessy soils. Classification of measured or derived attributes show not only the lateral variability but also gives hints to a variation in the vertical distribution of soil material. For all soils of course soil water content can be a critical factor concerning a succesful

Methods for enhancing mapping of thermal fronts in oil recovery

Science.gov (United States)

Lee, D.O.; Montoya, P.C.; Wayland, J.R. Jr.

1984-03-30

A method for enhancing the resistivity contrasts of a thermal front in an oil recovery production field as measured by the controlled source audio frequency magnetotelluric (CSAMT) technique is disclosed. This method includes the steps of: (1) preparing a CSAMT-determined topological resistivity map of the production field; (2) introducing a solution of a dopant material into the production field at a concentration effective to alter the resistivity associated with the thermal front; said dopant material having a high cation exchange capacity which might be selected from the group consisting of montmorillonite, illite, and chlorite clays; said material being soluble in the conate water of the production field; (3) preparing a CSAMT-determined topological resistivity map of the production field while said dopant material is moving therethrough; and (4) mathematically comparing the maps from step (1) and step (3) to determine the location of the thermal front. This method is effective with the steam flood, fire flood and water flood techniques.

Vegetation extraction from high-resolution satellite imagery using the Normalized Difference Vegetation Index (NDVI)

Science.gov (United States)

AlShamsi, Meera R.

2016-10-01

Over the past years, there has been various urban development all over the UAE. Dubai is one of the cities that experienced rapid growth in both development and population. That growth can have a negative effect on the surrounding environment. Hence, there has been a necessity to protect the environment from these fast pace changes. One of the major impacts this growth can have is on vegetation. As technology is evolving day by day, there is a possibility to monitor changes that are happening on different areas in the world using satellite imagery. The data from these imageries can be utilized to identify vegetation in different areas of an image through a process called vegetation detection. Being able to detect and monitor vegetation is very beneficial for municipal planning and management, and environment authorities. Through this, analysts can monitor vegetation growth in various areas and analyze these changes. By utilizing satellite imagery with the necessary data, different types of vegetation can be studied and analyzed, such as parks, farms, and artificial grass in sports fields. In this paper, vegetation features are detected and extracted through SAFIY system (i.e. the Smart Application for Feature extraction and 3D modeling using high resolution satellite ImagerY) by using high-resolution satellite imagery from DubaiSat-2 and DEIMOS-2 satellites, which provide panchromatic images of 1m resolution and spectral bands (red, green, blue and near infrared) of 4m resolution. SAFIY system is a joint collaboration between MBRSC and DEIMOS Space UK. It uses image-processing algorithms to extract different features (roads, water, vegetation, and buildings) to generate vector maps data. The process to extract green areas (vegetation) utilize spectral information (such as, the red and near infrared bands) from the satellite images. These detected vegetation features will be extracted as vector data in SAFIY system and can be updated and edited by end-users, such as

Comparison of model reference and map based control method for vehicle stability enhancement

NARCIS (Netherlands)

Baek, S.; Son, M.; Song, J.; Boo, K.; Kim, H.

2012-01-01

A map based controller method to improve a vehicle lateral stability is proposed in this study and compared with the conventional method, a model referenced controller. A model referenced controller to determine compensated yaw moment uses the sliding mode method, but the proposed map based

Contribution mapping: a method for mapping the contribution of research to enhance its impact

Science.gov (United States)

2012-01-01

Background At a time of growing emphasis on both the use of research and accountability, it is important for research funders, researchers and other stakeholders to monitor and evaluate the extent to which research contributes to better action for health, and find ways to enhance the likelihood that beneficial contributions are realized. Past attempts to assess research 'impact' struggle with operationalizing 'impact', identifying the users of research and attributing impact to research projects as source. In this article we describe Contribution Mapping, a novel approach to research monitoring and evaluation that aims to assess contributions instead of impacts. The approach focuses on processes and actors and systematically assesses anticipatory efforts that aim to enhance contributions, so-called alignment efforts. The approach is designed to be useful for both accountability purposes and for assisting in better employing research to contribute to better action for health. Methods Contribution Mapping is inspired by a perspective from social studies of science on how research and knowledge utilization processes evolve. For each research project that is assessed, a three-phase process map is developed that includes the main actors, activities and alignment efforts during research formulation, production and knowledge extension (e.g. dissemination and utilization). The approach focuses on the actors involved in, or interacting with, a research project (the linked actors) and the most likely influential users, who are referred to as potential key users. In the first stage, the investigators of the assessed project are interviewed to develop a preliminary version of the process map and first estimation of research-related contributions. In the second stage, potential key-users and other informants are interviewed to trace, explore and triangulate possible contributions. In the third stage, the presence and role of alignment efforts is analyzed and the preliminary

AVALIAÇÃO E MAPEAMENTO DA COBERTURA VEGETAL DA REGIÃO CENTRAL DA CIDADE DE JUIZ DE FORA – MG - EVALUATION AND MAPPING OF REGION CENTRAL VEGETATION COVER OF JUIZ DE FORA – MG

Directory of Open Access Journals (Sweden)

Isabela Fernanda Moraes de Paula

2017-04-01

proposed by Jim (1989, in the analysis of the shape and spatial distribution of vegetation cover. In this sense, the results achieved show that most regions of the central area of the city of Juiz de Fora are less than desirable in vegetation cover, requiring investments, mainly in the areas of urban integration, whose percentage of areas covered by vegetation in respect of all covers only 2%. It is noteworthy that the higher the population density, the lower the percentage of vegetation cover, it can be said that the vegetation cover in the central area of the city of Juiz de Fora is fragmented, discontinuous and presents many "empty spaces". In the mapping carried out was found 15.401% of areas covered by woody vegetation, about 1.694% of shrub and 8.59% of undergrowth. The largest expanses of green spots are scattered in between, scattered throughout the area and disconnect with each other. Therefore, its measurement, classification and spatial distribution are of paramount importance as it become essential basis for improvements and planning in the context of urban areas.

EnviroAtlas - New York, NY - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees & Forest and Grass & Herbaceous. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets)

Forgotten forests--issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study.

Science.gov (United States)

Särkinen, Tiina; Iganci, João R V; Linares-Palomino, Reynaldo; Simon, Marcelo F; Prado, Darién E

2011-11-24

South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species. Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be particularly useful for mapping

Classification of submersed aquatic vegetation of the Venice lagoon using MIVIS airborne data

Directory of Open Access Journals (Sweden)

S. Pignatti

2006-06-01

Full Text Available In July 2001 an aerial survey with MIVIS (Multispectral Infrared and Visible Spectrometer hyperspectral sensor and an in situ survey campaign were performed on Venice lagoon to map benthic macro-algae and sea phanerogams distribution. On MIVIS VIS spectral range images, training areas for benthic macro-algae and sea phanerogams have been selected by using sea truth data collected by CNR-ISMAR from in situ campaign and periodic area surveys used in the lagoon by the local authorities. The derived spectral signature has been used to classify the area in order to produce the maps of the pure and mixture submersed vegetation population. The algorithm applied to the data is based on the Subpixel Spectral Analytical Process (SSAP method. The method assumes that the spectrum of a single pixel is composed of a fraction of the material of interest while the remainder of the observed spectra contains background materials. In terms of recognition processes the produced maps present a very good agreement with the sea truth data even though the fraction material expressed in the maps does not represent a quantitative estimation of the material of interest.

A method for statistically comparing spatial distribution maps

Directory of Open Access Journals (Sweden)

Reynolds Mary G

2009-01-01

Full Text Available Abstract Background Ecological niche modeling is a method for estimation of species distributions based on certain ecological parameters. Thus far, empirical determination of significant differences between independently generated distribution maps for a single species (maps which are created through equivalent processes, but with different ecological input parameters, has been challenging. Results We describe a method for comparing model outcomes, which allows a statistical evaluation of whether the strength of prediction and breadth of predicted areas is measurably different between projected distributions. To create ecological niche models for statistical comparison, we utilized GARP (Genetic Algorithm for Rule-Set Production software to generate ecological niche models of human monkeypox in Africa. We created several models, keeping constant the case location input records for each model but varying the ecological input data. In order to assess the relative importance of each ecological parameter included in the development of the individual predicted distributions, we performed pixel-to-pixel comparisons between model outcomes and calculated the mean difference in pixel scores. We used a two sample Student's t-test, (assuming as null hypothesis that both maps were identical to each other regardless of which input parameters were used to examine whether the mean difference in corresponding pixel scores from one map to another was greater than would be expected by chance alone. We also utilized weighted kappa statistics, frequency distributions, and percent difference to look at the disparities in pixel scores. Multiple independent statistical tests indicated precipitation as the single most important independent ecological parameter in the niche model for human monkeypox disease. Conclusion In addition to improving our understanding of the natural factors influencing the distribution of human monkeypox disease, such pixel-to-pixel comparison

A recognition method research based on the heart sound texture map

Directory of Open Access Journals (Sweden)

Huizhong Cheng

2016-06-01

Full Text Available In order to improve the Heart Sound recognition rate and reduce the recognition time, in this paper, we introduces a new method for Heart Sound pattern recognition by using Heart Sound Texture Map. Based on the Heart Sound model, we give the Heart Sound time-frequency diagram and the Heart Sound Texture Map definition, we study the structure of the Heart Sound Window Function principle and realization method, and then discusses how to use the Heart Sound Window Function and the Short-time Fourier Transform to obtain two-dimensional Heart Sound time-frequency diagram, propose corner correlation recognition algorithm based on the Heart Sound Texture Map according to the characteristics of Heart Sound. The simulation results show that the Heart Sound Window Function compared with the traditional window function makes the first (S1 and the second (S2 Heart Sound texture clearer. And the corner correlation recognition algorithm based on the Heart Sound Texture Map can significantly improve the recognition rate and reduce the expense, which is an effective Heart Sound recognition method.

A reconnaissance survey of the vegetation of the North Luangwa National Park, Zambia

Directory of Open Access Journals (Sweden)

P. P. Smith

1998-10-01

Full Text Available A comprehensive survey of the vegetation of the North Luangwa National Park (NLNP was carried out over a period of two years. The main aims of the survey were to describe the major vegetation communities in the park and to produce a vegetation map of the NLNP Initial differentiation of vegetation units was established by the appearance of the vegetation on aerial photographs Further information was derived from 353 ground plots in which > 20 000 woody plants were identified and measured Thirteen broad vegetation types were recognised in the NLNP Details of their physiognomy, species composition, distribution, topography and edaphic associations are given.

Mapping Norway - a Method to Register and Survey the Status of Accessibility

Science.gov (United States)

Michaelis, Sven; Bögelsack, Kathrin

2018-05-01

The Norwegian mapping authority has developed a standard method for mapping accessibility mostly for people with limited or no walking abilities in urban and recreational areas. We choose an object-orientated approach where points, lines and polygons represents objects in the environment. All data are stored in a geospatial database, so they can be presented as web map and analyzed using GIS software. By the end of 2016 more than 160 municipalities are mapped using that method. The aim of this project is to establish a national standard for mapping and to provide a geodatabase that shows the status of accessibility throughout Norway. The data provide a useful tool for national statistics, local planning authorities and private users. First results show that accessibility is low and Norway still faces many challenges to meet the government's goals for Universal Design.

[Retrieval of Copper Pollution Information from Hyperspectral Satellite Data in a Vegetation Cover Mining Area].

Science.gov (United States)

Qu, Yong-hua; Jiao, Si-hong; Liu, Su-hong; Zhu, Ye-qing

2015-11-01

Heavy metal mining activities have caused the complex influence on the ecological environment of the mining regions. For example, a large amount of acidic waste water containing heavy metal ions have be produced in the process of copper mining which can bring serious pollution to the ecological environment of the region. In the previous research work, bare soil is mainly taken as the research target when monitoring environmental pollution, and thus the effects of land surface vegetation have been ignored. It is well known that vegetation condition is one of the most important indictors to reflect the ecological change in a certain region and there is a significant linkage between the vegetation spectral characteristics and the heavy metal when the vegetation is effected by the heavy metal pollution. It means the vegetation is sensitive to heavy metal pollution by their physiological behaviors in response to the physiological ecology change of their growing environment. The conventional methods, which often rely on large amounts of field survey data and laboratorial chemical analysis, are time consuming and costing a lot of material resources. The spectrum analysis method using remote sensing technology can acquire the information of the heavy mental content in the vegetation without touching it. However, the retrieval of that information from the hyperspectral data is not an easy job due to the difficulty in figuring out the specific band, which is sensitive to the specific heavy metal, from a huge number of hyperspectral bands. Thus the selection of the sensitive band is the key of the spectrum analysis method. This paper proposed a statistical analysis method to find the feature band sensitive to heavy metal ion from the hyperspectral data and to then retrieve the metal content using the field survey data and the hyperspectral images from China Environment Satellite HJ-1. This method selected copper ion content in the leaves as the indicator of copper pollution

INTEGRATION OF PALSAR AND ASTER SATELLITE DATA FOR GEOLOGICAL MAPPING IN TROPICS

Directory of Open Access Journals (Sweden)

A. Beiranvand Pour

2015-10-01

Full Text Available This research investigates the integration of the Phased Array type L-band Synthetic Aperture Radar (PALSAR and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER satellite data for geological mapping applications in tropical environments. The eastern part of the central belt of peninsular Malaysia has been investigated to identify structural features and mineral mapping using PALSAR and ASTER data. Adaptive local sigma and directional filters were applied to PALSAR data for detecting geological structure elements in the study area. The vegetation, mineralogic and lithologic indices for ASTER bands were tested in tropical climate. Lineaments (fault and fractures and curvilinear (anticline or syncline were detected using PALSAR fused image of directional filters (N-S, NE-SW, and NW-SE.Vegetation index image map show vegetation cover by fusing ASTER VNIR bands. High concentration of clay minerals zone was detected using fused image map derived from ASTER SWIR bands. Fusion of ASTER TIR bands produced image map of the lithological units. Results indicate that data integration and data fusion from PALSAR and ASTER sources enhanced information extraction for geological mapping in tropical environments.

Vegetation - Pine Creek WA and Fitzhugh Creek WA [ds484

Data.gov (United States)

California Natural Resource Agency — This fine-scale vegetation classification and map of the Pine Creek and Fitzhugh Creek Wildlife Areas, Modoc County, California was created following FGDC and...

Mapping Current and Potential Distribution of Non-Native Prosopis juliflora in the Afar Region of Ethiopia

OpenAIRE

Wakie, Tewodros T.; Evangelista, Paul H.; Jarnevich, Catherine S.; Laituri, Melinda

2014-01-01

We used correlative models with species occurrence points, Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices, and topo-climatic predictors to map the current distribution and potential habitat of invasive Prosopis juliflora in Afar, Ethiopia. Time-series of MODIS Enhanced Vegetation Indices (EVI) and Normalized Difference Vegetation Indices (NDVI) with 250 m2 spatial resolution were selected as remote sensing predictors for mapping distributions, while WorldClim bioclim...

Keyframes Global Map Establishing Method for Robot Localization through Content-Based Image Matching

Directory of Open Access Journals (Sweden)

Tianyang Cao

2017-01-01

Full Text Available Self-localization and mapping are important for indoor mobile robot. We report a robust algorithm for map building and subsequent localization especially suited for indoor floor-cleaning robots. Common methods, for example, SLAM, can easily be kidnapped by colliding or disturbed by similar objects. Therefore, keyframes global map establishing method for robot localization in multiple rooms and corridors is needed. Content-based image matching is the core of this method. It is designed for the situation, by establishing keyframes containing both floor and distorted wall images. Image distortion, caused by robot view angle and movement, is analyzed and deduced. And an image matching solution is presented, consisting of extraction of overlap regions of keyframes extraction and overlap region rebuild through subblocks matching. For improving accuracy, ceiling points detecting and mismatching subblocks checking methods are incorporated. This matching method can process environment video effectively. In experiments, less than 5% frames are extracted as keyframes to build global map, which have large space distance and overlap each other. Through this method, robot can localize itself by matching its real-time vision frames with our keyframes map. Even with many similar objects/background in the environment or kidnapping robot, robot localization is achieved with position RMSE <0.5 m.

Combining Semantic and Lexical Methods for Mapping MedDRA to VCM Icons.

Science.gov (United States)

Lamy, Jean-Baptiste; Tsopra, Rosy

2018-01-01

VCM (Visualization of Concept in Medicine) is an iconic language that represents medical concepts, such as disorders, by icons. VCM has a formal semantics described by an ontology. The icons can be used in medical software for providing a visual summary or enriching texts. However, the use of VCM icons in user interfaces requires to map standard medical terminologies to VCM. Here, we present a method combining semantic and lexical approaches for mapping MedDRA to VCM. The method takes advantage of the hierarchical relations in MedDRA. It also analyzes the groups of lemmas in the term's labels, and relies on a manual mapping of these groups to the concepts in the VCM ontology. We evaluate the method on 50 terms. Finally, we discuss the method and suggest perspectives.

Mapping Deciduous Rubber Plantation Areas and Stand Ages with PALSAR and Landsat Images

Directory of Open Access Journals (Sweden)

Weili Kou

2015-01-01

Full Text Available Accurate and updated finer resolution maps of rubber plantations and stand ages are needed to understand and assess the impacts of rubber plantations on regional ecosystem processes. This study presented a simple method for mapping rubber plantation areas and their stand ages by integration of PALSAR 50-m mosaic images and multi-temporal Landsat TM/ETM+ images. The L-band PALSAR 50-m mosaic images were used to map forests (including both natural forests and rubber trees and non-forests. For those PALSAR-based forest pixels, we analyzed the multi-temporal Landsat TM/ETM+ images from 2000 to 2009. We first studied phenological signatures of deciduous rubber plantations (defoliation and foliation and natural forests through analysis of surface reflectance, Normal Difference Vegetation Index (NDVI, Enhanced Vegetation Index (EVI, and Land Surface Water Index (LSWI and generated a map of rubber plantations in 2009. We then analyzed phenological signatures of rubber plantations with different stand ages and generated a map, in 2009, of rubber plantation stand ages (≤5, 6–10, >10 years-old based on multi-temporal Landsat images. The resultant maps clearly illustrated how rubber plantations have expanded into the mountains in the study area over the years. The results in this study demonstrate the potential of integrating microwave (e.g., PALSAR and optical remote sensing in the characterization of rubber plantations and their expansion over time.

How to Map Theory: Reliable Methods Are Fruitless Without Rigorous Theory.

Science.gov (United States)

Gray, Kurt

2017-09-01

Good science requires both reliable methods and rigorous theory. Theory allows us to build a unified structure of knowledge, to connect the dots of individual studies and reveal the bigger picture. Some have criticized the proliferation of pet "Theories," but generic "theory" is essential to healthy science, because questions of theory are ultimately those of validity. Although reliable methods and rigorous theory are synergistic, Action Identification suggests psychological tension between them: The more we focus on methodological details, the less we notice the broader connections. Therefore, psychology needs to supplement training in methods (how to design studies and analyze data) with training in theory (how to connect studies and synthesize ideas). This article provides a technique for visually outlining theory: theory mapping. Theory mapping contains five elements, which are illustrated with moral judgment and with cars. Also included are 15 additional theory maps provided by experts in emotion, culture, priming, power, stress, ideology, morality, marketing, decision-making, and more (see all at theorymaps.org ). Theory mapping provides both precision and synthesis, which helps to resolve arguments, prevent redundancies, assess the theoretical contribution of papers, and evaluate the likelihood of surprising effects.

Comparison Effectiveness of Pixel Based Classification and Object Based Classification Using High Resolution Image In Floristic Composition Mapping (Study Case: Gunung Tidar Magelang City)

Science.gov (United States)

Ardha Aryaguna, Prama; Danoedoro, Projo

2016-11-01

Developments of analysis remote sensing have same way with development of technology especially in sensor and plane. Now, a lot of image have high spatial and radiometric resolution, that's why a lot information. Vegetation object analysis such floristic composition got a lot advantage of that development. Floristic composition can be interpreted using a lot of method such pixel based classification and object based classification. The problems for pixel based method on high spatial resolution image are salt and paper who appear in result of classification. The purpose of this research are compare effectiveness between pixel based classification and object based classification for composition vegetation mapping on high resolution image Worldview-2. The results show that pixel based classification using majority 5×5 kernel windows give the highest accuracy between another classifications. The highest accuracy is 73.32% from image Worldview-2 are being radiometric corrected level surface reflectance, but for overall accuracy in every class, object based are the best between another methods. Reviewed from effectiveness aspect, pixel based are more effective then object based for vegetation composition mapping in Tidar forest.

Soil metal concentrations and vegetative assemblage structure in an urban brownfield

International Nuclear Information System (INIS)

Gallagher, Frank J.; Pechmann, Ildiko; Bogden, John D.; Grabosky, Jason; Weis, Peddrick

2008-01-01

Anthropogenic sources of toxic elements have had serious ecological and human health impacts. Analysis of the soil samples from a brownfield within Liberty State Park, Jersey City, NJ, USA, showed that arsenic, chromium, lead, zinc and vanadium exist at concentrations above those considered ambient for the area. Accumulation and translocation features were characterized for the dominant plant species of four vegetative assemblages. The trees Betula populifolia and Populus deltoides were found to be accumulating Zn in leaf tissue at extremely high levels. B. populifolia, P. deltoides and Rhus copallinum accumulated Cr primarily in the root tissue. A comparison of soil metal maps and vegetative assemblage maps indicates that areas of increasing total soil metal load were dominated by successional northern hardwoods while semi-emergent marshes consisting mostly of endemic species were restricted primarily to areas of low soil metal load. - The study yields insight into the impact of metal contaminates soils on vegetative assemblage structure and development

The vegetation and floristics of the Nkhuhlu Exclosures, Kruger National Park

Directory of Open Access Journals (Sweden)

Frances Siebert

2008-12-01

Full Text Available The need to conduct research on the impact of elephant on the environment prompted the construction of exclosures along two of the most important rivers in the Kruger National Park. Scientific research on these exclosures along the Sabie and Letaba rivers addresses how patterns of spatial and temporal heterogeneity of the riparian zone are affected by fire, flood and herbivory. To further assist this research programme, a vegetation survey was conducted at the Nkhuhlu exclosure site along the Sabie River to classify and map the vegetation of the area. This will provide baseline data to assess future changes in vegetation and floristic patterns due to small-scale environmental factors created by the presence/absence of herbivory and fire. Phytosociological data were analysed to identify plant communities and subsequent mapping units. Five plant communities, ten sub-communities and four variants were recognised and described in relation to prevailing soil forms. Differences in species richness, diversity and community structure of the plant communities are clearly articulated.

A scheme for the uniform mapping and monitoring of earth resources and environmental complexes: An assessment of natural vegetation, environmental, and crop analogs. [Sierra-Lahontan and Colorado Plateaus, Northern Great Valley (CA), and Louisiana Coastal Plain

Science.gov (United States)

Poulton, C. E.; Welch, R. I. (Principal Investigator)

1975-01-01

The author has identified the following significant results. A study was performed to develop and test a procedure for the uniform mapping and monitoring of natural ecosystems in the semi-arid and wood regions of the Sierra-Lahontan and Colorado Plateau areas, and for the estimating of rice crop production in the Northern Great Valley (Ca.) and the Louisiana Coastal Plain. ERTS-1 and high flight and low flight aerial photos were used in a visual photointerpretation scheme to identify vegetation complexes, map acreages, and evaluate crop vigor and stress. Results indicated that the vegetation analog concept is valid; that depending on the kind of vegetation and its density, analogs are interpretable at different levels in the hierarchical classification from second to the fourth level. The second level uses physiognomic growth form-structural criteria, and the fourth level uses floristic or taxonomic criteria, usually at generic level. It is recommended that analog comparisons should be made in relatively small test areas where large homogeneous examples can be found of each analog.

Optical and Physical Methods for Mapping Flooding with Satellite Imagery

Science.gov (United States)

Fayne, Jessica Fayne; Bolten, John; Lakshmi, Venkat; Ahamed, Aakash

2016-01-01

Flood and surface water mapping is becoming increasingly necessary, as extreme flooding events worldwide can damage crop yields and contribute to billions of dollars economic damages as well as social effects including fatalities and destroyed communities (Xaio et al. 2004; Kwak et al. 2015; Mueller et al. 2016).Utilizing earth observing satellite data to map standing water from space is indispensable to flood mapping for disaster response, mitigation, prevention, and warning (McFeeters 1996; Brakenridge and Anderson 2006). Since the early 1970s(Landsat, USGS 2013), researchers have been able to remotely sense surface processes such as extreme flood events to help offset some of these problems. Researchers have demonstrated countless methods and modifications of those methods to help increase knowledge of areas at risk and areas that are flooded using remote sensing data from optical and radar systems, as well as free publically available and costly commercial datasets.

Mapping swamp timothy (Cripsis schenoides) seed productivity using spectral values and vegetation indices in managed wetlands

Energy Technology Data Exchange (ETDEWEB)

Rahilly, P.J.A.; Li, D.; Guo, Q.; Zhu, J.; Ortega, R.; Quinn, N.W.T.; Harmon, T.C.

2010-01-15

This work examines the potential to predict the seed productivity of a key wetland plant species using spectral reflectance values and spectral vegetation indices. Specifically, the seed productivity of swamp timothy (Cripsis schenoides) was investigated in two wetland ponds, managed for waterfowl habitat, in California's San Joaquin Valley. Spectral reflectance values were obtained and associated spectral vegetation indices (SVI) calculated from two sets of high resolution aerial images (May 11, 2006 and June 9, 2006) and were compared to the collected vegetation data. Vegetation data were collected and analyzed from 156 plots for total aboveground biomass, total aboveground swamp timothy biomass, and total swamp timothy seed biomass. The SVI investigated included the Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Transformed Soil Adjusted Vegetation Index (TSAVI), Modified Soil Adjusted Vegetation Index (MSAVI), and Global Environment Monitoring Index (GEMI). We evaluated the correlation of the various SVI with in situ vegetation measurements for linear, quadratic, exponential and power functions. In all cases, the June image provided better predictive capacity relative to May, a result that underscores the importance of timing imagery to coincide with more favorable vegetation maturity. The north pond with the June image using SR and the exponential function (R{sup 2}=0.603) proved to be the best predictor of swamp timothy seed productivity. The June image for the south pond was less predictive, with TSAVI and the exponential function providing the best correlation (R{sup 2}=0.448). This result was attributed to insufficient vegetal cover in the south pond (or a higher percentage of bare soil) due to poor drainage conditions which resulted in a delay in swamp timothy germination. The results of this work suggest that spectral reflectance can be used to estimate seed productivity in managed seasonal

EnviroAtlas - Minneapolis/St. Paul, MN - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. In this community, vegetated cover is defined as Trees and Forest, Grass and Herbaceous, Woody Wetlands, and Emergent Wetlands. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the EnviroAtlas community area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Advances in estimation methods of vegetation water content based on optical remote sensing techniques

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

Quantitative estimation of vegetation water content(VWC) using optical remote sensing techniques is helpful in forest fire as-sessment,agricultural drought monitoring and crop yield estimation.This paper reviews the research advances of VWC retrieval using spectral reflectance,spectral water index and radiative transfer model(RTM) methods.It also evaluates the reli-ability of VWC estimation using spectral water index from the observation data and the RTM.Focusing on two main definitions of VWC-the fuel moisture content(FMC) and the equivalent water thickness(EWT),the retrieval accuracies of FMC and EWT using vegetation water indices are analyzed.Moreover,the measured information and the dataset are used to estimate VWC,the results show there are significant correlations among three kinds of vegetation water indices(i.e.,WSI,NDⅡ,NDWI1640,WI/NDVI) and canopy FMC of winter wheat(n=45).Finally,the future development directions of VWC detection based on optical remote sensing techniques are also summarized.

Hybrid image classification technique for land-cover mapping in the Arctic tundra, North Slope, Alaska

Science.gov (United States)

Chaudhuri, Debasish

Remotely sensed image classification techniques are very useful to understand vegetation patterns and species combination in the vast and mostly inaccessible arctic region. Previous researches that were done for mapping of land cover and vegetation in the remote areas of northern Alaska have considerably low accuracies compared to other biomes. The unique arctic tundra environment with short growing season length, cloud cover, low sun angles, snow and ice cover hinders the effectiveness of remote sensing studies. The majority of image classification research done in this area as reported in the literature used traditional unsupervised clustering technique with Landsat MSS data. It was also emphasized by previous researchers that SPOT/HRV-XS data lacked the spectral resolution to identify the small arctic tundra vegetation parcels. Thus, there is a motivation and research need to apply a new classification technique to develop an updated, detailed and accurate vegetation map at a higher spatial resolution i.e. SPOT-5 data. Traditional classification techniques in remotely sensed image interpretation are based on spectral reflectance values with an assumption of the training data being normally distributed. Hence it is difficult to add ancillary data in classification procedures to improve accuracy. The purpose of this dissertation was to develop a hybrid image classification approach that effectively integrates ancillary information into the classification process and combines ISODATA clustering, rule-based classifier and the Multilayer Perceptron (MLP) classifier which uses artificial neural network (ANN). The main goal was to find out the best possible combination or sequence of classifiers for typically classifying tundra type vegetation that yields higher accuracy than the existing classified vegetation map from SPOT data. Unsupervised ISODATA clustering and rule-based classification techniques were combined to produce an intermediate classified map which was

Study of Wetland Ecosystem Vegetation Using Satellite Data

Science.gov (United States)

Dyukarev, E. A.; Alekseeva, M. N.; Golovatskaya, E. A.

2017-12-01

The normalized difference vegetation index (NDVI) is used to estimate the aboveground net production (ANP) of wetland ecosystems for the key area at the South Taiga zone of West Siberia. The vegetation index and aboveground production are related by linear dependence and are specific for each wetland ecosystem. The NDVI grows with an increase in the ANP at wooded oligotrophic ecosystems. Open oligotrophic bogs and eutrophic wetlands are characterized by an opposite relation. Maps of aboveground production for wetland ecosystems are constructed for each study year and for the whole period of studies. The average aboveground production for all wetland ecosystems of the key area, which was estimated with consideration for the area they occupy and using the data of satellite measurements of the vegetation index, is 305 g C/m2/yr. The total annual carbon accumulation in aboveground wetland vegetation in the key area is 794600 t.

Comparison of Unsupervised Vegetation Classification Methods from Vhr Images after Shadows Removal by Innovative Algorithms

Science.gov (United States)

Movia, A.; Beinat, A.; Crosilla, F.

2015-04-01

The recognition of vegetation by the analysis of very high resolution (VHR) aerial images provides meaningful information about environmental features; nevertheless, VHR images frequently contain shadows that generate significant problems for the classification of the image components and for the extraction of the needed information. The aim of this research is to classify, from VHR aerial images, vegetation involved in the balance process of the environmental biochemical cycle, and to discriminate it with respect to urban and agricultural features. Three classification algorithms have been experimented in order to better recognize vegetation, and compared to NDVI index; unfortunately all these methods are conditioned by the presence of shadows on the images. Literature presents several algorithms to detect and remove shadows in the scene: most of them are based on the RGB to HSI transformations. In this work some of them have been implemented and compared with one based on RGB bands. Successively, in order to remove shadows and restore brightness on the images, some innovative algorithms, based on Procrustes theory, have been implemented and applied. Among these, we evaluate the capability of the so called "not-centered oblique Procrustes" and "anisotropic Procrustes" methods to efficiently restore brightness with respect to a linear correlation correction based on the Cholesky decomposition. Some experimental results obtained by different classification methods after shadows removal carried out with the innovative algorithms are presented and discussed.

Suitability aero-geophysical methods for generating conceptual soil maps and their use in the modeling of process-related susceptibility maps

Science.gov (United States)

Tilch, Nils; Römer, Alexander; Jochum, Birgit; Schattauer, Ingrid

2014-05-01

In the past years, several times large-scale disasters occurred in Austria, which were characterized not only by flooding, but also by numerous shallow landslides and debris flows. Therefore, for the purpose of risk prevention, national and regional authorities also require more objective and realistic maps with information about spatially variable susceptibility of the geosphere for hazard-relevant gravitational mass movements. There are many and various proven methods and models (e.g. neural networks, logistic regression, heuristic methods) available to create such process-related (e.g. flat gravitational mass movements in soil) suszeptibility maps. But numerous national and international studies show a dependence of the suitability of a method on the quality of process data and parameter maps (f.e. Tilch & Schwarz 2011, Schwarz & Tilch 2011). In this case, it is important that also maps with detailed and process-oriented information on the process-relevant geosphere will be considered. One major disadvantage is that only occasionally area-wide process-relevant information exists. Similarly, in Austria often only soil maps for treeless areas are available. However, in almost all previous studies, randomly existing geological and geotechnical maps were used, which often have been specially adapted to the issues and objectives. This is one reason why very often conceptual soil maps must be derived from geological maps with only hard rock information, which often have a rather low quality. Based on these maps, for example, adjacent areas of different geological composition and process-relevant physical properties are razor sharp delineated, which in nature appears quite rarly. In order to obtain more realistic information about the spatial variability of the process-relevant geosphere (soil cover) and its physical properties, aerogeophysical measurements (electromagnetic, radiometric), carried out by helicopter, from different regions of Austria were interpreted

Mapping background values of atmospheric nitrogen total depositions in Germany based on EMEP deposition modelling and the European Moss Survey 2005; Kartierung der Hintergrundwerte atmosphaerischer Stickstoff-Gesamtdepositionen in Deutschland anhand von Daten des EMEP-Messnetzes und des ICP Vegetation Moos-Monitoring 2005

Energy Technology Data Exchange (ETDEWEB)

Schroeder, Winfried; Holy, Marcel; Pesch, Roland [University of Vechta, Chair of Landscape Ecology, P.O.B. 1553, Vechta (Germany); Harmens, Harry [Environment Centre Wales, Centre for Ecology and Hydrology, Bangor, Gwynedd (United Kingdom); Fagerli, Hilde [Norwegian Meteorological Institute, Meteorological Synthesizing Centre-West of EMEP, P.O. Box 43-Blindern, Oslo (Norway)

2011-12-15

In order to map exceedances of critical atmospheric deposition loads for nitrogen (N) surface data on the atmospheric deposition of N compounds to terrestrial ecosystems are needed. Across Europe such information is provided by the international European Monitoring and Evaluation Programme (EMEP) in a resolution of 50 km by 50 km, relying on both emission data and measurement data on atmospheric depositions. The objective of the article at hand is on the improvement of the spatial resolution of the EMEP maps by combining them with data on the N concentration in mosses provided by the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation) of the United Nations Economic Commission for Europe (UNECE) Long-range Transboundary Air Pollution (LTRAP). Methods The map on atmospheric depositions of total N as modelled by EMEP was intersected with geostatistical surface estimations on the N concentration in mosses at a resolution of 5 km by 5 km. The medians of the N estimations in mosses were then calculated for each 50 km by 50 km grid cell. Both medians of moss estimations and corresponding modelled deposition values were ln-transformed and their relationship investigated and modelled by linear regression analysis. The regression equations were applied on the moss kriging estimates of the N concentration in mosses. The respective residuals were projected onto the centres of the EMEP grid cells and were mapped using variogram analysis and kriging procedures. Finally, the residual and the regression map were summed up to the map of total N deposition in terrestrial ecosystems throughout Europe. The regression analysis of the estimated N concentrations in mosses and the modelled EMEP depositions resulted in clear linear regression patterns with coefficients of determination of r{sup 2}=0.62 and Pearson correlations of r{sub p}=0.79 and Spearman correlations of r{sub s}=0.70, respectively. Regarding the German

Urban forest topographical mapping using UAV LIDAR

Science.gov (United States)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

Vegetation classification and quatification by satellite image processing. A case study in north Portugal

Energy Technology Data Exchange (ETDEWEB)

Aranha, J.T. [Dept. Florestal, UTAD, 5001-801 Vila Real (Portugal); Viana, H.F. [Instituto Politecnico de Viseu, Escola Superior Agraria, Viseu (Portugal); Rodrigues, R. [Bioflag - Consulting - Santo Tirso (Portugal)

2008-07-01

The expected increase in Forest Biomass demand for energy production leads to derive expeditious and non-expensive techniques in order to classify vegetal land cover and evaluate the available biomass like to be harvested. Satellite image processing and classification, combined to field work, is a suitable tool to achieve these aims. A vegetation index (NDVI) was created by means of a Landsat TM image, from 2006, manipulation, in order to create a general vegetation map. Then, the same image was submitted to a supervised classification process in order to produce a land cover map (overall accuracy of 85%). In a second stage, they were collected NDVI values for each sampling plot, in order to update the database previous developed with data collected within forestry stands and shrubland. This data merging enabled to transform general vegetation map into available biomass within forestry stands and shrubland. The results showed a range of values from 0.25 up to 6.00 dry ton./ha for recent and former burnt areas recovered by Pinus pinaster (maritime pine) young trees and from 2.00 up to 9.00 dry ton./ha for recent and former burnt areas recovered by shrubs (e.g. genista or broom).

GIS-Based Integration of Subjective and Objective Weighting Methods for Regional Landslides Susceptibility Mapping

Directory of Open Access Journals (Sweden)

Suhua Zhou

2016-04-01

Full Text Available The development of landslide susceptibility maps is of great importance due to rapid urbanization. The purpose of this study is to present a method to integrate the subjective weight with objective weight for regional landslide susceptibility mapping on the geographical information system (GIS platform. The analytical hierarchy process (AHP, which is subjective, was employed to weight predictive factors’ contribution to landslide occurrence. The frequency ratio (FR method, which is objective, was used to derive subclasses’ frequency ratio with respect to landslides that indicate the relative importance of a subclass within each predictive factor. A case study was carried out at Tsushima Island, Japan, using a historical inventory of 534 landslides and seven predictive factors: elevation, slope, aspect, terrain roughness index (TRI, lithology, land cover and mean annual precipitation (MAP. The landslide susceptibility index (LSI was calculated using the weighted linear combination of factors’ weights and subclasses’ weights. The study area was classified into five susceptibility zones according to the LSI. In addition, the produced susceptibility map was compared with maps generated using the conventional FR and AHP method and validated using the relative landslide index (RLI. The validation result showed that the proposed method performed better than the conventional application of the FR method and AHP method. The obtained landslide susceptibility maps could serve as a scientific basis for urban planning and landslide hazard management.

A novel multispectral glacier mapping method and its performance in Greenland

Science.gov (United States)

Citterio, M.; Fausto, R. S.; Ahlstrom, A. P.; Andersen, S. B.

2014-12-01

Multispectral land surface classification methods are widely used for mapping glacier outlines. Significant post-classification manual editing is typically required, and mapping glacier outlines over larger regions remains a rather labour intensive task. In this contribution we introduce a novel method for mapping glacier outlines from multispectral satellite imagery, requiring only minor manual editing.Over the last decade GLIMS (Global Land Ice Measurements from Space) improved the availability of glacier outlines, and in 2012 the Randolph Glacier Inventory (RGI) attained global coverage by compiling existing and new data sources in the wake of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). With the launch of Landsat 8 in 2013 and the upcoming ESA (European Space Agency) Sentinel 2 missions, the availability of multispectral imagery may grow faster than our ability to process it into timely and reliable glacier outline products. Improved automatic classification methods would enable a full exploitation of these new data sources.We outline the theoretical basis of the proposed classification algorithm, provide a step by step walk-through from raw imagery to finished ice cover grids and vector glacier outlines, and evaluate the performance of the new method in mapping the outlines of glaciers, ice caps and the Greenland Ice Sheet from Landsat 8 OLI imagery. The classification output is compared against manually digitized ice margin positions, the RGI vectors, and the PROMICE (Programme for Monitoring of the Greenland Ice Sheet) aerophotogrammetric map of Greenland ice masses over a sector of the Disko Island surge cluster in West Greenland, the Qassimiut ice sheet lobe in South Greenland, and the A.P. Olsen ice cap in NE Greenland.

Satellite-Based Assessment of the spatial extent of Aquatic Vegetation in Lake Victoria

Science.gov (United States)

Clark, W.; Aligeti, N.; Jeyaprakash, T.; Martins, M.; Stodghill, J.; Winstanley, H.

2011-12-01

Lake Victoria in Africa is the second largest freshwater lake in the world and is known for its abundance of aquatic wildlife. In particular over 200 different fish species are caught and sold by local fisherman. The lake is a major contributor to the local economy as a corridor of transportation, source of drinking water, and source of hydropower. However, the invasion of aquatic vegetation such as water hyacinth in the lake has disrupted each of these markets. Aquatic vegetation now covers a substantial area of the coastline blocking waterways, disrupting hydropower, hindering the collection of drinking water and decreasing the profitability of fishing. The vegetation serves as a habitat for disease carrying mosquitoes as well as snakes and snails that spread the parasitic disease bilharzia. The current control measures of invasive aquatic vegetation rely on biological, chemical and mechanical control. The objective of this study was to utilize remote sensing to map aquatic vegetation within Lake Victoria from 2000 to 2011. MODIS, Landsat 4-5TM, and Landsat 7-ETM imagery was employed to perform change detections in vegetation and identify the extent of aquatic vegetation throughout the years. The efficiency of containment efforts were evaluated and ideal time for application of such efforts were suggested. A methodology for aquatic vegetation surveillance was created. The results of this project were presented as a workshop to the Lake Victoria Fisheries Organization, SERVIR, and other partner organizations. The workshop provided instruction into the use of NASA and other satellite derived products. Time series animations of the spatial extent of aquatic vegetation within the lake were created. By identifying seasons of decreased aquatic vegetation, ideal times to employ control efforts were identified. SERVIR will subsequently utilize the methodologies and mapping results of this study to develop operational aquatic vegetation surveillance for Lake Victoria.

Comparison of Two Static in Vitro Digestion Methods for Screening the Bioaccessibility of Carotenoids in Fruits, Vegetables, and Animal Products.

Science.gov (United States)

Rodrigues, Daniele B; Chitchumroonchokchai, Chureeporn; Mariutti, Lilian R B; Mercadante, Adriana Z; Failla, Mark L

2017-12-27

In vitro digestion methods are routinely used to assess the bioaccessibility of carotenoids and other dietary lipophilic compounds. Here, we compared the recovery of carotenoids and their efficiency of micellarization in digested fruits, vegetables, egg yolk, and salmon and also in mixed-vegetable salads with and without either egg yolk or salmon using the static INFOGEST method22 and the procedure of Failla et al.16 Carotenoid stability during the simulated digestion was ≥70%. The efficiencies of the partitioning of carotenoids into mixed micelles were similar when individual plant foods and salad meals were digested using the two static methods. Furthermore, the addition of cooked egg or salmon to vegetable salads increased the bioaccessibility of some carotenoids. Our findings showed that the two methods of in vitro digestion generated similar estimates of carotenoid retention and bioaccessibility for diverse foods.

Functional brain mapping using H215O positron emission tomography (I): statistical parametric mapping method

International Nuclear Information System (INIS)

Lee, Dong Soo; Lee, Jae Sung; Kim, Kyeong Min; Chung, June Key; Lee, Myung Chul

1998-01-01

We investigated the statistical methods to compose the functional brain map of human working memory and the principal factors that have an effect on the methods for localization. Repeated PET scans with successive four tasks, which consist of one control and three different activation tasks, were performed on six right-handed normal volunteers for 2 minutes after bolus injections of 925 MBq H 2 15 O at the intervals of 30 minutes. Image data were analyzed using SPM96 (Statistical Parametric Mapping) implemented with Matlab (Mathworks Inc., U.S.A.). Images from the same subject were spatially registered and were normalized using linear and nonlinear transformation methods. Significant difference between control and each activation state was estimated at every voxel based on the general linear model. Differences of global counts were removed using analysis of covariance (ANCOVA) with global activity as covariate. Using the mean and variance for each condition which was adjusted using ANCOVA, t-statistics was performed on every voxel. To interpret the results more easily, t-values were transformed to the standard Gaussian distribution (Z-score). All the subjects carried out the activation and control tests successfully. Average rate of correct answers was 95%. The numbers of activated blobs were 4 for verbal memory I, 9 for verbal memory II, 9 for visual memory, and 6 for conjunctive activation of these three tasks. The verbal working memory activates predominantly left-sided structures, and the visual memory activates the right hemisphere. We conclude that rCBF PET imaging and statistical parametric mapping method were useful in the localization of the brain regions for verbal and visual working memory

Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

Science.gov (United States)

McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

2008-01-01

Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

Mapping Landslides Susceptibility in a Traditional Northern Nigerian City

Science.gov (United States)

Oluwafemi, Olawale A.; Yakubu, Tahir A.; Muhammad, Mahmud U.; Shitta, Nyofo; Akinwumiju, Akinola S.

2018-05-01

As a result of dearth of relevant information about Landslides Susceptibility in Nigeria, the monitoring and assessment appears intractable. Hence, the study developed a Remote Sensing approach to mapping landslides susceptibility, landuse and landcover analysis in Jos South LGA, Plateau State, Nigeria. Field Observation, SPOT 5 2009 and 2012, ASTER DEM 2009, Geological Map 2006, Topographical Map 1966 were used to map Landslide Susceptibility and Landuse /Lancover Analysis in the study area. Geospatial Analytical Operations employed using ArcGIS 10.3 and Erdas Imagine 2014 include Spatial Modeling, Vectorization, Pre-lineament Extraction, Image Processing among others. Result showed that 72.38 % of the study area is underlain by granitic rocks. The landuse/cover types delineated for the study area include floodplain (29.27 %), farmland (23.96 %), sparsely vegetated land (15.43 %), built up area (13.65 %), vegetated outcrop (8.48 %), light vegetation (5.37 %), thick vegetation (2.39 %), water body (0.58 %), plantation (0.50 %) and mining pond (0.37 %). Landslide Susceptibility Analysis also revealed that 87 % of the study area is relatively at low to very low risk of landslide event. While only 13 % of the study area is at high to very high risk of landslide event. The study revealed that the susceptibility of landslide event is very low in the study area. However, possible landslide event in the hot spots could be pronounced and could destabilize the natural and man-made environmental systems of the study area.

Assessment of Three Flood Hazard Mapping Methods: A Case Study of Perlis

Science.gov (United States)

Azizat, Nazirah; Omar, Wan Mohd Sabki Wan

2018-03-01

Flood is a common natural disaster and also affect the all state in Malaysia. Regarding to Drainage and Irrigation Department (DID) in 2007, about 29, 270 km2 or 9 percent of region of the country is prone to flooding. Flood can be such devastating catastrophic which can effected to people, economy and environment. Flood hazard mapping can be used is an important part in flood assessment to define those high risk area prone to flooding. The purposes of this study are to prepare a flood hazard mapping in Perlis and to evaluate flood hazard using frequency ratio, statistical index and Poisson method. The six factors affecting the occurrence of flood including elevation, distance from the drainage network, rainfall, soil texture, geology and erosion were created using ArcGIS 10.1 software. Flood location map in this study has been generated based on flooded area in year 2010 from DID. These parameters and flood location map were analysed to prepare flood hazard mapping in representing the probability of flood area. The results of the analysis were verified using flood location data in year 2013, 2014, 2015. The comparison result showed statistical index method is better in prediction of flood area rather than frequency ratio and Poisson method.

Phytosociological description of norite koppies in the Rustenburg area, North-West Province and refinement of the distribution of the Norite Koppies Bushveld on the national vegetation classification map of South Africa

Directory of Open Access Journals (Sweden)

A. J. H. Lamprecht

2011-12-01

Full Text Available The Norite Koppies Bushveld vegetation type boasts a distinctive and contrasting topography and species composition easily distinguished from that of surrounding areas. A phytosociological study was done on the leased mining area of the Impala Platinum Mining Company north of Rustenburg in the North-West Province. Similar norite koppies, situated west of the Norite Koppies Bushveld vegetation, and not yet mapped by Mucina & Rutherford (2006, were identified in the study area and phytosociologically described. Six plant communities and two subcommunities were identified. Multivariate statistical analyses (correspondence analyses confirmed that the species composition of these areas corresponds with and does therefore form part of the Norite Koppies Bushveld vegetation type as described by Mucina & Rutherford (2006. Some of these communities contain Boscia albitrunca, a protected plant species, and should therefore be considered as areas with conservation value.

Validation Study on a Rapid Method for Simultaneous Determination of Pesticide Residues in Vegetables and Fruits by LC-MS/MS.

Science.gov (United States)

Sato, Tamaki; Miyamoto, Iori; Uemura, Masako; Nakatani, Tadashi; Kakutani, Naoya; Yamano, Tetsuo

2016-01-01

A validation study was carried out on a rapid method for the simultaneous determination of pesticide residues in vegetables and fruits by LC-MS/MS. Preparation of the test solution was performed by a solid-phase extraction technique with QuEChERS (STQ method). Pesticide residues were extracted with acetonitrile using a homogenizer, followed by salting-out and dehydration at the same time. The acetonitrile layer was purified with C18 and PSA mini-columns. The method was assessed for 130 pesticide residues in 14 kinds of vegetables and fruits at the concentration level of 0.01 μg/g according to the method validation guideline of the Ministry of Health, Labour and Welfare of Japan. As a result 75 to 120 pesticide residues were determined satisfactorily in the tested samples. Thus, this method could be useful for a rapid and simultaneous determination of multi-class pesticide residues in various vegetables and fruits.

Methods to Measure Map Readability

OpenAIRE

Harrie, Lars

2009-01-01

Creation of maps in real-time web services introduces challenges concerning map readability. Therefore we must introduce analytical measures controlling the readability. The aim of this study is to develop and evaluate analytical readability measures with the help of user tests.

A simple method for estimating potential relative radiation (PRR) for landscape-vegetation analysis.

Science.gov (United States)

Kenneth B. Jr. Pierce; Todd Lookingbill; Dean. Urban

2005-01-01

Radiation is one of the primary influences on vegetation composition and spatial pattern. Topographic orientation is often used as a proxy for relative radiation load due to its effects on evaporative demand and local temperature. Common methods for incorporating this information (i.e., site measures of slope and aspect) fail to include daily or annual changes in solar...

Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

Directory of Open Access Journals (Sweden)

Särkinen Tiina

2011-11-01

Full Text Available Abstract Background South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF biome using herbarium data of habitat specialist species. Results Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1 poor spatial resolution, and (2 poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Conclusions Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in

Forgotten forests - issues and prospects in biome mapping using Seasonally Dry Tropical Forests as a case study

Science.gov (United States)

2011-01-01

Background South America is one of the most species diverse continents in the world. Within South America diversity is not distributed evenly at both local and continental scales and this has led to the recognition of various areas with unique species assemblages. Several schemes currently exist which divide the continental-level diversity into large species assemblages referred to as biomes. Here we review five currently available biome maps for South America, including the WWF Ecoregions, the Americas basemap, the Land Cover Map of South America, Morrone's Biogeographic regions of Latin America, and the Ecological Systems Map. The comparison is performed through a case study on the Seasonally Dry Tropical Forest (SDTF) biome using herbarium data of habitat specialist species. Results Current biome maps of South America perform poorly in depicting SDTF distribution. The poor performance of the maps can be attributed to two main factors: (1) poor spatial resolution, and (2) poor biome delimitation. Poor spatial resolution strongly limits the use of some of the maps in GIS applications, especially for areas with heterogeneous landscape such as the Andes. Whilst the Land Cover Map did not suffer from poor spatial resolution, it showed poor delimitation of biomes. The results highlight that delimiting structurally heterogeneous vegetation is difficult based on remote sensed data alone. A new refined working map of South American SDTF biome is proposed, derived using the Biome Distribution Modelling (BDM) approach where georeferenced herbarium data is used in conjunction with bioclimatic data. Conclusions Georeferenced specimen data play potentially an important role in biome mapping. Our study shows that herbarium data could be used as a way of ground-truthing biome maps in silico. The results also illustrate that herbarium data can be used to model vegetation maps through predictive modelling. The BDM approach is a promising new method in biome mapping, and could be

Remote sensing mapping of macroalgal farms by modifying thresholds in the classification tree

KAUST Repository

Zheng, Yuhan

2018-05-07

Remote sensing is the main approach used to classify and map aquatic vegetation, and classification tree (CT) analysis is superior to various classification methods. Based on previous studies, modified CT can be developed from traditional CT by adjusting the thresholds based on the statistical relationship between spectral features to classify different images without ground-truth data. However, no studies have yet employed this method to resolve marine vegetation. In this study, three Gao-Fen 1 satellite images obtained with the same sensor on January 30, 2014, November 5, 2014, and January 21, 2015 were selected, and two features were then employed to extract macroalgae from aquaculture farms from the seawater background. Besides, object-based classification and other image analysis methods were adopted to improve the classification accuracy in this study. Results show that the overall accuracies of traditional CTs for three images are 92.0%, 94.2% and 93.9%, respectively, whereas the overall accuracies of the two corresponding modified CTs for images obtained on January 21, 2015 and November 5, 2014 are 93.1% and 89.5%, respectively. This indicates modified CTs can help map macroalgae with multi-date imagery and monitor the spatiotemporal distribution of macroalgae in coastal environments.

Remote sensing mapping of macroalgal farms by modifying thresholds in the classification tree

KAUST Repository

Zheng, Yuhan; Duarte, Carlos M.; Chen, Jiang; Li, Dan; Lou, Zhaohan; Wu, Jiaping

2018-01-01

Remote sensing is the main approach used to classify and map aquatic vegetation, and classification tree (CT) analysis is superior to various classification methods. Based on previous studies, modified CT can be developed from traditional CT by adjusting the thresholds based on the statistical relationship between spectral features to classify different images without ground-truth data. However, no studies have yet employed this method to resolve marine vegetation. In this study, three Gao-Fen 1 satellite images obtained with the same sensor on January 30, 2014, November 5, 2014, and January 21, 2015 were selected, and two features were then employed to extract macroalgae from aquaculture farms from the seawater background. Besides, object-based classification and other image analysis methods were adopted to improve the classification accuracy in this study. Results show that the overall accuracies of traditional CTs for three images are 92.0%, 94.2% and 93.9%, respectively, whereas the overall accuracies of the two corresponding modified CTs for images obtained on January 21, 2015 and November 5, 2014 are 93.1% and 89.5%, respectively. This indicates modified CTs can help map macroalgae with multi-date imagery and monitor the spatiotemporal distribution of macroalgae in coastal environments.

High spatial resolution three-dimensional mapping of vegetation spectral dynamics using computer vision and hobbyist unmanned aerial vehicles

Science.gov (United States)

Dandois, J. P.; Ellis, E. C.

2013-12-01

High spatial resolution three-dimensional (3D) measurements of vegetation by remote sensing are advancing ecological research and environmental management. However, substantial economic and logistical costs limit this application, especially for observing phenological dynamics in ecosystem structure and spectral traits. Here we demonstrate a new aerial remote sensing system enabling routine and inexpensive aerial 3D measurements of canopy structure and spectral attributes, with properties similar to those of LIDAR, but with RGB (red-green-blue) spectral attributes for each point, enabling high frequency observations within a single growing season. This 'Ecosynth' methodology applies photogrammetric ''Structure from Motion'' computer vision algorithms to large sets of highly overlapping low altitude (USA. Ecosynth canopy height maps (CHMs) were strong predictors of field-measured tree heights (R2 0.63 to 0.84) and were highly correlated with a LIDAR CHM (R 0.87) acquired 4 days earlier, though Ecosynth-based estimates of aboveground biomass densities included significant errors (31 - 36% of field-based estimates). Repeated scanning of a 0.25 ha forested area at six different times across a 16 month period revealed ecologically significant dynamics in canopy color at different heights and a structural shift upward in canopy density, as demonstrated by changes in vertical height profiles of point density and relative RGB brightness. Changes in canopy relative greenness were highly correlated (R2 = 0.88) with MODIS NDVI time series for the same area and vertical differences in canopy color revealed the early green up of the dominant canopy species, Liriodendron tulipifera, strong evidence that Ecosynth time series measurements capture vegetation structural and spectral dynamics at the spatial scale of individual trees. Observing canopy phenology in 3D at high temporal resolutions represents a breakthrough in forest ecology. Inexpensive user-deployed technologies for

Quantitative vegetation reconstruction from pollen analysis and historical inventory data around a Danish small forest hollow

DEFF Research Database (Denmark)

Overballe-Petersen, Mette V; Nielsen, Anne Birgitte; Bradshaw, Richard H.W.

2013-01-01

of the pollen record? Location Denmark. The Gribskov-Ostrup small forest hollow (56°N, 12°20' E, 44 m a.s.l.) in the forest of Gribskov, eastern Denmark. Methods Pollen analysis was carried out on a small forest hollow, and LRA used to derive pollen-based quantitative estimates of past vegetation. Historical......Questions Can the model performance of the landscape reconstruction algorithm (LRA) for small forest hollows be validated through comparison to inventory-based vegetation reconstructions from the last 150 yrs? Does the application of LRA and the comparison to historical data enhance interpretation...... forest inventory data and maps were used to reconstruct the vegetation within three different circles around the hollow (20, 50 and 200 m ring widths) for five time periods during the last 150 yrs. The results of the two approaches were compared in order to evaluate model performance, and the LRA...

Method for mapping population-based case-control studies: an application using generalized additive models

Directory of Open Access Journals (Sweden)

Aschengrau Ann

2006-06-01

Full Text Available Abstract Background Mapping spatial distributions of disease occurrence and risk can serve as a useful tool for identifying exposures of public health concern. Disease registry data are often mapped by town or county of diagnosis and contain limited data on covariates. These maps often possess poor spatial resolution, the potential for spatial confounding, and the inability to consider latency. Population-based case-control studies can provide detailed information on residential history and covariates. Results Generalized additive models (GAMs provide a useful framework for mapping point-based epidemiologic data. Smoothing on location while controlling for covariates produces adjusted maps. We generate maps of odds ratios using the entire study area as a reference. We smooth using a locally weighted regression smoother (loess, a method that combines the advantages of nearest neighbor and kernel methods. We choose an optimal degree of smoothing by minimizing Akaike's Information Criterion. We use a deviance-based test to assess the overall importance of location in the model and pointwise permutation tests to locate regions of significantly increased or decreased risk. The method is illustrated with synthetic data and data from a population-based case-control study, using S-Plus and ArcView software. Conclusion Our goal is to develop practical methods for mapping population-based case-control and cohort studies. The method described here performs well for our synthetic data, reproducing important features of the data and adequately controlling the covariate. When applied to the population-based case-control data set, the method suggests spatial confounding and identifies statistically significant areas of increased and decreased odds ratios.

Program Merges SAR Data on Terrain and Vegetation Heights

Science.gov (United States)

Siqueira, Paul; Hensley, Scott; Rodriguez, Ernesto; Simard, Marc

2007-01-01

X/P Merge is a computer program that estimates ground-surface elevations and vegetation heights from multiple sets of data acquired by the GeoSAR instrument [a terrain-mapping synthetic-aperture radar (SAR) system that operates in the X and bands]. X/P Merge software combines data from X- and P-band digital elevation models, SAR backscatter magnitudes, and interferometric correlation magnitudes into a simplified set of output topographical maps of ground-surface elevation and tree height.

Determinants of vegetation distribution at continental scale. The contribution of natural and anthropogenic factors

DEFF Research Database (Denmark)

Greve, Michelle; Svenning, J.-C.; Lykke, Anne Mette

2011-01-01

It has long been debated what determines distribution of vegetation types, though this has rarely been tested at continental scale. We thus aimed to determine which vegetation types are most accurately predicted by natural environmental factors, and which of these factors best predict current veg...... was also assessed, and found to be of some importance for most vegetation types. We conclude that, in addition to including environmental variables in predicting vegetation distribution, it is essential that human impact be considered, also in future climate change scenarios....... vegetation distribution across Africa. Vegetation types were extracted from the Global Land Cover Map for the year 2000, and the distribution of vegetation types modelled in terms of climate, soil and topography. Annual precipitation was the best predictor of the distribution of all vegetation types...

Tundra vegetation effects on pan-Arctic albedo

International Nuclear Information System (INIS)

Loranty, Michael M; Goetz, Scott J; Beck, Pieter S A

2011-01-01

Recent field experiments in tundra ecosystems describe how increased shrub cover reduces winter albedo, and how subsequent changes in surface net radiation lead to altered rates of snowmelt. These findings imply that tundra vegetation change will alter regional energy budgets, but to date the effects have not been documented at regional or greater scales. Using satellite observations and a pan-Arctic vegetation map, we examined the effects of shrub vegetation on albedo across the terrestrial Arctic. We included vegetation classes dominated by low shrubs, dwarf shrubs, tussock-dominated graminoid tundra, and non-tussock graminoid tundra. Each class was further stratified by bioclimate subzones. Low-shrub tundra had higher normalized difference vegetation index values and earlier albedo decline in spring than dwarf-shrub tundra, but for tussock tundra, spring albedo declined earlier than for low-shrub tundra. Our results illustrate how relatively small changes in vegetation properties result in differences in albedo dynamics, regardless of shrub growth, that may lead to differences in net radiation upwards of 50 W m -2 at weekly time scales. Further, our findings imply that changes to the terrestrial Arctic energy budget during this important seasonal transition are under way regardless of whether recent satellite observed productivity trends are the result of shrub expansion. We conclude that a better understanding of changes in vegetation productivity and distribution in Arctic tundra is essential for accurately quantifying and predicting carbon and energy fluxes and associated climate feedbacks.

EnviroAtlas - Durham, NC - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas ) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets ).

EnviroAtlas - Portland, ME - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Milwaukee, WI - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Phoenix, AZ - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Woodbine, IA - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Portland, OR - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (http:/www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Pittsburgh, PA - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Fresno, CA - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

EnviroAtlas - Tampa, FL - 51m Riparian Buffer Vegetated Cover

Science.gov (United States)

This EnviroAtlas dataset describes the percentage of a 51-m riparian buffer that is vegetated. There is a potential for decreased water quality in areas where the riparian buffer is less vegetated. The displayed line represents the center of the analyzed riparian buffer. The water bodies analyzed include hydrologically connected streams, rivers, connectors, reservoirs, lakes/ponds, ice masses, washes, locks, and rapids within the Atlas Area. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Submerged Aquatic Vegetation of Bogue Sound, North Carolina 1992 Geoform

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — During 1992, 1:20,000 scale aerial photography for Bogue Sound, North Carolina was collected as part of an effort to map submerged aquatic vegetation (SAV) in...

Submerged Aquatic Vegetation of Bogue Sound, North Carolina 1992 Geodatabase

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — During 1992, 1:20,000 scale aerial photography for Bogue Sound, North Carolina was collected as part of an effort to map submerged aquatic vegetation (SAV) in...

Submerged Aquatic Vegetation of Bogue Sound, North Carolina 1992 Substrate

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — During 1992, 1:20,000 scale aerial photography for Bogue Sound, North Carolina was collected as part of an effort to map submerged aquatic vegetation (SAV) in...

Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

Science.gov (United States)

Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

2010-05-01

This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

A single method for recovery and concentration of enteric viruses and bacteria from fresh-cut vegetables.

Science.gov (United States)

Sánchez, G; Elizaquível, P; Aznar, R

2012-01-03

Fresh-cut vegetables are prone to be contaminated with foodborne pathogens during growth, harvest, transport and further processing and handling. As most of these products are generally eaten raw or mildly treated, there is an increase in the number of outbreaks caused by viruses and bacteria associated with fresh vegetables. Foodborne pathogens are usually present at very low levels and have to be concentrated (i.e. viruses) or enriched (i.e. bacteria) to enhance their detection. With this aim, a rapid concentration method has been developed for the simultaneous recovery of hepatitis A virus (HAV), norovirus (NV), murine norovirus (MNV) as a surrogate for NV, Escherichia coli O157:H7, Listeria monocytogenes and Salmonella enterica. Initial experiments focused on evaluating the elution conditions suitable for virus release from vegetables. Finally, elution with buffered peptone water (BPW), using a Pulsifier, and concentration by polyethylene glycol (PEG) precipitation were the methods selected for the elution and concentration of both, enteric viruses and bacteria, from three different types of fresh-cut vegetables by quantitative PCR (qPCR) using specific primers. The average recoveries from inoculated parsley, spinach and salad, were ca. 9.2%, 43.5%, and 20.7% for NV, MNV, and HAV, respectively. Detection limits were 132 RT-PCR units (PCRU), 1.5 50% tissue culture infectious dose (TCID₅₀), and 6.6 TCID₅₀ for NV, MNV, and HAV, respectively. This protocol resulted in average recoveries of 57.4%, 64.5% and 64.6% in three vegetables for E. coli O157:H7, L. monocytogenes and Salmonella with corresponding detection limits of 10³, 10² and 10³ CFU/g, respectively. Based on these results, it can be concluded that the procedure herein is suitable to recover, detect and quantify enteric viruses and foodborne pathogenic bacteria within 5 h and can be applied for the simultaneous detection of both types of foodborne pathogens in fresh-cut vegetables. Copyright �

The Holocene vegetation history of northern West Jutland

DEFF Research Database (Denmark)

Odgaard, Bent Vad

1994-01-01

. The Holocene history of each lake basin was investigated by mapping of sediment distribution, analysis of loss-on-ignition, coarse inorganic matter, humus content, mineral magnetics, 6°C. pollen and selected other microfossils. These techniques were supplemented by plant macrofossil analysis at one site....... Holocene terrestrial vegetational development was inferred at each site from analyses of pollen and microscopical charred particles. Chronologies were provided by numerous I4C dates. Stratigraphies of wet ground and terrestrial pollen and spore types were zooned by stratigraphically constrained cluster......, the synchronous timing of relatively rapid inferred change in lake and terrestrial vegetation around AD 600 may reflect changes in climate as well as in land-use. Redundancy analysis was used to develop a model between fire intensity (inferred from microscopical charred particles) and vegetational response...

Rendering Future Vegetation Change across Large Regions of the US

Science.gov (United States)

Sant'Anna Dias, Felipe; Gu, Yuting; Agarwalla, Yashika; Cheng, Yiwei; Patil, Sopan; Stieglitz, Marc; Turk, Greg

2015-04-01

We use two Machine Learning techniques, Decision Trees (DT) and Neural Networks (NN), to provide classified images and photorealistic renderings of future vegetation cover at three large regions in the US. The training data used to generate current vegetation cover include Landsat surface reflectance images, USGS Land Cover maps, 50 years of mean annual temperature and precipitation for the period 1950 - 2000, elevation, aspect and slope data. Present vegetation cover was generated on a 100m grid. Future vegetation cover for the period 2061- 2080 was predicted using the 1 km resolution bias corrected data from the NASA Goddard Institute for Space Studies Global Climate Model E simulation. The three test regions encompass a wide range of climatic gradients, topographic variation, and vegetation cover. The central Oregon site covers 19,182 square km and includes the Ochoco and Malheur National Forest. Vegetation cover is 50% evergreen forest and 50% shrubs and scrubland. The northwest Washington site covers 14,182 square km. Vegetation cover is 60% evergreen forest, 14% scrubs, 7% grassland, and 7% barren land. The remainder of the area includes deciduous forest, perennial snow cover, and wetlands. The third site, the Jemez mountain region of north central New Mexico, covers 5,500 square km. Vegetation cover is 47% evergreen forest, 31% shrubs, 13% grasses, and 3% deciduous forest. The remainder of the area includes developed and cultivated areas and wetlands. Using the above mentioned data sets we first trained our DT and NN models to reproduce current vegetation. The land cover classified images were compared directly to the USGS land cover data. The photorealistic generated vegetation images were compared directly to the remotely sensed surface reflectance maps. For all three sites, similarity between generated and observed vegetation cover was quite remarkable. The three trained models were then used to explore what the equilibrium vegetation would look like for

Fine mapping of multiple QTL using combined linkage and linkage disequilibrium mapping – A comparison of single QTL and multi QTL methods

Directory of Open Access Journals (Sweden)

Meuwissen Theo HE

2007-04-01

Full Text Available Abstract Two previously described QTL mapping methods, which combine linkage analysis (LA and linkage disequilibrium analysis (LD, were compared for their ability to detect and map multiple QTL. The methods were tested on five different simulated data sets in which the exact QTL positions were known. Every simulated data set contained two QTL, but the distances between these QTL were varied from 15 to 150 cM. The results show that the single QTL mapping method (LDLA gave good results as long as the distance between the QTL was large (> 90 cM. When the distance between the QTL was reduced, the single QTL method had problems positioning the two QTL and tended to position only one QTL, i.e. a "ghost" QTL, in between the two real QTL positions. The multi QTL mapping method (MP-LDLA gave good results for all evaluated distances between the QTL. For the large distances between the QTL (> 90 cM the single QTL method more often positioned the QTL in the correct marker bracket, but considering the broader likelihood peaks of the single point method it could be argued that the multi QTL method was more precise. Since the distances were reduced the multi QTL method was clearly more accurate than the single QTL method. The two methods combine well, and together provide a good tool to position single or multiple QTL in practical situations, where the number of QTL and their positions are unknown.

Status of vegetation cover after 25 years since the last wildfire (Río Verde, Spain)

Science.gov (United States)

Martinez-Murillo, Juan F.; Remond, Ricardo; Ruiz-Sinoga, José D.

2016-04-01

Climatic conditions play an important role in the post-fire vegetation recovery as well as other factors like topography, soil, and pre and post-fire land use (Shakesby, 2011; Robichaud et al., 2013). This study deals with the characterization of the vegetation cover status in an area affected by a wildfire 25 years ago. Namely, the objectives are to: i) compare the current and previous vegetation cover to wildfire; and ii) evaluate whether the current vegetation has recovered the previous cover to wildfire. The study area is mainly located in the Rio Verde watershed (Sierra de las Nieves, South of Spain). It corresponds to an area affected by a wildfire in August 8th, 1991. The burned area was equal to 8,156 ha. The burn severity was spatially very high. The main geographic features of the burned area are: mountainous topography (altitudes ranging from 250 m to 1700 m; slope gradient >25%; exposure mainly southfacing); igneous (peridotites), metamorphic (gneiss) and calcareous rocks (limestones); and predominant forest land use (Pinus pinaster sp. woodlands, 10%; pinus opened forest + shrubland, 40%; shrubland, 35%; and bare soil + grassland, 15%). Remote sensing techniques and GIS analysis has been applied to achieve the objectives. Landsat 5 and Landsat 8 images were used: July 13th, 1991 and July 1st, 2013, for the previous wildfire situation and 22-years after, respectively. The 1990 CORINE land cover was also considered to map 1991 land uses prior the wildfire. The Andalucía Regional Government wildfire historic records were used to select the burned area and its geographical limit. 1991 and 2013 land cover maps were obtained by means of object-oriented classifications. Also, NDVI index were calculated and mapped for both years in order to compare the status of vegetation cover. According to the results, the combination of remote sensing and GIS analysis let map the most recovered areas affected by the wildfire in 1991. The vegetation indexes indicated that

Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

Science.gov (United States)

Musick, H. Brad

1993-01-01

The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

Method of Automatic Ontology Mapping through Machine Learning and Logic Mining

Institute of Scientific and Technical Information of China (English)

王英林

2004-01-01

Ontology mapping is the bottleneck of handling conflicts among heterogeneous ontologies and of implementing reconfiguration or interoperability of legacy systems. We proposed an ontology mapping method by using machine learning, type constraints and logic mining techniques. This method is able to find concept correspondences through instances and the result is optimized by using an error function; it is able to find attribute correspondence between two equivalent concepts and the mapping accuracy is enhanced by combining together instances learning, type constraints and the logic relations that are imbedded in instances; moreover, it solves the most common kind of categorization conflicts. We then proposed a merging algorithm to generate the shared ontology and proposed a reconfigurable architecture for interoperation based on multi agents. The legacy systems are encapsulated as information agents to participate in the integration system. Finally we give a simplified case study.

Non supervised classification of vegetable covers on digital images of remote sensors: Landsat - ETM+

International Nuclear Information System (INIS)

Arango Gutierrez, Mauricio; Branch Bedoya, John William; Botero Fernandez, Veronica

2005-01-01

The plant species diversity in Colombia and the lack of inventory of them suggests the need for a process that facilitates the work of investigators in these disciplines. Remote satellite sensors such as landsat ETM+ and non-supervised artificial intelligence techniques, such as self-organizing maps - SOM, could provide viable alternatives for advancing in the rapid obtaining of information related to zones with different vegetative covers in the national geography. The zone proposed for the study case was classified in a supervised form by the method of maximum likelihood by another investigation in forest sciences and eight types of vegetative covers were discriminated. This information served as a base line to evaluate the performance of the non-supervised sort keys isodata and SOM. However, the information that the images provided had to first be purified according to the criteria of use and data quality, so that adequate information for these non-supervised methods were used. For this, several concepts were used; such as, image statistics, spectral behavior of the vegetative communities, sensor characteristics and the average divergence that allowed to define the best bands and their combinations. Principal component analysis was applied to these to reduce to the number of data while conserving a large percentage of the information. The non-supervised techniques were applied to these purified data, modifying some parameters that could yield a better convergence of the methods. The results obtained were compared with the supervised classification via confusion matrices and it was concluded that there was not a good convergence of non-supervised classification methods with this process for the case of vegetative covers

System, method, and apparatus for remote measurement of terrestrial biomass

Science.gov (United States)

Johnson, Patrick W [Jefferson, MD

2011-04-12

A system, method, and/or apparatus for remote measurement of terrestrial biomass contained in vegetative elements, such as large tree boles or trunks present in an area of interest, are provided. The method includes providing an airborne VHF radar system in combination with a LiDAR system, overflying the area of interest while directing energy toward the area of interest, using the VHF radar system to collect backscatter data from the trees as a function of incidence angle and frequency, and determining a magnitude of the biomass from the backscatter data and data from the laser radar system for each radar resolution cell. A biomass map is generated showing the magnitude of the biomass of the vegetative elements as a function of location on the map by using each resolution cell as a unique location thereon. In certain preferred embodiments, a single frequency is used with a linear array antenna.

Detailed maps of tropical forest types are within reach: forest tree communities for Trinidad and Tobago mapped with multiseason Landsat and multiseason fine-resolution imagery

Science.gov (United States)

Eileen H. Helmer; Thomas S. Ruzycki; Jay Benner; Shannon M. Voggesser; Barbara P. Scobie; Courtenay Park; David W. Fanning; Seepersad. Ramnarine

2012-01-01

Tropical forest managers need detailed maps of forest types for REDD+, but spectral similarity among forest types; cloud and scan-line gaps; and scarce vegetation ground plots make producing such maps with satellite imagery difficult. How can managers map tropical forest tree communities with satellite imagery given these challenges? Here we describe a case study of...

Remote Sensing for Mapping RAMSAR Heritage Site at Sungai Pulai Mangrove Forest Reserve, Johor, Malaysia

International Nuclear Information System (INIS)

Hasmadi, I.M.; Pakhriazad, H.Z.; Norlida, K.

2011-01-01

The Sungai Pulai Mangrove Forest Reserve (SPMFR) is the largest reverin mangrove system in Johore. In 2003 about 9,126 ha of the Sungai Pulai mangrove was designated as a RAMSAR site. RAMSAR sites are wetland areas that are deemed to have international importance and are included in the List of Wetlands of International Importance. The SPMFR plays a significant socio-economic role to the adjacent 38 villages. Satellite remote sensing is a useful source of information where it provides timely and complete coverage for vegetation mapping especially in mangroves where the accessibility is difficult. This study was carried out to identify and map land cover types using SPOT-4 imagery at the Sungai Pulai-RAMSAR site and its surrounding areas. Through unsupervised classification technique a total of seven classes of land cover type were mapped, where about 90 % mapping accuracy was gained from the accuracy assessment. Later, vegetation densities were classified into five levels namely very high, high, medium, low and very low based on crown density scale using vegetation indices model such as NDVI, AVI and OSAVI. Results from NDVI and OSAVI model were almost similar but AVI model detected more on medium vegetation which did not show the real ground condition. The study concludes that SPOT-4 imagery was able to discriminate mangrove area clearly from other land covers type. Vegetation indices model can be used as a tool for mapping vegetation density level in the SPMFR and its surrounding area. Therefore VIs models from remote sensing are useful to monitor and manage the mangrove forest for sustainable management and preserve the SPMFR as a RAMSAR site in Peninsular Malaysia. (author)

Indoor Map Acquisition System Using Global Scan Matching Method and Laser Range Scan Data