Luis Marcelo Tavares de Carvalho

Universidade Federal de Lavras (UFLA), لفراس, Minas Gerais, Brazil

Are you Luis Marcelo Tavares de Carvalho?

Claim your profile

Publications (50)6.9 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: This study aims to integrate spatial pattern modeled from field circumference measurements and airborne laser scanner data during volume estimation. The tree circumference determination was based in two approaches. In the first, the spatial variation of circumference is constant in average, and in the second, the spatial dependency of circumference was modeled based on the spatial distribution of height. The geo-statistical model considering spatial distribution of height was statistically superior based on Akaike's Information criterion, improving the performance in 32.7 units compared to the alternative modeling. Coefficient of determination also increased by 55%; no bias was detected, and the error was close to zero. The geo-statistical model estimated the circumference for trees extracted based on LiDAR data. Thus, the diameter and height was used as input to a logistic taper equation to estimate volume tree by tree. The results indicated that both methods showed similar results, differing by 0.7% as to volume and by 0.18% as to the number of trees.
    No preview · Article · Sep 2015 · Scientia Forestalis/Forest Sciences
  • Source
    Lisiane Zanella · Celio Helder Resende de Sousa · Carolina Gusmão Souza · Luis Marcelo Tavares de Carvalho
    [Show description] [Hide description]
    DESCRIPTION: The objective of this study was to evaluate if a multi-resolution segmentation algorithm is sensitive to the RapidEye’s Red Edge band and its benefits for vegetation mapping using GEOBIA and machine learning. We used a high-resolution multi-spectral RapidEye image taken in June, 2010. This image was segmented with a multiresolution segmentation algorithm (MRIS) using a fine scale parameter (300) and thirteen different weights (from ‘0’ to ‘100’) were assigned to the Red Edge spectral band to evaluate its influence in the segmentation and classification process. Each weight generated a segmented image. Attributes related to spectral information, geometry and texture were calculated for each image segment using the eCognition Developer®. Visual interpretation was performed along with field data to select seven classes (Dense vegetation, Meadow, Mining area, Bare land, Rock outcrop, Urban area and Water). A sample of 800 objects described by its attributes was selected from each segmented image. A decision tree approach based on CART was applied to the samples to select the attributes that provides the best separation among the classes within the scene. An accuracy assessment for the classification using CART was performed to compare the different weights assigned to the Red edge spectral band. Results showed that the Red Edge channel had no significant influence on the segmentation process. The attributes importance rank showed that the index derived from Red Edge channel can be used as input for image classification.
    Full-text · Research · Jun 2015
  • Aliny Aparecida dos Reis · Jose Marcio de Mello · Acerbi, F.W., Jr · Luis Marcelo Tavares de Carvalho
    [Show abstract] [Hide abstract]
    ABSTRACT: Remote sensing images are currently used as a source of auxiliary data for the inventory of native forests. These images when combined with geo-statistical techniques can provide gains in accuracy in inventory estimates. Accordingly, the aim of this study was to: (a) evaluate the spatial dependence structure of canopy reflectance values in a Cerrado Sensu Stricto fragment; (b) determine the correlations between the spectral and the wood volume data; (c) evaluate the pre-stratification efficiency based on the reflectance values from images of Landsat 5 TM satellite in a Cerrado fragment combined to kriging estimator and compare the random stratified sampling (RSS) estimates to systematic sampling (SS) estimates through the variable of interest in the forest inventory. The study area corresponds to a Cerrado Sensu Stricto fragment in C'nego Marinho city, MG. The forest inventory data were obtained from 41 plots distributed systematically. The wood volume was obtained by volumetric equations. The spectral data were collected from image in the satellite Landsat 5 TM. The spectral data were composed by TM1, TM2, TM3, TM4 and TM5 bands and the NDVI and SR vegetation indices. The spectral data have undergone a variographic analysis and were correlated with the total wood volume. Then, the stratification was carried out in the area from the spectral data. All the spectral variables showed spatially structured. The wood volume presented the highest correlations with the reflectance variables in TM4 band (r = -0,638) and reflectance in TM5 band (r = -0,501). The inventory error for SS was 19.11%, and ranged from 13.42% to 18.39% for different stratifications. Best stratifications were generated by spectral variables that presented the highest correlation values to the wood volume and those also presented the highest degree of spatial dependence (DE).
    No preview · Article · Jun 2015 · Scientia Forestalis/Forest Sciences
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Remote sensing images are currently used as a source of auxiliary data for the inventory of native forests. These images when combined with geo-statistical techniques can provide gains in accuracy in inventory estimates. Accordingly, the aim of this study was to: (a) evaluate the spatial dependence structure of canopy reflectance values in a Cerrado Sensu Stricto fragment; (b) determine the correlations between the spectral and the wood volume data; (c) evaluate the pre-stratification efficiency based on the reflectance values from images of Landsat 5 TM satellite in a Cerrado fragment combined to kriging estimator and compare the random stratified sampling (RSS) estimates to systematic sampling (SS) estimates through the variable of interest in the forest inventory. The study area corresponds to a Cerrado Sensu Stricto fragment in Cônego Marinho city, MG. The forest inventory data were obtained from 41 plots distributed systematically. The wood volume was obtained by volumetric equations. The spectral data were collected from image in the satellite Landsat 5 TM. The spectral data were composed by TM1, TM2, TM3, TM4 and TM5 bands and the NDVI and SR vegetation indices. The spectral data have undergone a variographic analysis and were correlated with the total wood volume. Then, the stratification was carried out in the area from the spectral data. All the spectral variables showed spatially structured. The wood volume presented the highest correlations with the reflectance variables in TM4 band (r = -0,638) and reflectance in TM5 band (r = -0,501). The inventory error for SS was 19.11%, and ranged from 13.42% to 18.39% for different stratifications. Best stratifications were generated by spectral variables that presented the highest correlation values to the wood volume and those also presented the highest degree of spatial dependence (DE).
    Full-text · Article · Jun 2015 · Scientia Forestalis/Forest Sciences
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study was evaluate which spectral indices have higher separability in the discrimination of burned areas of other targets in the Landsat 5 TM images on Cerrado areas in northern Minas Gerais. For this, nine spectral indices were calculated; Burned Area Index (BAI), Char Soil Index (CSI), Enhanced Vegetation Index (EVI), Normalized Burn Ratio (NBR), variation of Normalized Burn Ratio (nbr2), Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Mid-Infrared Burn index (MIRBI), Soil Adjusted Vegetation Index (SAVI) and checked your the separability by the index M. To assist the analysis, we calculated the basic statistics and the spectral signatures generated before and after the wildfire, and also the graph in space bi-spectral regions in red (band 3), near infrared (band 4), and shortwave infrared (bands 5 and 7). The results showed the MIRBI and NBR2 indices with better separability. Already NBR, NDVI, SAVI and CSI indices presented intermediate values of separability compared to other indices tested in this work. While the spectral indices BAI, EVI and NDMI had weak separability. We conclude that the indices using the bands of the shortwave infrared region showed the best results and are the most suitable for mapping fires in the region, Landsat 5 TM images.
    Full-text · Conference Paper · Apr 2015
  • [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this work was to determine the influence of stand age on the automatic detection of Eucalyptus sp. trees using LIDAR datasets. Three different stands 3, 5 and 7 years old were analyzed. The LIDAR cloud point data of the first return was split into two datasets: Class 1 (points for all vegetation), Class 2 (points for vegetation above 10m). Results for obtaining the number of stems for each dataset were compared to the census of the area, which was done by visual interpretation using an auxiliary high spatial resolution remote sensing image, and to forest inventory estimates. In comparison to the census data, tree counting using Class 1 dataset agreed well for all considered ages, with best results achieved in 3 and 5 year old stands. On the other hand, Class 2 biased toward underestimated values. The best results for this class were verified in 7 year old stands. When compared to the forest inventory data, this methodology proved to be more efficient. The number of stems derived from the forest inventory was biased towards overestimation. In order to achieve better estimates using forest inventory data, an intensification of the sampling procedure would be necessary.
    No preview · Article · Dec 2014 · Cerne
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: O objetivo deste trabalho foi avaliar a possibilidade de se estimar o diâmetro à altura do peito (DAP) com os dados de altura e de número de árvores derivados do escâner a laser aerotransportado (LiDAR, "light detection and ranging"), e determinar o volume de madeira de talhão de Eucalyptus sp. a partir dessas variáveis. O número total de árvores detectadas foi obtido com uso da filtragem de máxima local. A altura de plantas estimada pelo LiDAR apresentou tendência não significativa à subestimativa. A estimativa do DAP foi coerente com os valores encontrados no inventário florestal; porém, também mostrou tendência à subestimativa, em razão do comportamento observado quanto à altura. A variável número de fustes apresentou valores próximos aos observados nas parcelas do inventário. O LiDAR subestimou o volume total de madeira do talhão em 11,4%, em comparação ao volume posto na fábrica. A tendência de subestimação da altura das árvores (em média, cerca de 5%) impactou a estimativa do volume individual de árvores e, consequentemente, a do volume do talhão. No entanto, é possível gerar equações de regressão que estimam o DAP com boa precisão, a partir de dados de altura de plantas obtidos pelo LiDAR. O modelo parabólico é o que possibilita as melhores estimativas da produção volumétrica dos talhões de eucalipto.
    Full-text · Article · Sep 2014 · Pesquisa Agropecuária Brasileira
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Este trabalho analisou a fragmentação florestal da Área de Proteção Ambiental Coqueiral, que está localizada no município de Coqueiral, região Sul do estado de Minas Gerais. O objetivo foi avaliar a fragmentação florestal da área de estudo, a partir de métricas da paisagem, bem como elaborar modelos de simulação da paisagem, no intuito de fornecer cenários futuros de restauração ecológica, e compará-los com a situação atual da paisagem. A análise do uso e ocupação da terra foi obtida por meio de técnicas de Sistemas de Informação Geográfica e Sensoriamento Remoto, a partir de uma imagem (SPOTMAP) do satélite SPOT 5. A análise da fragmentação florestal foi realizada utilizando o software FRAGSTATS, para calcular as métricas da paisagem mensurando parâmetros como: área, perímetro, forma, conectividade dos fragmentos. Para as simulações da paisagem foram criados buffers de 1 e 5 m no entorno de todos os remanescentes florestais da área de estudo, bem como a recuperação virtual das áreas de preservação permanente. A análise da fragmentação da paisagem mostrou que a vegetação natural está distribuída em 360 fragmentos, sendo 137 deles menores que 1 ha. Os modelos de simulação da paisagem mostraram que a área de vegetação aumentou de 1943,13 ha para 2299,02 ha na simulação em que as APPs foram reflorestadas (Vegetação natural/APPs restauradas = VA). O tamanho médio dos fragmentos nesta mesma simulação aumentou em relação à paisagem atual, passando de 7,66 m para 15,75 m. A paisagem VA mostrou um menor valor de forma (1,93), indicando que a forma dos fragmentos nesta simulação foi mais simples, o que é importante do ponto de vista da conservação, pois diminui o efeito de borda nos fragmentos. Os valores de isolamento não apresentaram diferença considerável nas simulações: 38,9 m (VN); 40,64 m (VB1); 42,89 m (VB5) e 39,75 m (VA), indicando um baixo isolamento dos fragmentos, mesmo na paisagem atual. O índice de conectividade foi alto (acima de 99%) para todas as simulações, indicando que as paisagens apresentam elevada conectividade estrutural. Estes dados são relevantes subsídios para a tomada de decisão e para gestão e planejamento da Área Proteção Ambiental Coqueiral, permitindo a indicação de áreas prioritárias para conservação.
    Full-text · Article · Jul 2014
  • [Show abstract] [Hide abstract]
    ABSTRACT: This study analysed the forest fragmentation of Coqueiral Environmental Protected Area (APA Coqueiral), located in Coqueiral, South region of Minas Gerais state, Brazil. The objective was to evaluate the forest fragmentation of Coqueiral APA, using landscape metrics, as well as, elaborating landscape simulation models to provide future scenarios of ecological restoration, and then, to compare these simulations to the current landscape. Land use analyses were carried out through Geographic Information Systems and Remote Sensing techniques, using a SPOT 5 satellite image (SPOTMAP). Forest fragmentation was analysed by FRAGSTATS software for calculating landscape metrics such as: area, perimeter, shape, and, patch connectivity. We performed 1 and 5 m buffers maps, and a virtual restoration of the Permanent Protected Areas (APP) for landscape simulations. Landscape fragmentation analyses showed that natural vegetation is distributed within 360 patches, being 137 of them smaller than 1 ha. Landscape simulation models revealed that natural vegetation has increased from 1943.13 ha to 2299.02 ha in the restored APP simulation (natural vegetation/restored APPs = VA). The average patch size increased from 7.66 m to 15.75 m in the same simulation in comparison to the current landscape. VA showed a smaller shape value (1.93), indicating that patch shape is simpler in this simulation. This is an important result from the conservation point of view, because as simpler a shape of a patch is, smaller the edge effect is. Isolation values were not statistically different in the simulations: 38.9 m (VN); 40.64 m (VB1); 42.89 m (VB5) e 39.75 m (VA), what indicates low isolation between patches, even in the current landscape. Connectivity index was high (99%) for all simulations, indicating that landscapes have high structural connectivity. These data are relevant inputs to decision makers and to a better planning and management of the APA Coqueiral, allowing us to indicate the priority areas for conservation in this natural reserve. © 2014, Universidade Federal de Santa Maria. All rights reserved.
    No preview · Article · Jul 2014 · Ciencia Florestal
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The aim of this study was to develop a methodology for mapping land use and land cover in the northern region of Minas Gerais state, where, in addition to agricultural land, the landscape is dominated by native cerrado, deciduous forests, and extensive areas of vereda. Using forest inventory data, as well as RapidEye, Landsat TM and MODIS imagery, three specific objectives were defined: I) to test use of image segmentation techniques for an object-based classification encompassing spectral, spatial and temporal information, 2) to test use of high spatial resolution RapidEye imagery combined with Landsat TM time series imagery for capturing the effects of seasonality, and 3) to classify data using Artificial Neural Networks. Using MODIS time series and forest inventory data, time signatures were extracted from the dominant vegetation formations, enabling selection of the best periods of the year to be represented in the classification process. Objects created with the segmentation of RapidEye images, along with the Landsat TM time series images, were classified by ten different Multilayer Perceptron network architectures. Results showed that the methodology in question meets both the purposes of this study and the characteristics of the local plant life. With excellent accuracy values for native classes, the study showed the importance of a well-structured database for classification and the importance of suitable image segmentation to meet specific purposes.
    Full-text · Article · Apr 2014 · Cerne
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Lands (broader concept than soils, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities) of the state of Minas Gerais are in different soil, climate and socio-economics conditions and suitability for the production of agricultural goods is therefore distinct and mapping of agricultural suitability of the state lands is crucial for planning guided sustainability. Geoprocessing uses geographic information treatment techniques and GIS allows to evaluate geographic phenomena and their interrelationships using digital maps. To evaluate the agricultural suitability of state lands, we used soil maps, field knowledge, forest inventories and databases related to Ecological-Economic Zoning (EEZ) of Minas Gerais, to develop a map of land suitability in GIS. To do this, we have combined the maps of soil fertility, water stress, oxygen deficiency, vulnerability to erosion and impediments to mechanization. In terms of geographical expression, the main limiting factor of lands is soil fertility, followed by lack of water, impediments to mechanization and vulnerability to erosion. Regarding agricultural suitability, the group 2 (regular suitability for crops) is the most comprehensive, representing 45.13% of the state. For management levels A and B, low and moderate technological level, respectively, the most expressive suitability class is the regular, followed by the restricted class and last, the adequate class, while for the management level C (high technological level) the predominant class is the restricted. The predominant most intensive use type is for crops, whose area increases substantially with capital investment and technology (management levels B and C).
    Full-text · Article · Dec 2013 · Ciência e Agrotecnologia
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Light Detection and Ranging, or LIDAR, has become an effective ancillary tool to extract forest inventory data and for use in other forest studies. This work was aimed at establishing an effective methodology for using LIDAR for tree count in a stand of Eucalyptus sp. located in southern Bahia state. Information provided includes in-flight gross data processing to final tree count. Intermediate processing steps are of critical importance to the quality of results and include the following stages: organizing point clouds, creating a canopy surface model (CSM) through TIN and IDW interpolation and final automated tree count with a local maximum algorithm with 5 x 5 and 3 x 3 windows. Results were checked against manual tree count using Quickbird images, for verification of accuracy. Tree count using IDW interpolation with a 5x5 window for the count algorithm was found to be accurate to 97.36%. This result demonstrates the effectiveness of the methodology and its use potential for future applications.
    Full-text · Article · Jun 2012 · Cerne
  • Source
    Célio Helder Resende de Sousa · Carolina Gusmão Souza · Lisiane Zanella · Luis Marcelo Tavares de Carvalho
    [Show abstract] [Hide abstract]
    ABSTRACT: The objective of this study was to evaluate if a multi-resolution segmentation algorithm is sensitive to the RapidEye’s Red Edge band and its benefits for vegetation mapping using GEOBIA and machine learning. We used a high-resolution multi-spectral RapidEye image taken in June, 2010. This image was segmented with a multiresolution segmentation algorithm (MRIS) using a fine scale parameter (300) and thirteen different weights (from ‘0’ to ‘100’) were assigned to the Red Edge spectral band to evaluate its influence in the segmentation and classification process. Each weight generated a segmented image. Attributes related to spectral information, geometry and texture were calculated for each image segment using the eCognition Developer®. Visual interpretation was performed along with field data to select seven classes (Dense vegetation, Meadow, Mining area, Bare land, Rock outcrop, Urban area and Water). A sample of 800 objects described by its attributes was selected from each segmented image. A decision tree approach based on CART was applied to the samples to select the attributes that provides the best separation among the classes within the scene. An accuracy assessment for the classification using CART was performed to compare the different weights assigned to the Red edge spectral band. Results showed that the Red Edge channel had no significant influence on the segmentation process. The attributes importance rank showed that the index derived from Red Edge channel can be used as input for image classification.
    Full-text · Conference Paper · May 2012
  • Source

    Full-text · Chapter · Apr 2012
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This study analyzed the landscape structure of the Coqueiral Protected Area, located in southern Minas Gerais. We aimed to evaluate the landscape structure in the study area, based on landscape metrics and indicate priority areas for conservation. We use Geographic Information Systems and Remote Sensing tools to construct a land use map from a HCR SPOT 5 satellite image. Landscape structure analysis was carried out through Fragstats software and used landscape metrics. Results showed pasture class was considered as the landscape matrix and occupied almost half of the protected area. Landscape structure analysis showed the landscape is dominated by agropastoral activities. The landscape presented 704 units. Mean patch size area was higher for pasture than semideciduous forest, while semideciduous forest presented higher patch density. Land use classes showed complex shapes indicating higher edge effects. Pasture had the lower patch isolation. Data obtained in this study are relevant for decision making and environmental planning of the Coqueiral Protected Area, allowing suggest priority areas for conservation.
    Full-text · Article · Jan 2012
  • Carlos Augusto Zangrando Toneli · Luis Marcelo Tavares de Carvalho
    [Show abstract] [Hide abstract]
    ABSTRACT: Sub-pixel analysis is capable of generating continuous fi elds, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.
    No preview · Article · Jul 2011 · Cerne
  • [Show abstract] [Hide abstract]
    ABSTRACT: In view of the need to improve the planning of timber harvest and transportation, with both activities being the most infl uential in determining the fi nal cost of timber delivered to the mill yard, this work aims to develop a new methodological proposal using operations research and geotechnology tools in order to determine optimal locations for log stacking and also the amount of timber to be allocated to each selected stack. Analysis was performed using two software applications, geographic information system (GIS) and operations research (OR). GIS spatial analyses were based on layers of the study site, which is a property owned by Votorantim Celulose e Papel, located in the municipality of São José dos Campos, in order to obtain three variables: degree of diffi culty in operating forestry equipment, degree of diffi culty in log stacking, and distance between log stacks and existing roadways. To obtain these variables, layers containing information on terrain inclination and existing roadways were combined in another analysis named weighted overlay. Results were then fi ltered and inserted into an operations research environment for maximization of the timber volume in each selected stack. With results obtained from the geographic information system, 80 potential sites were selected for log stacking. By using operations research, 59 of these sites were ruled out, a 73% reduction in the number of potential sites, with only 21 sites remaining as potentially optimal for log storage. For each of these 21 sites, an optimal amount of timber was determined to be allocated to each one of them.
    No preview · Article · Jul 2011 · Cerne
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Conservation Units are among the best methods found to secure biodiversity conservation. The physical and biotic characteristics of high altitude areas such as Serra de Carrancas and Luminárias, in Minas Gerais state, make these places a home to endemic species and to rich biodiversity. However, these environments are highly susceptible to fast advancing erosive processes that potentially lead to soil, habitat and species loss. This study aims to evaluate the physical and biotic characteristics of the Serra de Carrancas and Luminárias region using Natural Vulnerability indicators, and also to propose Conservation Unit implementation in areas which, as per this index, are considered environmentally critical and highly sensitive to anthropic actions. Biotic and abiotic indicators, as managed by a geographic information system, identifi ed the most vulnerable areas in the study site and, given the sensitivity and scope of Serra de Carrancas and Luminárias, a State Park was proposed. The natural vulnerability index proved to be an effective tool to pinpoint prospective conservation unit areas, gathering important environmental factors and thus improving the effi ciency of conservation strategies.
    Full-text · Article · Apr 2011 · Cerne
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Conservation Units are among the best methods found to secure biodiversity conservation. The physical and biotic characteristics of high altitude areas such as Serra de Carrancas and Luminárias, in Minas Gerais state, make these places a home to endemic species and to rich biodiversity. However, these environments are highly susceptible to fast advancing erosive processes that potentially lead to soil, habitat and species loss. This study aims to evaluate the physical and biotic characteristics of the Serra de Carrancas and Luminárias region using Natural Vulnerability indicators, and also to propose Conservation Unit implementation in areas which, as per this index, are considered environmentally critical and highly sensitive to anthropic actions. Biotic and abiotic indicators, as managed by a geographic information system, identifi ed the most vulnerable areas in the study site and, given the sensitivity and scope of Serra de Carrancas and Luminárias, a State Park was proposed. The natural vulnerability index proved to be an effective tool to pinpoint prospective conservation unit areas, gathering important environmental factors and thus improving the effi ciency of conservation strategies.
    Full-text · Article · Jan 2011 · Cerne
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Multi-temporal images are now of standard use in remote sensing of vegetation during monitoring and classification.Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated, poses many challenges, primarily due tosignal to noise-related issues. This study investigates which methods generate the most appropriate smoothed curves of vegetationsignatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm which is based on Fourieranalyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The study was conductedin four different regions of the Minas Gerais State. The smoothed data were used as input data vectors for vegetation classificationby means of artificial neural networks for comparison purpose. A comparison of the results was ultimately discussed in this workshowing encouraging results and similarity between the two filtering techniques used.
    Full-text · Article · Apr 2010 · Cerne