Mapping and monitoring forest remnants : a multiscale analysis of spatio-temporal data

KEYWORDS : Landsat, time series, machine learning, semideciduous Atlantic forest, Brazil, wavelet transforms, classification, change detectionForests play a major role in important global matters such as carbon cycle, climate change, and biodiversity. Besides, forests also influence soil and water dynamics with major consequences for ecological relations and decision-making. One basic requirement to quantify and model these processes is the availability of accurate maps of forest cover. Data acquisition and analysis at appropriate scales is the keystone to achieve the mapping accuracy needed for development and reliable use of ecological models.The current and upcoming production of high-resolution data sets plus the ever-increasing time series that have been collected since the seventieth must be effectively explored. Missing values and distortions further complicate the analysis of this data set. Thus, integration and proper analysis is of utmost importance for environmental research. New conceptual models in environmental sciences, like the perception of multiple scales, require the development of effective implementation techniques.This thesis presents new methodologies to map and monitor forests on large, highly fragmented areas with complex land use patterns. The use of temporal information is extensively explored to distinguish natural forests from other land cover types that are spectrally similar. In chapter 4, novel schemes based on multiscale wavelet analysis are introduced, which enabled an effective preprocessing of long time series of Landsat data and improved its applicability on environmental assessment.In chapter 5, the produced time series as well as other information on spectral and spatial characteristics were used to classify forested areas in an experiment relating a number of combinations of attribute features. Feature sets were defined based on expert knowledge and on data mining techniques to be input to traditional and machine learning algorithms for pattern recognition, viz . maximum likelihood, univariate and multivariate decision trees, and neural networks. The results showed that maximum likelihood classification using temporal texture descriptors as extracted with wavelet transforms was most accurate to classify the semideciduous Atlantic forest in the study area.In chapter 6, a multiscale approach to digital change detection was developed to deal with multisensor and noisy remotely sensed images. Changes were extracted according to size classes minimising the effects of geometric and radiometric misregistration.Finally, in chapter 7, an automated procedure for GIS updating based on feature extraction, segmentation and classification was developed to monitor the remnants of semideciduos Atlantic forest. The procedure showed significant improvements over post classification comparison and direct multidate classification based on artificial neural networks.</p

Selection of imagery data and classifiers for mapping Brazilian semideciduous Atlantic forests

This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature sets were defined based on expert knowledge and on data mining techniques to be input to traditional and machine learning algorithms for pattern recognition, viz. maximum likelihood, univariate decision trees, multivariate decision trees, and neural networks. The results showed that the maximum likelihood classification using temporal texture descriptors as extracted with wavelet transforms was most accurate to classify the semideciduous Atlantic forest. In this study, a special accuracy measure was used: the so-called class mapping accuracy. Maximum likelihood performed relatively well, with forest mapping accuracies ranging from 34.5 to 51.3%. In contrast, accuracies for neural networks ranged from 19.0 to 45.2%. Classification confusion occurred mainly with coffee and eucalyptus plantations. Univariate trees provided the most robust results for different feature sets, with accuracies ranging from 39.6 to 46.7%. Temporal information of vegetation indices was more important than image texture, terrain topography and raw spectral information for discriminating semideciduous Atlantic forest

Selection of imagery data and classifiers for mapping Brazilian semideciduous Atlantic forests

This paper presents a case study on the use of features derived from remote sensing data for mapping the highly fragmented semideciduous Atlantic forest in Brazil. Innovative aspects of this research include the evaluation of different feature sets in order to improve land cover mapping. The feature sets were defined based on expert knowledge and on data mining techniques to be input to traditional and machine learning algorithms for pattern recognition, viz. maximum likelihood, univariate decision trees, multivariate decision trees, and neural networks. The results showed that the maximum likelihood classification using temporal texture descriptors as extracted with wavelet transforms was most accurate to classify the semideciduous Atlantic forest. In this study, a special accuracy measure was used: the so-called class mapping accuracy. Maximum likelihood performed relatively well, with forest mapping accuracies ranging from 34.5 to 51.3%. In contrast, accuracies for neural networks ranged from 19.0 to 45.2%. Classification confusion occurred mainly with coffee and eucalyptus plantations. Univariate trees provided the most robust results for different feature sets, with accuracies ranging from 39.6 to 46.7%. Temporal information of vegetation indices was more important than image texture, terrain topography and raw spectral information for discriminating semideciduous Atlantic forest

Methodology For Planning Log Stacking Using Geotechnology And Operations Research [metodologia Para Planejamento Das Pilhas De Madeira Utilizando Geotecnologia E Pesquisa Operacional]

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.173309319Arce, J.E., (1997) Um Sistema De Programação Do Transporte Principal De Multiprodutos Fl Orestais Visando À Minimização De Custos, , 98 f. Dissertação (Mestrado em Ciências Florestais) - Universidade Federal do Paraná, Curitiba, 1997Banhara, J.R., Rodriguez, L.C.E., Seixas, F., Moreira J.M.M.A., P., da Silva, L.M.S., Nobre, S.R., Cogswell, A., Agendamento otimizado da colheita de madeira de eucaliptos sob restrições operacionais, espaciais e climáticas (2010) Scientia Florestalis, 38 (85), pp. 85-95. , Piracicaba, marContreras, M., Chung, W., A computer approach to fi nding an optimal log landing location and analyzing infl uencing factors for ground-based timber harvesting (2007) Canadian Journal of Forest Research, 37 (2), pp. 276-292. , Ottawa, FebFlisberg, P., Forsberg, M., Rönnqvist, M., Optimization based planning tools for routing of forwarders at harvest areas (2007) Canadian Journal of Forest Research, 37 (11), pp. 2153-2163. , Ottawa, NovLeite, H.G., (1994) Conversão De Troncos Em Multiprodutos Da Madeira, Utilizando Programação Dinâmica, p. 230. , Tese (Doutorado em Ciência Florestal) - Universidade Federal de Viçosa, Viçosa, 1994de Oliveira, C.A., (2001) Turfa De São José Dos Campos: Estado De São Paulo, p. 14. , São Paulo: CPRM, Série oportunidades minerais, 24Rodriguez, L.C.E., Lima, A.B.N.P.M., A utilização da programação linear na determinação de uma estratégia ótima de reforma de um talhão florestal (1985) Scientia Florestalis, (31), pp. 47-53. , PiracicabaSeixas, F., Planejamento e estudo de sistema de exploração fl orestal (1986) Circular Técnica IPEF, (34), pp. 250-303. , Piracicaba, dezSilva, G.F., Leite, H.G., Silva, M.L., Rodrigues, F.L., Santos, H.N., Problemas com o uso de programação linear com posterior arredondamento da solução ótima, em regulação fl orestal (2003) Revista Árvore, 27 (5), pp. 677-688. , Viçosada Silva, M.L., Miranda, G.M., Custos (2008) Colheita Fl Orestal, pp. 185-230. , MACHADO, C. C. (Ed.), 2. ed. Viçosa, MG: UFVSoares, C.P.B., Ribeiro, J.C., Nascimento, F.J., Ribeiro, J.C.L., Determinação de fatores de empilhamento através de fotografi as digitais (2003) Revista Árvore, 27 (4), pp. 473-479. , ViçosaWeintraub, A., Romero, C., Operations research models and the management of agricultural and forestry resources: A review and comparison (2006) Interfaces, 36 (5), pp. 446-457. , New Yor

Application Of Lidar To Forest Inventory For Tree Count In Stands Of Eucalyptus Sp [aplicação Do Lidar No Inventário De Florestas Plantadas Com Eucalyptus Sp Para Contagem De árvores]

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 × 5 and 3 × 3 windows. Results were checked against manual tree count using Quickbird images, for verification of accuracy. Tree count using IDW interpolation with a 5×5 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.182175184Burrogh, P.A., McDonnell, R.A., (1998) Principles of Geographical Information Systems, p. 333. , New York: Oxford UniversityCarvalho, L.M.T., Detecção de modificações na cobertura do solo (2008) Inventário Florestal De Minas Gerais: Monitoramento Da Flora Nativa 2005-2007, p. 357. , In: CARVALHO, L. M. T, Lavras: UFLACarvalho, L.M.T., (2001) Mapping and Monitoring Forest Remanants: A Multi-scale Analysis of Spatio-temporal Data, p. 140. , Thesis (Ph. D.) - Wageningen University, WageningenCastro, F.C., Centeno, T.M., Segmentação De Imagens Geradas Por Perfilamento a Laser Para Delimitação De Árvores Individuais Em Uma Área De Reflorestamento De Eucaliptos (2005), In: Simpósio Brasileiro de Sensoriamento Remoto, 12., 2005, Goiânia. Anais... Goiânia: SBSR, CD-ROMCoelho, A.H., Vargas, R.M.A., Geração De Modelos Digitais De Terreno a Partir De Dados De Laser Scanner Aerotransportado Em Área De Floresta Usando O Software Livre GRASS (2007), pp. 3653-3660. , Simpósio Brasileiro de Sensoriamento Remoto, 13., 2007, Florianópolis, 2007. Anais... Florianópolis: SBSRCrow, P., Benham, S., Devereux, B.J., Amable, G.S., Woodland vegetation and its implications for archaeological survey using LiDAR (2007) Forestry, 80 (3), pp. 101-106. , AmsterdamDisperati, A.A., Santos, J.R., Oliveira Filho, P.C., Neeff, T., Aplicação da técnica "filtragem de locais máximas" em fotografia aérea digital para a contagem de copas em reflorestamento de Pinus elliottii Scientia Forestalis, 76, pp. 45-55. , Piracicaba, dez. 2007Heurich, M., Thoma, F., Estimation of forestry stand parameters using laser scanning data intemperature, structurally rich natural European beech (Fagus sylvatica) and Norway spruce (Picea abies) forests (2008) Forestry, 81 (5), pp. 645-661. , AmsterdamIoki, K., Junichi, I., Sasaki, T., Morimoto, Y., Kitada, K., Estimating stand volume in broad-leaved forest using discrete-return LiDAR: Plot-based approach (2010) Landscape Ecological Engeneering, 6, pp. 29-36. , LondonJensen, J.R., (2009) Sensoriamento Remoto Do Ambiente: Uma Perspectiva Em Recursos Terrestres, p. 598. , São José dos Campos: ParênteseJupp, D., Culvenor, D., Lovell, G., Newham, G., Strahler, A., Woodcock, C., Estimating forest LAI profiles and structural parameters using a ground-based laser called Echidna (2007) Tree Physiology, 29, pp. 171-181. , AmsterdamKanegae Jr., H., Scolforo, J.R., Mello, J.M., Oliveira, A.D., Avaliação de interpoladores estatísticos e determinísticos como instrumento de estratificação de povoamentos clonais de Eucalyptus sp Cerne, 12 (2), pp. 123-136. , Lavras, abr./jun. 2006Koch, B., Heyder, U., Welnacker, H., Detection of individual tree crowns in airbone lidar data Photogrammetric Engineering & Remote Sensing, 72 (4), pp. 357-363. , New York, Apr. 2006Lauri, K., Jussi, P., Jukka, M., Aki, S., Matti, M., Petteri, P., Jyrki, K., The use of airbourne laser scanning to estimate sawlog volumes (2008) Forestry, 81 (4), pp. 499-509. , AmsterdamLee, A.C., Lucas, R.M., A LiDAR-derived canopy density model for tree stem and crown mapping in Australian forests Remote Sensing of Environment, 111 (4), pp. 493-518. , New York, Dec. 2007Lillessand, T.M., Kiefer, R.W., (2000) Remote Sensingand Image Interpretation, p. 724. , 4. ed. New York: J. WileyMcCombs, J.W., Roberts, S.D., Evans, D.L., Influence of fusing lidar and multispectral imagery on remotely sensed estimates of stand density and mean tree height in a managed loblolly pine plantation (2003) Forest Science, 49 (3), pp. 457-466. , OxfordMacedo, R.C., Estimativa Volumétrica De Povoamento Clonal De Eucalyptus Sp. Através De Laserscanner Aerotransportado (2009), Dissertação (Mestrado) - Instituto Nacional de Pesquisas Espaciais, São José dos Campos, 2009Maltamo, M., Eerikäinen, K., Pitkänen, J., Hyyppä, J., Vehmas, M., Estimation of Timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions (2004) Remote Sensing of the Environment, 90, pp. 319-330. , New YorkMiqueles, M.A., Cavassim Jr., I., Weihing, D., Centeno, J., Classificação De Imagens Obtidas Do Laser Scanner Baseada Em Atributos Espectrais E Espaciais (2003), pp. 1883-1890. , In: Simpósio Brasileiro de Sensoriamento Remoto, 11., 2003, Belo Horizonte. Anais... Belo Horizonte: SBSRMorsdorf, F., Meier, E., Kotz, B., Itten, K.I., Dobbertin, M., Allgower, B., LIDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management (2004) Remote Sensing of Environment, 92, pp. 353-362. , New YorkNaesset, E., Bjerknes, K., Estimating tree heights and number of stems in young forest stands using airborne laser scanner data (2001) Remote Sensing of Environment, 78, pp. 328-340. , New YorkOliveira, A.C., Geotecnologia Na Estratificação De Povoamentos De Eucalyptus Spp (2006), p. 2006. , Dissertação (Mestrado) - Universidade Federal de Lavras, LavrasPopescu, S.C., Wynne, R.H., Nelson, R.F., Estimating plot-level tree heights with lidar: Local filtering with a canopy-height based variable window size Computers and Electronics In Agriculture, 37 (1-3), pp. 71-95. , Oxford, Dec. 2002Sasaki, T., Imanishi, J., Ioki, K., Morimoto, Y., Kitada, K., Estimation of Leaf Area index and canopy openness in broad-leaved forest using airborne laser scanner in comparison with high-resolution near-infrared digital photography (2008) Landscap Ecological Engineering, 4, pp. 47-55. , ChicagoScolforo, J.R.S., Mello, J.M., Inventário Florestal (2006), p. 561. , Lavras: FAEPESouza, C.S., Moreira, A.A., Schimith, R.S., Brandão, P.C., Silva, E., Técnicas de sensoriamento remoto como subsídios aos estudos de florestas implantadas no Brasil: Uma revisão bibliográfica Ciência Florestal, 17 (4), pp. 409-417. , Santa Maria, out./dez. 2007Tiede, D., Hochleitner, G., Blaschke, T., A full GIS-based workflow for tree identification and tree crown delineation using laser scanning 3D City Models, Road Databases, and Traffic Monitoring: Concepts, Algorithms, and Evaluation, p. 2005. , In: TIEDE, D.HOCHLEITNER, G.BLASCHKE, T, Vienna: IAPRSYu, X., Hyyppä, J., Kaartinene, H., Maltamo, M., Automatic detection of harvested trees and determination of forest growth using airborne laser scanning (2004) Remote Sensing of the Environment, 90, pp. 451-462. , New YorkZandoná, D.F., Lingnau, C., Nakajima, N.Y., Varredura a laser aerotransportado para estimativa de variáveis dendrométricas Scientia Forestalis, 36 (80), pp. 295-306. , Piracicaba, dez. 2008Zonete, M.F., Análise Do Uso Da Tecnologia Laser Aerotransportado Para Inventários Florestais Em Plantios Clonais De Eucalyptus Sp No Sul Da Bahia (2009), Dissertação (Mestrado) - Escola Superior de Agricultura "Luiz de Queiroz", Piracicaba, 2009Zonete, M.F., Rodriguez, R.C.E., Packalén, P., Estimação de parâmetros biométricos de plantios clonais de eucalipto no sul da Bahia: Uma aplicação da tecnologia laser aerotransportada Scientia Forestalis, 38 (86), pp. 225-235. , Piracicaba, jun. 201