Mapping Macrophyte Species in the Amazon Floodplain Wetlands Using Fully Polarimetric ALOS/PALSAR Data

The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Fieldwork was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical-based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

Investigations on the full polarimetric PALSAR data to discriminate macrophytes species in the Amazon floodplain wetland

The purpose of this work is to evaluate the capacity of full polarimetric L band data to discriminate macrophyte species in Amazon wetland. Fieldwork was carried out almost simultaneously to the acquisition of the full polarimetric PALSAR data. Coherent and incoherent attributes were extracted from the image, and macrophyte morphological variables were measured on the ground. The image attributes and the macrophyte variables were compared in order to evaluate their application for discriminating macrophytes species. The findings suggest that polarimetric information could be adopted to discriminate plant species based on morphology, and that estimation of plant biomass and productivity could be improved by using the polarimetric information. © 2010 IEEE.

Imagens multitemporais ALOS/PALSAR baseada em orientação a objeto na discriminação da cobertura da terra

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Informação polarimétrica PALSAR/ALOS aplicada à discriminação de espécies e estimação de parâmetros morfológicos de macrófitas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Combining ALOS/PALSAR derived vegetation structure and inundation patterns to characterize major vegetation types in the Mamiraua Sustainable Development Reserve, Central Amazon floodplain, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Utilização de imagens do ALOS/PALSAR no mapeamento digital de atributos físicos dos solos.

O levantamento e a análise da espacialização dos atributos do solo através de ferramentas de geoestatística são fundamentais para que cada hectare de terra seja cultivado segundo as suas reais aptidões. As imagens de radar de abertura sintética (SAR) têm um grande potencial para a estimação de umidade do solo e, desta forma, estes sensores podem auxiliar no mapeamento de propriedades físicas e físico-hídricas dos solos. O objetivo geral deste estudo foi avaliar o potencial de utilização de imagens de radar (micro-ondas) ALOS/PALSAR na identificação de solos em uma área da Formação Botucatu, dominada por solos de textura arenosa e média no município de Mineiros - GO. A área tem aproximadamente 946 ha, com o relevo da região variando de plano a suave ondulado e geologia da área é composta basicamente, por Arenitos da Formação Botucatu. No presente estudo foram amostrados 84 pontos para calibração e 25 pontos para validação, coletados nas profundidades de 0-20 cm e 60-80 cm. As amostras de solo analisadas para a determinação de areia, silte, argila, capacidade de campo (CC), ponto de murcha permanente (PMP) e água total disponível (AD). Para o desenvolvimento do trabalho foram adquiridas imagens de cinco datas e diferentes polarizações, totalizando 14 imagens, que foram processadas para a correção geométrica e correção radiométrica, utilizando o MDE. Também foram gerados covariáveis dos atributos do terreno: elevação (ELEV), declividade (DECLIV), posição relativa da declividade (PR-DECL), distância vertical do canal de drenagem (DVCD), fator-ls (FATOR-LS) e distância euclidiana (D-EUCL). A predição dos atributos do solo foi realizada utilizando os métodos Random Forest (RF) e Random Forest Krigagem (RFK), tendo como covariáveis preditoras as imagens de radar e os atributos do terreno. O processamento das imagens do radar ALOS/PALSAR possibilitou as correções geométrica e radiométrica, transformando os dados em unidades de coeficiente de retroespalhamento (?º) corrigidos pelo modelo digital de elevação (MDE). As imagens adquiridas representaram de forma ampla as variações de ?º ocorridos em diferentes datas. Os solos da área de estudo são predominantemente arenosos, com a maioria dos pontos amostrados classificados como NEOSSOLOS QUARTZARÊNICOS, seguidos dos LATOSSOLOS. Os modelos RF empregados para a predição dos atributos físicos e físico-hídricos dos solos proporcionaram a análise da contribuição das covariáveis preditoras. Os atributos do terreno que exerceram maior influência na predição dos atributos estudados estão relacionados à elevação. As imagens de 03/05/2009 (HH1, VV1, HV1 e VH1) e 26/09/2010 (HH3 e HV3), obtidas em períodos mais secos, tiveram melhores correlações com os atributos do solo. As análises dos semivariogramas dos resíduos da predição dos modelos RF demonstraram maior dependência espacial na camada de 60 a 80 cm. A abordagem da Krigagem somada ao modelo RF contribuíram para a melhoria da predição dos atributos areia, argila, CC e PMP. O uso de imagens de radar ALOS/PALSAR e atributos do terreno como covariáveis em modelos RFK mostrou potencial para estimar os atributos físicos (areia e argila) e físico-hídricos (CC e PMP), que podem auxiliar no mapeamento de solos associados aos materiais de origem da Formação Botucatu.

L’utilisation de la polarimétrie radar et de la décomposition de Touzi pour la caractérisation et la classification des physionomies végétales des milieux humides : le cas du Lac Saint-Pierre.

Les milieux humides remplissent plusieurs fonctions écologiques d’importance et contribuent à la biodiversité de la faune et de la flore. Même s’il existe une reconnaissance croissante sur l’importante de protéger ces milieux, il n’en demeure pas moins que leur intégrité est encore menacée par la pression des activités humaines. L’inventaire et le suivi systématique des milieux humides constituent une nécessité et la télédétection est le seul moyen réaliste d’atteindre ce but. L’objectif de cette thèse consiste à contribuer et à améliorer la caractérisation des milieux humides en utilisant des données satellites acquises par des radars polarimétriques en bande L (ALOS-PALSAR) et C (RADARSAT-2). Cette thèse se fonde sur deux hypothèses (chap. 1). La première hypothèse stipule que les classes de physionomies végétales, basées sur la structure des végétaux, sont plus appropriées que les classes d’espèces végétales car mieux adaptées au contenu informationnel des images radar polarimétriques. La seconde hypothèse stipule que les algorithmes de décompositions polarimétriques permettent une extraction optimale de l’information polarimétrique comparativement à une approche multipolarisée basée sur les canaux de polarisation HH, HV et VV (chap. 3). En particulier, l’apport de la décomposition incohérente de Touzi pour l’inventaire et le suivi de milieux humides est examiné en détail. Cette décomposition permet de caractériser le type de diffusion, la phase, l’orientation, la symétrie, le degré de polarisation et la puissance rétrodiffusée d’une cible à l’aide d’une série de paramètres extraits d’une analyse des vecteurs et des valeurs propres de la matrice de cohérence. La région du lac Saint-Pierre a été sélectionnée comme site d’étude étant donné la grande diversité de ses milieux humides qui y couvrent plus de 20 000 ha. L’un des défis posés par cette thèse consiste au fait qu’il n’existe pas de système standard énumérant l’ensemble possible des classes physionomiques ni d’indications précises quant à leurs caractéristiques et dimensions. Une grande attention a donc été portée à la création de ces classes par recoupement de sources de données diverses et plus de 50 espèces végétales ont été regroupées en 9 classes physionomiques (chap. 7, 8 et 9). Plusieurs analyses sont proposées pour valider les hypothèses de cette thèse (chap. 9). Des analyses de sensibilité par diffusiogramme sont utilisées pour étudier les caractéristiques et la dispersion des physionomies végétales dans différents espaces constitués de paramètres polarimétriques ou canaux de polarisation (chap. 10 et 12). Des séries temporelles d’images RADARSAT-2 sont utilisées pour approfondir la compréhension de l’évolution saisonnière des physionomies végétales (chap. 12). L’algorithme de la divergence transformée est utilisé pour quantifier la séparabilité entre les classes physionomiques et pour identifier le ou les paramètres ayant le plus contribué(s) à leur séparabilité (chap. 11 et 13). Des classifications sont aussi proposées et les résultats comparés à une carte existante des milieux humide du lac Saint-Pierre (14). Finalement, une analyse du potentiel des paramètres polarimétrique en bande C et L est proposé pour le suivi de l’hydrologie des tourbières (chap. 15 et 16). Les analyses de sensibilité montrent que les paramètres de la 1re composante, relatifs à la portion dominante (polarisée) du signal, sont suffisants pour une caractérisation générale des physionomies végétales. Les paramètres des 2e et 3e composantes sont cependant nécessaires pour obtenir de meilleures séparabilités entre les classes (chap. 11 et 13) et une meilleure discrimination entre milieux humides et milieux secs (chap. 14). Cette thèse montre qu’il est préférable de considérer individuellement les paramètres des 1re, 2e et 3e composantes plutôt que leur somme pondérée par leurs valeurs propres respectives (chap. 10 et 12). Cette thèse examine également la complémentarité entre les paramètres de structure et ceux relatifs à la puissance rétrodiffusée, souvent ignorée et normalisée par la plupart des décompositions polarimétriques. La dimension temporelle (saisonnière) est essentielle pour la caractérisation et la classification des physionomies végétales (chap. 12, 13 et 14). Des images acquises au printemps (avril et mai) sont nécessaires pour discriminer les milieux secs des milieux humides alors que des images acquises en été (juillet et août) sont nécessaires pour raffiner la classification des physionomies végétales. Un arbre hiérarchique de classification développé dans cette thèse constitue une synthèse des connaissances acquises (chap. 14). À l’aide d’un nombre relativement réduit de paramètres polarimétriques et de règles de décisions simples, il est possible d’identifier, entre autres, trois classes de bas marais et de discriminer avec succès les hauts marais herbacés des autres classes physionomiques sans avoir recours à des sources de données auxiliaires. Les résultats obtenus sont comparables à ceux provenant d’une classification supervisée utilisant deux images Landsat-5 avec une exactitude globale de 77.3% et 79.0% respectivement. Diverses classifications utilisant la machine à vecteurs de support (SVM) permettent de reproduire les résultats obtenus avec l’arbre hiérarchique de classification. L’exploitation d’une plus forte dimensionalitée par le SVM, avec une précision globale maximale de 79.1%, ne permet cependant pas d’obtenir des résultats significativement meilleurs. Finalement, la phase de la décomposition de Touzi apparaît être le seul paramètre (en bande L) sensible aux variations du niveau d’eau sous la surface des tourbières ouvertes (chap. 16). Ce paramètre offre donc un grand potentiel pour le suivi de l’hydrologie des tourbières comparativement à la différence de phase entre les canaux HH et VV. Cette thèse démontre que les paramètres de la décomposition de Touzi permettent une meilleure caractérisation, de meilleures séparabilités et de meilleures classifications des physionomies végétales des milieux humides que les canaux de polarisation HH, HV et VV. Le regroupement des espèces végétales en classes physionomiques est un concept valable. Mais certaines espèces végétales partageant une physionomie similaire, mais occupant un milieu différent (haut vs bas marais), ont cependant présenté des différences significatives quant aux propriétés de leur rétrodiffusion.

Metodologia de utilização de dados de sensoriamento remoto em zonas costeiras sob influência da indústria petrolífera

Oil spills in marine environments represent immediate environmental impacts of large magnitude. For that reason the Environmental Sensitivity to Oil Maps constitute a major instrument for planning actions of containment and cleanup. For both the Environmental Sensitivity Maps always need to be updated, to have an appropriate scale and to represent accurately the coastal areas. In this context, this thesis presents a methodology for collecting and processing remote sensing data for the purpose of updating the territorial basis of thematic maps of Environmental Sensitivity to Oil. To ensure greater applicability of the methodology, sensors with complementary characteristics, which provide their data at a low financial cost, were selected and tested. To test the methodology, an area located on the northern coast of the Northeast of Brazil was chosen. The results showed that the products of ASTER data and image hybrid sensor PALSAR + CCD and HRC + CCD, have a great potential to be used as a source of cartographic information on projects that seek to update the Environmental Sensitivity Maps of Oil

Atributos polarimétricos de imagem radar na inferência de parâmetros morfológicos de macrófitas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Geodetic and satellite derived ice surface velocities of Vestfonna ice cap

During 2007 we launched a geodetic campaign on the Svalbard ice cap Vestfonna in order to estimate the velocity field of the ice cap. This was done within the frame of the IPY project KINNVIKA. We present here the velocity measurements derived from our campaigns 2007-2010 and compare the geodetic measurements against InSAR velocity fields from satellite platforms from 1995/96 and 2008. We find the spatial distribution of ice speeds from the InSAR is in good agreement within the uncertainty limits with our geodetic measurements. We observe no clear indication of seasonal ice speed differences, but we find a speed-up of the outlet glacier Franklinbreen between the InSAR campaigns, and speculate the outlet is having a surge phase.

(Table 1) Accumulation and ice discharge of West Antarctic glaciers draining into the Amundsen Sea between 1974 and 2007

The Advanced Land Observation System (ALOS) Phased-Array Synthetic-Aperture Radar (PALSAR) is an L-band frequency (1.27 GHz) radar capable of continental-scale interferometric observations of ice sheet motion. Here, we show that PALSAR data yield excellent measurements of ice motion compared to C-band (5.6 GHz) radar data because of greater temporal coherence over snow and firn. We compare PALSAR velocities from year 2006 in Pine Island Bay, West Antarctica with those spanning years 1974 to 2007. Between 1996 and 2007, Pine Island Glacier sped up 42% and ungrounded over most of its ice plain. Smith Glacier accelerated 83% and ungrounded as well. Their largest speed up are recorded in 2007. Thwaites Glacier is not accelerating but widening with time and its eastern ice shelf doubled its speed. Total ice discharge from these glaciers increased 30% in 12 yr and the net mass loss increased 170% from 39 ± 15 Gt/yr to 105 ± 27 Gt/yr. Longer-term velocity changes suggest only a moderate loss in the 1970s. As the glaciers unground into the deeper, smoother beds inland, the mass loss from this region will grow considerably larger in years to come.

Surface velocity and mass balance of Livingston Island ice cap, Antarctica

The mass budget of the ice caps surrounding the Antarctica Peninsula and, in particular, the partitioning of its main components are poorly known. Here we approximate frontal ablation (i.e. the sum of mass losses by calving and submarine melt) and surface mass balance of the ice cap of Livingston Island, the second largest island in the South Shetland Islands archipelago, and analyse variations in surface velocity for the period 2007–2011. Velocities are obtained from feature tracking using 25 PALSAR-1 images, and used in conjunction with estimates of glacier ice thicknesses inferred from principles of glacier dynamics and ground-penetrating radar observations to estimate frontal ablation rates by a flux-gate approach. Glacier-wide surface mass-balance rates are approximated from in situ observations on two glaciers of the ice cap. Within the limitations of the large uncertainties mostly due to unknown ice thicknesses at the flux gates, we find that frontal ablation (−509 ± 263 Mt yr−1, equivalent to −0.73 ± 0.38 m w.e. yr−1 over the ice cap area of 697 km2) and surface ablation (−0.73 ± 0.10 m w.e. yr−1) contribute similar shares to total ablation (−1.46 ± 0.39 m w.e. yr−1). Total mass change (δM = −0.67 ± 0.40 m w.e. yr−1) is negative despite a slightly positive surface mass balance (0.06 ± 0.14 m w.e. yr−1). We find large interannual and, for some basins, pronounced seasonal variations in surface velocities at the flux gates, with higher velocities in summer than in winter. Associated variations in frontal ablation (of ~237 Mt yr−1; −0.34 m w.e. yr−1) highlight the importance of taking into account the seasonality in ice velocities when computing frontal ablation with a flux-gate approach.

Twenty-year advanced DInSAR analysis of severe land subsidence: The Alto Guadalentín Basin (Spain) case study

A twenty-year period of severe land subsidence evolution in the Alto Guadalentín Basin (southeast Spain) is monitored using multi-sensor SAR images, processed by advanced differential interferometric synthetic aperture radar (DInSAR) techniques. The SAR images used in this study consist of four datasets acquired by ERS-1/2, ENVISAT, ALOS and COSMO-SkyMed satellites between 1992 and 2012. The integration of ground surface displacement maps retrieved for different time periods allows us to quantify up to 2.50 m of cumulated displacements that occurred between 1992 and 2012 in the Alto Guadalentín Basin. DInSAR results were locally compared with global positioning system (GPS) data available for two continuous stations located in the study area, demonstrating the high consistency of local vertical motion measurements between the two different surveying techniques. An average absolute error of 4.6 ± 4 mm for the ALOS data and of 4.8 ± 3.5 mm for the COSMO-SkyMed data confirmed the reliability of the analysis. The spatial analysis of DInSAR ground surface displacement reveals a direct correlation with the thickness of the compressible alluvial deposits. Detected ground subsidence in the past 20 years is most likely a consequence of a 100–200 m groundwater level drop that has persisted since the 1970s due to the overexploitation of the Alto Guadalentín aquifer system. The negative gradient of the pore pressure is responsible for the extremely slow consolidation of a very thick (> 100 m) layer of fine-grained silt and clay layers with low vertical hydraulic permeability (approximately 50 mm/h) wherein the maximum settlement has still not been reached.

Application of multi-sensor advanced DInSAR analysis to severe land subsidence recognition: Alto Guadalentín Basin (Spain)

Multi-sensor advanced DInSAR analyses have been performed and compared with two GPS station measurements, in order to evaluate the land subsidence evolution in a 20-year period, in the Alto Guadalentín Basin where the highest rate of man-induced subsidence (> 10 cm yr−1) of Europe had been detected. The control mechanisms have been examined comparing the advanced DInSAR data with conditioning and triggering factors (i.e. isobaths of Plio-Quaternary deposits, soft soil thickness and piezometric level).