Évaluation de la biomasse et du stockage de carbone dans les plantations de Para rubber dans l'Est de la Thaïlande par l'utilisation de l'objet en fonction de la classification des données du satellite THAICHOTE

This study explored to the improve efficiency of measurements of carbon stock by remote sensing techniques on Para rubber (Hevea brasiliensis) plantations in East Thailand. Current methods of carbon stock estimations use classical pixel based classification on middle-resolution images and thus produce results with a large uncertainty. In this study, the method use very high resolution images from the THAICHOTE satellite, associated to field measurements to estimates the carbon stock and its evolution in the Mae num Prasae watershed. Using object based classifications, the plantations have been mapped and their age and girth have been estimated from a parametric model derived from spectral, textural, 3D information and field data. The results of this study show that these data can be used to map Para rubber plantation and distinguish age classes of trees in the plantations. The study propose that textural information is more useful than spectral information to capture tree canopy architecture and thus the age of the canopy. One spectral of Global Environment Monitoring (GEMI) and four textural information of Homogeneity, Dissimilarity, Contrast and Variance were used in the fit model (multiple linear regression R2=0.87) for estimating the Para rubber tree girth and age while the 3D information (canopy height model: CHM) was not appropriated to build the image classification information. Around 154 km2 of the 232 km2 of the studied area are covered by Para rubber plantations. The total amount of biomass and carbon stocks are 2.23 Megatons and 0.99 Megatons C respectively with uncertainty of 11%. In 2011, the total area sequestered 121 tCO2 by Para rubber plantations.Cette étude a été effectuée pour améliorer l'efficacité des mesures de stockage de carbone par des techniques de télédétection dans les plantations de Para rubber (Hevea brasiliensis) en Thaïlande. Les estimations des méthodes actuelles de stockage de carbone s’opèrent à l’aide de la classification classique basée sur le système des pixels basée sur des images de moyenne résolution et produit donc des résultats d’une grande incertitude. En revanche, dans cette étude, la méthode utilisée est basée sur des images de très haute résolution provenant du satellite THAICHOTE, associés à des mesures sur le terrain, dans le bassin de Mae num Prasae. L’utilisation de l'objet en fonction des classifications, les plantations cartographiées, leur âge et leur circonférence ont été estimées à partir d'un modèle paramétrique dérivé de données spectrales, de texture et 3D. L'étude propose une information de texture plus utile que l'information spectrale pour capturer l’architecture des arbres du couvert et donc l'âge de la canopée. Un spectrale de Global Environment Monitoring (GEMI) et quatre texturales de Homogeneity, Dissimilarity, Contrast et Variance ont été utilisées dans l'ajustement du modèle (régression R2 = 0,87) pour estimer la circonférence et l'âge des arbres tandis que le Canopy Height Model (CHM) de 3D n’était pas autorisée pour construire l'information de classement d'images. Environ 154 km2 des 232 km2 de la zone étudiée sont couverts par des plantations. La quantité totale de la biomasse et des stocks de carbone s’élève à 2,23 mégatonnes et 0,99 mégatonnes C, respectivement avec une incertitude de 11%. En 2011, la superficie totale séquestrée était de 121 tCO2 par des plantations

Assessments of Nipa Forest Using Landsat Imagery Enhanced with Unmanned Aerial Vehicle Photography

Nipa palms are exposed by the transformation of land use and land cover changes (LULCC) due to changes to aquaculture and orchards. Modern remote sensing for environmental monitoring of LULCC has been made easier by the use of high spatial resolution images, innovative image processing and Geographic Information Systems (GIS). The expense of high-resolution satellite imagery has resulted in investigators moving to open sources (e.g., Landsat), therefore, the interpretation of images at a medium resolution can be classified simply as LULCC classes and are constrained by the detection of small-scale disturbances. This research applied Landsat imagery with very high-resolution imagery from Unmanned Aerial Vehicles (UAVs). In order to be useful for real-world applications, the accuracy of remote sensing data must be validated using proven ground-based methods. UAVs equipped with multispectral sensors were flown over the Nipa palms at the Prasae River, Rayong Province, Thailand. The main advantage of UAV-based remote sensing is that it reduces costs and immediate availability of high-resolution data. The UAV imagery was expensed as “drone truthing data” to train image classification algorithms. These results show that UAV data can be used effectively to support and categorize similar land-cover/use classes (aquaculture vs. mangrove forest vs. nipa forest) with consistently high identification of over 87.6% on the generated thematic map, where the mangrove forest detection rate was as high as 86%. For that reason, UAVs are engaged successively in management and conservation tasks, which can be used for regional or local scale studies to compare the achieved accuracy to a general regional land cover map. This approach can be used for the variability of plants to rectify land-cover classification. Therefore, UAV images are a very useful tool to fill the gap between remote sensing information and expensive ground field campaigns

Limiting the risk inherent to geological CO2 storage: The importance of predicting inorganic and organic chemical species behavior under supercritical CO2 fluid conditions

International audienceField tests have clearly demonstrated that injecting CO2 in geological storage sites results in the release of heavy metals and organic species to groundwater, implying that CO2 injection may have potentially dramatic consequences for the environment. Numerous laboratory experiments using rock and cement samples from different geological formations typical of injection sites show that rocks reacting with synthetic or natural fluids and supercritical CO2 at their respective temperature and pressure conditions generate fluids with As, Cr, Cu, Cd, Pb, Fe, and Mn concentrations above Environmental Protection Agency drinking water standards. The solubility of a compound in supercritical-CO2 (sc-CO2), expressed in terms of the compound's activity or fugacity, also depends on the composition of the phases present at the pressure and temperature of the storage site. In a brine sc-CO2 system, estimating the activity of an inorganic compound or the fugacity of an organic compound is a prerequisite to predicting the solubility of a compound in sc-CO2 phases. Available models (e.g. Pitzer equations) require the use of binary salt concentrations and are best applicable to polar ionic compounds; but the effect of brines on larger hydrocarbons has not yet been explored. New experimental data will be needed to determine the magnitude of pH effects on the partitioning behavior of organic acids and trace metal complexes from brine to sc-CO2

Estimation of biomass and carbon stock in Para rubber plantations using object-based classification from Thaichote satellite data in Eastern Thailand

International audienceThis paper deals with the efficiency of measurements of carbon stock by remote sensing techniques on Para rubber plantations in Thailand. These plantations could play an important role in carbon budget and thus are part of the Clean Development Mechanism of the Kyoto Protocol. Current methods of carbon stock estimations use middle resolution images and produce results with a large uncertainty. We use very high resolution images from the Thaichote satellite, associated with field measurements to estimate the carbon stock and its evolution in the Mae num Prasae watershed, Eastern Thailand. Using object-based classifications, the plantations have been mapped and their age has been estimated from a parametric model derived from both spectral and textural information and field data. The total biomass and carbon stocked are 2.23 and 0.99 Megaton with an uncertainty of 11%. One hundred and twenty one tons of carbon are sequestered annually in the Para rubber plantations of the studied area