Confronto tra tecniche di remote sensing per la caratterizzazione di un ammasso roccioso presso le Gole di Scascoli, Loiano (BO)

Il versante sinistro delle Gole di Scascoli (BO) è caratterizzato da una marcata tendenza evolutiva per crollo e ribaltamento. Negli ultimi 25 anni si sono verificati eventi parossistici con volumi di roccia coinvolti rispettivamente di 7000 m3, 20000 m3 e 35000 m3. Il sito è di grande rilevanza a causa del forte fattore di rischio rappresentato per la strada di fondovalle ad esso adiacente. Il lavoro di tesi è stato finalizzato allo studio dei fenomeni di versante di una parete rocciosa inaccessibile nota in letteratura come “ex-Mammellone 1” mediante tecniche di telerilevamento quali TLS (Terrestrial Laser Scanning) e CRP (Close Range Photogrammetry) al fine affiancare il rilievo geomeccanico soggettivo dell’area svolto nel 2003 da ENSER Srl in seguito ai fenomeni di crollo del 2002. Lo sviluppo di tecnologie e metodi innovativi per l’analisi territoriale basata sull’impiego di UAV (Unmanned Aerial Vehicle, meglio noti come Droni), associata alle tecniche di fotogrammetria digitale costituisce un elemento di notevole ausilio nelle pratiche di rilevamento in campo di sicurezza e tempi di esecuzione. Il lavoro ha previsto una prima fase di rilevamento areo-fotogrammetrico mediante strumentazione professionale e amatoriale, a cui è seguita l’elaborazione dei rispettivi modelli. I diversi output sono stati confrontati dal punto di vista geomorfologico, geometrico, geomeccanico e di modellazione numerica di caduta massi. Dal lavoro è stato possibile indagare l’evoluzione morfologica del sito in esame negli ultimi 10 anni, confrontare diversi metodi di rilevamento e analisi dati, sperimentare la robustezza e ripetibilità geometrica del metodo fotogrammetrico per il rilievo di fronti rocciosi e mettere a punto un metodo semiautomatico di individuazione e analisi delle giaciture delle discontinuità.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.

Antibacterial and cytotoxic properties of isoprenoids from the red sea soft coral, Lobophytum sp

Purpose: To evaluate the antibacterial and cytotoxic activities of the secondary metabolites of Lobophytum sp. Methods: Maceration with methanol: chloroform (1:1) was applied to extract the coral material. Chromatographic and spectroscopic techniques were employed for fractionation, isolation and elucidation of pure compounds. Antibacterial activities were performed by well diffusion method against three Gram-positive and four Gram-negative bacteria. Brine shrimp lethality test was employed to predict toxicity, while antitumor activity were tested by 3-(4, 5-dimethylthiazol-2-yl)-2, 5- diphenyltetrazolium bromide (MTT) method against Ehrlich carcinoma cells. Results: Four sesquiterpenes, one cembranoid type diterpenes and two steroids were isolated. 1 exhibited significant antibacterial activity against four tested bacteria (P. aeruginosa, S. aureus, S. epidermis, and S. pneumonia) with MIC value of 15 μg/mL. Moreover, 1 showed high diameter zone of inhibition ranging from 16 - 18 mm against test bacteria. Compounds 4 and 5 displayed moderate antibacterial activity against all test bacteria with inhibition zone diameter (IZD) ranging from 11 – 15 mm and MIC values of 30 μg/mL. 2, 3, 6 and 7 exhibited weak antibacterial activity (IZD, 7 - 11 mm; MIC ≥ 30 μg/mL). In addition, only diterpene compound (4) showed high toxicity against A. Salina and antitumor activity against Erhlich carcinoma cells with the LD50 of 25 and 50 μg/mL, respectively. Conclusion: This study reveals the strong antibacterial activity of sesquiterpene alismol (1) and the potential antibacterial and antitumor activity of cembranoid type diterpene, cembrene A (4).

A COMPARISON OF PIXEL-BASED VERSUS OBJECT ORIENTED ANALYSIS OF LANDSLIDES USING HISTORICAL REMOTE SENSING DATA

With recent advances in remote sensing processing technology, it has become more feasible to begin analysis of the enormous historic archive of remotely sensed data. This historical data provides valuable information on a wide variety of topics which can influence the lives of millions of people if processed correctly and in a timely manner. One such field of benefit is that of landslide mapping and inventory. This data provides a historical reference to those who live near high risk areas so future disasters may be avoided. In order to properly map landslides remotely, an optimum method must first be determined. Historically, mapping has been attempted using pixel based methods such as unsupervised and supervised classification. These methods are limited by their ability to only characterize an image spectrally based on single pixel values. This creates a result prone to false positives and often without meaningful objects created. Recently, several reliable methods of Object Oriented Analysis (OOA) have been developed which utilize a full range of spectral, spatial, textural, and contextual parameters to delineate regions of interest. A comparison of these two methods on a historical dataset of the landslide affected city of San Juan La Laguna, Guatemala has proven the benefits of OOA methods over those of unsupervised classification. Overall accuracies of 96.5% and 94.3% and F-score of 84.3% and 77.9% were achieved for OOA and unsupervised classification methods respectively. The greater difference in F-score is a result of the low precision values of unsupervised classification caused by poor false positive removal, the greatest shortcoming of this method.

A REMOTE SENSING APPROACH TO CHARACTERIZE THE HYDROGEOLOGY OF MOUNTAINOUS AREAS: APPLICATION TO THE QUITO AQUIFER SYSTEM (QAS), ECUADOR

Climate change, intensive use, and population growth are threatening the availability of water resources. New sources of water, better knowledge of existing ones, and improved water management strategies are of paramount importance. Ground water is often considered as primary water source due to its advantages in terms of quantity, spatial distribution, and natural quality. Remote sensing techniques afford scientists a unique opportunity to characterize landscapes in order to assess groundwater resources, particularly in tectonically influenced areas. Aquifers in volcanic basins are considered the most productive aquifers in Latin America. Although topography is considered the primary driving force for groundwater flows in mountainous terrains, tectonic activity increases the complexity of these groundwater systems by altering the integrity of sedimentary rock units and the overlying drainage networks. Structural controls affect the primary hydraulic properties of the rock formations by developing barriers to flow in some cases and zones of preferential infiltration and subterranean in others. The study area focuses on the Quito Aquifer System (QAS) in Ecuador. The characterization of the hydrogeology started with a lineament analysis based on a combined remote sensing and digital terrain analysis approach. The application of classical tools for regional hydrogeological evaluation and shallow geophysical methods were useful to evaluate the impact of faulting and fracturing on the aquifer system. Given the spatial extension of the area and the complexity of the system, two levels of analysis were applied in this study. At the regional level, a lineament map was created for the QAS. Relationships between fractures, faults and lineaments and the configuration of the groundwater flow on the QAS were determined. At the local level, on the Plateaus region of the QAS, a detailed lineament map was obtained by using high-spatial-resolution satellite imagery and aspect map derived from a digital elevation model (DEM). This map was complemented by the analysis of morphotectonic indicators and shallow geophysics that characterize fracture patterns. The development of the groundwater flow system was studied, drawing upon data pertaining to the aquifer system physical characteristics and topography. Hydrochemistry was used to ascertain the groundwater evolution and verify the correspondence of the flow patterns proposed in the flow system analysis. Isotopic analysis was employed to verify the origin of groundwater. The results of this study show that tectonism plays a very important role for the hydrology of the QAS. The results also demonstrate that faults influence a great deal of the topographic characteristics of the QAS and subsequently the configuration of the groundwater flow. Moreover, for the Plateaus region, the results demonstrate that the aquifer flow systems are affected by secondary porosity. This is a new conceptualization of the functioning of the aquifers on the QAS that will significantly contribute to the development of better strategies for the management of this important water resource.

Assessing the impact of agricultural drought on maize prices in Kenya with the approach of the SPOT-VEGETATION NDVI remote sensing

The high cost of maize in Kenya is basically driven by East African regional commodity demand forces and agricultural drought. The production of maize, which is a common staple food in Kenya, is greatly affected by agricultural drought. However, calculations of drought risk and impact on maize production in Kenya is limited by the scarcity of reliable rainfall data. The objective of this study was to apply a novel hyperspectral remote sensing method to modelling temporal fluctuations of maize production and prices in five markets in Kenya. SPOT-VEGETATION NDVI time series were corrected for seasonal effects by computing the standardized NDVI anomalies. The maize residual price time series was further related to the NDVI seasonal anomalies using a multiple linear regression modelling approach. The result shows a moderately strong positive relationship (0.67) between residual price series and global maize prices. Maize prices were high during drought periods (i.e. negative NDVI anomalies) and low during wet seasons (i.e. positive NDVI anomalies). This study concludes that NDVI is a good index for monitoring the evolution of maize prices and food security emergency planning in Kenya. To obtain a very strong correlation for the relationship between the wholesale maize price and the global maize price, future research could consider adding other price-driving factors into the regression models.

Species and size selectivity in a 'red' sea bream longline 'metier' in the Algarve (southern Portugal)

A longline 'metier' using small hooks for 'red' sea breams (Pagellus acarne and Pagellus erythrinus) in the Algarve (south of Portugal) was studied. Experimental longlining was carried out with three sizes of "Mustad" round bend, flatted, spade end Quality 2316 DT hooks (numbers 11, 13 and 15) and two types of bait: razor shell (Ensis siliqua) and mud shrimp (Upogebia pusilla). A total of 3 328 fish and at least 36 species were caught with 33 600 hooks fished in 28 longline sets. Five species of sea breams (Sparidae) accounted for 79% of the catch: Pagellus acarne, Pagellus erythrinus, Diplodus vulgaris, Spondyliosoma cantharus, and Boops boops. High catch rates of 20-30 fish per 100 hooks were made in a number of 1 200 hook longline sets, with total catch weights of 40 to more than 60 kg per set. In general, the smallest hook (number 15) had the highest catch rate. Bait type did not significantly affect the catch size distributions. Although more fish were caught with the razor shell bait, higher catch rates of 'red' sea breams were obtained with mud shrimp. Catch rates were also affected by the location of the fishing grounds and the time of the set, with the highest catch rates obtained when the longline was set within two hours before sunrise. A wide size range was caught for each species, with highly overlapped catch size frequency distributions for the three hook sizes used. Except for Spondyliosoma cantharus, few illegal-sized fish were caught, even with the smallest hook. The logistic model fitted by maximum likelihood was used to describe hook selectivity for Diplodus vulgaris, Pagellus acarne, Pagellus erythrinus, and Spondyliosoma cantharus. (C) Ifremer-Elsevier, Paris.

Irrigation management with remote sensing: Evaluating irrigation requirement for maize under Mediterranean climate condition

tWater use control methods and water resources planning are of high priority. In irrigated agriculture, theright way to save water is to increase water use efficiency through better management. The present workvalidates procedures and methodologies using remote sensing to determine the water availability in thesoil at each moment, giving the opportunity for the application of the water depth strictly necessaryto optimise crop growth (optimum irrigation timing and irrigation amount). The analysis is applied tothe Irrigation District of Divor, Évora, using 7 experimental plots, which are areas irrigated by centre-pivot systems, cultivated to maize. Data were determined from images of the cultivated surface obtainedby satellite and integrated with atmosphere and crop parameters to calculate biophysical indicatorsand indices of water stress in the vegetation—Normalized Difference Vegetation Index (NDVI), Kc, andKcb. Therefore, evapotranspiration (ETc) was estimated and used to calculate crop water requirement,together with the opportunity and the amount of irrigation water to allocate. Although remote sensingdata available from satellite imagery presented some practical constraints, the study could contribute tothe validation of a new methodology that can be used for irrigation management of a large irrigated area,easier and at lower costs than the traditional FAO recommended crop coefficients method. The remotesensing based methodology can also contribute to significant saves of irrigation water.

Assessing the role of Mediterranean evergreen oaks canopy cover in land surface albedo and temperature using a remote sensing-based approach

Modifications in vegetation cover can have an impact on the climate through changes in biogeochemical and biogeophysical processes. In this paper, the tree canopy cover percentage of a savannah-like ecosystem (montado/dehesa) was estimated at Landsat pixel level for 2011, and the role of different canopy cover percentages on land surface albedo (LSA) and land surface temperature (LST) were analysed. A modelling procedure using a SGB machine-learning algorithm and Landsat 5-TM spectral bands and derived vegetation indices as explanatory variables, showed that the estimation of montado canopy cover was obtained with good agreement (R2 = 78.4%). Overall, montado canopy cover estimations showed that low canopy cover class (MT_1) is the most representative with 50.63% of total montado area. MODIS LSA and LST products were used to investigate the magnitude of differences in mean annual LSA and LST values between contrasting montado canopy cover percentages. As a result, it was found a significant statistical relationship between montado canopy cover percentage and mean annual surface albedo (R2 = 0.866, p < 0.001) and surface temperature (R2 = 0.942, p < 0.001). The comparisons between the four contrasting montado canopy cover classes showed marked differences in LSA (χ2 = 192.17, df = 3, p < 0.001) and LST (χ2 = 318.18, df = 3, p < 0.001). The highest montado canopy cover percentage (MT_4) generally had lower albedo than lowest canopy cover class, presenting a difference of −11.2% in mean annual albedo values. It was also showed that MT_4 and MT_3 are the cooler canopy cover classes, and MT_2 and MT_1 the warmer, where MT_1 class had a difference of 3.42 °C compared with MT_4 class. Overall, this research highlighted the role that potential changes in montado canopy cover may play in local land surface albedo and temperature variations, as an increase in these two biogeophysical parameters may potentially bring about, in the long term, local/regional climatic changes moving towards greater aridity.

Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Avaliação ambiental de manguezais adjacentes aos campos petrolíferos de Macau e Serra (RN), como subsídio às medidas mitigadoras ao processo erosivo

Among the various effects caused by the climate change and human intervention, the mangrove ecosystem changes through of the years has been worth mentioning, which hasn t known which are the pros and cons for the adjacent coastal and estuarine environments yet. It happens due to the present dynamism in these areas, besides of the difficult understanding of the processes associated with evolution. This study aimed to environmentally evaluate adjacent mangroves from the Macau and Serra oil fields, located on Rio Grande do Norte northern coast, to support the mitigating actions related to the containment of the erosive process, as well as, according to the principles of the Clean Development Mechanism (CDM), to assess the amount of atmospheric carbon sequestered by the studied ecosystem. An inventory was conducted through mangrouve mapping which has supplied this research, especially regarding to the structural characterization of mangrove areas. To understand the local mangrove behavior in a greater level detail, techniques of remote sensing, GIS and GPS were used to make an analogy between the current and past states of the mangrove studied, allowing to make anticipated projections for the future impacts or changes in that region. This study combined data from multispectral LANDSAT 5 TM, Landsat 7 ETM+ with radar microwave data from SAR RADARSAT-1, which increased the interpretation capacity of the data from optical sensor systems. The interpretations have been supported by the data field, representing a better and innovative methodology for the environmental and taxonomic characterization of mangrove forests considered. The results reveal that mangroves of the Ponta do Tubarão Sustainable Development Reserve are biologically representative areas and providing a variety of benefits, especially for local communities, constituting the priority sites for actions development aimed at conservation. They also have been showing the necessity to make mitigating measures in order to recover degraded areas through reforestation or creating new areas of mangrove, as currently 7.1% of the mangrove forests studied are dead or in an advanced state of decomposition. The amount of atmospheric carbon sequestered proved very significant when analyzed for the whole area, which is able to sequester atmospheric 4,294,458 Ton CO2 per year

Aplicação de geotecnologias e do modelo EUPS como subsídio ao planejamento do uso da terra: estudo de caso no alto curso da microbacia hidrográfica do Ribeirão Cachoeirinha, Iracemápolis, SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Diagnóstico de conflitos em áreas de preservação permanente na bacia do Rio Capivara - Botucatu (SP)

The permanent preservation areas (PPA) established by Brazilian law are there to protect the natural environment. With the expansion of space occupied by man and development of economic activities in these areas were engaged in conflicts characterized PPA, where the use is other than the natural vegetation. According to these paradigms work aims to raise these conflict areas in the River Basin Capivara, Botucatu (SP) with the help of GIS Ilwis 3.4, topographic maps of IBGE and satellite images CBERS 2B. The map was generated from PPA in the GIS by distance calculation in relation to drainage, springs and break line on Cuesta de Botucatu. The classes of land use and natural vegetation were determined by interpretation of satellite images and field visits to check their veracity. With the cutting of the map of land use and natural vegetation in relation to PPA unit it was determined that the total 44,63% PPA is in conflict occupied by pasture, forest plantation, orange, annual crops, farms and irrigated rice project in lowland. This diagnostic characterizes the degradation of the environment and highlights the need to harmonize the economic and urban development with the preservation of the environment to ensure sustainability of the region.