929 resultados para Satellite images
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Pós-graduação em Geografia - IGCE
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Pós-graduação em Geografia - IGCE
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Submesoscale activity over the Argentinian shelf is investigated by means of high resolution primitive equation numerical solutions. These reveal energetic turbulent activity (visually similar to the one occasionally seen in satellite images) at scales O(5 km) in fall and winter that is linked to mixed layer baroclinic instability. The air-sea heat flux responsible for (i) deepening the upper ocean boundary layer (at these seasons) and (ii) maintaining a cross-shelf background density gradient is the key environmental parameter controlling submesoscale activity. Implications of submesoscale turbulence are investigated. Its mixing efficiency estimated by computing a diffusivity coefficient is above 30 m(2) s(-1) away from the shallowest regions. Aggregation of surface buoyant material by submesoscale currents occurs within hours and is presumably important to the ecosystem.
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The Restinga of Marambaia is an emerged sand bar located between the Sepetiba Bay and the South Atlantic Ocean, on the south-east coast of Brazil. The objective of this study was to observe the geomorphologic evolution of the coastal zone of the Restinga of Marambaia using multitemporal satellite images acquired by multisensors from 1975 to 2004. The images were digitally segmented by a region growth algorithm and submitted to an unsupervised classification procedure (ISOSEG) followed by a raster edit based on visual interpretation. The image time-series showed a general trend of decrease in the total sand bar area with values varying from 80.61km(2) in 1975 to 78.15km(2) in 2004. The total area calculation based on the 1975 and 1978 Landsat MSS data was shown to be super-estimated in relation to the Landsat TM, Landsat ETM+, and CBERS-2 CCD data. These differences can also be associated to the relatively poorer spatial resolution of the MSS data, nominally 79m, against the 20m of the CCD data and 30m of the TM and ETM+ data. For the estimates of the width in the central portion of the sand bar the variation was from 158m (1975) to 100m (2004). The formation of a spit in the northern region of the study area was visually observed. The area of the spit was estimated, with values varying from 0.82km(2) (1975) to 0.55km(2) (2004).
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Site-specific agriculture has been adopted in a high-tech context using, for instance, in situ sensors, satellite images for remote sensing analysis, and some other technological devices. However, farmers and smallholders without the economic resources and required knowledge to use and to access the latest technology seem to find an impediment to precision agricultural practices. This article discusses the possibility of adopting precision agriculture (PA) principles for site-specific management but in a low technology context for such farmers. The proposed methodology to support PA combines low technology dependency and a participatory approach by involving smallholders, farmers and experts. The case studies demonstrate how the interplay of low technology and a participative approach may be suitable for smallholders for site-specific agriculture analysis.
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The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.
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Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international market places. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.
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Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.
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En el presente estudio, una serie de pares de imágenes consecutivas del sensor Advance Very High Resolution Radiometer separadas entre si 24 horas son utilizadas con el objetivo de deducir velocidades de flujo superficial en el área del afloramiento del NW de África. El método utilizado es el método de las correlaciones cruzadas bidimensionales entre imágenes de satélite sucesivas, que representan el movimiento de las estructuras observadas. Los resultados de aplicar este método son analizados y discutidos. ABSTRACT In this study, some pairs of consecutive satellite images from the Advance Very High Resolution Radiometer (AVHRR) with a time separation of 24 hours are used in order to derive the sea surface flow velocities in the Northwest African up welling area. The method used is the Maximum Cross Correlation Method (MCC), and it consists in locate the maxima of bidimensional cross correlations between consecutive images. That maxima represent the movement of the observed features. The results are analyzed and discussed
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Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.
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CAPITOLO 1 INTRODUZIONE Il lavoro presentato è relativo all’utilizzo a fini metrici di immagini satellitari storiche a geometria panoramica; in particolare sono state elaborate immagini satellitari acquisite dalla piattaforma statunitense CORONA, progettata ed impiegata essenzialmente a scopi militari tra gli anni ’60 e ’70 del secolo scorso, e recentemente soggette ad una declassificazione che ne ha consentito l’accesso anche a scopi ed utenti non militari. Il tema del recupero di immagini aeree e satellitari del passato è di grande interesse per un ampio spettro di applicazioni sul territorio, dall’analisi dello sviluppo urbano o in ambito regionale fino ad indagini specifiche locali relative a siti di interesse archeologico, industriale, ambientale. Esiste infatti un grandissimo patrimonio informativo che potrebbe colmare le lacune della documentazione cartografica, di per sé, per ovvi motivi tecnici ed economici, limitata a rappresentare l’evoluzione territoriale in modo asincrono e sporadico, e con “forzature” e limitazioni nel contenuto informativo legate agli scopi ed alle modalità di rappresentazione delle carte nel corso del tempo e per diversi tipi di applicazioni. L’immagine di tipo fotografico offre una rappresentazione completa, ancorché non soggettiva, dell’esistente e può complementare molto efficacemente il dato cartografico o farne le veci laddove questo non esista. La maggior parte del patrimonio di immagini storiche è certamente legata a voli fotogrammetrici che, a partire dai primi decenni del ‘900, hanno interessato vaste aree dei paesi più avanzati, o regioni di interesse a fini bellici. Accanto a queste, ed ovviamente su periodi più vicini a noi, si collocano le immagini acquisite da piattaforma satellitare, tra le quali rivestono un grande interesse quelle realizzate a scopo di spionaggio militare, essendo ad alta risoluzione geometrica e di ottimo dettaglio. Purtroppo, questo ricco patrimonio è ancora oggi in gran parte inaccessibile, anche se recentemente sono state avviate iniziative per permetterne l’accesso a fini civili, in considerazione anche dell’obsolescenza del dato e della disponibilità di altre e migliori fonti di informazione che il moderno telerilevamento ci propone. L’impiego di immagini storiche, siano esse aeree o satellitari, è nella gran parte dei casi di carattere qualitativo, inteso ad investigare sulla presenza o assenza di oggetti o fenomeni, e di rado assume un carattere metrico ed oggettivo, che richiederebbe tra l’altro la conoscenza di dati tecnici (per esempio il certificato di calibrazione nel caso delle camere aerofotogrammetriche) che sono andati perduti o sono inaccessibili. Va ricordato anche che i mezzi di presa dell’epoca erano spesso soggetti a fenomeni di distorsione ottica o altro tipo di degrado delle immagini che ne rendevano difficile un uso metrico. D’altra parte, un utilizzo metrico di queste immagini consentirebbe di conferire all’analisi del territorio e delle modifiche in esso intercorse anche un significato oggettivo che sarebbe essenziale per diversi scopi: per esempio, per potere effettuare misure su oggetti non più esistenti o per potere confrontare con precisione o co-registrare le immagini storiche con quelle attuali opportunamente georeferenziate. Il caso delle immagini Corona è molto interessante, per una serie di specificità che esse presentano: in primo luogo esse associano ad una alta risoluzione (dimensione del pixel a terra fino a 1.80 metri) una ampia copertura a terra (i fotogrammi di alcune missioni coprono strisce lunghe fino a 250 chilometri). Queste due caratteristiche “derivano” dal principio adottato in fase di acquisizione delle immagini stesse, vale a dire la geometria panoramica scelta appunto perché l’unica che consente di associare le due caratteristiche predette e quindi molto indicata ai fini spionaggio. Inoltre, data la numerosità e la frequenza delle missioni all’interno dell’omonimo programma, le serie storiche di questi fotogrammi permettono una ricostruzione “ricca” e “minuziosa” degli assetti territoriali pregressi, data appunto la maggior quantità di informazioni e l’imparzialità associabili ai prodotti fotografici. Va precisato sin dall’inizio come queste immagini, seppur rappresentino una risorsa “storica” notevole (sono datate fra il 1959 ed il 1972 e coprono regioni moto ampie e di grandissimo interesse per analisi territoriali), siano state molto raramente impiegate a scopi metrici. Ciò è probabilmente imputabile al fatto che il loro trattamento a fini metrici non è affatto semplice per tutta una serie di motivi che saranno evidenziati nei capitoli successivi. La sperimentazione condotta nell’ambito della tesi ha avuto due obiettivi primari, uno generale ed uno più particolare: da un lato il tentativo di valutare in senso lato le potenzialità dell’enorme patrimonio rappresentato da tali immagini (reperibili ad un costo basso in confronto a prodotti simili) e dall’altro l’opportunità di indagare la situazione territoriale locale per una zona della Turchia sud orientale (intorno al sito archeologico di Tilmen Höyük) sulla quale è attivo un progetto condotto dall’Università di Bologna (responsabile scientifico il Prof. Nicolò Marchetti del Dipartimento di Archeologia), a cui il DISTART collabora attivamente dal 2005. L’attività è condotta in collaborazione con l’Università di Istanbul ed il Museo Archeologico di Gaziantep. Questo lavoro si inserisce, inoltre, in un’ottica più ampia di quelle esposta, dello studio cioè a carattere regionale della zona in cui si trovano gli scavi archeologici di Tilmen Höyük; la disponibilità di immagini multitemporali su un ampio intervallo temporale, nonché di tipo multi sensore, con dati multispettrali, doterebbe questo studio di strumenti di conoscenza di altissimo interesse per la caratterizzazione dei cambiamenti intercorsi. Per quanto riguarda l’aspetto più generale, mettere a punto una procedura per il trattamento metrico delle immagini CORONA può rivelarsi utile all’intera comunità che ruota attorno al “mondo” dei GIS e del telerilevamento; come prima ricordato tali immagini (che coprono una superficie di quasi due milioni di chilometri quadrati) rappresentano un patrimonio storico fotografico immenso che potrebbe (e dovrebbe) essere utilizzato sia a scopi archeologici, sia come supporto per lo studio, in ambiente GIS, delle dinamiche territoriali di sviluppo di quelle zone in cui sono scarse o addirittura assenti immagini satellitari dati cartografici pregressi. Il lavoro è stato suddiviso in 6 capitoli, di cui il presente costituisce il primo. Il secondo capitolo è stato dedicato alla descrizione sommaria del progetto spaziale CORONA (progetto statunitense condotto a scopo di fotoricognizione del territorio dell’ex Unione Sovietica e delle aree Mediorientali politicamente correlate ad essa); in questa fase vengono riportate notizie in merito alla nascita e all’evoluzione di tale programma, vengono descritti piuttosto dettagliatamente gli aspetti concernenti le ottiche impiegate e le modalità di acquisizione delle immagini, vengono riportati tutti i riferimenti (storici e non) utili a chi volesse approfondire la conoscenza di questo straordinario programma spaziale. Nel terzo capitolo viene presentata una breve discussione in merito alle immagini panoramiche in generale, vale a dire le modalità di acquisizione, gli aspetti geometrici e prospettici alla base del principio panoramico, i pregi ed i difetti di questo tipo di immagini. Vengono inoltre presentati i diversi metodi rintracciabili in bibliografia per la correzione delle immagini panoramiche e quelli impiegati dai diversi autori (pochi per la verità) che hanno scelto di conferire un significato metrico (quindi quantitativo e non solo qualitativo come è accaduto per lungo tempo) alle immagini CORONA. Il quarto capitolo rappresenta una breve descrizione del sito archeologico di Tilmen Höyuk; collocazione geografica, cronologia delle varie campagne di studio che l’hanno riguardato, monumenti e suppellettili rinvenute nell’area e che hanno reso possibili una ricostruzione virtuale dell’aspetto originario della città ed una più profonda comprensione della situazione delle capitali del Mediterraneo durante il periodo del Bronzo Medio. Il quinto capitolo è dedicato allo “scopo” principe del lavoro affrontato, vale a dire la generazione dell’ortofotomosaico relativo alla zona di cui sopra. Dopo un’introduzione teorica in merito alla produzione di questo tipo di prodotto (procedure e trasformazioni utilizzabili, metodi di interpolazione dei pixel, qualità del DEM utilizzato), vengono presentati e commentati i risultati ottenuti, cercando di evidenziare le correlazioni fra gli stessi e le problematiche di diversa natura incontrate nella redazione di questo lavoro di tesi. Nel sesto ed ultimo capitolo sono contenute le conclusioni in merito al lavoro in questa sede presentato. Nell’appendice A vengono riportate le tabelle dei punti di controllo utilizzati in fase di orientamento esterno dei fotogrammi.
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Images of a scene, static or dynamic, are generally acquired at different epochs from different viewpoints. They potentially gather information about the whole scene and its relative motion with respect to the acquisition device. Data from different (in the spatial or temporal domain) visual sources can be fused together to provide a unique consistent representation of the whole scene, even recovering the third dimension, permitting a more complete understanding of the scene content. Moreover, the pose of the acquisition device can be achieved by estimating the relative motion parameters linking different views, thus providing localization information for automatic guidance purposes. Image registration is based on the use of pattern recognition techniques to match among corresponding parts of different views of the acquired scene. Depending on hypotheses or prior information about the sensor model, the motion model and/or the scene model, this information can be used to estimate global or local geometrical mapping functions between different images or different parts of them. These mapping functions contain relative motion parameters between the scene and the sensor(s) and can be used to integrate accordingly informations coming from the different sources to build a wider or even augmented representation of the scene. Accordingly, for their scene reconstruction and pose estimation capabilities, nowadays image registration techniques from multiple views are increasingly stirring up the interest of the scientific and industrial community. Depending on the applicative domain, accuracy, robustness, and computational payload of the algorithms represent important issues to be addressed and generally a trade-off among them has to be reached. Moreover, on-line performance is desirable in order to guarantee the direct interaction of the vision device with human actors or control systems. This thesis follows a general research approach to cope with these issues, almost independently from the scene content, under the constraint of rigid motions. This approach has been motivated by the portability to very different domains as a very desirable property to achieve. A general image registration approach suitable for on-line applications has been devised and assessed through two challenging case studies in different applicative domains. The first case study regards scene reconstruction through on-line mosaicing of optical microscopy cell images acquired with non automated equipment, while moving manually the microscope holder. By registering the images the field of view of the microscope can be widened, preserving the resolution while reconstructing the whole cell culture and permitting the microscopist to interactively explore the cell culture. In the second case study, the registration of terrestrial satellite images acquired by a camera integral with the satellite is utilized to estimate its three-dimensional orientation from visual data, for automatic guidance purposes. Critical aspects of these applications are emphasized and the choices adopted are motivated accordingly. Results are discussed in view of promising future developments.
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Throughout the alpine domain, shallow landslides represent a serious geologic hazard, often causing severe damages to infrastructures, private properties, natural resources and in the most catastrophic events, threatening human lives. Landslides are a major factor of landscape evolution in mountainous and hilly regions and represent a critical issue for mountainous land management, since they cause loss of pastoral lands. In several alpine contexts, shallow landsliding distribution is strictly connected to the presence and condition of vegetation on the slopes. With the aid of high-resolution satellite images, it's possible to divide automatically the mountainous territory in land cover classes, which contribute with different magnitude to the stability of the slopes. The aim of this research is to combine EO (Earth Observation) land cover maps with ground-based measurements of the land cover properties. In order to achieve this goal, a new procedure has been developed to automatically detect grass mantle degradation patterns from satellite images. Moreover, innovative surveying techniques and instruments are tested to measure in situ the shear strength of grass mantle and the geomechanical and geotechnical properties of these alpine soils. Shallow landsliding distribution is assessed with the aid of physically based models, which use the EO-based map to distribute the resistance parameters across the landscape.
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The study was arranged to manifest its objectives through preceding it with an intro-duction. Particular attention was paid in the second part to detect the physical settings of the study area, together with an attempt to show the climatic characteristics in Libya. In the third part, observed temporal and spatial climate change in Libya was investigated through the trends of temperature, precipitation, relative humidity and cloud amount over the peri-ods (1946-2000), (1946-1975), and (1976-2000), comparing the results with the global scales. The forth part detected the natural and human causes of climate change concentrat-ing on the greenhouse effect. The potential impacts of climate change on Libya were ex-amined in the fifth chapter. As a case study, desertification of Jifara Plain was studied in the sixth part. In the seventh chapter, projections and mitigations of climate change and desertification were discussed. Ultimately, the main results and recommendations of the study were summarized. In order to carry through the objectives outlined above, the following methods and approaches were used: a simple linear regression analysis was computed to detect the trends of climatic parameters over time; a trend test based on a trend-to-noise-ratio was applied for detecting linear or non-linear trends; the non-parametric Mann-Kendall test for trend was used to reveal the behavior of the trends and their significance; PCA was applied to construct the all-Libya climatic parameters trends; aridity index after Walter-Lieth was shown for computing humid respectively arid months in Libya; correlation coefficient, (after Pearson) for detecting the teleconnection between sun spot numbers, NAOI, SOI, GHGs, and global warming, climate changes in Libya; aridity index, after De Martonne, to elaborate the trends of aridity in Jifara Plain; Geographical Information System and Re-mote Sensing techniques were applied to clarify the illustrations and to monitor desertifi-cation of Jifara Plain using the available satellite images MSS, TM, ETM+ and Shuttle Radar Topography Mission (SRTM). The results are explained by 88 tables, 96 figures and 10 photos. Temporal and spatial temperature changes in Libya indicated remarkably different an-nual and seasonal trends over the long observation period 1946-2000 and the short obser-vation periods 1946-1975 and 1976-2000. Trends of mean annual temperature were posi-tive at all study stations except at one from 1946-2000, negative trends prevailed at most stations from 1946-1975, while strongly positive trends were computed at all study stations from 1976-2000 corresponding with the global warming trend. Positive trends of mean minimum temperatures were observed at all reference stations from 1946-2000 and 1976-2000, while negative trends prevailed at most stations over the period 1946-1975. For mean maximum temperature, positive trends were shown from 1946-2000 and from 1976-2000 at most stations, while most trends were negative from 1946-1975. Minimum tem-peratures increased at nearly more than twice the rate of maximum temperatures at most stations. In respect of seasonal temperature, warming mostly occurred in summer and au-tumn in contrast to the global observations identifying warming mostly in winter and spring in both study periods. Precipitation across Libya is characterized by scanty and sporadically totals, as well as high intensities and very high spatial and temporal variabilities. From 1946-2000, large inter-annual and intra-annual variabilities were observed. Positive trends of annual precipi-tation totals have been observed from 1946-2000, negative trends from 1976-2000 at most stations. Variabilities of seasonal precipitation over Libya are more strikingly experienced from 1976-2000 than from 1951-1975 indicating a growing magnitude of climate change in more recent times. Negative trends of mean annual relative humidity were computed at eight stations, while positive trends prevailed at seven stations from 1946-2000. For the short observation period 1976-2000, positive trends were computed at most stations. Annual cloud amount totals decreased at most study stations in Libya over both long and short periods. Re-markably large spatial variations of climate changes were observed from north to south over Libya. Causes of climate change were discussed showing high correlation between tempera-ture increasing over Libya and CO2 emissions; weakly positive correlation between pre-cipitation and North Atlantic Oscillation index; negative correlation between temperature and sunspot numbers; negative correlation between precipitation over Libya and Southern Oscillation Index. The years 1992 and 1993 were shown as the coldest in the 1990s result-ing from the eruption of Mount Pinatubo, 1991. Libya is affected by climate change in many ways, in particular, crop production and food security, water resources, human health, population settlement and biodiversity. But the effects of climate change depend on its magnitude and the rate with which it occurs. Jifara Plain, located in northwestern Libya, has been seriously exposed to desertifica-tion as a result of climate change, landforms, overgrazing, over-cultivation and population growth. Soils have been degraded, vegetation cover disappeared and the groundwater wells were getting dry in many parts. The effect of desertification on Jifara Plain appears through reducing soil fertility and crop productivity, leading to long-term declines in agri-cultural yields, livestock yields, plant standing biomass, and plant biodiversity. Desertifi-cation has also significant implications on livestock industry and the national economy. Desertification accelerates migration from rural and nomadic areas to urban areas as the land cannot support the original inhabitants. In the absence of major shifts in policy, economic growth, energy prices, and con-sumer trends, climate change in Libya and desertification of Jifara Plain are expected to continue in the future. Libya cooperated with United Nations and other international organizations. It has signed and ratified a number of international and regional agreements which effectively established a policy framework for actions to mitigate climate change and combat deserti-fication. Libya has implemented several laws and legislative acts, with a number of ancil-lary and supplementary rules to regulate. Despite the current efforts and ongoing projects being undertaken in Libya in the field of climate change and desertification, urgent actions and projects are needed to mitigate climate change and combat desertification in the near future.
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Despite an increasing number of publications regarding the Pre-Columbian earthworks of the Llanos de Moxos, there have been no serious attempts to undertake a systematic survey of the archaeological remains of this lowland region in the Bolivian Amazon. Based on the GIS analysis of data gathered in the field and retrieved from satellite images, we discuss the spatial distribution of the Pre-Columbian settlements in a 4500 Km2 area of the Llanos de Moxos to the east of Trinidad, capital of the Beni Department, and their relationship with the geographical settings. Our findings shed new light on the prehistory of the region and bear important implications for our understanding of the impact of Pre-Columbian human occupation.