Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach

Remote sensing and geographical information technologies were used to discriminate areas of high and low risk for contracting kala-azar or visceral leishmaniasis. Satellite data were digitally processed to generate maps of land cover and spectral indices, such as the normalised difference vegetation index and wetness index. To map estimated vector abundance and indoor climate data, local polynomial interpolations were used based on the weightage values. Attribute layers were prepared based on illiteracy and the unemployed proportion of the population and associated with village boundaries. Pearson's correlation coefficient was used to estimate the relationship between environmental variables and disease incidence across the study area. The cell values for each input raster in the analysis were assigned values from the evaluation scale. Simple weighting/ratings based on the degree of favourable conditions for kala-azar transmission were used for all the variables, leading to geo-environmental risk model. Variables such as, land use/land cover, vegetation conditions, surface dampness, the indoor climate, illiteracy rates and the size of the unemployed population were considered for inclusion in the geo-environmental kala-azar risk model. The risk model was stratified into areas of "risk"and "non-risk"for the disease, based on calculation of risk indices. The described approach constitutes a promising tool for microlevel kala-azar surveillance and aids in directing control efforts.

Spatial distribution of triatomines in domiciles of an urban area of the Brazilian Southeast Region

Reports of triatomine infestation in urban areas have increased. We analysed the spatial distribution of infestation by triatomines in the urban area of Diamantina, in the state of Minas Gerais, Brazil. Triatomines were obtained by community-based entomological surveillance. Spatial patterns of infestation were analysed by Ripley’s K function and Kernel density estimator. Normalised difference vegetation index (NDVI) and land cover derived from satellite imagery were compared between infested and uninfested areas. A total of 140 adults of four species were captured (100 Triatoma vitticeps, 25Panstrongylus geniculatus, 8 Panstrongylus megistus, and 7 Triatoma arthurneivai specimens). In total, 87.9% were captured within domiciles. Infection by trypanosomes was observed in 19.6% of 107 examined insects. The spatial distributions ofT. vitticeps, P. geniculatus, T. arthurneivai, and trypanosome-positive triatomines were clustered, occurring mainly in peripheral areas. NDVI values were statistically higher in areas infested by T. vitticeps and P. geniculatus. Buildings infested by these species were located closer to open fields, whereas infestations of P. megistus andT. arthurneivai were closer to bare soil. Human occupation and modification of natural areas may be involved in triatomine invasion, exposing the population to these vectors.

Model d'adequació de l'hàbitat del llop a Catalunya

Des de l’any 2000 es té constància de la presencia del llop a Catalunya. Des de llavors, com a mínim 14 llops diferents han entrat i sortit del territori català, encara que cap d’ells s’ha assentat de manera permanent. L’estudi analitza l’entorn català utilitzant GIS, creant un model d’adequació de l’hàbitat tenint en compte les següents variables: la distància a la carretera més propera, la biomassa disponible a la zona, l’altitud i el tipus i tant per cent de recobriment. El model es basa en la informació obtinguda mitjançant la consulta a experts tant del llop com del territori català, així com en una recerca bibliogràfica sobre l’adequació de l’hàbitat del llop. L’enquesta que es dirigí als experts té en compte els valors que cada variable pot prendre dins l’àrea d’estudi, estableix rangs dels valors de cada variable i pregunta als experts com cada rang pot afectar a l’adequació de l’hàbitat pel llop. Els resultats mostren com bona part de la zona Nord de Catalunya té unes condicions adequades perquè el llop pugui arribar a reproduir-s’hi. Es desenvolupa també una anàlisi dels possibles punts de conflicte humà-llop i una superposició dels espais protegits amb les zones més adequades per l’establiment del llop.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

De viles rurals a indrets de la regió metropolitana de Barcelona: transformacions històriques del paisatge a la Vall del Congost (Figaró-Montmany, l’Ametlla del Vallès i la Garriga, 1850-2010)

El projecte ha assolit la majoria d’objectius, ajustats a la reducció d'una quarta part de l'import concedit: 1) caracteritzar la transformació del paisatge agro-forestal i urbà a dos municipis de la vall del Congost, La Garriga i Figaró-Montmany, reconstruint amb SIG els mapes d'ús del sòl de 1854, 1949, 1956 i 2005, obtenint per intersecció de cobertes les matrius dels canvis d'ús; i 2) avaluar amb l’índex de connectivitat ecològica l'impacte ambiental d'aquells canvis des del punt de vista de la biodiversitat i la resiliència del paisatges, amb un especial èmfasi en la reforestació induïda per l'abandonament rural i la pèrdua de paisatges en mosaic, en un àmbit més gran pel període 1956-1993-2005. Aquests resultats han permès preparar varis articles per publicar en co-autoría a revistes com Landscape History, Environment and History o Landscape and Urban Planning. Ja és a punt de poder-se lliurar el primer amb el títol de "Looking backwards into a Mediterranean edge environment: Landscape changes and ecological connectivity in El Congost Valley (province of Barcelona, Catalonia) 1850-2005", incloent dos objectius esmentats a la memòria: identificar les principals forces motores d'aquells canvis en el paisatge relacionant els usos del sòl amb les formes d'ordenació del territori, caracteritzar-ne les forces rectores econòmico-socials i el paper jugat per la protecció del Parc Natural del Montseny i els Cingles de Bertí. Els resultats també permetran abordar en el futur altres aspectes, com per exemple estimar el potencial energètic de la biomassa local tot cercant que el seu aprofitament generi sinèrgies territorials positives per a l'ecologia del paisatge amb la recuperació d’una ramaderia extensiva i una agricultura ecològica que facin possible la restauració dels paisatges en mosaic. L'estudi ha pogut incorporar un aspecte inicialment no previst, el cens d'orquídies mediterrànies a Figaró-Montmany elaborat pel naturalista Paul Wilcox

Modeling the biophysical impacts of global change in mountain biosphere reserves

Mountains and mountain societies provide a wide range of goods and services to humanity, but they are particularly sensitive to the effects of global environmental change. Thus, the definition of appropriate management regimes that maintain the multiple functions of mountain regions in a time of greatly changing climatic, economic, and societal drivers constitutes a significant challenge. Management decisions must be based on a sound understanding of the future dynamics of these systems. The present article reviews the elements required for an integrated effort to project the impacts of global change on mountain regions, and recommends tools that can be used at 3 scientific levels (essential, improved, and optimum). The proposed strategy is evaluated with respect to UNESCO's network of Mountain Biosphere Reserves (MBRs), with the intention of implementing it in other mountain regions as well. First, methods for generating scenarios of key drivers of global change are reviewed, including land use/land cover and climate change. This is followed by a brief review of the models available for projecting the impacts of these scenarios on (1) cryospheric systems, (2) ecosystem structure and diversity, and (3) ecosystem functions such as carbon and water relations. Finally, the cross-cutting role of remote sensing techniques is evaluated with respect to both monitoring and modeling efforts. We conclude that a broad range of techniques is available for both scenario generation and impact assessments, many of which can be implemented without much capacity building across many or even most MBRs. However, to foster implementation of the proposed strategy, further efforts are required to establish partnerships between scientists and resource managers in mountain areas.

Aplicação de SIG no Processamento do Inventário Florestal Nacional – Cabo Verde

Cabo Verde desde do século passado tem envidado esforço na florestação, sobretudo depois de 1975 para atenuar os efeitos da seca e da desertificação criando deste modo grandes áreas arborizadas. Entretanto, à medida que os recursos florestais foram sendo criados, a problemática da sua avaliação e da sua gestão sustentável, passaram a merecer maior atenção das autoridades nacionais. A lei florestal, promulgada em 1998 define como uma das atribuições e acções do Estado, através dos serviços florestais, a elaboração dos planos de gestão das zonas florestais. Este plano de gestão implica a análise e a apreciação de dados concretos e actualizados sobre a situação real das zonas florestais, sendo possível apenas através do inventário florestal nacional (IFN). Neste trabalho é proposta uma metodologia de processamento do IFN em que se utilizam as potencialidades dos Sistemas de Informação Geográfica (SIG). Foram utilizados para este trabalho os programas: ArcGis 9.1, para produção cartográfica, geoprocessamento e análise espacial e o Field-Map 8.1 para a classificação de ortofotos num esquema de classificação hierárquica, em cinco níveis, adaptado a Cabo Verde (classes de uso do solo adoptado ao esquema de classificação do território europeu – CORINE Land Cover e da Organização das Nações Unidas para a Agricultura e Alimentação (FAO). Os dados utilizados foram compilados no âmbito do projecto do inventário florestal. Os resultados obtidos, para a Ilha de Santiago, constituem uma base cartográfica para o IFN com diversos temas cartográficos, nomeadamente, mapas das zonas florestadas, mapas de ocupação do solo e mapas de amostras inventariáveis cuja metodologia de elaboração poderá ser facilmente replicada para as restantes ilhas do arquipélago

Distribuição Espacial da Susceptibilidade à Erosão Hídrica nas Bacias das Ribeiras de Picos e Seca (Santiago, Cabo Verde)

Os processos de erosão hídrica em Cabo Verde são os mais marcantes da dinâmica actual das vertentes, pois são os mais comuns e que afectam áreas extensasdurante a curta estação húmida de três meses. A ocorrência de episódios chuvosos concentrados no tempo e com uma evidente irregularidade espacial permitem umaacentuada erosividade das precipitações, marcada por uma forte irregularidade regional. A forte variabilidade das formas de relevo, a diversidade da natureza das unidadesgeológicas e a multiplicidade de ocupação do solo favorecem condições deerodibilidade muito contrastadas no espaço. O objectivo deste trabalho é estabelecer um modelo desusceptibilidade à erosão hídricaem função de factores geomorfológicos (declive, perfil e traçado das vertentes eerodibilidade das unidades litológicas e dos materiais de cobertura), climáticos(intensidade pluviométrica) e de ocupação do solo para as bacias das ribeiras dos Picose Seca. Os resultados foram obtidos com recurso ao ambiente de Sistemas deInformação Geográfica (SIG). Este trabalho surge na sequência de outros já realizadospelos autores, onde se apresentaram as condições de erodibilidade e erosividade paraáreas mais restritas da Ilha de Santiago. O modelo de susceptibilidade à erosão hídrica resultou do cruzamento dos mapas dedeclives, de perfil e do traçado das vertentes, obtidos a partir do modelo digital deterreno (DTM), do mapa geológico, da distribuição espacial da intensidadepluviométrica e da densidade de ocupação do solo, tendo em conta que são estas asprincipais condicionantes de erosão hídrica, referidas pelos autores que estudaram estaregião. Cada um destes mapas foi reclassificado com base numa análise qualitativa dograu de erodibilidade, sendo atribuído um número de ordem a cada classe, em função da sua susceptibilidade à erosão hídrica, conforme foi localmente reconhecido. Verifica-se que as áreas de maior susceptibilidade à erosão hídrica são as do sectorsudeste da bacia da Ribeira Seca e as vertentes dos principais vales da bacia da Ribeira dos Picos, onde se encontram as unidades geológicas mais friáveis, os declives mais acentuados e onde predominam sectores das vertentes de traçado côncavo, a que seassocia pontualmente a mais elevada intensidade pluviométrica.

Susceptibilidade à Erosão Hídrica na Bacia da Ribeira Seca (Santiago, Cabo Verde)

Na Ilha de Santiago, em Cabo Verde, a erosão hídrica é o processo que afecta áreas mais extensas. A ocorrência de aguaceiros intensos e concentrados no tempo e no espaço promovem uma marcada erosividade das precipitações, com forte irregularidade regional. A grande variabilidade dos declives e das formas das vertentes, associadas à diversidade litológica, bem como à multiplicidade de ocupação do solo, permitem condições de erodibilidade muito contrastadas no espaço. O objectivo deste trabalho é obter um mapa de susceptibilidade à erosão hídrica para a bacia da Ribeira Seca (Santiago oriental) com base no modelo digital do terreno (MDT), nos mapas geológico e de ocupação do solo e na distribuição da erosividade das precipitações. Verifica-se que o sector sudeste da bacia é o mais susceptível à erosão hídrica, pois nele ocorrem a maior concentração diária das precipitações e as condições geomorfológicas e de coberto do solo de mais elevada erodibilidade.

Parallelizing remote sensing image geometric correction

Remote sensing spatial, spectral, and temporal resolutions of images, acquired over a reasonably sized image extent, result in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is very attractive for monitoring, management, and scienti c activities. With Moore's Law alive and well, more and more parallelism is introduced into all computing platforms, at all levels of integration and programming to achieve higher performance and energy e ciency. Being the geometric calibration process one of the most time consuming processes when using remote sensing images, the aim of this work is to accelerate this process by taking advantage of new computing architectures and technologies, specially focusing in exploiting computation over shared memory multi-threading hardware. A parallel implementation of the most time consuming process in the remote sensing geometric correction has been implemented using OpenMP directives. This work compares the performance of the original serial binary versus the parallelized implementation, using several multi-threaded modern CPU architectures, discussing about the approach to nd the optimum hardware for a cost-e ective execution.

Surface topography and mixed-pixel effects on the simulated L-band brightness temperatures.

The impact of topography and mixed pixels on L-band radiometric observations over land needs to be quantified to improve the accuracy of soil moisture retrievals. For this purpose, a series of simulations has been performed with an improved version of the soil moisture and ocean salinity (SMOS) end-to-end performance simulator (SEPS). The brightness temperature generator of SEPS has been modified to include a 100-m-resolution land cover map and a 30-m-resolution digital elevation map of Catalonia (northeast of Spain). This high-resolution generator allows the assessment of the errors in soil moisture retrieval algorithms due to limited spatial resolution and provides a basis for the development of pixel disaggregation techniques. Variation of the local incidence angle, shadowing, and atmospheric effects (up- and downwelling radiation) due to surface topography has been analyzed. Results are compared to brightness temperatures that are computed under the assumption of an ellipsoidal Earth.

Ruutupohjainen maasto-GIS otantamenetelmä videokamerakuvan ja sateliittikuvan digitaalisen luokituksen luotettavuuden määrittämisessä

Summary in English: Accuracy assessment for land use classification using the grid and road based sampling method

Evaluating effects of spectral training data distribution on continuous field mapping performance

Continuous field mapping has to address two conflicting remote sensing requirements when collecting training data. On one hand, continuous field mapping trains fractional land cover and thus favours mixed training pixels. On the other hand, the spectral signature has to be preferably distinct and thus favours pure training pixels. The aim of this study was to evaluate the sensitivity of training data distribution along fractional and spectral gradients on the resulting mapping performance. We derived four continuous fields (tree, shrubherb, bare, water) from aerial photographs as response variables and processed corresponding spectral signatures from multitemporal Landsat 5 TM data as explanatory variables. Subsequent controlled experiments along fractional cover gradients were then based on generalised linear models. Resulting fractional and spectral distribution differed between single continuous fields, but could be satisfactorily trained and mapped. Pixels with fractional or without respective cover were much more critical than pure full cover pixels. Error distribution of continuous field models was non-uniform with respect to horizontal and vertical spatial distribution of target fields. We conclude that a sampling for continuous field training data should be based on extent and densities in the fractional and spectral, rather than the real spatial space. Consequently, adequate training plots are most probably not systematically distributed in the real spatial space, but cover the gradient and covariate structure of the fractional and spectral space well. (C) 2009 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

20 Native Trees to Plant, January 25, 2010

If you have ever flown in an airplane over Iowa, you would see that our woodlands are scattered along the rivers and streams and areas too steep to farm. You would also see a green carpet of trees within out cities and towns. Did you know the 90% of the over 2.7 million acres of forest in Iowa is owned by over 138,000 different private owners? Or that 30% of the land cover in a typical Iowa community if covered by trees? Trees are vital for the protection of our drinking water supply, critical for wildlife habitat, and help sustain employment of over 7,000 Iowans in the wood products industry. This booklet "20 Native trees to Plant" will help you gain a greater knowledge about Iowa's trees and forests. Learn about and enjoy Iowa's trees. Consider ways that you can improve our environment by planting and caring for Iowa's trees and forests.

Global habitat suitability models of terrestrial mammals.

Detailed large-scale information on mammal distribution has often been lacking, hindering conservation efforts. We used the information from the 2009 IUCN Red List of Threatened Species as a baseline for developing habitat suitability models for 5027 out of 5330 known terrestrial mammal species, based on their habitat relationships. We focused on the following environmental variables: land cover, elevation and hydrological features. Models were developed at 300 m resolution and limited to within species' known geographical ranges. A subset of the models was validated using points of known species occurrence. We conducted a global, fine-scale analysis of patterns of species richness. The richness of mammal species estimated by the overlap of their suitable habitat is on average one-third less than that estimated by the overlap of their geographical ranges. The highest absolute difference is found in tropical and subtropical regions in South America, Africa and Southeast Asia that are not covered by dense forest. The proportion of suitable habitat within mammal geographical ranges correlates with the IUCN Red List category to which they have been assigned, decreasing monotonically from Least Concern to Endangered. These results demonstrate the importance of fine-resolution distribution data for the development of global conservation strategies for mammals.