Study of Aerosol Impact on the Solar Potential Available in Burkina Faso, West Africa

This paper is an assessment of aerosols impact on solar potential available in Burkina Faso in 2017. Three measurement stations were selected from the North to the South according to the climatic zones, with sites at Dori (14.035°N, 0.034°W) in the North, Ouagadougou (12.20°N, 1.40°W) in the Center and Gaoua (10.29°N, 3.25°W) in the Southwest, respectively. This study is based on in-situ measurements, satellite observations and a tropospheric standard model of the Streamer radiative transfer code of atmospheric particles. The results show a high availability of solar irradiation with average monthly values ranging between 4.46 kWh/m²/d and 6.82 kWh/m²/d. The most favorable periods with maximum radiation are observed in Spring in March and in Fall in October. Yet, the qualitative comparison between the evolution of aerosols and that of solar potential clearly shows aerosols capacity to influence the radiation at the crossing of the atmosphere. Thus, the aerosols maxima correspond to the solar potential minima. Moreover, a comparison between the day cycles of solar radiation and those of the simulation model shows a good accuracy of the Streamer code to estimate the solar flows at the surface in a standard atmosphere without clouds in Burkina Faso.However, a quantification of the aerosol impact by the Streamer code reveals a reduction in the normal direct flow compared to clear days defined by aerosol optical depth (AOD) less than 0.2 (AOD<0.2) of nearly 75.04% at the Dori site in the North, 57.33% at the Ouagadougou site in the Center and 40.89 % at the Gaoua site in the Southwest during polluted days corresponding to AOD higher than 0.8.This corresponds to an increase in the diffuse flow of 279.69 W/m², 246.05 W/m² and 226.09 W/m², respectively calculated on the same sites. In case of a mixed day (0.2 <AOD <0.8), this decrease in direct solar flow is estimated at 41.25%, 22.11% and 37.13% with an increasein the diffuse solar flux of 115.04 W/m², 150.43 W/m² and 79.58 W/m² at the sites of Dori, Ouagadougou and Gaoua, respectively.

Assigning dates and identifying areas affected by fires in Portugal based on MODIS data

ABSTRACT An automated procedure is here presented that allows identifying and dating burned areas in Portugal using values of daily reflectance from near-infrared and middle-infrared bands, as obtained from the MODIS instrument. The algorithm detects persistent changes in monthly composites of the so-called (V,W) Burn-Sensitive Index and the day of maximum change in daily time series of W is in turn identified as the day of the burning event. The procedure is tested for 2005, the second worst fire season ever recorded in Portugal. Comparison between the obtained burned area map and the reference derived from Landsat imagery resulted in a Proportion Correct of 95.6%. Despite being applied only to the months of August and September, the algorithm is able to identify almost two-thirds of all scars that have occurred during the entire year of 2005. An assessment of the temporal accuracy of the dating procedure was also conducted, showing that 75% of estimated dates presented deviations between -5 and 5 days from dates of hotspots derived from the MODIS instrument. Information about location and date of burning events as provided by the proposed procedure may be viewed as complementary to the currently available official maps based on end-of-season Landsat imagery.

Vegetation loss and the 2016 Oropouche fever outbreak in Peru

BACKGROUND Oropouche virus causes Oropouche fever, an arboviral disease transmitted mainly by midges of the genus Culicoides and Culex mosquitoes. Clinical presentation of Oropouche fever in humans includes fever, headache, rash, myalgia, and in rare cases spontaneous bleeding and aseptic meningitis. Landscape change has been proposed as a driver of Oropouche fever emergence. OBJECTIVE To investigate the landscape epidemiology of the Oropouche fever outbreak that began in April 2016 in Cusco, Peru. METHODS We used information of vegetation and multivariate spatial analyses including ecological niche modeling. Vegetation was characterised using16-day composite enhanced vegetation index (EVI) images at 500 m spatial resolution from the MODIS sensor carried by the Terra satellite. FINDINGS Cases were distributed across seven Peruvian districts in two provinces. La Concepcion was the province with most of the affected districts. EVI time series across 2000 to 2016 suggested a decline in the vegetation in sites with Oropouche fever cases before the epidemic. Our ecological niche modeling suggests that other areas in Junin, Apurimac, and Madre de Dios departments are at risk of Oropouche fever occurrence. MAIN CONCLUSIONS Our results may provide a guide for future fieldwork to test hypotheses regarding Oropouche fever emergence and habitat loss in tropical Latin America.

Análise da variação da cobertura do solo no Pantanal de 2003 a 2010 através de sensoriamento remoto / Analysis of landcover changes using remote sensing between 2003 and 2010 in the Pantanal region

O Pantanal é um dos ecossistemas mais ricos em biodiversidade do Brasil, estendendo-se pelos territórios de Mato Grosso e de Mato Grosso do Sul, além de pequenas porções da Bolívia e Paraguai. A compreensão desse sistema é muito importante, já que para preservar é necessário conhecer. Assim, através da utilização de imagens MODIS, objetivou-se estimar as diferenças de cobertura do solo do Pantanal entre os anos de 2003 e 2010, avaliando a capacidade dessas imagens na identificação das mudanças na cobertura do solo da região. O limite de Pantanal adotado foi adaptado de limites consagrados na literatura; o método utilizado para a classificação das imagens foi o da classificação automática não supervisionada. Como resultado foi identificada a diminuição da vegetação arbóreo-arbustiva e o aumento das áreas de gramíneas entre os anos de estudo.

The Pantanal is one of the richest Brazilian ecosystems in terms of biodiversity, extending into the territories of Mato Grosso and Mato Grosso do Sul, as well as small portions of Bolivia and Paraguay. Understanding this system is very important because in order to preserve it is necessary to understand. Thus, using MODIS images, the present work aimed to estimate the differences in soil covering the Pantanal region between the years 2003 and 2010, evaluating the capacity of these images to identify changes in land cover. The Pantanal boundary used was adapted from boundary consecrated in the literature. The method used for image classification was the unsupervised automatic classification. As a result we identified a decrease in forest vegetation and an increase in grassland areas during the studied years.

An A-Train Satellite Based Stratiform Mixed Phase Cloud Retrieval Algorithm by Combining Active and Passive Sensor Measurements.

Aims: To develop a new satellite-based mixed-phase cloud retrieval algorithm for improving mixed-phase cloud liquid water path (LWP) retrievals by combining Moderate Resolution Imaging Spectroradiometer (MODIS), CloudSat, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements. Study Design: Algorithm development and evaluation by using collocated NASA A-Train and the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) measurements at the North Slope Alaska (NSA) site. Place and Duration of Study: Collocated MODIS and ground-based measurements at NSA site from March 2000 to October 2004, MODIS measurements and retrievals during July 2006 over Eastern Pacific, and MODIS, CloudSat and CALIPSO measurements on April 04, 2007 over the Arctic Region. Methodology: The stratiform mixed-phase cloudswere treated as two adjunct water and ice layers for radiative calculations with the Discrete Ordinate Radiative Transfer (DISORT) model. The ice-phase properties were provided with the 2C-ICE product, which is produced from CloudSat radar and CALIPSO lidar measurements, and they were used as inputs in DISORT for the calculations. Then, the calculated mixed-phase cloud reflectances at selected wavelengths were compared with MODIS reflectances to retrieve liquid-phase cloud properties. Results: A new algorithm was developed to retrieve LWP in stratiform mixed-phase clouds by using MODIS radiances and ice cloud properties from active sensor measurements. The algorithm was validated separately by using Operational MODIS retrievals of warm marine stratiform clouds and collocated surface measurements of Arctic stratiform mixed-phase clouds. The results show that the new algorithm reduced the positive LWP biases in the Operational MODIS LWP retrievals for stratiform mixedphase clouds from 35 and 68% to 10 and 22% in the temperature ranges of -5 to -10ºC and -10 to -20ºC, respectively. Conclusion: The combined A-Train active and MODIS measurements can be used to improve global mixed-phase cloud property retrievals.

Assessing Surface PM2.5 Estimates Using Data Fusion of Active and Passive Remote Sensing Methods.

In this paper, we focus on estimations of fine particulate matter by combining MODIS satellite Aerosol Optical Depth (AOD) with Weather Research Forecast (WRF) PBL information using a neural network approach and assess its performance. As part of our analysis, we first explore the baseline effectiveness of AOD and PBL as relevant factors in estimating PM2.5 in passive radiometer and active lidar data at CCNY and demonstrate that the PBL height is the most critical additional parameter for accurate PM2.5. Furthermore, active measurements from both ground and satellite based lidar are used to show that summer WRF model PBL heights are most accurate. We then expand our analysis to a regional domain where daily estimations are obtained and compared with operational GEOS-CHEM PM2.5 product. Using our approach, we also create regional daily PM2.5 maps and compare against GEOS-CHEM outputs. Finally, we also consider additional improvements, where multiple satellite observations are used as regressors to predict PM2.5. These results illustrate the significant improvement we obtain within this framework in comparison to a “one size fits all continental scale approach”.

Scientometric diagnosis of the use of remote sensing images in Landscape Ecology studies / Diagnóstico cienciométrico do uso de imagens de sensores remotos em estudos de Ecologia de Paisagens

This work analyzed the implementation of images from the remote sensors ASTER, CBERS, IKONOS, LANDSAT, MODIS, NOAA, QUICKBIRD and SPOT in Brazilian and international Landscape Ecology studies, developed between 1991 and July 2009. The study analyzed works published in article form using the ISI Web of Knowledge website, and theses and dissertations from the "Thesis Database" at CAPES (Coordenação de Aperfeiçoamento de Pessoal de Ensino Superior). A total of 124 Brazilian and 144 international published works were examined, analyzing 11 and six parameters, respectively. It was observed that the images from sensors MODIS (53%) and LANDSAT (32%) are employed more frequently in international research studies, whereas in Brazil there is preference for products from LANDSAT (65%) and SPOT (11%). The interval with the highest scientific output occurred between 1999 and 2009 (95%) in Brazil and from 1997 to 2009 (93%) internationally, while 2008 was the most significant year for both assessments, accounting for 19 and 18% of published works, respectively. The intense use of satellite imagery in Landscape Ecology studies observed in the last decade indicates there will be an increase in this technology in landscape analysis in coming years.

Este trabalho analisou a implementação das imagens dos sensores remotos ASTER, CBERS, IKONOS, LANDSAT, MODIS, NOAA, QUICKBIRD e SPOT nos estudos nacionais e internacionais de Ecologia de Paisagem, desenvolvidos entre 1991 e julho de 2009. Foram examinadas publicações em forma de artigos, teses e dissertações, com o auxílio do sítio ISI Web of Knowledge para os primeiros do "Banco de Teses" da Coordenação de Aperfeiçoamento de Pessoal de Ensino Superior (Capes) para os demais. Foram examinadas 124 publicações nacionais e 144 internacionais, com a análise de 11 e seis parâmetros, respectivamente. Constatou-se que as imagens dos sensores MODIS (53%) e LANDSAT (32%) são mais empregadas em pesquisas internacionais, enquanto no Brasil há preferência pelos produtos do LANDSAT (65%) e do SPOT (11%). O maior intervalo de produção científica ocorreu entre 1999 e 2009 (95%) no Brasil e entre 1997 a 2009 (93%) no exterior, enquanto o ano de 2008 foi o mais significativo para ambos os levantamentos, com índices de publicação de 19 e 18%, respectivamente. A intensa utilização de imagens de satélite em estudos de Ecologia de Paisagem verificada na última década suscita que haverá incremento crescente desta tecnologia nas análises da paisagem nos próximos anos.

Prediciendo la distribución de Polylepis: bosques Andinos vulnerables y cada vez más importantes

Los bosques de Polylepis son recursos vitales para la conservación de la biodiversidad y funciones hidrológicas, la cual se verá alterada por el cambio climático a nivel mundial desafiando la sostenibilidad de las comunidades locales. Sin embargo, estos ecosistemas andinos de gran altitud son cada vez más vulnerables debido a la presión antropogénica como la fragmentación, deforestación y el incremento en el ganado. La importancia para predecir la distribución de bosques nativos ha aumentado para contrarrestar los efectos negativos del cambio climático a través de la conservación y la reforestación. El objetivo de este estudio fue desarrollar y analizar los modelos de distribución de dos especies, Polylepis sericea y P. besseri, que forman bosques extensos a lo largo de los Andes. Este estudio utilizó el programa Maxent, el clima y capas ambientales de una resolución de 1 Km. El modelo de distribución previsto para P. sericea indica que la especie podría estar situada en una variedad de hábitats a lo largo de la Cordillera de los Andes, mientras que P. besseri se limitaba a las grandes alturas del sur de Perú y Bolivia. Para ambas especies, los metros de elevación y la temperatura son los factores más importantes para la distribución prevista. El perfeccionamiento del modelo de Polylepis y otras especies andinas utilizando datos de satélites cada vez más disponibles al público demuestran el potencial para ayudar a definir las áreas de diversidad y mejorar las estrategias de conservación en los Andes.

Polylepis woodlands are a vital resource for preserving biodiversity and hydrological functions, which will be altered by climate change and challenge the sustainability of local human communities. However, these high-altitude Andean ecosystems are becoming increasingly vulnerable due to anthropogenic pressure including fragmentation, deforestation and the increase in livestock. Predicting the distribution of native woodlands has become increasingly important to counteract the negative effects of climate change through reforestation and conservation. The objective of this study was to develop and analyze the distribution models of two species that form extensive woodlands along the Andes, namely Polylepis sericea and P. weberbaueri. This study utilized the program Maxent, climate and remotely sensed environmental layers at 1 Km resolution. The predicted distribution model for P. sericea indicated that the species could be located in a variety of habitats along the Andean Cordillera, while P. weberbaueri was restricted to the high elevations of southern Peru and Bolivia. For both species, elevation and temperature metrics were the most significant factors for predicted distribution. Further model refinement of Polylepis and other Andean species using increasingly available satellite data demonstrate the potential to help define areas of diversity and improve conservation strategies for the Andes.

Caracterização espectral multitemporal dos cereais de estação fria em imagens de satélite com média resolução espacial / Multitemporal spectral characterization of cool season cereals in satellite images with moderate spatial resolution

A fim de avaliar os padrões de resposta de áreas cultivadas com cereais de estação fria destinados para pastagens e para produção de grãos em imagens de satélite, foram analisados perfis temporais de índice de vegetação por diferença normalizada (NDVI), adquiridos em 29 áreas cultivadas com trigo e azevém anual, nos Estados do Rio Grande do Sul e Paraná. Para cada área foi informada a espécie cultivada (trigo ou azevém anual) e a coordenada do ponto central da área adquirido por meio do Global Positioning System (GPS). Foram usadas as imagens do sensor MODIS (Moderate Resolution Imaging Spectroradiometer), com resolução espacial de 250 metros, sobre cada área monitorada, de onde os valores de NDVI foram extraídos. Os perfis temporais de NDVI mostraram que os cultivos de produção de grãos têm um comportamento espectral típico de cultivos agrícolas, enquanto que, nas áreas cultivadas para a produção de pastagem, não foi observado esse mesmo padrão. As diferenças nos padrões temporais observadas se devem a modificações que o pastoreio impõe na fenologia e na morfologia dessas plantas.

In order to evaluate the satellite image patterns between such cool season cereals cultivated areas intended for grazing or grain production, Normalized Difference Vegetation Index (NDVI) temporal profiles were analyzed. This data was acquired from twenty nine wheat and annual ryegrass cultivated areas in the states of Rio Grande do Sul and Paraná. For each area, the cultivated species (wheat or ryegrass), as well as the respective central point coordinates, acquired via Global Positioning System (GPS) was informed. NDVI values were extracted over each monitored area from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor images, with spatial resolution of 250 meters. The NDVI temporal profiles showed that grain production areas have a typical agricultural field spectral pattern. The same pattern was not observed for the grazing pasture areas. The differences observed in these temporal patterns are defined by the changes that grazing has imposed on the phenology and morphology of these plants.

Avaliação do desenvolvimento das culturas de cereais de inverno no Rio Grande do Sul por meio de perfis temporais do índice de vegetação por diferença normalizada / Winter cereal crop development in Rio Grande do Sul, Brazil, throughout the temporal profiles of normalized difference vegetation index

Os objetivos deste trabalho foram elaborar perfis temporais de NDVI/MODIS, mediante a construção de máscaras de cultivo, verificando as variações interanuais dos perfis associadas à variação do rendimento de grãos de trigo no Rio Grande do Sul. Foram utilizadas imagens MOD13 dos meses de maio a novembro para os anos 2000 a 2006, pontos de controle na superfície (coletados em lavouras de trigo, aveia e cevada) e dados oficiais de rendimento médio de grãos de trigo (IBGE e Cotrijal). Os resultados mostraram que, por meio da metodologia de construção de máscaras de cultivo, é possível gerar perfis temporais de NDVI que permitem monitorar o desenvolvimento das lavouras de cereais de inverno e que podem ser empregados no estudo das variações interanuais de rendimento de grãos de trigo. Os maiores rendimentos de grãos estão relacionados à manutenção de altos valores de NDVI (acima de 0,7) por um período maior de tempo. Porém, a metodologia não permitiu a distinção de lavouras de trigo, aveia e cevada, sendo necessários estudos subseqüentes.

This research aimed to elaborate temporal NDVI profiles through the crop masks building, and find the interannual variations of profiles associated with variation of wheat grain yield in Rio Grande do Sul, Brazil. The data set were composed by MODIS13 images (NDVI product from May to November, 2000 to 2006), ground control points (collected in wheat, oat and barley fields) and official wheat grain yield (IBGE and Cotrijal). The results showed that using the proposed methodology for crop masking it is possible to generate consistent NDVI temporal profiles, which allows monitoring the development of winter cereal crops and can be used to evaluate the interannual variations of grain yield. The profiles showed that wheat grain yield was related to the maintenance of high NDVI values (above 0.7) for a larger period of time. However, the methodology did not allow the wheat, oats and barley discrimination, pointing for subsequent studies.