Evolución temporal de humedales de la región ayacucho, mediante imágenes modis periodo 2002-2013

La presente investigación responde a la necesidad de caracterizar la evolución temporal de los humedales mediante imágenes satelitales, su procesamiento, análisis, interpretación y discusión, pues los cambios climáticos hacen necesario tener en cuenta que son ecosistemas importantes de gran interés por las diferentes funciones que realizan. Las imágenes satelitales del satélite TERRA del sensor AQUA, fueron procesadas con el software ENVI y se determinó el parámetro del Índice de Vegetación de Diferencia Normalizada (NDVI), más el uso del Google Earth nos permitió a grandes rasgos discriminar entre zonas de vegetación, suelo desnudo, agua y la variación en el tiempo de los Humedales de la Región de Ayacucho. La teledetección nos ofrece grandes progresos en el conocimiento de la naturaleza, aunque es necesario un mayor rigor científico en la interpretación de los resultados y tener como objetivo eliminar los efectos ocasionados por la variabilidad en las condiciones de captación, distorsión provocada por la atmósfera, y la influencia de parámetros radiométricos geométricos tales como la radiancia, reflectancia, emisividad, posición del Sol, pendiente, y altitud. Por lo cual esperamos que contribuya al conocimiento de datos importantes quedando pendiente estimar otros parámetros como la humedad de suelos, evaporación, etc. a través de la cual se precisará y reorientar la tecnología propuesta. images, processing, analysis, interpretation and discussion, as the climate changes make it necessary to consider that are important ecosystems of great interest in the different functions performed. Satellite images of the TERRA satellite AQUA sensor were processed with ENVI software and parameters Index Normalized Difference Vegetation (NDVI) was determined, plus the use of Google Earth allowed us to broadly discriminate between areas of vegetation, soil nude, water and variation in time of Wetlands in the region of Ayacucho. Remote sensing offers great progress in the knowledge of nature, although a greater scientific rigor in the interpretation of the results is necessary and aim to eliminate the effects caused by the variability in the conditions of recruitment, distortion caused by the atmosphere, and the influence of geometric radiometric parameters such as radiance, reflectance, emissivity, position of the Sun, slope, and altitude. So we hope to contribute to the knowledge of important data pending estimate other parameters such as soil moisture, evaporation, etc. through which shall specify and redirect the proposed technology.

Patterns of relationship between PM10 from air monitoring quality station and AOT data from MODIS sensor onboard of Terra satellite

Thailand, especially in the northern region, often encounters the problem of having PM10 exceeding the normal standard level, which could do harm to people’s health. Mostly, such problem is caused by the burning of forest area and open area; this is clearly seen during January–April of every year. Also, the problem as mentioned is caused by the meteorological conditions and the terrains in the northern region that make it easy for PM10 to be accumulated. The aim of this study was to analyze the patterns of relationship between PM10 measured from the ground monitoring station and AOT data received from MODIS sensor onboard of Terra satellite in Phrae Province located in the northern region of Thailand. The method performed was by analyzing the correlation between PM10 data obtained from the ground monitoring station and the AOT data received from the MODIS sensor onboard of Terra satellite during January–April 2018. It was found from the study that the change of the intensity of PM10 and AOT in the climate was highly related; it appeared that the correlation coefficient (r) in January–April was 0.92, 0.91, 0.91 and 0.92, respectively. This research pointed out that during February– –April, the areas of Phrae Province had the level of PM10 that affected health. Besides, from the method in this research, it revealed AOT data received from MODIS sensor onboard of Terra satellite could be applied in order to follow up, monitor, and notify the spatial changes of PM10 efficiently.

Study of Atmospheric Turbidity in a Northern Tropical Region Using Models and Measurements of Global Solar Radiation

Radiative transfer in the Earth’s atmosphere under clear-sky conditions strongly depends on turbidity due to aerosols and hydrometeors. It is therefore important to know its temporal radiative properties for a given site when the objective is to optimize the solar energy that is collected there. Turbidity can be studied via measurements and models of the global solar radiation reaching the ground in cloudless conditions. These models generally depend on two parameters, namely the Angström turbidity coefficient and the Linke factor. This article aims to do a comparative study of five models of global solar radiation, all dependent on the Linke factor, based on real data. The measurements are provided by the Tamanrasset Meteorological Center (Algeria), which has a long series of global solar radiation data recorded between 2005 and 2011. Additional data from AERONET and MODIS onboard the TERRA satellite were also used to perform the comparison between the two estimated parameters and those obtained from AERONET. The study shows that the ESRA models are the most reliable among the five models for estimating the Linke factor with a correlation coefficient R of the data fits of 0.9995, a RMSE of 13.44 W/m2, a MBE of −0.64 W/m2 and a MAPE of 6.44%. The maximum and minimum statistical values were reached, respectively, in June and during the autumn months. The best correlation is also observed in the case of ESRA models between the Linke parameter and the joint optical thickness of aerosols and the total column-integrated water vapor. The Angström turbidity coefficient β, calculated from the Linke factor and MODIS data, has values less than 0.02 at 9% of the cases, and 76% present values ranging between 0.02 and 0.15 and 13% higher than 0.15. These β values are validated by AERONET measurements since a very good correlation (R≈0.87) is observed between the two datasets. The temporal variations of β also show a maximum in June. Satellite observations confirm more aerosols during the summer season, which are mostly related to the African monsoon.

Drought Extent and Severity on Arable Lands in Romania Derived from Normalized Difference Drought Index (2001–2020)

The aim of this study was to evaluate the frequency and severity of drought over the arable lands of Romania using the Normalized Difference Drought Index (NDDI). This index was obtained from the Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensor of the Terra satellite. The interval between March and September was investigated to study the drought occurrence from the early stage of crop growth to its harvest time. The study covered a long period (2001–2020), hence it is able to provide a sound climatological image of crop vegetation conditions. Corine Land Cover 2018 (CLC) was used to extract the arable land surfaces. According to this index, the driest year was 2003 with 25.6% of arable land affected by drought. On the contrary, the wettest year was 2016, with only 10.8% of arable land affected by drought. Regarding the multiannual average of the period 2001–2020, it can be seen that drought is not a phenomenon that occurs consistently each year, therefore only 11.7% of arable land was affected constantly by severe and extreme drought. The correlation between NDDI and precipitation amount was also investigated. Although the correlations at weekly or monthly levels are more complicated, the annual regional mean NDDI is overall negatively correlated with annual rainfall. Thus, from a climatic perspective, we consider that NDDI is a reliable and valuable tool for the assessment of droughts over the arable lands in Romania.

Influência topoedafoclimática na produção primária bruta no semiárido

O relevo influencia a precipitação, a produção de biomassa e a produção primária bruta (Gross Primary Production-GPP). Em ecossistemas secos qualquer variação GPP tem importância cientifica uma vez que são ecossistemas bastante vulneráveis devido a alta variabilidade espacial e temporal do clima. Além disso, avaliar a relação entre o relevo e GPP em ecossistemas secos se torna mais fácil por existir um período bem definido com zero de precipitação. O estudo objetivou avaliar a influência do relevo, da altitude, da precipitação e do solo na Gross Primary Production-GPP no Bioma Caatinga. Foram utilizados os produtos MOD17 (GPP), sensor MODIS do satélite Terra e dados de precipitação para os anos de 2015 e 2016, com a aplicação de estatísticas descritivas e multivariadas para identificar correlações e similaridades entre áreas e amostras. Ocorreu grande variação espacial e temporal da GPP em áreas de Caatinga, devido ao relevo, clima e solo. A quantificação da GPP nas áreas de maiores altitudes apresentou médias de 46,87 e 55,84 gC m-2 e menores valores de GPP, de 2,49 e 3,75 gC m-2, em 2015 e 2016, respectivamente. Nas áreas planas, as maiores médias foram 46,03 e 55,84 gC m-2 e as menores 3,75 e 2,49 gC m-², em 2015 e 2016, respectivamente. Ocorreu uma diferença de quase 40% para os menores valores de GPP, quando comparados aos relativos às áreas mais altas e mais baixas. Foi possível avaliar a influência do relevo na GPP devido existir um período seco bem definido e de precipitação zero. Os anos de maiores precipitação têm forte influência nos menores valores de GPP das áreas planas. Assim, no período chuvoso é mais difícil identificar a influência de outros fatores, que não sejam a precipitação, na GPP. Esses resultados são de grande importância para mitigar ou avaliar os efeitos das mudanças climáticas sobre os ecossistemas secos.Palavras-Chave: relevo, sensoriamento remoto, produção primária bruta, sensor MODISEdapho-topo-climatic Influence on gross primary production in semi-arid A B S T R A C TRelief influences formation, biomass production and gross primary production (Gross primary production-GPP). In dry ecosystems any GPP variation is of scientific importance since they are very vulnerable ecosystems due to the high spatial and temporal variability of the climate. In addition, assessing the relationship between relief and GPP in dry ecosystems makes it easier to have a well-defined period with zero special. The study aimed to evaluate the influence of relief, altitude, exclusion and soil in the Primary Gross Production-GPP in the Caatinga Biome. The products MOD17 (GPP), MODIS sensor from the Terra satellite and capacity data for the years 2015 and 2016 were used, with the application of descriptive and multivariate statistics to identify correlations and similarities between areas and accounts. There was a great spatial and temporal variation of the GPP in Caatinga areas, due to the relief, climate and soil. Quantification of GPP in areas of higher altitudes showed averages of 46.87 and 55.84 gC m-2 and lower values of GPP, of 2.49 and 3.75 gC m-2, in 2015 and 2016, respectively. In the flat areas, the highest averages were 46.03 and 55.84 gC m-2 and the lowest 3.75 and 2.49 gC m-2, in 2015 and 2016, respectively. There was a difference of almost 40% for the lowest values of the GPP, when compared to those related to the highest and lowest areas. It was possible to evaluate the influence of the relief on the GPP because there is a well-defined dry period with zero capacity. The years of greater capacity have a strong influence on the lower values of GPP in flat areas. Thus, in the rainy season, it is more difficult to identify the influence of factors other than exclusion on GPP. These results are of great importance to mitigate or assess the effects of climate change on dry ecosystems.Keywords: relief, remote sensing, gross primary production, MODIS sensor

Investigation of Spatial and Temporal Changes in the Land Surface Albedo for the Entire Chinese Territory

Currently, global climate change (GCC) and the urban heat island (UHI) phenomena are becoming serious problems, partly due to the artificial construction of the land surface. When sunlight reaches the land surface, some of it is absorbed and some is reflected. The state of the land surface directly affects the surface albedo, which determines the magnitude of solar radiation reflected by the land surface in the daytime. In order to better understand the spatial and temporal changes in surface albedo, this study investigated and analyzed the surface albedo from 2000 to 2016 (2000, 2008, and 2016) in the entire Chinese territory, based on the measurement database obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, aboard NASA’s Terra satellite. It was shown that the Northeast China exhibited the largest decline in surface albedo and North China showed the largest rising trend of surface albedo from 2000 to 2016. The correlation between changes in surface albedo and the Normalized Difference Vegetation Index (NDVI) indicated that the change trend of surface albedo was opposite to that of NDVI. In addition, in order to better understand the distribution of surface albedo in the entire Chinese territory, the classifications of surface albedo in three years (2000, 2008, and 2016) were implemented using five classification methods in this study.

CERES Gimbal Performance on Terra

The Terra satellite has been operating in orbit for 20 years. The Terra satellite is also called the flagship earth-observing satellite. The two Clouds and the Earth’s Radiant Energy System CERES instruments on board continue to function nominally. Their expected mission lifetime was 7 years. Critical to their performance is the longevity of the scanning gimbals. This can be traced to the performance of the fluid-lubricated bearings. Two metrics are used to estimate their lifetime and health. Both lend themselves to readily available data and ease of interpretation. One is predicting the evaporative lubricant loss. This analysis indicates that the lubricant supply is adequate for the continual life of the gimbals. The second is trending the torque with time. Torque precursors are sampled quarterly. These data are converted to torque. Two types of torque behavior were examined. Contrasting torque data have supported the conclusion that the gimbals are operating nominally. This can be partially attributed to the design choices for the bearings and lubricant. The aim of this paper is to quantitatively describe the present health and expected life of the CERES gimbals on the Terra satellite.