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Technical innovation in agriculture is of extreme importance, in particular to address global challenges such as population growth, climate change and the limited availability of important plant nutrients such as phosphorus and potassium. Sensors applied to agricultural production could play a fundamental role for this purpose and research into agricultural applications has been ongoing for largely a decade [1]. Relevance of the paper is to develop a system for smart agriculture necessary for the development of agricultural production in our country in a similar manner to the European Union. Agriculture and allied activities play a vital role in a country's economic prosperity. The conventional methods in agricultural practices have become grossly inadequate to cater to the increasing needs. Thus it has become imperative to adopt novel technologies to raise agricultural standards. This paper proposes a system in a limited, enclosed area wherein different sensors are strategically positioned to measure parameters such as moisture content, temperature, pressure, light intensity and pH of the soil [5].

Understanding how urban forest land cover responds to climate change requires knowledge of land-surface interaction processes, which control the degree to which interannual variability and mean trends in climatic variables affect the surface energy budget and by this forest vegetation. Urban forest represents unique areas for the detection of climatic change and the assessment of climate-related impacts. Effects of climate extremes and anthropogenic changes on urban/periurban forest systems in Romania can have both short-term and long-term implications for standing biomass, tree health and species composition. This paper used time series of normalized difference of vegetation index (NDVI) and enhanced vegetation index (EVI) as well as leaf area index (LAI) as a measurement indicators of forest dynamics at metropolitan scale in order to assess impacts of climate changes on forest ecosystem phenology in metropolitan area of Bucharest. Use of satellite remote sensing to monitor the forest changes due to climatic stressors is an excellent example of the value of multispectral, multiresolution and multitemporal observations. Fusion technique was applied to time series satellite imagery data (Landsat TM/ETM/OLI, Sentinel 2 and MODIS Terra/Aqua satellite data) for urban/periurban forest ecosystem of Bucharest metropolitan area in Romania over 2000-2019 period. Also, this paper addresses a number of issues related to changes in land surface temperature (LST), and analyses correlations between NDVI/EVI time series and climatic variables under different scenarios for summer heat waves, windstorms and heavy precipitation.

In this paper, the negative impact of extreme climate events and urbanization and the subsequent effects on increasing trend of land surface temperature and degradation of urban green system of Bucharest metropolitan region in Romania was assessed using the geospatial and field survey data. Due to anthropogenic and natural factors, urban land covers changes are reflected in the land surfaces albedo changes. The main aim of this paper is to investigate the urban green albedo patterns dynamics due to the impact of atmospheric pollution, deforestation and climate variations on urban green land cover of Bucharest metropolitan area based on satellite remote sensing Landsat TM/ETM/OLI and MODIS Terra/Aqua time series data over 2000–2017 time period. This study is based on MODIS derived biogeophysical parameters land surface BRDF/albedo, LST (land surface temperature) and NDVI products and in-situ monitoring ground data (as air temperature, aerosols distribution, relative humidity, etc.). Due to deforestation in the periurban areas albedo change appears to be the most significant biogeophysical effect in temperate forests. Satellite data and climate station observations show that surface albedo changes of Baneasa forested zone placed close to a large urban area highly respond to atmospheric pollution influence and climate variations. As the physical climate system is very sensitive to surface albedo, urban/periurban vegetation systems could significantly feedback to the projected climate change modeling scenarios through albedo changes.

Sustained ocean color monitoring is vital to understanding the marine ecosystem. It has been identified as an Essential Climate Variable (ECV) and is a vital parameter in understanding long-term climate change. Furthermore, observations can be beneficial in observing oil spills, harmful algal blooms and the health of fisheries. Space-based remote sensing, through MERIS, SeaWiFS and MODIS instruments, have provided a means of observing the vast area covered by the ocean which would otherwise be impossible using ships alone. However, the large pixel size makes measurements of lakes, rivers, estuaries and coastal zones difficult. Furthermore, retirement of a number of widely used and relied upon ocean observation instruments, particularly MERIS and SeaWiFS, leaves a significant gap in ocean color observation opportunities This paper presents an overview of the SeaHawk mission, a collaborative effort between Clyde Space Ltd., the University of North Carolina Wilmington, Cloudland Instruments, and Goddard Spaceflight Center, funded by the Gordon and Betty Moore Foundation. The goal of the project is to enhance the ability to observe ocean color in high temporal and spatial resolution through use of a low-cost, next-generation ocean color sensor flown aboard a CubeSat. The final product will be 530 times smaller (0.0034 vs 1.81m 3 ) and 115 time less massive (3.4 vs 390.0kg) but with a ground resolution 10 times better whilst maintaining a signal/noise ratio 50% that of SeaWiFs. This paper will describe the objectives of the mission, outline the payload specification and the spacecraft platform to support it.

The Cultural landscapes are witnesses of "the creative genius, social development and the imaginative and spiritual vitality of humanity. They are part of our collective identity", as it is internationally defined and accepted (ICOMOSUNESCO). The need for their protection, management and inclusion in the territorial policies has already been widely accepted and pursued. There is a great number of risks to which the cultural landscapes are exposed, arising mainly from natural (both due to slow geo-physical phenomena as well as hazards) and anthropogenic causes (e.g. urbanisation pressure, agriculture, landscape fragmentation etc.). This paper explores to what extent Earth Observation (EO) technologies can contribute to identify and evaluate the risks to which Cultural Landscapes of Cyprus are exposed, taking into consideration specific phenomena, such as land movements and soil erosion. The research of the paper is illustrated as part of the activities carried out in the CLIMA project - "Cultural Landscape risk Identification, Management and Assessment". It aims to combine the fields of remote sensing technologies, including Sentinel data, and monitoring of cultural landscape for its improved protection and management. Part of this approach will be based on the use of InSAR techniques in order to monitor the temporal evolution of deformations through the detection and measurement of the effects of surface movements caused by various factors. The case study selected for Cyprus is the Nea Paphos archeological site and historical center of Paphos, which are listed as UNESCO World Heritage sites. The interdisciplinary approach adopted in this research was useful to identify major risks affecting the landscape of Cyprus and to classify the most suitable EO methods to assess and map such risks.

The distribution and change of snow coverage are sensitive factors of climate change. In northeast part of China, farmlands are still covered with snow in spring. Since sowing activity can only be done when the snow melted, fields snow coverage monitoring provides reference for the determination of sowing date. Because of the restriction of the sensors and application requirements, current researches on remote sensing of snow focus more on the study of musicale and large scale, rather than the study of small scale, and especially research on snow melting period is rarely reported.HJ-1A/B satellites are parts of little satellite constellation, focusing on environment and disaster monitoring and meteorological forecast. Compared to other data sources, HJ-1A/B satellites both have comparatively higher temporal and spatial resolution and are more conducive to monitor the variations of melting snow coverage at small watershed. This paper was based on HJ-1A/1B data, taking Hongxing farm of Bei’an, Heilongjiang Province, China as the study area. In this paper, we exploited the methods for extraction of snow cover information on farmland in two cases, both HJ-1A/1B CCD with HJ-1B IRS data and just HJ-1A/1B CCD data. The reason we chose the two cases is that, the two optical satellites HJ-1A/B are capable of providing a whole territory coverage period in visible light spectrum in two days, infrared spectrum in four days. So sometimes we can only obtain CCD image. In this case, the method of normalized snow index cannot be used to extract snow coverage information. Using HJ-1A/1B CCD with HJ-1B IRS data, combined with the theory of snow remote sensing monitoring, this paper analyzed spectral response characteristics of HJ-1A/1B satellites data, then the widely used Normalized Difference Snow Index(NDSI) and S3 Index were quoted to the HJ-1A/1B satellites data. The NDSI uses reflectance values of Red and SWIR spectral bands of HJ-1B, and S3 index uses reflectance values of NIR, Red and SWIR spectral bands. With multi-temporal HJ satellite data, the optimal threshold of normalized snow index was determined to divide the farmland into snow covering area, melting snow area and non-snow area. The results are quite similar to each other and of high accuracy, and the melting snow coverage can be well extracted by two types of normalized snow index. When we can only obtain CCD image, we use supervised classification method to extract melting snow coverage. With this method, the accuracy of fields snow coverage extraction is slightly lower than that using normalized snow index methods mentioned above. And in mountain area, the snow coverage area is slightly larger than that is extracted by normalized snow index methods, because the shadows make the color of snow in the valley darker, the supervised classification method divides it into non-snow coverage area, while the normalized snow index method well weakened the effect of shadow. This study shows that extraction accuracy in both cases is assessed, and both of them can meet the needs of practical applications. HJ-1A/1B satellites are conducive to monitor the variations of melting snow coverage over farmland, and they can provide reference for the determination of sowing date.

Recently, frequency and strength of global wildfire are on the increase. The wildfire encourages the climate change through release of GHGs into the atmosphere over one time occur. The effect of wildfire GHGs can be estimate by FRP(fire radiative power), many research using the remote sensing are trying for its efficient produce. A satellite fire product including fire mask and FRP was produced by polar orbit satellite at first, thereafter it was expanded to geostationary satellites for continuous monitoring of wide areas. However, geostationary satellites observing in East Asia no got a standard to produce the fire product yet. This paper described a retrieval of FRP using the COMS(Communication, Ocean and Meteorological satellite) that is a Korean geostationary satellite. The COMS FRP was retrieved MIR(Middle infrared) radiance method which approaches by brightness temperature of single waveband. Our test was presented that large scale wildfires(FRP > 300MW and confidence level > 9) occurred in the each April. The COMS FRP showed MAE = 103.67 MW(16%) with the MODIS. This result represents much as possibility of the FRP in East Asia. This paper is expected to provide to baseline for the FRP in East Asia, and apply to biomass loss and estimate the GHGs. In addition, the COMS FRP will contribute to studies of aerosols, economic losses and ecosystem damages as basic data.

Proceedings of SPIE - The International Society for Optical Engineering, Volume 9229, 2014, Article number 922912 Accurate assessment of water use is an important issue in a globally changing climate and environment, where water is becoming a scarce but essential resource. The concept "?Water Footprint (WF) of a crop is defined as the volume of water consumed for its production, where green and blue WF stand for rain and irrigation water usage, respectively. This indicator provides valuable information for a global assessment of how water resources are used. Remote sensing (RS) provides physically-based, worldwide, and consistent spatial information over space and time, and has been used in hydrological applications in order to estimate relevant variables at different temporal and spatial scales. The paper focuses on exploring and exploiting the potential of using RS techniques and data for WF assessment in agriculture. Based on recent papers initiated in this research topic the investigation focuses on how variables needed in the calculation of water footprint are obtained (based on non RS and on RS approaches), on identifying the inputs required for estimating the WF of crops and whether it is feasible to integrate various RS approaches. The results of this study demonstrate the usefulness of satellite data for water footprint assessment, which were obtained by the Remote Sensing Working Group in the framework of the ESSEM COST Action ES1106, "Assessment of EUROpean AGRIculture WATer use and trade under climate change"? (EURO-AGRIWAT). © 2014 SPIE.

In the quest for a better understanding of climate change, greater importance is attached to monitoring the levels of atmospheric carbon dioxide to gain an improved knowledge of sources and sinks. Remote sensing is a critical tool in this research area and differential absorption lidar (DIAL) is one important technique. The laser is the critical component of a DIAL instrument. This paper describes the development of a laser source for the detection and measurement of carbon dioxide. Publisher PDF

Climate variability and change are risk factors for climate sensitive activities such as forestry. Managing these risks requires “climate knowledge”, i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Thresholding based on biophysical variables derived from time series satellite data is a new approach to classifying forest land cover via remote sensing through use of Normalized Difference Vegetation Index –NDVI and Enhanced vegetation Index- EVI. This paper aims to assess spatio-temporal forest changes through applied time-series Landsat TM, ETM, MODIS Terra/Aqua and IKONOS satellite remote sensing data of Cernica forest area near Bucharest, Romania, during 1990-2011 period. Additional forest biophysical parameter Land Surface Temperature/Emissivity - LST was considered in this paper. This information is complemented by in-situ monitoring data (field measurements, data collection) together with modeling tools (theoretical developments, mathematical and bio-geophysical parameterization, statistics of the main urban structures in their interdependency) and spatial analysis methods.

Understanding the earth's climate and collecting the requisite signatures over the next 10, 20, 30 years is a shared mandate by many of the world's governments. But there remains a daunting challenge to bridge scientific missions to 'operational' systems that truly support the demands of decision makers, scientific investigators and global users' requirements for trusted data. For this Part III paper, we will examine the required components of a coupled modeling framework to perform, with benefit of adjoint constraints , optimal forward modeling of the climate's GHG's for both demonstration and verification. Interrogating such forward modeling in detail will help uncover the most efficient and sufficient set of critical climate parameters & metrics needed to systematic capture and attribute climate monitoring environmental records. This in turn would allow globally trusted algorithms to produce climate products that the world's governments can use to most accurately assess man's impacts on earth's climate and promote informed decisions sustaining the earth's ability to support life. This paper is the climate modeling based extension to two earlier papers from 2009 & 2010.

This paper apply an statistical technique to correct radiometric data measured by Advanced Very High Resolution Radiometers(AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites(POES). This paper study Normalized Difference Vegetation Index (NDVI) stability in the NOAA/NESDIS Global Vegetation Index (GVI) data for the period 1982-2003. AVHRR weekly data for the five NOAA afternoon satellites NOAA-7, NOAA-9, NOAA-11, NOAA-14, and NOAA-16 are used for the China dataset, for it includes a wide variety or different ecosystems represented globally. GVI has found wide use for studying and monitoring land surface, atmosphere, and recently for analyzing climate and environmental changes. Unfortunately the POES AVHRR data, though informative, can not be directly used in climate change studies because of the orbital drift in the NOAA satellites over these satellites' life time. This orbital drift introduces errors in AVHRR data sets for some satellites. To correct this error of satellite data, this paper implements Empirical Distribution Function (EDF) which is a statistical technique to generate error free long-term time-series for GVI data sets. We can use the same methodology globally to create vegetation index to improve the climatology.

This paper apply an statistical technique to correct radiometric data measured by Advanced Very High Resolution Radiometers(AVHRR) onboard the National Oceanic and Atmospheric Administration (NOAA) Polar Orbiting Environmental Satellites(POES). This paper study Normalized Difference Vegetation Index (NDVI) stability in the NOAA/NESDIS Global Vegetation Index (GVI) data for the period 1982-2003. AVHRR weekly data for the five NOAA afternoon satellites NOAA-7, NOAA-9, NOAA-11, NOAA-14, and NOAA-16 are used for the China dataset, for it includes a wide variety or different ecosystems represented globally. GVI has found wide use for studying and monitoring land surface, atmosphere, and recently for analyzing climate and environmental changes. Unfortunately the POES AVHRR data, though informative, can not be directly used in climate change studies because of the orbital drift in the NOAA satellites over these satellites' life time. This orbital drift introduces errors in AVHRR data sets for some satellites. To correct this error of satellite data, this paper implements Empirical Distribution Function (EDF) which is a statistical technique to generate error free long-term time-series for GVI data sets. It allows one to represent any global ecosystem from desert to tropical forest and to correct deviations in satellite data due to orbit degradation. The corrected datasets can be used as proxy to study climate change, epidemic analysis, and drought prediction etc.

The vegetation covering land surface is main component of biosphere which is one of five significant spheres on the earth. The vegetation plays a very important role on the natural environment conservation and improvement to keep human being's living environment evergreen while the vegetation supplies many natural resources to human living and development continuously. Under the background of global warming, vegetation is changing as climate changes. It is not doubt that human activities have great effects on the vegetation dynamic. In general, there are two aspects of the interaction between vegetation and climate, the climatic adaptation of vegetation and the vegetation feedback on climate. On the base of the research on the long term vegetation growth dynamics, it can be found out the vegetation adaptation to climate change. The dynamic change of vegetation is the direct indicator of the ecological environment changes. Therefore, study on the dynamic change of vegetation will be very interest and useful. In this paper, the vegetation change in special region of China will be described in detail. In addition to the methods of the long term in-situ observation of vegetation, remote sensing technologies can also be used to study the long time series vegetation dynamic. The widely used NDVI was often employed to monitor the status of vegetation growth. Actually, NDVI can indicate the vigor and the fractional cover of vegetation effectively. So the long time series of NDVI datasets are a very valuable data source supporting the study on the long term vegetation dynamics. Since 1980, a series of NOAA satellites have been launched successfully, which have already supplied more than 20 years NOAA/AVHRR satellites data. In this paper, we selected Ningxia Hui autonomic region of China as the case study area and used 20 years pathfinder AVHRR NDVI data to carry out the case study on the vegetation dynamics in order to further understand the phenomena of 20 years vegetation dynamics of the whole Ningxia region. Ningxia Hui autonomic region is one of provinces in west china. Ningxia is a small region with square area of about 66, 4000 km2. Ningxia has special land cover with irrigated crop land in north and natural grass land in central and south. In addition to NDVI data, we also collected land cover and land use data and administrative border vector data with the scale of 1:4,000,000 and other data. The results show that (1)vegetation dynamic of Ningxia presents the characters of one season per year with the length of the growth season from the first decade May to the middle decade October and the range of NDVI value 0.05-0.25; the season characters vary with the local area; the max value of NDVI in the central dry area is only 0.2 and the date of reaching the peak of time series NDVI in the irrigation area is the latest while that in the south mountain area is the earliest; the Helan mountain area presents the characters of forest and the range of NDVI is narrower than those in the irrigation area and the south mountain area and higher in winter than those in two area above; in recent 18 years, the length of growth season in whole Ningxia has prolonged one decade, mainly in spring one decade in advance.(2) from 1982 to 1999, the trend of the whole Ningxia mean NDVI is increasing and presents the stable or better of vegetation growth; compared to NDVI in 1980's, NDVI in 1990's has increased already and the anomaly of growth season mean NDVI is mainly negative in 1980's while mainly positive in 1990's; NDVI in the central dry area is the lowest while NDVI in the Helan mountain is the highest; the values of NDVI in the irrigation area, the Helan mountain area and the south mountain area are higher than that of the whole Ningxia; the increasing trend of vegetation dynamic in the irrigation area, the south mountain area and the central dry area is similar with the whole Ningxia while the trend in the Helan mountain area is increasing from 1982-1988 but decreasing after 1988.

The northwestern Hebei mountains area is located in the transitional area from the subhumid and temperate zone to the semiarid zone, pertaining to the ecologically fragile area. Closing to Beijing and Tianjin, the area is in the windward and upriver area of the two cities. It is of great significance to study the climate change in this area for the purpose of understanding the law of local ecological development and constructing the Beijing-Tianjin ecological protective barrier. Based on the average monthly temperatures and precipitation data collected by three weather stations in the northwestern mountains area between 1956 and 2001, this paper studied the climate changes in this area over the past 46 years, by analyzing the average temperature anomaly and precipitation anomaly of yearly and quarterly, calculating the five years sliding average value of them, and applying the way of univariate linear regression to get linear regression equation of the five years sliding average value. Preliminary research was conducted on the average temperature anomaly and precipitation anomaly values and their development trends with the adoption of correlation analysis. Discussion on factors causing the climate change was carried out. The result shows that the average temperature was on an upward trend in the period 1956-2001 at a rate of 0.41 deg. Celcius /10a, with the highest growth rate seen in winter. In contrast, the annual precipitation was on decrease during the same period at a rate of 7.765mm/10a, with the highest rate seen in summer. The area under research is turning warmer and drier. The correlation analysis indicates no apparent correlation between the upward annual average temperature and the downward precipitation, which should be regarded as a process of independent change. This paper also explores the possible causes that have affected the climate in this area, including the global warming, the climate change in a larger area such as the circulation of water vapor in East Asia as well as the changes to local ecological environment such as pollution, greenhouse gas emissions, increased particulate matters in the atmosphere, ecological damages, etc.

The aim of the paper is mountain forest landuse/cover changes analysis due to anthropogenic and climatic stressors. Our analysis indicates a potentially application of threshold techniques to land-cover classification and changes analysis due to climatic effects for Romanian Carpathian mountain forest ecosystem. The climate of the Carpathians is moderately cool and humid, with both temperature and precipitation strongly correlated with elevation. Extreme climatic events and anthropogenic effects have a strong impact on forest ecosystem. Specific aim of this paper is to assess, forecast, and mitigate the risks of air pollution and climatic changes and extreme events on mountain forest ecosystem in Prahova Valley, Romanian Carpathians test area and to provide early warning strategies on the basis of spectral information derived from Landsat TM, ETM and MODIS satellite data over 1987- 2007 period. The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Tibetan Plateau serves as the sources of several big rivers such as Yangtze River and Yellow River. Due to the high elevation of the plateau, it has profound thermal and dynamical influence on both local and global climate and atmospheric circulation. Land surface temperature (LST) plays a significant role in climate change and glacier melting. In this paper we present our study on mapping land surface temperature variations for the years 2005-2006 in the plateau using MODIS satellite data. Since the plateau has a very rough ground surface that is difficult to estimate the necessary parameters for the mapping, we have developed a practical approach for LST retrieval from the MODIS thermal band data. The approach was alternated from the split window algorithm proposed by Qin et al. (2001) for NOAA-AVHRR data. Detailed methods for atmospheric transmittance and ground emissivity have been presented in the paper. Results from our study indicate that ground temperature in the plateau is featured with obvious spatial and temporal variations. Generally the temperature in winter and spring is less than 0°C and it is also not very high in summer, due to the high altitude. Because of topological form, Chaidamu Basin of the plateau has the highest temperature in summer, usually high up to above 40°C. Our study provides an alternative to understand the environmental changes in the plateau that shape significant impacts on atmospheric dynamics of East Asia and South Asia.

During the past few years, the European Space Agency has launched several projects related to forest fires from global to local scales. The ATSR World Fire Atlas (WFA) project started in late 1995 and is still running today. It provides the longest time series ever produced on the global distribution of active fires. The WFA consists of 12 years of coherent and consistent data sets. The night time fire occurrences are derived from the 3.7 micron channel on-board the ATSR instrument series hosted by the ERS-2 and ENVISAT satellites. The ATSR WFA products were validated first in 1998 with the support of IGBP and more recently by extensive comparisons with existing data sets on forest fires events. A smooth transition from the ERS-2 ATSR-2 to the ENVISAT AATSR has been performed in January 2003 and the quality of the WFA products continuity verified. The ATSR WFA products are available in near real time since May 2006. The distribution of the ATSR WFA products will be thoroughly analyzed in this paper and a synthesis of the work performed by more than 900 registered users will be presented. The GlobCarbon project started in early 2003 with the objective to develop a service for the production of multi-year / multi-sensors global level 3 Land products to be used as input to carbon assimilation models. Understanding the spatial and temporal variation in carbon fluxes is essential to constrain models that predict climate change. However our current knowledge of these spatial and temporal patterns is uncertain, particularly over land. One of the bio-geophysical parameters that the GlobCarbon project aims to measure is the fully calibrated estimate of the burned areas quasi-independent of the original satellite sensor. These burned areas estimates are used in dynamic global vegetation models, a central component of the IGBP-IHDP-WCRP Global Carbon Cycle Joint Project. The service will feature global estimates of burned areas amongst other variables from 1998 to 2007, derived from Earth Observation sensors (ERS-2 ATSR-2, ENVISAT AATSR and SPOT VEGETATION). Finally the RISK-EOS project started in 2003 under the framework of the Global Monitoring for Environment and Security (GMES) initiative, with the objective to establish a network of European service providers for the provision of geoinformation services in support to the risk management of meteorological hazards (floods and fires). The Fire component of RISK-EOS feature two main services: the Burn Scar Mapping (BSM) service that provides some seasonal mapping of forests and semi-natural burned areas at high spatial resolution (minimum mapping unit of 3 to 5 ha); and the Regional Fire Monitoring (RFM) service that provides near real time observation of active fires, based on middle resolution satellite data (AQUA/TERRA MODIS and MSG SEVIRI). The RISK-EOS BSM service builds on the achievements of ITALSCAR, a demonstration project for the yearly mapping of burned areas in Italy, using the LANDSAT Thematic Mapper sensor. The paper will provide a synthesis of the RISK-EOS products validation and utility reports collected during the 2006 summer season.

According to the theory of abrupt climatic change, the regional economic development process in Jiangsu province since 1978 is divided into three periods in this paper. Then the paper employs urban centrality index and time cost for transportation, instead of the city scale and the distance factor, to modify the original potential model. Based on the grid arithmetic of GIS methodology, the paper points out the ranges of urban economic effect regions (UEERs) for central cities at different rank in Jiangsu province of main years. Accordingly, Jiangsu province can be separated into different rank of urban economic effect regions. Consequently, the characteristics of UEERs in Jiangsu province since 1978 can be summarized as below: (1) the change in spatial structure from South-North to East-West, (2) the expanding tendency to north for UEERs in the south, (3) the emergence of new central cities in southern Jiangsu province. Furthermore, the mechanism of evolution of UEERs in Jiangsu is also analyzed in this paper, and the development of transportation axes, the diversities of economic development level and the disparities among the input of social product factors are the three main reasons.

In recent years, the impacts of natural disaster are more and more severe on coastal lowland areas. Aim to the threat of climate change and sea level rise, the natural disaster reduction in coastal lowland areas is paid highly attention. Based on a number of literatures, the paper summarizes the categories and characteristic of natural disasters emerging in coastal lowland areas, such as windstorm and storm surge, hurricanes and hurricane winds, tsunamis and floods, and analyzes the most devastating natural disasters in coastal lowland in the world 2005. The paper also summarizes the effects of typhoons on the coastal lowland areas of China in 2005 and review to analyze the natural disaster mitigation measures and its researches. At last, the paper discusses the vulnerability assessment and response strategies.

The state-of-the-art electro-optical sensors being designed for today's space-based environmental applications require a complete characterization and thorough calibration. This is especially true for sensors designed to assess global climate change, which require very small uncertainties. This paper describes a system-level approach that addresses each phase of calibration, from planning to on-orbit operations. This approach encourages early planning and continuity of effort throughout the lifetime of the project (pre- and post-flight) to promote an optimum calibration approach that will minimize uncertainty for the intended application. This paper also discusses considerations for component level characterization, ground calibration and standards, in-flight calibration sources and trending, and in-flight validation assessment.

We present results of studies of instrument concepts for a spaceborne imaging Fabry-Perot interferometer to measure tropospheric ozone. Ozone is recognized as one of the most important trace constituents of the troposphere. Tropospheric ozone is responsible for acute and chronic human health problems and contributes toward destruction of plant and animal populations. Furthermore, it is a greenhouse gas and contributes toward radiative forcing and climate change. Tropospheric ozone levels have been increasing and will continue to do so as concentrations of precursor gases (oxides of nitrogen, methane, and other hydrocarbons) necessary for the photochemical formation of tropospheric ozone continue to rise. Space-based detection and monitoring of tropospheric ozone is critical for enhancing scientific understanding of creation and transport of this important trace gas and for providing data needed to help develop strategies for mitigating impacts of exposure to elevated concentrations of tropospheric ozone. Measurement concept details are discussed in a companion paper by Larar et al. Development of an airborne prototype instrument for this application is discussed by Cook et al. in another companion paper.

With the intensification of global warming, low-carbon city construction has become an inevitable trend to curb climate change and seek sustainable development. As an important low-carbon indicator, urban carbon balance has become a research hotspot of the urban ecosystems. This paper has taken Tianjin as an example, quantified the changing trend of urban carbon balance from 2002 to 2030 through the simulation of system dynamics model, and made simulation prediction for four different development scenarios. The research results showed that Tianjin's carbon balance is in a state of significant deficit growth by 2030, the growth rate of carbon emissions will be about 8.5-10.1%, and there is no significant change in carbon sinks, which can offset about 2.3%~6.4% of carbon emission. Compared with the other three scenarios, the scenario Ⅳ has the stable carbon balance and better comprehensive development benefits. The indicators and results of this model can provide a reference for the sustainable development and low-carbon planning of Tianjin.

Climate change represents the biggest global threat of the 21st century. This has been widely recognized and is currently responded to by major international initiatives, summarizing the most pressing, globally relevant requirements in addressing the effects of a changing climate, such as the United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement, the UN’s “2030 Agenda for Sustainable Development” and the Sendai Framework for Disaster Risk Reduction 2015–2030. The European Space Agency (ESA) is already addressing a large number of the requirements that respond to the above main drivers for climate action through being a main developer of European Earth Observation (EO) capabilities to deliver climate science and services. ESA’s satellites provide the global view, enabling the science community to detect signs of change, identify significant trends and constrain the models to predict the future. Through its role as a major provider of systematic and global climate observations ESA interacts with a number of international organisations, stakeholders and users, within the climate landscape that are working toward strengthening the scientific understanding and projection of climate and addressing the consequences of future change. One of the keystones of ESA’s climate activities is the Climate Change Initiative (CCI), which has been running for more than 10 years and is led by the ESA Climate Office. This unique scientific effort involves ca. 450 world-leading experts across ESA Member States to generate global multi-mission and multi-decadal datasets satisfying the requirements for 22 Essential Climate Variables (ECVs) defined by the Global Climate Observing System (GCOS), on behalf of UNFCCC. These datasets have fully characterised uncertainties and are validated using independent, traceable, in-situ measurements. They provide an impartial yardstick to understand climate processes and to improve and validate climate models, thereby enhancing the quality, credibility and exploitation of model predictions. In association with Earth System Models (ESMs), CCI data also provide the observational record to study drivers, interactions and feedbacks due to climate change, as well as reservoirs, teleconnections, tipping points, global energy, water and carbon budgets and other Earth-system cycles, etc. The scientific results of the CCI programme, published in more than 900 papers to date, are a major contribution to the physical science base of IPCC Assessment Reports. The keynote will provide an assessment on the challenges and opportunities that space-borne data provide in our quest to tackle climate change, and will focus on the current and future satellite missions developed by ESA, underlying data storage and processing systems and how users will be able to integrate such data into potential scientific and commercial applications.

Remote sensing of the Earth allows receiving medium, high spatial resolution, and hyperspectral measurements from spacecraft. This study presents a remote sensing application using time-series satellite images to monitor solid waste disposal facilities (WDF) of northern and high mountainous areas with landfills. This study develops a mathematical model describing the physicochemical process of changing the natural state of the snowy regions of the Earth. This technique is directly related to the landfill's physicochemical and biological processes, which can be assessed using space monitoring data. This is relevant for the implementation of geological monitoring of territories covered by snow cover, particularly for the regions of the North Caucasus. It also studies the consequences of climate change on forming the biomedical component of the process under study. The paper proposes a methodology and a mathematical model of the impact of solid domestic and industrial waste on the snow cover using remote sensing technologies. The work uses the methods of fractal-percolation, chemical, biological, and regression analysis. The algorithm results are shown on the example of satellite images of the mountainous territories of the North Caucasus.

The impact of climate change on snow cover evolution is evident. Increasing amounts of winter precipitation as well as rising temperatures are causing the winter snow cover to change more and more rapidly within one season. To quantify the direct effects on hydrological cycles, spatially and temporally high-resolution information on snow height and the amount of water stored as snow (Snow Water Equivalent, SWE) is required on watershed scales. This paper presents the concept for a novel airborne light detection and ranging (LiDAR) system combining high-resolution snow height mapping with co-registered spatial information on the water content of the snowpack. Based on the optical characteristics of snow, we outline a detailed plan for dual-wavelength LiDAR sensor working at wavelengths of 1030 nm and 515 nm. By comparing the intensities received in the two channels, snow cover parameters like the effective grain size can be inferred. By means of recent snow hydrological models, from these data and the topographic snow depth maps then high resolution SWE maps can be deduced. We supplement our outline with conceptual LiDAR snow depth and reflectance measurements using a commercially available system, pointing out the impact of view angle dependence of received intensity and general applicability for future airborne LiDAR surveys.

The paper deals with climate change and global warning and concentrates on the various forms of renewable energy, mainly Photovoltaics, Solar Thermal, Biomass, Geothermal, Wave, Hydro and Wind Energy. Specific examples will be placed on Photovoltaic applications and the future prospects of this discipline to meet 20% of the electricity generated on a global scale by the year 2020. The paper discusses the various fundings and programs available around the world in renewable energy and concludes that renewable energy is the best energy strategy for any country.

The study of urban heat islands (UHI) is of great importance in the context of climate change (CC) and global warming. Cities accumulate heat in urban land covers as well as in built infrastructures, representing true islands of heat in relation to their rural (less artificialized) environment. The densest urban spaces as well as the industrial and commercial areas are characterized by accumulating more heat during the day. On the other hand, the areas of lower density, the Urban Sprawl, tend to have a better climatic behaviour. The lower density as well as the greater amount of vegetation in the Urban Sprawl areas reduce the UHI during daylight hours. Nevertheless, the literature on urban climate has highlighted the singular importance of the nighttime UHI. It is during the night that the effects of UHI become more apparent, due to the low cooling capacity of urban construction materials and is during nighttime that temperatures can cause higher health risks, leading to the aggravation of negative impacts on people’s health and comfort in extreme events such as heat waves becoming more and more frequent and lasting longer. However, the study of nocturnal UHIs is still poorly developed, due to the structural problems regarding the availability of land surface and air temperature data for night time. This paper aims to develop a model for nocturnal UHI using data from Landsat thermal bands (with spatial resolution of 30 square meters per pixel) and contrasting Landsat's very limited nighttime images with daytime ones. The contrast allows the construction of “cooling” models of the LST based on geographical (longitude, latitude, distance to the sea, DTM, slope, orientation, etc.) and land covers characteristics (density, vegetation and building indexes, impervious surface, and others parameters). Said models will allow evaluating the nighttime LST of the different urban landscapes: historical centers, "ensanches", discontinuous urban fabrics (of different densities), scattered building areas and industrial and commercial areas, trying to clarify the nightly UHI of Urban Sprawl. The case study is the Metropolitan Area of Barcelona (636 km2, 3.3 million inhabitants).

The paper discusses the trends in air temperature and NDVI during the vegetation period for the territory of Western Siberia. The increase in NDVI values is observed with significant positive trends in air temperature in some months of the spring-summer period, both for the taiga zone and for the tundra zone. The trends of air temperature and NDVI for the taiga and tundra zones from April to October 1982-2015 have been calculated. The spatial distribution of air temperature and NDVI trends in the territory under consideration is non-uniform. The greatest contribution to the changes in the vegetation cover during the growing season is made by the temperature conditions of April and May for taiga, and of June for tundra.

The paper is devoted to large-scale and zonal atmospheric factors of climate variability over the territory of the Baikal region. This territory is considered to be one of the regions with highest rates of climate change according to Russian Federal Service for Hydrometeorology and Environmental Monitoring (Roshydromet). The investigation was made of high- and low-frequency components in multidecadal timescales of climatic indices dynamics on the basis of trend, correlation, and spectrum analyses. The climatic indices determine and distinguish variability in pressure fields and geopotential at high latitudes in the Northern hemisphere, in the northern parts of the Atlantic and Pacific oceans throughout the time period of 1950–2017. Particular emphasis was put on searching for causes of increasingly arid climate in the Baikal region in summer months of 2000–2017, when the number of forest fires in the region rose dramatically. Winds having a southerly component at the height of middle troposphere were identified as the contributing factor for enhancing heat advection.

In a number of works, it is shown that the reaction of extratropical circulation to strong eruptions of tropical volcanoes is the strengthening of the Northern polar vortex. The observations show that at the winter following after the autumn eruptions of volcanoes in the tropical belt there is a positive anomaly in the intensity of the polar vortex. In this paper, the reaction of the Northern polar vortex to tropical volcanic eruptions is numerically investigated. The possible mechanism of vortex amplification is shown.

Climate change is an environmental threat, and to keep global warming under 2°C, actions are needed to prevent escalating negative effects like droughts and flooding. Cutting emissions might not suffice, and other methods might be needed. One suggested method is Oceanic Iron Fertilization (OIF), where oceans are fertilized with iron to increase primary production and sequestration of CO2 from atmosphere. OIF has been criticized as risky due to unknown sideeffects. Fertilization research was explored in-depth to identify risks and opportunities, and how it could be assisted by remote sensing. The Southern Ocean has been a focus of research for OIF. This region is productive, but limited by the short growth season and lack of iron. One factor in this Southern Ocean region is whale numbers. Whales are effective fertilizers, diving deep to hunt and bringing important nutrients to the surface. Whales have been focused on this paper, as OIF within their natural habitat could resemble natural fertilization. Locating whales can be done with remote sensing. Satellites can also play a role in iron fertilization by tracking resulting algal blooms. The Southern Ocean has highest potential for OIF, and the option should be explored with remote sensing and whale knowledge.

Climate changes and rapid urbanization are the main factors affecting forest vegetation land cover around the globe. Satellite remote sensing data provide important information to detect changes in forest landscapes over long time periods in contrast to conventional approaches. Satellite remote sensing provides a useful tool to capture the temporal dynamics of forest vegetation change in response to climate shifts, at spatial resolutions fine enough to capture the spatial heterogeneity. In this paper, we present an integrated, standardized approach that aims at combining remote sensing data provided by different sensors, available for a long-term period (2000-2018). This multi-sensor and multi-temporal approach detects Cernica-Branesti periurban forest vegetation dynamics based on derived biophysical parameters within the highly dynamic city of Bucharest, as a test case. Landsat TM/ETM/OLI, MODIS Terra/Aqua, and Sentinel 2 data are combined in an integrated procedure to locate forest disturbances in relation with potential climate and anthropogenic drivers. To apply the approach for detecting forest land cover changes, the MODIS Normalized Difference Vegetation Index/Enhanced Vegetation Index (NDVI/EVI), and Leaf Area Index (LAI) data are used to provide forest vegetation change detection information in relation with land surface temperature (LST) and climate stressors and to monitor forest vegetation phenological variations. Correlations between NDVI/EVI time series and climatic variables were computed. Forest vegetation dynamics at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system.

This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables for Bucharest and Timisoara cities in Romania. Satellite remote sensing provides a cost-effective and time-saving methodology for spatio-temporal analyses of land surface temperature (Ts) distribution and urban thermal environment monitoring. Time series satellite remote sensing data from Landsat TM/ETM+/OLI, MODIS Terra/Aqua and NOAA AVHRR were used to assess urban vegetation land cover– temperature interactions over period between 2000 and 2018 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. For this purpose, a set of meteorological and climatic data recorded in synoptic stations were used. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. Results show that the city area ratio of impervious surface in both towns Bucharest and Timisoara increased significantly during investigated period, the intensity of urban heat island and heat wave events being most significant. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively.

Due to global warming and climate changes forest ecosystems in Romania experienced environmental degradation. Climate models scenaria evidenced that some of the most severe weather events could become more frequent in Romania over the next 50 to 100 years. In the case of Carpathian mountain forests, winter storms, heavy rains, summer draughts and heat waves are considered main keys of climate risks, particularly in prealpine and alpine areas. Forest phenology is a multi-scale phenomenon, arising from processes in leaves and trees, which controls carbon and water cycles, observable at the ecosystem scale (e.g. eddy flux measurements), very important to characterize the relation between phenophase transition events at different spatial scales. Through time series of the Normalized Difference Vegetation Index (NDVI), provided by MODIS Terra/Aqua data is possible to examine trends and seasonality in forest vegetation Leaf Area Index (LAI) and in primary productivity, as well as to identify the impacts of human disturbances (clearcutting, etc.). In order to extract forest phenological changes, this paper applied fusion technique to multitemporal satellite imagery data (Landsat TM/ETM/OLI, Sentinel 2 and MODIS Terra/Aqua satellite data) for a mountain forest ecosystem placed in Prahova Valley, South Carpathians in Romania over 2000-2018 period. Effects of climate extremes on forests can have both short-term and long-term implications for standing biomass, tree health and species composition. The preservation and enhancement of mountain forest vegetation cover in natural, semi-natural forestry ecosystems is an essential factor in sustaining environmental health and averting natural hazards.

Aerosol and water vapor are two important atmospheric parameters. The accurate quantification of diurnal variation of these parameters are very useful for environment assessment and climate change studies. A moveable, compact and unattended lidar system based on modular design is developed for aerosol extinction coefficients and water vapor mixing ratios measurements. In the southern suburbs of Beijing, the continuous observation was carried out by this lidar since the middle of the year of 2017. The lidar equipment is presented and the case study is also described in this paper. The observational results show that the lidar kept a very good status from the long-time continuous measurements which is suitable for networking especially in meteorological research field.

Due to anthropogenic and climatic changes, Carpathian Mountains forests in Romania experience environmental degradation. As a result of global climate change, there is growing evidence that some of the most severe weather events could become more frequent in Romania over the next 50 to 100 years. In the case of Carpathian mountain forests, winter storms and heat waves are considered key climate risks, particularly in prealpine and alpine areas. Effects of climate extremes on forests can have both short-term and long-term implications for standing biomass, tree health and species composition. The preservation and enhancement of mountain forest vegetation cover in natural, semi-natural forestry ecosystems is an essential factor in sustaining environmental health and averting natural hazards. This paper aims to: (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from satellite time series NOAA AVHRR, MODIS Terra/Aqua and Landsat TM/ETM+/OLI NDVI and LAI data recorded during 2000-2016 period correlated with meteorological parameters, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts of climate changes and extreme events on Carpathian mountain forest system in Romania. The response of forest land cover vegetation in Carpathian Mountains, Romania to climatic factors varies in different seasons of the years, the diverse vegetation feedbacks to climate changes being related to different vegetation characteristics and meteorological conditions. Based on integrated analysis of satellite and field data was concluded that forest ecosystem functions are responsible of the relationships between mountain specific vegetation and climate.

Stratification is of critical importance to the circulation, mixing and productivity of the ocean, and is expected to be modified by climate change. Stratification is also understood to affect the surface aggregation of pelagic fish and hence the foraging behaviour and distribution of their predators such as seabirds and cetaceans. Hence it would be prudent to monitor the stratification of the global ocean, though this is currently only possible using in situ sampling, profiling buoys or underwater autonomous vehicles. Earth observation (EO) sensors cannot directly detect stratification, but can observe surface features related to the presence of stratification, for example shelf-sea fronts that separate tidally-mixed water from seasonally stratified water. This paper describes a novel algorithm that accumulates evidence for stratification from a sequence of oceanic front maps, and discusses preliminary results in comparison with in situ data and simulations from 3D hydrodynamic models. In certain regions, this method can reveal the timing of the seasonal onset and breakdown of stratification.

Nepal is one of the poorest nations of the world and the Koshi Basin includes some of the poorest regions of this country. It’s farming system is subsistence agriculture, mainly rainfed, with crop productivity among the lowest in South Asia. Nepal is also severely impacted by climate changes, such as retreat of glaciers, rise in temperature, erratic rainfalls and increase in frequency of extreme weather. This paper describes the spatio-temporal evolution of cultivated land in Dudh Koshi during the last four decades (1970s-2010s), by mapping the farming of its four main cereals in the districts of Solukhumbu, Okhaldunga and Kothang from space. The analysis of satellite time series showed a 10% of increment in farmland from 1970s to 1990s, and about 60% in the following twenty years. With a shift of cropping to higher altitudes. Data belonging to of the second twenty years are strongly correlated with the population growth observed in the same period (0.97

Proceedings of SPIE - The International Society for Optical Engineering, 2017, Volume 10429, Article number 1042906 The aim of this article is to present the importance of a permanent state-of-the-art atmospheric remote sensing ground based station in the region of the Eastern Mediterranean and Middle East (EMME). The Eratosthenes Research Centre (ERC) with the vision to become a Centre of Excellence for Earth Surveillance and Space-Based Monitoring of the Environment (EXCELSIOR H2020: Teaming project) already operates (within Phase 1) a fully established EARLINETt-Cloudnet supersite at Limassol, Cyprus, for a period of 2 years, in close collaboration with the German Leibniz Institute for Tropospheric Research (TROPOS), The scientific aspects of this prototype-like field campaign CyCARE (Cyprus Cloud Aerosol and Rain Experiment) - a common initiative between the Cyprus University of Technology (CUT), Limassol and TROPOS- are presented in this paper. Cy-CARE has been designed by TROPOS and CUT to fill a gap in the understanding of aerosol-cloud interaction in one of the key regions of climate change and how precipitation formation is influenced by varying aerosol/pollution and meteorological conditions The guiding questions are: How may rain patterns change in future and what may be the consequences of climate change in arid regions such as EMME. EXCELSIOR is a team effort between CUT (acting as the coordinator), the German Aerospace Centre (DLR), the Institute for Astronomy and Astrophysics Space Applications and Remote Sensing of the National Observatory of Athens (NOA), TROPOS and the Cyprus Department of Electronic Communications of the Ministry of Transport, Communications and Works (DEC-MTCW) who will work together to improve the network structures significantly, resulting in Cyprus being regarded as a cornerstone of a European Network of active remote sensing of the atmosphere.

The Global Change Observation Mission (GCOM) aims to establish and demonstrate a global, long-term satelliteobserving system to measure essential geophysical parameters to facilitate understanding the global water circulation and climate change, and eventually contribute to improving future climate projection through a collaborative framework with climate model institutions. GCOM consists of two polar orbiting satellite observing systems, GCOM-W (Water) and GCOM-C (Climate). The first satellite, GCOM-W with Advance Microwave Radiometer -2 (AMSR-2), was already launched in 2012 and has been observing continuously. The follower satellite, GCOM-C with Second Generation Global Imager (SGLI), will be launched in Japanese fiscal year 2017. SGLI enables a new generation of operational moderate resolution-imaging capabilities following the legacy of the GLI on ADEOS-II (Advanced Earth Observing Satellite-II) satellite. The SGLI empowers surface and atmospheric measurements related to the carbon cycle and radiation budget, with two radiometers of Visible and Near Infrared Radiometer (VNR) and Infrared Scanning Radiometer (IRS) which perform a wide-band (380nm-12μm) optical observation not only with as wide as 1150-1400km FOV (field of view) but also with as high as 250-500m resolution. Also, polarization and along-track slant view observation are quite characteristic of SGLI, providing the sensor data records for more than 28 standard products and 23 research products including clouds, aerosols, ocean color, vegetation, snow and ice, and other applications. Sensor instrument proto-flight tests including optical characterization tests such as radiometric and geometric were completed, and satellite system proto-flight tests have finished including thermal vacuum, vibration and acoustic test. In this paper, the pre-launch phase instrument characterization of SGLI flight model and status of GCOM-C satellite system flight model along with the overview of them will be described. Especially we focus on the pre-launch geometric and radiometric performance test results, in-orbit calibration activities and methodologies: VNR's on-board calibrator, IRS's on-board calibrator and calibration maneuver, and in-orbit verification plan during a commissioning phase lasting approximately 3 months.

Snow cover information has great significance for monitoring and preventing snowstorms. With the development of satellite technology, geostationary satellites are playing more important roles in snow monitoring. Currently, cloud interference is a serious problem for obtaining accurate snow cover information. Therefore, the cloud pixels located in the MODIS snow products are usually replaced by cloud-free pixels around the day, which ignores snow cover dynamics. FengYun-2(FY-2) is the first generation of geostationary satellite in our country which complements the polar orbit satellite. The snow cover monitoring of Northeast China using FY-2G data in January and February 2016 is introduced in this paper. First of all, geometric and radiometric corrections are carried out for visible and infrared channels. Secondly, snow cover information is extracted according to its characteristics in different channels. Multi-threshold judgment methods for the different land types and similarity separation techniques are combined to discriminate snow and cloud. Furthermore, multi-temporal data is used to eliminate cloud effect. Finally, the experimental results are compared with the MOD10A1 and MYD10A1 (MODIS daily snow cover) product. The MODIS product can provide higher resolution of the snow cover information in cloudless conditions. Multi-temporal FY-2G data can get more accurate snow cover information in cloudy conditions, which is beneficial for monitoring snowstorms and climate changes.

This paper is to answer the question “How can inter- and intra-annual variability in the ocean be leveraged by the submarine Force?” through quantifying inter- and intra-annual variability in (T, S) fields and in turn underwater acoustic characteristics such as transmission loss, signal excess, and range of detection. The Navy’s Generalized Digital Environmental Model (GDEM) is the climatological monthly mean data and represents mean annual variability. An optimal spectral decomposition method is used to produce a synoptic monthly gridded (SMG) (T, S) dataset for the world oceans with 1o×1o horizontal resolution, 28 vertical levels (surface to 3,000 m depth), monthly time increment from January 1945 to December 2014 now available at the NOAA/NCEI website: http://data.nodc.noaa.gov/cgi- bin/iso?id=gov.noaa.nodc:0140938. The sound velocity decreases from 1945 to 1975 and increases afterwards due to global climate change. Effect of the inter- and intra-annual (T, S) variability on acoustic propagation in the Yellow Sea is investigated using a well-developed acoustic model (Bellhop) in frequencies from 3.5 kHz to 5 kHz with sound velocity profile (SVP) calculated from GDEM and SMG datasets, various bottom types (silty clay, fine sand, gravelly mud, sandy mud, and cobble or gravel) from the NAVOCEANO‘s High Frequency Environmental Algorithms (HFEVA), source and receiver depths. Acoustic propagation ranges are extended drastically due to the inter-annual variability in comparison with the climatological SVP (from GDEM). Submarines’ vulnerability of detection as its depth varies and avoidance of short acoustic range due to inter-annual variability are also discussed.

The paper presents lecture materials given at the Nineteenth International Conference and School on Quantum Electronics “Laser Physics and Applications” (19th ICSQE) in 2016, Sozopol, Bulgaria and contains the results of the 10-year research of Belarusian Antarctic expeditions to study the atmospheric aerosol and Earth surface in Antarctica. The works focus on the studying variability and trends of aerosol, cloud and snow characteristics in the Antarctic and the links of these processes with the long range transport of atmospheric pollutants and climate changes.

Presented is a recently started Russian Science Foundation project “Virtual computational information environment for analysis, evaluation and prediction of the impacts of global climate change on the environment and climate of a selected region” aimed at development of accessible in Internet a computation and information environment providing unskilled in numerical modeling and software design specialists, decision-makers and stakeholders with reliable and easily used tools for in-depth statistical analysis of climatic characteristics, and instruments for detailed analysis, assessment and prediction of impacts of global climate change on the environment and climate of the targeted region. Two actively discussed nowadays problems are addressed by the project. The first one is a development of an environment in which scientists from different disciplines, stakeholders and decision makers, regardless of their geographical position, can freely access various data resources and processing services through a Web browser. Since progress in development of so called virtual research environment is based on information-computational technologies it will be discussed in this paper in more details. The second problem belongs to basic and applied climatology and will be discussed here rather briefly. It is a provision of interested parties with detailed climatic and ecological characteristics of targeted region and tools allowing get scientifically solid data necessary for the study of regional economic, political and social consequences of global climate change.

Urban vegetation land cover change is a direct measure of quantitative increase or decrease in sources of urban pollution and the dimension of extreme climate events and changes that determine environment quality. This study addresses climate changes effects and anthropogenic impacts on urban green biophysical variables based on time series satellite data in synergy with in-situ data and new analytical methods. This paper explored the use of time-series MODIS Terra/Aqua Normalized Difference Vegetation Index (NDVI/EVI), Land Surface Temperature (LST) and Leaf Area Index (LAI), land surface albedo data to provide vegetation change detection information for Bucharest test area during 2000- 2015 period. Training and validation are based on a reference dataset collected from Landsat ETM remote sensing data. The mean detection accuracy for investigated period was 89%, with a reasonable balance between change commission errors (19.74%), change omission errors (24.72%), and Kappa coefficient of 0.74. Annual change detection rates across the urban/peri-urban green areas over the study period were estimated at 0.77% per annum in the range of 0.45% (2000) to 0.78% (2015).Vegetation dynamics in urban areas at seasonal and longer timescales reflect large-scale interactions between the terrestrial biosphere and the climate system.

Climate change is considered to be the biggest environmental threat in the future in the South- Eastern part of Europe. In frame of predicted global warming, urban climate is an important issue in scientific research. Surface energy processes have an essential role in urban weather, climate and hydrosphere cycles, as well in urban heat redistribution. This paper investigated the influences of urban growth on thermal environment in relationship with other biophysical variables in Bucharest metropolitan area of Romania. Remote sensing data from Landsat TM/ETM+ and time series MODIS Terra/Aqua sensors have been used to assess urban land cover– climate interactions over period between 2000 and 2015 years. Vegetation abundances and percent impervious surfaces were derived by means of linear spectral mixture model, and a method for effectively enhancing impervious surface has been developed to accurately examine the urban growth. The land surface temperature (Ts), a key parameter for urban thermal characteristics analysis, was also analyzed in relation with the Normalized Difference Vegetation Index (NDVI) at city level. Based on these parameters, the urban growth, and urban heat island effect (UHI) and the relationships of Ts to other biophysical parameters have been analyzed. The correlation analyses revealed that, at the pixel-scale, Ts possessed a strong positive correlation with percent impervious surfaces and negative correlation with vegetation abundances at the regional scale, respectively. This analysis provided an integrated research scheme and the findings can be very useful for urban ecosystem modeling.

Agricultural land use conversion is inevitable to meet the needs of growing population, together with climate change issue which has become global concern. This research aims at investigating the impact of climate change on agriculture by identifying land use conversion in part of Central Java, Indonesia, namely Tegal District. Research was carried out in August 2014 until March 2015.This is a survey research with explorative descriptive method, data processing using ENVI 4.5. and ArcGIS 10.1. The satellite image of Landsat was analyzed by determining and comparing the land use changes of the last 20 years, then the interview data with farmers was analyzed using logistic regression. The results showed that many lands converted into settlement, with increasing rate in 2003-2014 was almost twice than 1994-2003, while the reduce of irrigation rice field lands are lower in the period of 2003-2014 than 1994-2003. It is presumed that the factors encourage irrigation rice field land conversion are erratic rainfall, floods in the 1990s, and water lack in the 2000s. This paper discusses briefly about agricultural land use conversion as the impact of the past and current climate variability on farm land.

We discuss the issues of primary importance for understanding the nature of climate changes in the 20th century and main physical processes responsible for them. Special attention is paid to climate changes which occurred in 1943–1976 and 2000–2014. These periods exhibit the maximum increase in CO2 in the atmosphere, with virtually unchanged global temperature and its reduction in some regions. We study atmospheric and sea surface temperature effects of solar activity. The paper deals with results of the analysis of regularities and peculiarities of a tropospheric and sea surface temperature response to separate heliogeophysical disturbances as well as to long-term solar and geomagnetic activity variations. We also present results of the analysis of a change in sea surface temperature covering the time period 1854–2012 and their relation to solar activity variations. We find further evidence for the solar effect on climatic processes in the troposphere and ocean. We reveal a significant response in the major climatic characteristics, namely, surface air temperature and sea surface temperature (SST). It is established that the climatic response is characterized by significant space-time inhomogeneity, is regional and depends on the climate epoch. We discuss a role of wind stress and thermohaline circulation in the observable climate changes.

Climate change affects forest both directly and indirectly through disturbances, that are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. Forest vegetation characteristics, including land cover and phenology, affect processes such as water cycle, absorption and re-emission of solar radiation, momentum transfer, carbon cycle, and latent and sensible heat fluxes. The climate system responds in complex ways to changes in forcing that may be natural or human-induced. Drastic climate change over the last decades has greatly increased the importance of forest land cover changes monitoring through time-series satellite data. Satellite based derived biophysical parameters for assessment of climate impacts on forest vegetation have to meet particularly high quality requirements. Forest vegetation and climate interact through a series of complex feedbacks, which are not very well understood. Satellite remote sensing is suited tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and GPP (Gross Primary Production), which are key biophysical variables for studying land surface processes and surface-atmosphere interactions for forested areas. The aim of this paper was to investigate their pattern dynamics due to the impact of climate variations on a periurban forest Branesti-Cernica, placed to the North-Eastern part of Bucharest city, Romania. The forest vegetation analysis was based on derived biogeophysical parameters from time-series satellite remote sensing MODIS Terra/Aqua and NOAA AVHRR data and in-situ monitoring ground data (as air temperature, aerosols distribution, relative humidity, etc.) over 2002–2014 period.