Ore Mountains (west of the Czech republic) are an example of the area that suffered from severe environmental pollution originating in coal mining and heavy industry leading to massive dieback of the local Norway spruce forests between 1970’ and 1990’. The situation became getting better at the end of 1990’ after significant decrease of pollution loads. In 1998, ASAS airborne hyperspectral data were used to study the health status of the Norway spruce forests in this area. New hyperspectral data acquisition (APEX) was organized in 2013. Therefore there is a unique opportunity to study recovery of the originally damaged forest stands and compare them with the stands that have been less affected by environmental pollution. The analysis was conducted assessing a set of 16 vegetation indices to provide complex information on vegetation foliage biochemistry, canopy biophysics and structure. Five of them (NDVI, NDVI₇₀₅, VOG₁, MSR and TCARI/OSAVI) showing the best results were employed to study their spatial gradients as well as temporal changes. The obtained results indicate that the original significant differences between the damaged and undamaged stands have been generally levelled until 2013, although it is still possible to detect some signs of the previous damages in several cases.

With the advancement of Urban Intelligence and Smart Cities, the importance of remote monitoring and data collection increased. Concerning monitoring, IP-Proxy is an important equipment to perform the interconnection between the sensors and the Internet. In the recent literature, several gateway architectures for network sensors have been proposed to integrate Wireless Sensor Networks (WSN) and Internet. Most  implementations of WSN gateways retrieve sensors data on the WSN and display the results to customers through the web. The disadvantage of these solutions is that they use specific protocols to connect the sensors, thereby prohibiting the direct interaction between customers and sensor nodes. As an option, the adoption of the SNMP protocol for sensor management has the potential to reduce the gateway complexity of most gateway.  For this reason, this article presents the design and implementation of a low-cost open platform IP-Proxy with the usage and modification of a commercial out-of-the-shelf wireless router, with serial connection to communicate with the sensors, that are connected to an expanded microcontroller Arduino Nano board. The results of the experiments showed that the IP-Proxy can successfully interconnect sensor networks and the Internet, where data can be worldwide broadcasted via Ethernet or WLAN. His features include ease of implementation, integration and robust operation.

Nowadays, global warming has become more interested for scientist, because the global surface temperature has been increased since last century. More than fifty percent of people are living in cities, in this regard, urbanization has become a key factor for global warming. The urban heat island (UHI) refers to the event of higher atmospheric and surface temperatures occurring in cities than in the surrounding rural areas due to urbanization. The annual average air temperature of urban area with almost one million people can be one to three degree warmer than its surroundings. This phenomena can affect societies by increasing summertime, air pollution, air conditioning costs, heat related illness, greenhouse gas emissions and water quality.

Tehran, a capital city of Iran is case study of this research. Additionally, Tehran is one of megacities of the world. A megacity is usually defined as a metropolitan area with a total population in excess of ten million people. Due to rapid urbanization progress that has resulted in significant UHI effect in this area. Furthermore, Tehran houses to almost twenty percent of Iranian people. In this study, new launched Landsat series (Landsat 8) was used for monitoring UHI and retrieving the brightness temperatures and land use/cover types. The Landsat 8 carries two kind of sensors: The Operational Land Imager (OLI) sensor has former Landsat bands, with three new bands: a deep blue band for coastal/aerosol studies (band 1), a shortwave infrared band for cirrus detection (band 9), and a Quality Assessment band. The Thermal Infrared Sensor (TIRS) sensor provides two high resolution (near to 30 meters) thermal bands (band 10, 11). These sensors both use corrected signal-to-noise (SNR) radiometric quantized over a 12-bit. Corrected SNR performance cause better determination of land cover type. Moreover, Landsat 8 images incorporate two valuable thermal bands in 10.9 µm and 12.0 µm. These two thermal bands improve estimation of UHI by incorporating split-window methods.

Recently, quantitative models for urban thermal environment and related factors have been studied, for example, the relation between UHI and land cover structure and established corresponding regression equation. Similar works have been done and models of the relation between the surface temperature and various vegetation Indices have been established. In order to monitor the relationship between UHI and land cover indices, this paper tried to employ a quantitative approach for exploring the relationship land surface temperature and common land cover indices and select suitable indices by incorporating supervised Feature Selection (FS) procedures, including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Water Index (NDWI) in two definition, Normalized Difference Bareness Index (NDBaI), Normalized Difference Build-up Index (NDBI), Modified Normalized Difference Water Index (MNDWI), Bare Soil Index (BI), Urban Index (UI), Index-based Built-Up Index (IBI) and Enhanced Built-Up and Bareness Index (EBBI). In this regards, the objectives of this research are to develop a non-linear analysis model for urban thermal environment by employing Support Vector Regression (SVR) method and Multivariate Regression (MR) algorithms. In addition, providing the hazard map for Tehran city is also one of the byproducts of proposed methods for managing and mitigating UHI effects. 

With the development of quantitative remote sensing, regional evapotranspiration modeling based on the feature space has made substantial progresses. Among many remote sensing evapotranspiration models, accurate determination of the theoretical dry/wet lines remains a challenging task. This paper reports the development of a new method, named DDTI (Determination of dry line by Thermal Inertia), which determines the theoretical dry line based on the relationship between thermal inertia and soil moisture. The Simplified Thermal Inertia value estimated in the North China Plain is consistent with the value computed in the laboratory. Two evaluation methods, which are based on the comparison of the location of theoretical dry line and the comparison of Evaporative fraction, were used to assess the performance of the new method DDTI. The location of the theoretical dry line determined by DDTI is higher than the heat energy balance method, which is more reasonable in wet conditions. When compared with the in situ measurement of Evaporative fraction at YuCheng Experimental Station, the ET model based on DDTI reproduces the pixel scale EF with a RMSE(Root Mean Square Error) of 0.071, which is much lower than that based on heat energy balance method with a RMSE of 0.65. Also, the bias between in situ measurements and DDTI method is 0.056，which is ower than that between in situ and the heat energy balance method with a bias of 0.645.

The seismic vulnerability analysis of urban environments is an operational issue that concerns the comprehensive knowledge of both building structural features and soils geophysical parameters, especially when considering areas that are prone to hydrogeological and seismic disasters. The protection of such environments, together with the population growth and the urbanization processes, requires a multi-disciplinary approach aiming at providing both an effective assessment of urban resources and synthetic parameters for managing post crisis events, restoration activities and search & rescue operations. Within such a framework, airborne Light Detection and Ranging (LiDAR) and Hyperspectral sensors have demonstrated to be powerful remote sensing instruments, whose jointly use allow providing meaningful parameters to describe both the topographic settings of urbanized areas and the buildings properties, in terms of geometrical, spectral and structural features. Based on this rationale, in this study, the operational benefits obtained by combining airborne LiDAR and Hyperspectral measurements are provided to support the seismic vulnerability assessment of urban seismic areas. The digital elevation model as well as the building height and the shape of the observed area are gathered by using airborne LiDAR measurements. Spectral and structural information of urban buildings are provided through the supervised classification of IMSpectorV10E VNIR (wavelength range between 400 and 1000nm subdivided into 503 bands) measurements acquired by the IPERGEO sensor. The objective is to combine the different products provided by LiDAR and Hyperspectral image processing analysis within a Geographic Information System (GIS) platform, to evaluate the intrinsic properties of buildings (e.g. perimeter, covered area, height and type of roofs) together with the topographic features of the surrounding area (e.g. the surface height and slope) for providing synthetic parameters and thematic maps useful for seismic assessment and mitigation purposes, such as: (i) the identification of steep slope areas, (ii) the analysis of building roof typology for supporting the evaluation of structural load conditions, (iii) the detection of critical structures (e.g. asbestos buildings), (iv) the identification of primary roads (in terms of escape or access routes) for supporting search and rescue operations, (v) the analysis of main road conditions after building collapses. Meaningful experimental results, gathered for the historical center of Cosenza city (Italy), allow demonstrating the benefits of the proposed approach for both seismic assessment and mitigation purposes.

The present work is supported and funded by Ministero dell'Università, dell'Istruzione e della Ricerca (MIUR) under the project PON01-02710 "MASSIMO" - "Monitoraggio in Area Sismica di SIstemi MOnumentali".