We have devised a simple optical parameter classification system using the three apparent optical property (AOP) parameters available in the NASA Geospatial Interactive Online Visualization and Analysis Infrastructure (Giovanni). These parameters are produced by the NASA Ocean Biology Processing Group (OBPG). The three AOP parameters are: a_dg, the absorption coefficient of dissolved and detrital matter; a_ph, the absorption coefficient of phytoplankton, and b_bp, the backscatter coefficient. The Microsoft Excel ternary diagram plotting spreadsheet Tri-Plot (Graham and Midgely 2000) was used for visualization of the three-parameter ocean optical parameter classification scheme. This simple analysis method can be utilized by researchers, continuous water quality monitoring campaigns, citizen scientists, and students.

In this paper we demonstrate the use of this ternary optical classification system by applying it to an examination of the seasonal outflow of the Orinoco River into the eastern Caribbean Sea. End-member optical regimes consist of the river mouth waters during the rainy season, and high clarity Caribbean Sea waters which are not influenced by the optically active constituents in the Orinoco River plume. The variability of the optical characteristics of the surface waters between the rainy and dry seasons is clearly distinguishable in the ternary plots, particularly in the coastal region adjacent to the northern coast of South America.

French Guiana is located in South America close to the equator (between 2° and 4° N), a huge asset in the production of electrical power with the use of solar panels. The yearly average solar-radiation is 5.8 kWh/m²day .The main focus of this study is to determine the solar energy potential in French Guiana using Kernel density estimation.

The knowledge of surface solar irradiance may be obtained using physical laws such as radiative transfert functions that link satellite apparent albedo to surface irradiance. However, due to the complexity of physical processes, it is difficult to develop accurate and reliable nonlinear observation law, in particular in a tropical area (our area of study). In this work we used a two dimensional Kernel density estimation with a learning dataset of clearness index data and apparent albedo data to estimate surface solar irradiance.

A time series of images every 30 min from the visible channel of the GOES-13 meteorological geostationary satellites from the year 2010 to 2013 has been selected with a spatial resolution of 1 km x 1 km. Hourly in-situ measurement data from six ground reference stations were provided by the French national meteorological agency.

The predicted solar irradiance values from the Kernel density estimation were given in the form of hourly, monthly and annual maps. The maps obtained highlighted interesting trends: the annual average maps showed that the western side of French Guiana receives the highest irradiance values and is dependent on the position of the InterTropical Convergence Zone (ITCZ).

The mean bias percentage error and mean RMSE values were respectively found to be less than 5% and 10% for the testing stations on a hourly basis. The kernel density estimation show great accuracies for evaluating solar resource potential. These results give a first overview of the solar energy potential in French Guiana.

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.

We processed an archive of more than 300 permanent Global Navigation Satellite Systems (GNSS) station with the aid of software Gamit/Globk 10.5 developed and maintained by MIT, Scripps Institution of Oceanography, and Harvard University with support from the National Science Foundation (http://www-gpsg.mit.edu/~simon/gtgk/), using our facilities based on the distributed sessions approach implemented in the package. The Global Positioning System (GPS) data are comprised in the period January 2008 – December 2012, and belongs to several different permanent GPS network in Italy like: the RING of the National Institute of Geophysics and Volcanology (INGV), ASI Italian spatial agency, EUREF – European Reference Network, IGS – International GNSS Service for geodynamics, ITALPOS of Leica Geosystems and other institution networks maintained by public and private administration and universities. The data collected daily by different sensors and archived in RINEX compressed Hatanaka format were gathered, divided in several clusters, and routinely processed using Gamit data processor, based on least square method.
Successively, our solutions were combined with SOPAC (http://garner.ucsd.edu) ones to obtain stable and high quality solutions (h_files) containing coordinates, velocities and covariance of more than 300 GPS sites. A Global Kalman filter based package (Globk) was used to compute position time series and velocities registered in the ITRF2008 reference frame. The almost rigid rotation of the Eurasian plate was removed using Altamimi’s definition of rotation pole, and residual intra-plate velocities for all the 300 stations were computed. Indications about the tectonics of Mediterranean regions can be available by studing the computed high density velocity field.

Today, with massive flow of the spatial and non-spatial database, enormous field data collection with enhanced electronic protocols in agricultural research has led to assemblage of massive caches of digital information on agriculture that describe the context-options for technological as well as socio-economic interventions at multiple scales and scenarios.  However such tools and web services are often limited to certain geographical regions and do not exist for drylands in developing countries. In a bid to improve digital agricultural services in the dry areas, the International Center for Agricultural Research in Dry Areas (ICARDA) recognizes that Geoinformatics in agriculture is critical in obtaining adequate data for tackling food security and improving livelihoods, particularly in dry areas of the developing world that struggle with limited natural resources.  In order to make spatial information available at the finger tips in the era of smart phones and personal computations, the ICARDA developed number of geospatial tools and web portals for data access, visualization and sharing to help researcher and decision makers at various scales to influence agricultural research, programs, and policies. In this paper we discuss latest trends and advances in an integrated web based spatial data visualization tools and technology for agro-ecological research and application. The workflow uses the hybrid protocols for data storage/access (e.g., AWS, SAN), processing (e.g., numpy, rasterio and GDAL) and map server interface (e.g., ArcGIS online, OA APIs). An interactive end-user segment consists of Django, AngularJS, Open Layers and WDSL. System renders multiple spatial data to website and web services via Open Geospatial Consortium (OGC) standards, Web Mapping Service (WMS) for map images and Web Coverage Service (WCS) for raster data. Such user friendly map interface allows researchers to take into account of different factors such as land cover dynamics, cropping patterns and intensities, water use and availability, changing demographics, infrastructure, poverty, markets, climate change, and more.  Information generated can be used to assess vulnerable areas for possible pathways to increased resilience and mitigation of risks whether biophysical (land degradation and drought) or socioeconomic (price shocks or policy changes in land tenure).