Climatic variability analysis is an emerging scientific issue for SouthAsian regions, where recent climate change has imposed substantial challenges. In this paper, we analyzed the spatiotemporal variability of the yearly maximum temperature (TXx), which characterizes the summer in Bangladesh, sampled at 34 meteorological stations during 1948-2007. We identified monotonic and robust temporal tr...

A tangent linear adjoint for a low-resolution dynamical model of the atmosphere is used to derive the optimal forcing perturbations for all state variables such that after a specified lead time the model response has a given projection, in terms of an energy norm, on the pattern associated with the 51-yr trend in the Northern Hemisphere winter tropospheric circulation, 1948/49–1998/99. A featur...

Quantifying the spatial pattern of large-scale forest biomass can provide a general picture of the carbon stocks within a region and is of great scientific and political importance. The combination of the advantages of remote sensing data and field survey data can reduce uncertainty as well as demonstrate the spatial distribution of forest biomass. In this study, the seventh national forest inv...

Information concerning the home and workplace of residents is the basis of analyzing the urban job-housing spatial relationship. Traditional methods conduct time-consuming user surveys to obtain personal job and housing location information. Some new methods define rules to detect personal places based on human mobility data. However, because the travel patterns of residents are variable, simpl...

Through a geographically weighted panel regression analysis, we demonstrate the spatially varying relationship between weather and corn yields. A balanced panel data of 958 U.S. corn production counties for the period 2002-2006 is used. The results indicate that the relationship between weather and corn yield has large spatial variability. In specific, temperature tends to have negative margina...

This paper considers models for panel data in which the individual effects vary over time. The temporal pattern of variation is arbitrary, but it is the same for all individuals. The model thus allows one to control for time-varying unobservables that are faced by all individuals (e.g., macroeconomic events) and to which individuals may respond differently. A generalized within estimator is con...

I show that it may be possible to explain the present evidence for a gamma-ray emission from the galactic halo as due to halo WIMP annihilations. Not only the intensity and spatial pattern of the halo emission can be matched but also the relic density of the candidate WIMP can be in the cosmologically interesting domain. After a model-independent analysis to learn about the properties of a suit...

The SLEUTH model, based on the Cellular Automata (CA), can be applied to city development simulation in metropolitan areas. In this study the SLEUTH model was used to model the urban expansion and predict the future possible behavior of the urban growth in Tehran. The fundamental data were five Landsat TM and ETM images of 1988, 1992, 1998, 2001 and 2010. Three scenarios were designed to simula...

The rodent whisker-barrel system has been an ideal model for studying somatosensory representations in the cortex. However, it remains a challenge to experimentally stimulate whiskers with a given pattern under spatiotemporal precision. Recently the optogenetic manipulation of neuronal activity has made possible the analysis of the neuronal network with precise spatiotemporal resolution. Here w...

With the fast development of positioning technology, spatiotemporal data has become widely available nowadays. Mining patterns from spatiotemporal data has many important applications in human mobility understanding, smart transportation, urban planning and ecological studies. In this chapter, we provide an overview of spatiotemporal data mining methods. We classify the patterns into three cate...