Modeling land-use change is a prerequisite to understanding the complexity of land-usechange patterns. This paper presents a novel method to model urban land-use change using support-vector machines (SVMs), a new generation of machine learning algorithms used in classification and regression domains. An SVM modeling framework has been developed to analyze land-use change in relation to various ...

The loss of low-lying farm-land to marshes and swamps was a striking phenomenon in Italy and other regions of Europe after the fall of the Roman Empire. Throughout the Middle Ages extensive fertile agricultural lands were abandoned due to increased marshiness and the risk of the spread of malaria diffusion. In economic and social terms, this was a further source of decline. In this scenario of ...

For the past two millennia the Holy Land was under the yoke of successive invaders and oppressors, not a fertile ground for growth of historiographic traditions. Consequently, earthquake cataloguers had to rely largely on chronicles and texts written at distant administrative and cultural centers of the day, where earthquake destruction suffered by a culturally and economically depressed provin...

Epidemiologists are adopting new remote sensing techniques to study a variety of vector-borne diseases. Associations between satellite-derived environmental variables such as temperature, humidity, and land cover type and vector density are used to identify and characterize vector habitats. The convergence of factors such as the availability of multi-temporal satellite data and georeferenced ep...