Nel comparto dell’edilizia, si assiste a un enorme dispendio di energie e risorse. Ciononostante, a fronte di una crescente sensibilizzazione ai problemi dell’ambiente globale, gli operatori di questo comparto hanno individuato anche la necessità di fornire qualche contributo volto ad attenuare concretamente le problematiche ambientali. In un simile contesto, è scaturita l’esigenza di sviluppare BREEAM.

Le Pubbliche Amministrazioni (PA) accumulano dati. Lo fanno per poter funzionare e per dimostrare di aver ben funzionato. La rivoluzione digitale rende trascurabile il costo di mettere a

This paper is intended to explore the potential of the Building Information Modelling (BIM) methodologies to be applied to the various stages of the construction process, particularly as far as international guidelines and best practices supporting virtuous operating flows are concerned: the IT component, mostly graphic during the design phase, is mainly integrated and renewed in an alphanumeric format, and becomes an integrating part of the management and maintenance of the artefacts.

Il coinvolgimento del pubblico e degli stakeholder nelle moderne attività di pianificazione territoriale richiede l’utilizzo di strumenti e metodologie adeguati che supportino i planner nell’acquisizione e

L’espropriazione di beni soggetti a uso civico costituisce una fattispecie particolare dell’istituto espropriativo la cui regolamentazione, nella parte in cui coinvolge le indennità e i diritti su esse vantate, va ricercata in normative speciali molto spesso anche lontane nel tempo o in pronunce giurisprudenziali.

Land change in the Greater Antilles differs markedly among countries because of varying socioeconomic histories and global influences. We assessed land change between 2001 and 2010 in municipalities (second administrative units) of Cuba, Dominican Republic, Haiti, Jamaica, and Puerto Rico. Our analysis used annual land-use/land-cover maps derived from MODIS satellite imagery to model linear change in woody vegetation, mixed-woody/plantations and agriculture/herbaceous vegetation. Using this approach, we focused on municipalities with significant change (p ? 0.05).

Focuses on two themes in the study of ethnopedology: (1) the hows and whys of indigenous soil classifications. (2) the differences and overlaps between indigenous soil classifications and western soil classifications. Aims to come to a synthesis of how to link the two sources of information to improve the success of cooperation in sustainable agricultural development.

The new land cover dataset will allow mapping of natural resources, human settlements and human activities in South Sudan and within neighboring countries. It will represent the most innovative and updated dataset developed for South Sudan, integrating high-resolution multi-temporal imagery, object-based image analysis

The habitat of tsetse fly (Glossina spp.) depends upon climatic conditions, host availability and land cover characteristics. In this paper, the Land Cover Classification System (LCCS), developed by the Food and Agriculture Organization (FAO) and the United Nations Environment Programme (UNEP), is proposed as a tool to harmonize land cover mapping exercises carried out in the context of tsetse and trypanosomiasis (T&T) research and control.

The National Forestry Authority has monitored Uganda’s land cover, including forested areas, periodically since 1990. The land cover classification is comprised of 13 classes as shown in the table below. The first five classes in the table refer to the different types of forests in Uganda. The largest forest type is woodland. Compared to other landcover types, forests are a small proportion of the country area.

Vegetation mapping provides basic information for forest management and planning. In remote sensing research, the process of creating an accurate vegetation map is an important subject. Recently, there has been growing research interest in the object-oriented image classification techniques. The object-oriented image classification consists of multi-dimensional features including object features and thus requires multi-dimensional image classification approaches.