Fuel type, as well as topography and microclimatic conditions, are some of the most important factors that should be taken into consideration for pre-fire planning. These factors have additional importance in the areas of forest protection and regeneration. A problem that remains unsolved is that an adequate classification method which is able to provide satisfactory results, has still not been developed. Until now, most of the techniques that have employed aerial photography or satellite imagery are based on differences within spectral information.

This work presents a high resolution image classification based on object oriented. The objects are derived by means of multiresolution segmentation. It allows a creation of different levels of segments supporting a hierarchy structure, generating spatial relations between objects and sub-objects. This hierarchy is the bedding for the semantic network. The knowledge is the basis of the semantic. The classification is based on fuzzy rules by the means of descriptors such as: form, texture and relations between objects and sub-objects.

Mangrove stands of differing species composition are hard to distinguish in conventional, coarse resolution satellite images. The new generation of meter-level satellite imagery provides a unique opportunity to achieve this goal. In this study, an IKONOS Geo bundle image and a QuickBird Standard bundle image were acquired for a study area located at Punta Galeta on the Caribbean coast of Panama. The two images cover the same area and were acquired under equivalent conditions.

Rapid expansion of coastal aquacultre/shrimp farming in several countries has necessitated the inventory and monitoring of shrimp farms. these are essential tools for decision making on aquaculture development, including regulatory laws,environmental protection and revenue collection. In the context of aquaculture development policies of respective governments, much attention are focused on the identification and classification of shrimp farms, often located in remote areas.

Two techniques for extracting flooded areas out of RADAR-imagery in a time-efficient way are presented in this paper. The results of the object-oriented classification technique, based on the commercial eCognition software, and the active contour technique, are both obtained on 2 ENVISAT ASAR images; one recorded during a flood period in Flanders on January the 2nd of 2003 and one during a non-flooded region on June the 26thof the same year. In both techniques the net flooded result is based on the subtraction of the existing water bodies (i.e.

The ARGUS system is a shore-based, optical video system offering a suitable remote sensing technique for the purpose of longterm, high-resolution monitoring of coastal morphodynamics. Ten-minute time-exposure (timex) images obtained by the ARGUS cameras during low tide show the intertidal morphology (bars, troughs and rips) by the differences between water, wet sand and dry sand, where dry sand represents bars, and wet sand and water represent troughs and rips.

Federal Clean Water Act requires that states develop Total Maximum Daily Loads (TMDLs) for water bodies. Once the state has developed an inventory of TMDLs, it is required to provide public notice of the report and have it approved by the Environmental Protection Agency. The South Dakota Department of Environment and Natural Resources (DENR) is using the USDA’s annualized Agricultural Non-Point Source Pollution Model to determine what land use changes are required to meet TMDL goals (South Dakota DENR, 2006).

The tidal wetlands within the Long Island Sound estuary serve a critical role in maintaining the health of the Sound. Over the past two centuries, there has been significant disturbance and loss of tidal wetlands along the Sound due primarily to anthropogenic activities.

Turkey is affected by many natural and manmade hazards, mainly by earthquakes, floods, fires and landslides that cause considerable damage to towns, roads and agriculture with a high loss of life. In general floods, as being the most devastating natural hazard in the world, are caused by heavy rain, snowmelt, or dam failures.

Introduction
The coast of Texas supports a diversity of marine habitats as well as providing an abundance of recreational opportunities and contributing significantly to the Texas economy. However, as populations increase, human impacts to Texas coastal ecosystems are also increasing. Managing and protecting this diverse and sensitive resource requires knowledge of the state’s coastal marine habitats and understanding of the causes of change in these habitats over time.