Image processing techniques (band rationing, color composite, Principal Component Analyses)

are widely used by many researchers to describe various mines and minerals. The primary aim of

this study is to use remote sensing data to identify iron deposits and gossans located in Kaman,

Kırşehir region in the central part of Anatolia, Turkey. Capability of image processing techniques is

proved to be highly useful to detect iron and gossan zones. Landsat ETM+ was used to create remote

sensing images with the purpose of enhancing iron and gossan detection by applying ArcMap image

processing techniques. The methods used for mapping iron and gossan area are 3/1 band rationing,

3/5 : 1/3 : 5/7 color composite, third PC and PC4 : PC3 : PC2 as RG B which obtained result from

Standard Principal Component Analysis and third PC which obtained result from Developed Selected

Principal Component Analyses (Crosta Technique), respectively. Iron-rich or gossan zones were mapped

through classification technique applied to obtained images. Iron and gossan content maps were

designed as final products. These data were confirmed by field observations. It was observed that iron

rich and gossan zones could be detected through remote sensing techniques to a great extent. This

study shows that remote sensing techniques offer significant advantages to detect iron rich and gossan

zones. It is necessary to confirm the iron deposites and gossan zones that have been detected for the

time being through field observations.

The possibilities of remote sensing techniques in the field of the Earth surface monitoring and protection specifically for the problems caused by petroleum contaminations, for the mapping of insufficiently plugged and abandoned old oil wells and for the analysis of onshore oil seeps are described. Explained is the methodology for analyzing and detection of potential hydrocarbon contaminations using the Earth observation in the area of interest in Slovakia (Korňa) and in Czech Republic (Nesyt), mainly building and calibrating the spectral library for oil seeps. The acquisition of the in-situ field data (ASD, Cropscan spectroradiometers) for this purpose, the successful building and verification of hydrocarbon spectral library, the application of hydrocarbon indexes and use of shift in red-edge part of electromagnetic spectra, the spectral analysis of input data are clarified in the paper. Described is approach which could innovate the routine methods for investigating the occurrence of hydrocarbons and can assist during the mapping and locating the potential oil seep sites. Important outcome is the successful establishment of a spectral library (database with calibration data) suitable for further application in data classification for identifying the occurrence of hydrocarbons.

Of late, the science of Remote Sensing has been gaining a lot of interest and attention due to its wide variety of applications. Remotely sensed data can be used in various fields such as medicine, agriculture, engineering, weather forecasting, military tactics, disaster management etc. only to name a few. This article presents a study of the two categories of sensors namely optical and microwave which are used for remotely sensing the occurrence of disasters such as earthquakes, floods, landslides, avalanches, tropical cyclones and suspicious movements. The remotely sensed data acquired either through satellites or through ground based- synthetic aperture radar systems could be used to avert or mitigate a disaster or to perform a post-disaster analysis.

Satellite remote sensing provides a synoptic view of the land and a spatial context for measuring drought impacts, which have proved to be a valuable source of spatially continuous data with improved information for monitoring vegetation dynamics. Many studies have focused on detecting drought effects over large areas, given the wide availability of low-resolution images. In this study, however, the objective was to focus on a smaller area (1085 km2) using Landsat ETM+ images (multispectral resolution of 30 m and 15 m panchromatic), and to process very accurate Land Use Land Cover (LULC) classification to determine with great precision the effects of drought in specific classes. The study area was the Tortugas-Tepezata sub watershed (Moctezuma River), located in the state of Hidalgo in central Mexico. The LULC classification was processed using a new method based on available ancillary information plus analysis of three single date satellite images. The newly developed LULC methodology developed produced overall accuracies ranging from 87.88% to 92.42%. Spectral indices for vegetation and soil/vegetation moisture were used to detect anomalies in vegetation development caused by drought; furthermore, the area of water bodies was measured and compared to detect changes in water availability for irrigated crops. The proposed methodology has the potential to be used as a tool to identify, in detail, the effects of drought in rainfed agricultural lands in developing regions, and it can also be used as a mechanism to prevent and provide relief in the event of droughts.

Paper presents the description and floristic and ecologica characteristics of three plant communities on the area of Jasnorzewski Gardens in the region of Arctowski Station (Polish Academy of Sciences) on King George Island. They are: 1) Deschampsio antarctici-Colobanthetum quitensis, 2) Polytrichetum alpini, 3) Calliergidio austro-straminei-Calliergonetum sarmentosi. All communities show a considerable differentiation to several variants. Distribution of plant communities on the studied area is presented on a map based on computer analysis of multispectral air photographs.

Traditional methods of mineral exploration are mainly based on very expensive drilling and seismic methods. The proposed approach assumes the preliminary recognition of prospecting areas using satellite remote sensing methods. Maps of mineral groups created using Landsat 8 images can narrow the search area, thereby reducing the costs of geological exploration during mineral prospecting. This study focuses on the identification of mineralized zones located in the southeastern part of Europe (Kosovo, area of Selac) where hydrothermal mineralization and alterations can be found. The article describes all the stages of research, from collecting in-situ rock samples, obtaining spectral characteristics with laboratory measurements, preprocessing and analysis of satellite images, to the validation of results through field reconnaissance in detail. The authors introduce a curve-index fitting technique to determine the degree of similarity of a rock sample to a given pixel of satellite imagery. A comparison of the reflectance of rock samples against surface reflectance obtained from satellite images allows the places where the related type of rock can be found to be determined. Finally, the results were compared with geological and mineral maps to confirm the effectiveness of the method. It was shown that the free multispectral data obtained by the Landsat 8 satellite, even with a resolution of 30 meters, can be considered as a valuable source of information that helps narrow down the exploration areas.

A map was made of the distribution of macroalgae groupings in shallow waters of Admiralty Bay. The map was plotted on the basis of analysis of color reversal air photograph taken from a helicopter. A significant agreement of the results of the pictures analysis with the field studies was found. Also a number of areas not covered by field studies was determined as the ones of probable occurrence of macroalgae. A detailed map of distribution of four distinguished forms of macroalgae groupings was plotted for a small area in the region of Shag Point. Each of these forms is characterised by different association of algal species.

Priority wise channelization of resources is the key to successful environmental management, especially when funds are limited. The study in hand has successfully developed an algorithmic criterion to compare hazardous effects of Municipal Solid Waste (MSW) dumping sites quantitatively. It is a Multi Criteria Analysis (MCA) that has made use of the scaling function to normalize the data values, Analytical Hierarchy Process (AHP) for assigning weights to input parameters showing their relevant importance, and Weighted Linear Combination (WLC) for aggregating the normalized scores. Input parameters have been divided into three classes namely Resident’s Concerns, Groundwater Vulnerability and Surface Facilities. Remote Sensing data and GIS analysis were used to prepare most of the input data. To elaborate the idea, four dumpsites have been chosen as case study, namely Old-FSD, New-FSD, Saggian and Mahmood Booti. The comparison has been made first at class levels and then class scores have been aggregated into environmental normalized index for environmental impact ranking. The hierarchy of goodness found for the selected sites is New-FSD > Old-FSD > Mahmood Booti > Saggian with comparative scores of goodness to environment as 36.67, 28.43, 21.26 and 13.63 respectively. Flexibility of proposed model to adjust any number of classes and parameters in one class will be very helpful for developing world where availability of data is the biggest hurdle in research based environmental sustainability planning. The model can be run even without purchasing satellite data and GIS software, with little inaccuracy, using imagery and measurement tools provided by Google Earth.