Spectral Characteristics of Common Reed Beds: Studies on Spatial and Temporal Variability
نویسندگان
چکیده
Reed beds are the second largest producer of biomass in Olkiluoto Island. Quantitative information on the extent and amount of reed stands is an integral part of the biosphere assessment related to long-term safety analysis of nuclear fuel repository site currently under construction. The major challenge in reed bed mapping is discrimination between reed and other green vegetation. Spectral field measurements were used to study the temporal and spatial variability of spectral characteristics of reed beds. Feasibility of discriminating reed beds from other vegetation based on hyperspectral measurements was studied as well. Results indicate that there is large temporal variation of reed bed spectra and the optimal time for data acquisition differs for old and new reed bed types. Comparing spectral characteristics of the reed bed and meadow classes in a local neighborhood indicated that the classes have high within-class spectral variability and similar mean spectra, however, 10 out of 11 targets had lower angle to the mean spectrum of the corresponding class than that of the other class when Spectral Angle Mapper (SAM) was used. Comparing the spectral characteristics of reed beds at four test sites within the Olkiluoto Island indicated that while some of the sites had similar spectra, the difference between others was remarkable. This is partly explained by different density and height of dead and live reed stems at the four sites.
منابع مشابه
Mapping spatial variability of soil salinity in a coastal area located in an arid environment using geostatistical and correlation methods based on the satellite data
Saline lakes can increase the soil and water salinity of the coastal areas. The main aim of this study is to distinguish the characteristics of the spectral reflectance of saline soil, analyze the statistical relationship between soil EC and characteristics of the spectral reflectance of saline soil, and to map soil salinity east of the Maharloo Lake. The correlation between field measurements ...
متن کاملTemporal-Spatial Variability of the Severest Dry Spells in the North-West of Iran
The variability of temperature and precipitation is regarded as one of the main characteristics of the climate.Precipitation and its results, especially results such as droughts, vary on different temporal and spatial scales. Thepurpose of this paper is to determine the frequency of the inter-annual variability of the driest month in north-westIran. In order to obtain the best results, we used ...
متن کاملLong-term spatial and temporal variability of ambient carbon monoxide in Urmia, Iran
One of the pillars of epidemiologic research on the long-term health effects of air pollution is to estimate the chronic exposures over space and time. In this study, we aimed to measure the intra-urban ambient carbon monoxide (CO) concentrations within Urmia city in Iran, and to build a model within the geographic information system (GIS) to estimate the annual and seasonal means anywhere with...
متن کاملSpatial and Temporal Variability of Water Quality for Karun River, in Upstream and Downstream Gotvand Dam
In this study, the spatial and temporal variability of water quality including monthly series of TDS, EC, So4, Cl, Ca and Na in common statistical period 1993-2014 was evaluated for the Karun River. This assessment is based on qualitative data stations including Susan in the upstream of Gotvand reservoir, Gotvand, Mollasani and Ahvaz in the downstream. To determine the parameters trend process,...
متن کاملImpact of spatial-temporal variations of climatic variables on summer maize yield in North China Plain
Summer maize (Zea mays L.) is one of the dominant crops in the North China Plain (NCP). Its growth is greatly influenced by the spatial-temporal variation of climatic variables, especially solar radiation, temperature and rainfall. The WOFOST (version 7.1) model was applied to evaluate the impact of climatic variability on summer maize yields using historical meteorological data from 1961 to 20...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 8 شماره
صفحات -
تاریخ انتشار 2016