Automated extraction of meandering river morphodynamics from multitemporal remotely sensed data
نویسندگان
چکیده
منابع مشابه
Curvilinear Network Extraction from Remotely Sensed Images
still of wide interest, not only in the analysis of remotely sensed images. We describe a new approach to the extraction of networks of narrow curvilinear features such as road and river networks from remotely sensed MINIMUM COST PATHS images. The approach begins with the identification of points in the image with a high probability of being on the network. In the second stage the broad topolog...
متن کاملSelection of Remotely Sensed Data
An increasing number of sensors are available for forest ecologists and managers seeking to map attributes of forest canopy cover, forest structure and composition, and their dynamics. This Chapter seeks to put these advances within the context of the needs of forest managers and scientists. To do so, we review the basic physics behind a variety of imagery types, discuss fundamental limitations...
متن کاملUsing multitemporal, multispectral and multisource remotely sensed data to classify crops : An innovative approximation
This paper describes some preliminary results of an innovative methodology for classifying agricultural crops using multi-temporal, multi-spectral and multi-source remotely-sensed data. The procedure firstly characterises the individual training class data by considering these data values as a function of time of imaging and waveband. An analytical surface is fitted to these data points, which ...
متن کامل248 Remotely Sensed Data Characterization
EMPs Extended morphological profiles EMPs Extended morphological profiles LDA Linear discriminant analysis LogDA Logarithmic discriminant analysis MLR Multinomial logistic regression MLRsubMRF Subspace-based multinomial logistic regression followed by Markov random fields MPs Morphological profiles MRFs Markov random fields PCA Principal component analysis QDA Quadratic discriminant analysis RH...
متن کاملCommercial Remotely Sensed (CRS) Data
Natural disasters can severely impact transportation networks. In the hours and days following a major flooding event, knowing the location and extent of the damage is crucial for incident managers for a number of reasons: it allows for emergency vehicle access to affected areas; it facilitates the efficient rerouting of traffic; it raises the quality and reduces the cost of repairs; and it all...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Environmental Modelling & Software
سال: 2018
ISSN: 1364-8152
DOI: 10.1016/j.envsoft.2018.03.028