The appetite for up-to-date information about earth's surface is ever increasing, as such
information provides a base for a large number of applications, including local, regional and …

Ideal for both undergraduate and graduate students in the fields of geography, forestry,
ecology, geographic information science, remote sensing, and photogrammetric …

Image classification is one of the most basic operations of digital image processing. The
present review focuses on the strengths and weaknesses of traditional pixel-based …

Automatic subdivision of landscapes into terrain units remains a challenge. Slope units are
terrain units bounded by drainage and divide lines, but their use in hydrological and …

Agricultural production is the immediate basis for food security and income of the majority of
Central Ethiopia׳ s population. Demographic change has led to ever-decreasing farmland …

This paper introduces a multi-temporal image processing framework towards an efficient
and (semi-) automated detection of urban changes. Nonlinear scale space filtering was …

This paper presents the impact of machine learning in precision agriculture. State-of-the-art
image recognition is applied to a dataset composed of high precision aerial pictures of …

In this research, an object-oriented image classification framework was developed which
incorporates nonlinear scale-space filtering into the multi-scale segmentation and …

Although many machine learning methods have been successfully applied for the object-
based classification of high resolution (HR) remote sensing imagery, current methods are …

KLASIFIKASI TUTUPAN LAHAN MENGGUNAKAN METODE SEGMENTASI BERBASIS
ALGORITMA MULTIRESOLUSI (Studi Kasus Kabupaten Purwakarta, Jawa Barat) …