Buried archeological features show up as crop marks that are mostly visible using high-resolution image data. Such data are costly and restricted to small regions and time domains. However, a time series of freely available medium resolution imagery can be employed to detect crop growth changes to reveal subtle surface marks in large areas. This paper aims to study the classical Chinese settlem...

The improvements in crop production needed to meet the increasing food demand in the 21st Century will rely on improved crop management and better crop varieties. In the last decade our ability to use genetics and genomics in crop science has been revolutionised, but these advances have not been matched by our ability to phenotype crops. As rapid and effective phenotyping is the basis of any la...

An accurate estimation of soybean crop areas while the plants are still in the field is highly necessary for reliable calculation of real crop parameters as to yield, production and other data important to decision-making policies related to government planning. An algorithm for soybean classification over the Rio Grande do Sul State, Brazil, was developed as an objective, automated tool. It is...

In the contemporary world aerospace information gathered by different sensors and numerous observation missions has become a genuine necessity in various investigation and application fields. Remote sensing technologies are used for natural resources management, ecosystem change detection, environment preservation and in many other world significant problems. Vegetation monitoring is among the ...

Food losses due to crop infections from pathogens such as bacteria, viruses and fungi are persistent issues in agriculture for centuries across the globe. In order to minimize the disease induced damage in crops during growth, harvest and postharvest processing, as well as to maximize productivity and ensure agricultural sustainability, advanced disease detection and prevention in crops are imp...

Nitrogen is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. In this study an image processing based approach was used for detection of nitrogen status in winter wheat. Four N fertilization rates (0, 60, 120 and 240 kg N ha, in total) and two water regimes (irrigated and non-irrigated) were applied to winter wheat. Digital ima...

Soybean is the main food crop and an important economical crop of the world. Proper disease control measures must be undertaken to minimize losses. Techniques of machine vision and image processing were applied mostly to plant protection in recent years. Disease detection and segmentation are very important, but the diseases of soybean are complex in real environment and traditional segmentatio...

This paper presents a review of the literature on the application of data mining techniques for the detection of insurance fraud. Academic literature were analyzed and classified into three types of insurance fraud (automobile insurance, crop insurance and healthcare insurance) and six classes of data mining techniques (classification, regression, clustering, prediction, outlier detection, and ...

Image processing algorithms for individual corn plant and plant stem center identification were developed. These algorithms were applied to mosaicked crop row image for automatically measuring corn plant spacing at early growth stages. These algorithms utilized multiple sources of information for corn plant detection and plant center location estimation including plant color, plant morphologica...