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This Sixth International Conference on Agro-Geoinformatics (Agro-Geoinformatics 2017) took place in Fairfax VA, USA on August 7-10, 2017. This conference is organized and hosted by Center for Spatial Information Science and Systems of George Mason University, Agriculture and Agri-Food Canada, IEEE Geoscience & Remote Sensing Society, National Agricultural Statistical Service of United States Department...
Citizens is becoming an important source of geographic information. Volunteered Geographic Information (VGI) offers an opportunity of involving public to collect disaster information which is individually generated and available in time. This paper propose a VGI oriented approach for Disaster Risk Reduction (DRR) with application to urban waterlogging. An algorithm based on VGI is proposed to deal...
Climate change has become a hot topic in recent years. Flood is one of the most common natural hazards caused from extreme climate change. Scientists have spent a lot of money and time on monitoring flood in past decades. The development of Remote Sensing and Geographic Information System (GIS) brings new ways for scientists to analyze, monitor, and predict floods. Remote Sensing provides an alternative...
Wi-Fi is a technology which can connect PC, handhold devices and other terminal wireless with low cost and very high data bandwidth, and it is used worldwide. At the same time, Wi-Fi can be used for wireless localization based on the distribution feature of its signal strength. Therefore, it is necessary to collect Wi-Fi signals and store it with some ways. Lots of researchers have proposed different...
Big data technologies have shown great promise for managing geospatial data in recent years. In order to deal with the growing spatial data, a high performance spatial data processing system layered on big data technologies is needed. In this paper, we present an approach to process big spatial data with Apache Spark, a fast and generic engine for large-scale data processing. We developed a software...
Traditional relational database management systems (RDBMS) have shown limitations in storing and analyzing big data. For example, a RDBMS is suitable for transactional operations yet not good at large-scale data analysis and processing, since a large-scale record scan or full table scan is often time-consuming. An efficient storage method for reading and writing big geospatial data is still needed...
By means of Interferometric Synthetic Aperture Radar (InSAR) data, our aim in this work is to examine the ground deformation changes of eight agricultural plains in northwestern part of Turkey. This part of the country is tectonically active, highly vegetated, experiencing rapid human population growth and infrastructural change. All these influences make the agricultural plains monitoring and control...
Agricultural textures are in the interest of classification in image processing. Natural images have unique textural shapes inside which cause a tough problem for classification. This paper tests different feature extraction and classification approaches to serve a benchmarking on several agricultural databases like seeds and leaves. Features are obtained using Local Binary Pattern (LBP), Gray Level...
Geospatial web service of agricultural information has a wide variety of consumers. An operational agricultural service will receive considerable requests and process a huge amount of datasets each day. To ensure the service quality, many strategies have to be taken during developing and deploying agricultural information services. This paper presents a set of methods to build robust geospatial web...
Two GF-1 WFV images on August 3, 2015 and October 2, 2015 were selected to extract the cultivated area of paddy rice in Jianhu county of Jiangsu Province. Vegetation indexes were extracted from the original spectrum data in order to extract paddy rice area with Maximum Likelihood Classifier (MLC), Support Vector Machine (SVM) and Classification and Regression Trees (CART). The extraction accuracy...
Agricultural landscape is designated as important landscape components for partly controlling water quality, biodiversity, as well as for their aesthetic role in landscapes. Therefore, the change of agricultural landscape is at the top of the agenda for many policy makers and landscape planners. As a basis for conservation management, sufficient information about landscape structure should be providing...
Spatial clustering analysis is one kind of spatial data mining tools to explore the spatial auto-correlation of things that occur in a particular space, that is, whether the observed values of the spatial variables are related to the spatial position where they occur. In this paper, the cigarettes in 2013 in Guizhou province, China were collected, and the spatial correlation analysis was carried out...
Crop phenology is a critical component of implementing agricultural activities and providing important indicators for climate related research. The needs for crop phenology estimation not only exist in large scale but also in medium or small scale. In this work, Jianhu County was chosen to test the ability of crop phenology estimation by Moderate Resolution Imaging Spectroradiometer (MODIS) data....
In this paper, some preliminary results of mapping rice growth using TerraSAR-X HHVV dual polarization data are presented. Three TerraSAR-X images were collected in southern China during a rice growth cycle to analyze the temporal response of the rice fields at X-band. The height, the leaf area index (LAI) and the biomass of rice were also measured during acquisition of the SAR data, and empirical...
Agricultural drought greatly impacts the crop yield. Monitoring agricultural drought can deliver critical information to farmers on when, where and how much to irrigate. However, precisely monitoring which requires many kinds of data sources and data fusion and mining is still a huge challenge for scientists. In recent years, many data sources like remote sensed hyperspectral images are released online...
Statistics show the volume of Earth Observation (EO) data increases in the exponential level during the past decade. As the new generation computing platform to meet the big data challenge, cloud computing significantly facilitates the large-scale EO data processing depending on its powerful computing capability. In this paper, we propose a Cloud WPS architecture integrating the cloud computing environment...
It is a hotspot in the field of remote sensing image analysis and application by using the macro and real-time features of the remote sensing image data for its change in Land and Resources. This paper introduces an automatic change monitoring method with remote sensing image data and historical interpretation vector data, which is based on the Gaussian Mixture Model and the vector-guided image spot...
Most previous studies applied land surface temperature and vegetation index retrieved by optical remote sensing data to drought monitoring. But the vegetation index indicates drought indirectly and lag behind, while the precipitation is directly affect the drought and flood disasters, and microwave remote sensing has its unique advantages to detect precipitation. So, in this paper, on the basis of...
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