Time filter

Source Type

Zhang X.,University of North Dakota | Shi L.,National Satellite Ocean Application Service | Jia X.,North Dakota State University | Seielstad G.,University of North Dakota | Helgason C.,University of North Dakota
Precision Agriculture | Year: 2010

A web-based decision support tool, zone mapping application for precision farming (ZoneMAP, http://zonemap. umac. org), has been developed to automatically determine the optimal number of management zones and delineate them using satellite imagery and field data provided by users. Application rates, such as of fertilizer, can be prescribed for each zone and downloaded in a variety of formats to ensure compatibility with GPS-enabled farming equipment. ZoneMAP is linked to Digital Northern Great Plains, a web-based application which hosts an archive of satellite imagery, as well as high resolution imagery from airborne sensors. Management zones created by ZoneMAP mapped natural variation of the soil organic matter and other nutrients relatively well and were consistent with zone maps created by traditional means. The results demonstrated that ZoneMAP can serve as an effective and easy-to-use tool for those who practice precision agriculture. © 2009 The Author(s). Source

Feng L.,Wuhan University | Feng L.,University of South Florida | Hu C.,University of South Florida | Chen X.,Wuhan University | And 2 more authors.
Remote Sensing of Environment | Year: 2014

Several studies showed the linkage of the Three Gorges Dam to the downstream coastal ecosystem in the East China Sea, yet its potential influence on the total suspended matters (TSM) in the Yangtze Estuary and its adjacent coastal waters has not been reported, possibly due to technical difficulties in obtaining statistically meaningful results. Here, a new remote sensing algorithm was established to estimate TSM from MODIS observations over the Yangtze Estuary and its adjacent coastal waters. The algorithm was based on a piecewise regression between TSM and surface reflectance at 645 and 869nm, leading to RMS uncertainties of only 20-30% for TSM between 2mgL-1 and 1762mgL-1. The algorithm was applied to MODIS data to derive TSM distribution maps from 2000 to 2010 at 250m resolution, which revealed significant spatial and temporal (seasonal and inter-annual) variability. Mean TSM in the Yangtze Estuary increased from 44.4±34.1mgL-1 in May to 96.0±58.0mgL-1 in October, while much higher TSM was found in the nearby Hangzhou Bay (between 100.3±51.6mgL-1 in August and 290.2±120.0mgL-1 in February). Two regions showed significantly out-of-phase seasonality: region A1 in the Yangtze Estuary driven by sediment discharge from the Yangtze River and region A2 in offshore waters and part of Hangzhou Bay driven by winds. The annual mean TSM in region A1 showed significantly decreasing trend in the 11-year period (-2.8mgL-1/yr), which appeared to be caused by the construction of the TGD. The study also has established a TSM environmental data record (EDR) to assess future TSM in the ecologically and economically important Yangtze Estuary and Hangzhou Bay. © 2013 Elsevier Inc. Source

Liu L.,National Satellite Ocean Application Service | Yu H.-B.,CAS Shenyang Institute of Automation
Tongxin Xuebao/Journal on Communications | Year: 2010

Cluster-based method has better adaptability and energy-efficiency to wireless sensor networks (WSN) used for environmental monitoring. If the cluster head is served by more powerful node, the performance of WSN will be improved greatly. In large scale WSN, high-power cluster head deployment is a kind of NP-hard problem. The optimal problem of cluster head deployment was formulated as an integer programming with the condition of restrictions of cluster head capacity and the maximal cluster radius. To satisfy the time effectiveness, a heuristic algorithm called KMSA was proposed which was a hybrid algorithm of K-mean and simulated annealing. The simulation results show that the KMSA can improve the performance of WSN on varieties of network size and cluster number. Source

Shan Z.,Chinese Academy of Sciences | Wang C.,Chinese Academy of Sciences | Zhang H.,Chinese Academy of Sciences | An W.,National Satellite Ocean Application Service
IEEE Geoscience and Remote Sensing Letters | Year: 2012

An improved four-component model-based target decomposition scheme for polarimetric synthetic aperture radar data is proposed in this letter. The reason for the emergence of the negative powers in the Yamaguchi decomposition has been analyzed, and three corresponding additional steps are added in the proposed scheme. First, the orientation angle compensation is applied to the coherency matrix. Second, the coherency matrix with the maximum entropy, i.e., the identity matrix is used as the volume scattering model instead of the traditional ones. Third, corresponding power constraints are appended to the scheme. Moreover, the densely vegetated areas and the residual areas are processed separately via the H/α/A classification in the proposed scheme. Finally, the polarimetric-scattering-characteristic-preserving classification is utilized to verify the improvements of the proposed scheme. To demonstrate the effectiveness of the decomposition, an Advanced Land Observing Satellite Phased-Array-type L-band Synthetic Aperture Radar polarimetric image acquired over Beijing, China, is analyzed, and the results are presented in this letter. With negative powers eliminated by the proposed scheme, improvements can be observed in the experimental results, particularly for the urban areas. © 2011 IEEE. Source

Chen J.,Ocean University of China | Chen J.,CAS Qingdao Institute of Oceanology | Cui T.,State Oceanic Administration | Tang J.,National Ocean Technology Center | Song Q.,National Satellite Ocean Application Service
Remote Sensing of Environment | Year: 2014

The objectives of this study are to evaluate the applicability of three existing retrieval algorithms of diffuse attenuation coefficients of downwelling irradiance at 490nm, Kd(490), for turbid Case II waters, and to improve these existing models using a simple semi-analytical (SSA) model. In this study, based on comparison of the Kd(490) predicted by these models with field measurements taken in the Bohai Sea and Yellow Sea, it is shown that the SSA model provides a stronger performance than these three selected existing models. The atmospheric influences on the MODIS data are removed using an improved shortwave infrared band-based (ISWIR-based) model, which is capable of retrieving spectral remote sensing reflectance within 19% uncertainty. The Kd(490) data was quantified from the MODIS images after atmospheric correction using the SSA model and Wang's model. The study results indicate that the SSA model produces 31.51% uncertainty in deriving Kd(490) from MODIS data, which is 12.1% higher than Wang's model. This study demonstrates the potential of the SSA model in estimating Kd(490) even in highly turbid coastal waters. © 2013 Elsevier Inc. Source

Discover hidden collaborations