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- 实验方案
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[IEEE 2018 International Conference on Applied Engineering (ICAE) - Batam, Indonesia (2018.10.3-2018.10.4)] 2018 International Conference on Applied Engineering (ICAE) - An Integrated Comparative Approach to Estimating Forest Aboveground Carbon Stock Using Advanced Remote Sensing Technologies
摘要： Greenhouse gases in the atmosphere play a very important role in maintaining the temperature of the earth. Plants absorb carbon in the atmosphere in the form of CO2 which is beneficial for photosynthesis which will produce O2 into the atmosphere. By utilizing remote sensing technology and field data integration, this research aims to estimating aboveground carbon reserves in the research area. The results of this research indicate that the above ground carbon stock resulting from estimation calculations using remote sensing data and field calculations using brown allometric are 103,397 TonC / Ha with an error rate of 1,8354. This error level indicates the size of the error in the estimated value of each pixel.
关键词： Carbon Stock,Batam Island,Temperature,Remote Sensing Data,Greenhouse Gases
更新于2025-09-23 15:22:29
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Effects of Photovoltaic Module Materials and Design on Module Deformation Under Load
摘要： We developed and successfully applied data-driven models that heavily rely on readily available remote sensing datasets to investigate probabilities of algal bloom occurrences in Kuwait Bay. An artificial neural network (ANN) model, a multivariate regression (MR) model, and a spatiotemporal hybrid model were constructed, optimized, and validated. Temporal and spatial submodels were coupled in a hybrid modeling framework to improve on the predictive powers of conventional ANN and MR generic models. Sixteen variables (sea surface temperature [SST], chlorophyll a OC3M, chlorophyll a Generalized Inherent Optical Property (GIOP), chlorophyll a Garver-Siegel-Maritorena (GSM), precipitation, CDOM, turbidity index, PAR, euphotic depth, Secchi depth, wind direction, wind speed, bathymetry, distance to nearest river outlet, distance to shore, and distance to aquaculture) were used as inputs for the spatial submodel; all of these, with the exception of bathymetry, distance to nearest river outlet, distance to shore, and distance to aquaculture were used for the temporal submodel as well. Findings include: 1) the ANN model performance exceeded that of the MR model and 2) the hybrid models improved the model performance significantly; 3) the temporal variables most indicative of the timing of bloom propagation are sea surface temperature, Secchi disk depth, wind direction, chlorophyll a (OC3M), and wind speed; and 4) the spatial variables most indicative of algal bloom distribution are the ocean chlorophyll from OC3M, GSM, and the GIOP products; distance to shore; and SST. The adopted methodologies are reliable, cost-effective and could be used to forecast algal bloom occurrences in data-scarce regions.
关键词： remote sensing,data mining,neural networks,Coupled spatiotemporal algal bloom model,Kuwait bay
更新于2025-09-19 17:13:59
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Similarity Evaluation Modal for Remote Sensing Data Distribution
摘要： The growth in the remote sensing data available has led to information overload, as seeking out the precise data has become more and more challenging. In this paper, a similarity evaluation modal is proposed to assist the user in his/her quest for accurate data. In the modal, correlation degree and correlation functions combining topology are proposed to evaluate the similarity degree between user’s requirement and data quantitatively. Therefore, the advantages and disadvantages of different schemes can be compared.
关键词： similarity evaluation modal,correlation degree,dissemination of remote sensing data,correlation function
更新于2025-09-10 09:29:36
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Towards a Framework for Offering Remote Sensing Data in an Analysis-Ready Format
摘要： Diverse storage formats, archive dispersal, and inconsistent naming make it difficult for researchers and the general public to find and access remote sensing data. To facilitate the use of remote sensing data, this paper provides an integrated framework for direct reading remote sensing data in a widely compatible and analysis-ready format, NumPy ndarray. The framework is composed of two main components. One is the raster data processing and storage model. All the operational gridded remote sensing data are split into tiles, and reorganized in n-dimensional array. Then the N-Dimensional data array is serialized into netCDF and stored into distributed file system. The other is the spatiotemporal filter to achieve parallel query, and it has been encapsulated into Internet-accessible application programming interfaces (APIs). The scenario of calculating NDVI of a specified spatiotemporal range given at last illustrate the efficiency and convenience of our platform provided for remote sensing data analysis.
关键词： remote sensing data,spatiotemporal retrieval,multi-dimensional array,analysis-ready format
更新于2025-09-09 09:28:46
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Fractal Filters Intended for Signal Detection during Remote-Sensing Data Processing
摘要： A new approach to processing and analysis of noisy data inherent to the optical systems of Earth remote sensing systems is proposed and investigated. This approach involves the system integration of several conceptual ideas based on the multiscale representation of fractal sets, recursive scans, and wavelet transforms, making it possible to improve the signal detection efficiency under complex background?target conditions.
关键词： signal detection,wavelet transforms,multiscale representation,recursive scans,fractal filters,remote-sensing data processing
更新于2025-09-04 15:30:14