Possibility of the Application of the Ultra-long Electromagnetic Wave Remote Sensor to Marine Geological Exploration

The ultra-long electromagnetic wave remote sensing technique developed by Peking University is one of new future techniques, which can detect the submarine geological information from the depth of 20 to 10000 m below the surface by receiving natural ultra-long electromagnetic waves (n Hz to n 100 Hz). The new remote sensor is composed of three parts: a main instrument with a portable computer, an antenna with an amplifier and an external power.

Study on straw incineration monitoring based on the combination of remote sensing image

Straw incineration monitor is a key part of international environmental governance.In the paper,the combination of MODIS,MUX and TLC remote sensors is used to monitor straw burning fire points accurately.MODIS remote sensor has the characteristics of high temporal resolution and thermal infrared band,which can be used to judge the regional thermal abnormal variation and preliminary extract the suspicious thermal abnormal points.Combining with GIS information,the preliminary position of MODIS thermal abnormal points can be acquired.The MUX and TLC sensors of ZY-3 satellite in the preliminary position area can be pretreated,which includes radiometric calibration,atmospheric correction,geometric precision correction,ortho-rectification,etc.Through analyzing the physical properties and spectral information in the straw incineration area,the interpretation features of the straw incineration area will be determined.Then the high geographical resolution fusion image with two meters resolution can be interpreted,and the information of fire-point in high geographical resolution remote sensor can be extracted.Combining with the Google earth map to compare interpretation images in different time range of this area,and using ArcGIS platform to accurately position the confirmed fire point,the final position of the fire can be determined.Correspondingly,the combination of remote sensing sensors with high,medium and low resolution can be used to monitor the straw incineration point in county area.In experimental area,there are twenty-three straw burning fire points are found.The experimental results show that,this method can realize precise monitoring of straw incineration point in county area.However,straw incineration point monitoring in real time still need to be further investigated.

Thermal Analysis and Validation of GF-4 Remote Sensing Camera

The Chinese GF-4 satellite remote sensor is the highest spatial resolution among the civil satellite on the geosynchronous orbit, which carries on a camera with spatial resolution of 50 meter in the bands of visible and near infrared red and 400 meter in middle infrared red band. The thermal design of the spacecraft was challenging because the high resolution and the sensitivity requirement to achieve the desired scientific objectives. This paper presents the thermal analysis and test of the GF-4 in GEO orbit. The major findings of the analyses are the following. The GF-4 experiences complex, alternating external heat flux and faces direct sunlight in most of the orbital period. By applying a finite element model, the predicted temperature variation of the components remains in the desired temperature regime even in the extreme conditions. Comparing the thermal analysis results, the difference between the predicted and measured temperatures was less than 3°C for most of the components. The thermal control system functioned properly and the thermal model simulated the actual thermal design of GF-4. This thermal design method realizes the high efficiency and precision thermal control of the first high resolution geostationary orbit camera in China, which can provide reference for the high precision and stability thermal control of large aperture optical camera.

Remote sensing imagery in vegetation mapping: a review

Aims Mapping vegetation through remotely sensed images involves various considerations,processes and techniques.Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources.Various sources of imagery are known for their differences in spectral,spatial,radioactive and temporal characteristics and thus are suitable for different purposes of vegetation mapping.Generally,it needs to develop a vegetation classification at first for classifying and mapping vegetation cover from remote sensed images either at a community level or species level.Then,correlations of the vegetation types(communities or species)within this classification system with discernible spectral characteristics of remote sensed imagery have to be identified.These spectral classes of the imagery are finally translated into the vegetation types in the image interpretation process,which is also called image processing.This paper presents an overview of how to use remote sensing imagery to classify and map vegetation cover.Methods Specifically,this paper focuses on the comparisons of popular remote sensing sensors,commonly adopted image processing methods and prevailing classification accuracy assessments.Important findings The basic concepts,available imagery sources and classification techniques of remote sensing imagery related to vegetation mapping were introduced,analyzed and compared.The advantages and limitations of using remote sensing imagery for vegetation cover mapping were provided to iterate the importance of thorough understanding of the related concepts and careful design of the technical procedures,which can be utilized to study vegetation cover from remote sensed images.

A tree counting algorithm for precision agriculture tasks

This study proposes an automatic procedure for individual fruit tree identification using GeoEye-1 sensor data.Depending on site-specific pruning practices,the morphologic characteristics of tree crowns may generate one or more brightness peaks(tree top)on the imagery.To optimize tree counting and to minimize typical background noises from orchards(i.e.bare soil,weeds,and man-made objects),a four-step algorithm was implemented with spatial transforms and functions suitable for spaced stands(asymmetrical smoothing filter,local minimum filter,mask layer,and spatial aggregation operator).System perfor-mance was evaluated through objective criteria,showing consistent results in fast capturing tree position for precision agriculture tasks.