APPLICATION OF REMOTE SENSING TECHNOLOGY TO POPULATION ESTIMATION

This paper attempts to explore a new avenue of urban small-regional population estimation by remote sensing technology, creatively and comprehensively for the first time using a residence count method, area (density) method and model method, incorporating the application experience of American scholars in the light of the state of our country. Firstly, the author proposes theoretical basis for population estimation by remote sensing, on the basis of analysing and evaluating the history and state quo of application of methods of population estimation by remote sensing. Secondly, two original types of mathematical models of population estimation are developed on the basis of remote sensing data, taking Tianjin City as an example. By both of the mathematical models the regional population may be estimated from remote sensing variable values with high accuracy. The number of the independent variables in the latter model is somewhat smaller and the collection of remote sensing data is somewhat easier, but the deviation is a little larger. Finally, some viewpoints on the principled problems about the practical application of remote sensing to population estimation are put forward.

Research on the evolution law of permafrost under the influence of urbanization based on remote sensing technology

The permafrost of Mohe County and its suburbs in the Daxing′an Mountains has been influenced by the urbanization.Remote sensing,GIS technology and numerical simulation was used to study the temperature variations of permafrost with the changes in surface vegetation that cover Mohe County and suburban areas,and the law of permafrost degradation on the study area was analyzed.The research results show that the urban area of the study area increased 114.42%from 2000 to 2016,and the urbanization process is continuing to accelerate.The Normalized Difference Vegetation Index map of 2017 in Mohe County and its suburbs was studied and the maximum proportion of vegetation coverage was different in the four seasons.The numerical calculation model results show that the permafrost temperature change in the study area cyclically fluctuates in a cosine form.The annual variation curve of permafrost temperature gradually decreased and its accompanying phase lag increased with depth.The annual temperature change value with the different depths of the town was greater than the natural ground.The maximum permafrost thawing depths of the town and natural ground were 4.2 m and 2.82 m in 50 a,and the degradation rates of the two permafrost are,respectively,0.88 cm/a and 0.46 cm/a.These results show that urbanization has accelerated the degradation of permafrost.

The Assessment of Soil Quality on the Arable Land in Yellow River Delta Combined with Remote Sensing Technology

Soil quality assessment is essential to improve the understanding of soil quality and make proper agricultural practices. However, soil quality assessments are extremely difficult to implement in a large-scale area, since they are time and labor consuming. Remote sensing technique gained more attention in plant and soil information monitoring recently for its high effi-ciency and convenience. But seldom studies tested the applicability of remote sensing techniques before implementing. This study conducted the soil quality assessment in a typical agricultural county in the Yellow River delta (Kenli). We found the soil quality in Kenli was dominantly in the low grade (71.85%), with deficient nutrient (SOM and TN), poor structure (high BD) and high EC. Salinity is the primary limiting factor for soil quality in Kenli, and adjustment of soil salinization through suitable farming practices such as organic fertilizers application, irrigation for leaching, and salt-tolerant crop planting is the key point for soil quality improvement. We obtained the normalized difference vegetation index (NDVI) of the study area by remote sensing technique, and found the high correlation between NDVI and soil quality indicator (SOM, TN and EC) and yield. The NDVI can help to study the soil conditions as a soil quality assessment indicator. More studies about the ap-plication of remote sensing technique on soil quality detecting are expected.

Application of High-Resolution Remote Sensing Technology in Quantitative Study on Coseismic Surface Rupture Zones: An Example of the 2008 M_w7.2 Yutian Earthquake

Objective Nowadays, high-resolution remote sensing technology has brought new changes to surveys of earthquakes, and the quantitative study of seismic faults based on this technology has become a trend in the world(Barzegari et al., 2017). An Mw 7.2 earthquake occurred in Yutian of Xinjiang on the western end of the Altyn Tagh fault on March 21 st, 2008. It is difficult to access this depopulated zone because of the high altitude and only 1–2 months of snowmelt. This study utilized high-resolution

THE LAND USE INVESTIGATION IN TIBET PLATEAU USING REMOTE SENSING TECHNOLOGY

Tibet Plateau is Known as "the Roof of the World" with the area of 1,220,000km^2, which is about 1/8 land area of China. Because of the high elevation, cold climate and it caused difficulties in regional economic planning and land resources management. Since 1985, the land use investigation in Tibet has been carried out, in which the basic data and thematic maps must be obtained and completed at county and township levels, in order to meet the needs of local administrations. In the investigation, remote sensing technology was comprehensively adopted. At present, the investigation in county level had been completed and the compilation is going to be carried out. Due to paying a great attention to studying on a series of key technical problems, the systematic methods of using remote sensing technology in the plateau land use investigation were formed and successfully put into application.

Research on the Agricultural Remote Sensing Image Enhancement Technology Based on the Mixed Entropy Model

Uncertainty is the most important factor affecting the quality of the remote sensing image classification.Aiming at the characteristics ofboth the random and the fuzzy uncertainties in the process of the remote sensing image classification,a method based on the mixed entropy model is proposed to measure these two uncertainties comprehensively,and a multi-scale evaluation index is established.Based on the analysis of the basic principles of the mixed entropy model,a method of using the statistical data of the feature space and the fuzzy classifier to establish the information entropy,the fuzzy entropy and the mixed entropy is proposed.At the same time,on the scale of the pixel and the category,the index of the mixed entropy of the pixel and the mixed entropy of the category are established to evaluate the uncertainty of the classification.

Remote Sensing Technology and Applications for Earthquake Disasters

Disaster warning,disaster estimation and relief depend more and more on the application of space remote sensing technologies,such as those used for optic-camera,hyperspectrum,infrared,SAR,seismo-electromagnet and gravitation measurement.On May 12,2008,a magnitude of 8.

Applications of Satellite Remote Sensing Technology in China's Environmental Monitoring

The environmental conditions in China are still very serious. In the years to come, the mission for environmental treatment and protection, supervision,

Remote Sensing Dynamic Monitoring System for Agricultural Disaster in Henan Province Based on Multi-source Satellite Data

Using 3S technology, relying on earth-space three-dimensional agriculture disaster monitoring network, remote sensing monitoring model for agricultural disaster in Henan Province was established, and agricultural disaster monitoring system plat- form of Henan Province based on multi-souroe satellite data was further constructed, which realizes dynamic monitoring of agricultural disasters in Henan Province （drought, flood, snow cover and straw burning）.

A new algorithm of retrieving a petroleum substances absorption coefficient in sea water based on a remote sensing image

Establishing the remote sensing algorithm of retrieving the absorption coefficient of seawater petroleum substances is an efficient way to improve the accuracy of retrieving a seawater petroleum concentration using a remote sensing technology. A remote sensing reflectance is a basic physical parameter in water color remote sensing. Apply it to directly retrieve the absorption coefficient of seawater petroleum substances is of potential advantage. The absorption coefficient of waters containing petroleum [ACWCP, a_o（λ）], consists of the absorption coefficient of pure water [ACPW, a_w（λ）], plankton [ACP, a_（ph）（λ）], colored scraps [ACCS, a_（d,g）（λ）], and petroleum substance [ACPS, a_（oil）（λ）]. Among those, ACCS consists of the absorption coefficient of nonalgal particle [ACNP, a_d（λ）] and colored dissolved organic matter [ACCDOM, a_g（λ）]. For waters containing petroleum, the retrieved ACCS using the existing method is a combination absorption coefficient of ACNP,ACCDOM and ACPA [CAC, a_（d,g,oil）（λ）]. Therefore, the principle question is how to extract ACPS from CAC.Through the analysis of the three proportion tests conducted between the year of 2013 and 2015 and the corresponding remote sensing data, an algorithm of retrieving the absorption coefficient of petroleum substances is proposed based on remote sensing reflectance. First of all, ACPS and CAC are retrieved from the reflectance using the quasi-analytical algorithm（QAA）, with some parameter modified. Secondly, given the fact that the backscatter coefficient [BC, b_（bp）（555）] of total particles at 555 nm can be obtained completely from the reflectance, the relation between BC and ACNP in petroleum contaminated water can be established. As a result, ACNP can be calculated. Then, combining the remote sensing retrieving algorithm of a_g（440）, the method of achieving the spectral slope of the absorption coefficient can be established, from which ACCDOM,can be calculated. Finally, ACPS can be computed as the residual. The accuracy of ACPS based on this algorithm is 86% compared with the in situ measurements.

An operational satellite remote sensing system for ocean fishery

Ocean environmental information is very important to supporting the fishermen in fishing and satellite remote sensing technology can provide it in large scale and in near real-time. Ocean fishery locations are always far away beyond the coverage of the satellite data received by a land-based satellite receiving station. A nice idea is to install the satellite ground station on a fishing boat. When the boat moves to a fishery location, the station can receive the satellite data to cover the fishery areas. One satellite remote sensing system was once installed in a fishing boat and served fishing in the North Pacific fishery areas when the boat stayed there. The system can provide some oceanic environmental charts such as sea surface temperature (SST) and relevant derived products which are in most popular use in fishery industry. The accuracy of SST is the most important and affects the performance of the operational system, which is found to be dissatisfactory. Many factors affect the accuracy of SST and it is difficult to increase the accuracy by SST retrieval algorithms and clouds detection technology. A new technology of temperature error control is developed to detect the abnormity of satellite-measured SST. The performance of the technology is evaluated to change the temperature bias from -3.04 to 0.05 ℃ and the root mean square (RMS) from 5.71 to 1.75℃. It is suitable for employing in an operational satellite-measured SST system and improves the performance of the system in fishery applications. The system has been running for 3 a and proved to be very useful in fishing. It can help to locate the candidates of the fishery areas and monitor the typhoon which is very dangerous to the safety of fishing boats.

GIScience and remote sensing in natural resource and environmental research:Status quo and future perspectives

Geographic information science(GIScience)and remote sensing have long provided essential data and method-ological support for natural resource challenges and environmental problems research.With increasing advances in information technology,natural resource and environmental science research faces the dual challenges of data and computational intensiveness.Therefore,the role of remote sensing and GIScience in the fields of natural resources and environmental science in this new information era is a key concern of researchers.This study clarifies the definition and frameworks of these two disciplines and discusses their role in natural resource and environmental research.GIScience is the discipline that studies the abstract and formal expressions of the basic concepts and laws of geography,and its research framework mainly consists of geo-modeling,geo-analysis,and geo-computation.Remote sensing is a comprehensive technology that deals with the mechanisms of human ef-fects on the natural ecological environment system by observing the earth surface system.Its main areas include sensors and platforms,information processing and interpretation,and natural resource and environmental appli-cations.GIScience and remote sensing provide data and methodological support for resource and environmental science research.They play essential roles in promoting the development of resource and environmental science and other related technologies.This paper provides forecasts of ten future directions for GIScience and eight future directions for remote sensing,which aim to solve issues related to natural resources and the environment.

Research on a Watermarking Algorithm for Remote Sensing Images Resist Screen Capture Attacks in Urban Planning Information Management

Remote Sensing data, as an essential urban basic information in urban planning, has the characteristics of large information capacity, real time, high update speed and accuracy. Because of urban spatial information involving multi-faceted public and public interests, its data security is very important. The use of digital watermarking technology can effectively protect the secu-rity of urban planning basic data. In practical applications, the “screen capture” poses a great threat to the security of remote sensing image. In order to resist the screen capture attacks, the QR code watermark information is encoded and converted, and combined with a circular angle template watermark, a digital watermarking algorithm for remote sensing images in urban planning information management is proposed. And the proposed algorithm is experimentally verified. Experiments show that the algorithm is robust against screen capture attacks, and provide security guarantee for urban construction and management.

Development and evaluation of low-altitude remote sensing systems for crop production management

Precision agriculture accounts for within-field variability for targeted treatment rather than uniform treatment of an entire field.It is built on agricultural mechanization and state-of-the-art technologies of geographical information systems(GIS),global positioning systems(GPS)and remote sensing,and is used to monitor soil,crop growth,weed infestation,insects,diseases,and water status in farm fields to provide data and information to guide agricultural management practices.Precision agriculture began with mapping of crop fields at different scales to support agricultural planning and decision making.With the development of variable-rate technology,precision agriculture focuses more on tactical actions in controlling variable-rate seeding,fertilizer and pesticide application,and irrigation in real-time or within the crop season instead of mapping a field in one crop season to make decisions for the next crop season.With the development of aerial variable-rate systems,low-altitude airborne systems can provide high-resolution data for prescription variable-rate operations.Airborne systems for multispectral imaging using a number of imaging sensors(cameras)were developed.Unmanned aerial vehicles(UAVs)provide a unique platform for remote sensing of crop fields at slow speeds and low-altitudes,and they are efficient and more flexible than manned agricultural airplanes,which often cannot provide images at both low altitude and low speed for capture of high-quality images.UAVs are also more universal in their applicability than agricultural aircraft since the latter are used only in specific regions.This study presents the low-altitude remote sensing systems developed for detection of crop stress caused by multiple factors.UAVs,as a special platform,were discussed for crop sensing based on the researchers'studies.

Estimation of carbon and nitrogen contents in citrus canopy by low-altitude remote sensing

The study aimed to investigate the fast and nondestructive method for detecting carbon and nitrogen content in citrus canopy.The multispectral imagery of Tarocco blood orange(Citrus sinensis L.Osbeck)plant canopy was obtained by a multispectral camera array mounted at an eight-rotor unmanned aerial vehicle(UAV)flying at an altitude of 100 m above the canopy in Wanzhou District of Chongqing Municipality,China.Average spectral reflectance data of the whole canopy,mature leaf areas and young leaves areas were extracted from the imagery.Two spectral pre-processing methods,multiplicative scatter correction(MSC)and standard normal variable(SNV),and two modeling methods,the partial least squares(PLS)and the least squares support vector machine(LS-SVM),were adopted and compared for their prediction accuracy of total content of nitrogen,soluble sugar and starch in the leaves.The results showed that,based on the spectral data extracted from the mature leaves in the multispectral imagery,the PLS model based on the original spectrum obtained a Rp(correlation coefficient)of 0.6469 and RMSEP(root mean squares error of prediction)of 0.1296,suggested that it was the best for the prediction of total nitrogen content;the PLS model based on MSC(multiplicative scatter correction)spectrum pre-processing was the best for predicting total soluble sugar content(Rp=0.6398 and RMSEP=8.8891);and the LS-SVM model based on MSC was the best for the starch content prediction(Rp=0.6822 and RMSEP=14.9303).The prediction accuracy for carbon and nitrogen contents based on the spectral data extracted from the whole canopy and the young leaves were lower than that from the mature leaves.The results indicate that it is feasible to estimate the carbon and nitrogen contents by low-altitude airborne multispectral images.

Application Advantages of Staring Area Imaging Technology(SAIT) for Microsatellites

The Staring Area Imaging Technology(SAIT) satellite continuously "images" the target over a certain time range, and can realize continuous imaging and multi-angle imaging of the area of interest. It has the characteristics of flexible imaging parameter setting and fast image preprocessing speed, enabling dynamic target detection and tracking, super-resolution, surface 3 D model construction, night-time imaging and many other application tasks. Based on the technical characteristics of the SAIT satellite, this paper analyzes the challenges in satellite development and data processing, focuses on the quasi-realtime application of SAIT satellite data, and looks at the development trend of the SAIT satellite.

Space Technology for Decarbonising City Precincts

Space technology is a powerful tool for climate research. Satellite data improve knowledge of the human impact on the Planet’s physical geography. Similarly, remote sensing technology enhances understanding of the human impact on rising global carbon emissions. However, so far satellites have been principally limited to measuring the carbon emissions of cities from space. Standing alone, satellite technology is incapable of advancing the goal of decarbonisation. This will be achieved only if cities create local methodologies that significantly enhance the carbon reduction process. There exists enormous potential to bridge remote sensing for earth observation and global environmental change with local action towards decarbonised urban renewal and redevelopment. Satellite remote sensing has the ability to demonstrate if local remedial strategies are succeeding, and assist with planning, developing, and monitoring low and zero carbon infrastructure systems. Satellite-derived data can facilitate informed discussion and decision-making between community stakeholders to deliver low carbon outcomes at the precinct scale. Satellite-based systems can be integrated within the urban fabric to assist climate change mitigation. This paper is based on current work implemented jointly with municipalities to ascertain where within city precincts carbon emissions originate and how they can ultimately be reduced. It presents space technology as an instrumental tool for understanding the carbon impact of cities—in terms of the carbon intensive patterns and processes that shape human society, as well as having great potential for providing end-user products to communities to enhance the process of decarbonising city precincts.

A Brief Review of 3S Technology Application on Biodiversity Monitoring and Assessment

Remote sensing,geographic information system and GPS(3S)technology have been well recognized as comprehensive,accurate and up-to-date information collection methods,which are increasingly adopted in biodiversity conservation.This review summarizes the application of object-oriented classification methods on biodiversity monitoring projects based on high-resolution remote sensing imagines in China.Biodiversity conservation research based on GIS technology in China is also discussed,with emphasis on the advantages of GIS analysis and modeling function.

Application of 3S Technology in Dynamic Monitoring of Capital Farmland

Firstly,this paper introduces current situations of protection of capital farmland. According to current situations,it analyzes significance in protecting capital farmland and significance and functions of application of 3S technology in dynamic monitoring of capital farmland. With the aid of examples,it discusses functions of remote sensing and GIS in dynamic monitoring of capital farmland. It is believed that 3S technology not only can provide accurate parcel data of capital farmland changes for reviewing land change survey,but also can provide data for monitoring development situations of capital farmland,as well as provide basic current information for decision-making department.

Using remote sensing to research Beijing wetlands dynamics

In Beijing, where wetlands are important to municipal freshwater conservation and biodiversity retention, three different types of wetlands were identified: riverside wetlands, wetlands surrounding lakes and reservoirs, and wetlands in municipal parks.Remote sensing technology was applied in combination with field investigations to monitor and analyze the changes in these wetlands, and a combination of fusion technologies,Landsat TM/ETM+ and IKONOS imaging, was used to investigate and map them. This study indicates that not only have wetland areas been reduced by half, but also their ecological environments have been degraded because of rapid economic development and population increase. Suggestions based on this research are made to reconstruct the ecological environment of the wetlands and return them to their previous state.