Remote Sensing Roles on Driving Science and Major Applications
Wu Bingfang, Xing Qiang
Key laboratory of Digital Earth Sciences, Chinese Academy of Sciences Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing100101, China
Abstract
This paper aims at discussing the roles of remote sensing on driving the development of Earth System Science and the major application domains based on domestic and foreign remote sensing cases. Remote sensing has led to the development of the research on global change, making human beings being capable of exploring the future of the life on earth with a new perspective. Remote sensing has also driven the transformation of Earth Science from qualitative analysis to quantitative development, from description to further analysis, from single site to regional application with multiple temporal and spatial scales. As a result, it leads to the appearance of many emerging cross-disciplines. Remote sensing is an application-driven subject, with numerous application fields after many years of development. However, different countries in the world have different priorities, which are dependent on their own national conditions. For China, safeguarding national global interests, rapid response to disasters and assessment after disasters, independent supervision from the third party and safeguarding national defense security are the major applications. Remote Sensing data consistency is of crucial importance in order to allow for time series comparison analysis and anomaly detection, which is recognized as the core of quantitative remote sensing and also the basis for driving remote sensing applications to a deeper level continually.
Keyword:
Remote sensing; Global change; Earth science; Global interests; Defense security.
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At present, global change is the hot area in geo-science, at the same time, it is also one of the core pans ofgeo-informatics. Global change emphasizes the research on the interaction between the geo-spheres, such as theatmosphere, the biosphere and the hydrological sphere,and on the environmental impacts caused by human beings.Geographic information system(GIS), which has been developing very quickly since 1970s, has been applied to many areas of management of earth resources and environment. But now, GIS is still at its primary stage especially in China, for example only very few of GIS function has been used in the built GIS systems, such assome urban GIS systems built recently in China.From the historical view, that men observe and understand the earth is accelerating in many fields, such as advancement of observing techniques, acquired data amounts and quality etc.. In the space, the earth observingsatellites have been keeping on eyeing our planet and its changes. Much data has been gathered pretty enough formonitoring our environment, and only in this time the each could be studied and understand systematically and onthe global scale.The earth is a very complicated system. In the system much physical process, including gradual changes andsudden changes, exist and sometimes seem hard to predict, and in the unique system, human migration, materialflow, energy flow and information flow interact in its own wad. Observed dsta from space, which is vast andtheme diverse, becomes the base material source to understand global change systematically. But unfortunatelythese data are not fully studied at the present time because of data vastness and method deficiency. As a geospatial information system, GIS should be applied to solve complex problems in geo-science. In global change study, based on observed data of different scales, GIS should be applied tot nature modeling; human-earthrelationship study; pro.jecting and forecasting, and therefore facilitate the global change studies and decisionmakings in the sustainable development planning at present and in the future.
Remote sensing technology has a special capability with rapid speed, multispectral, and large and periodic coverage. It has been playing an increasingly important role in global environment change study. As a fast development of remote sensing technology in the world, it is widely used for global environment change study in China. This paper summarizes the activities and achievements of remote sensing application to investigation of land use, forest, pasture land and oceans and monitoring of disasters in China.This achievement is a base for the remote sensing further application to global environment change study in China.
Remote sensing has the potential to provide quantitative spatially explicit hydrological information across northern peatland complexes. This paper details a multi-scale remote sensing approach for assessing the use of Sphagnum mosses as proxy indicators of near-surface hydrology. Several spectral indices developed from the near infra-red (NIR) and shortwave infra-red (SWIR) liquid water absorption bands, as well as a biophysical index can be correlated with measures of near-surface moisture in the laboratory, in the field and from airborne imagery. Data from all platforms revealed similar patterns in the spectral indices in relation to changes in moisture although the strength of correlations was reduced as the spatial scale increased. The rapid collection of temporally and spatially explicit hydrological data means that the technique has potential practical application for environmental managers and peatland scientists at the local scale. The task of up-scaling the technique for use in operational peatland hydrological monitoring to the global scale is challenging but achievable, and requires further investigation into the heterogeneity of near-surface moisture across Sphagnum patches and the application of novel image processing techniques to improve the spatial resolution of currently available satellite imagery.
Shifts in the timing of spring phenology are a central feature of global change research. Long-term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start-of-spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground-based phenology, and two temperature-driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day-of-year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground- or model-based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.
Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
“CropWatch”, developed and operated by Institute of Remote Sensing Applications (Chinese Academy of Sciences), is one of the three operational crop monitoring systems with remote sensing that can provide global-scale crop information. The system can provide information on crop yield, crop condition, crop acreage, crop production and agricultural drought, etc. The system has been developing since 1998. After 12 years′ improvement, it has been developed into a system that can provide independent, comprehensive and fast large scale crop information with advanced monitoring technology. A special issue on “CropWatch” was published by “Journal of Remote Sensing” in 2004 to summarize its methodology and development from 1998 to 2004. After that (20052009), “CropWatch” has made great improvement on system efficiency and independency. Great contribution from the system has been witnessed in snow disaster in south China in 2008, Wenchuan earthquake in 2008, drought in north China in 2009 and drought in southwest China in 2010. The paper introduces the development of the system between 2005 and 2009 in systematization, independency, system application and system extension in detail, and then presentes a future perspective on the system′s development in the Twelfth Five Years (from 2011 to 2016).
What the future integrated watershed management patterns requires is that data, information, and knowledge can flowfreely among all the managers, scientists, engineers and stakeholders. Basin-scale data acquisition, information extraction, andknowledge abstraction are the basis for such activities. Satellite remote sensing technology provides a new technological meansfor this mode of management. In the past, the application of remote sensing in watershed management was limited, due to the difficultyin obtaining data and the scarcity of the application methods. This paper introduces the progress of watershed managementand its requirements for data and methods; analyzes the progress of remote sensing methods used in watershed management and itsdevelopment potential, and proposes two types of remote sensing methods for watershed management including remote sensing coprocessing(as inversion) and watershed space management. Furthermore, taking the Hai Basin as a typical study area, the researchresults about the watershed remote sensing methods and application cases obtained from a sub-project of the Key Innovation Projectof Chinese Academy of Sciences, which is called the “Environmental Effects Monitoring and Evaluation of the Hai Basin ManagementProject Using Remote Sensing” were introduced, and the prospects of remote sensing for watershed management in the futurewill be demonstrated.
Imaging radar (SAR) posseses unique capabilities, which can work all day/all night and allm weather, can penetrate some special objects and can detect the shapes of ground objects. Especially, with the developments of new imaging radars,such as polSAR, InSAR, and data processing technologies, environmental remote sensing using SAR can provide more and more information about terrestrial ecosystems.All these can greatly propel and improve the SAR applications to ecological environment. The paper reviews the demonstrated capabilities of imaging radars for investigating terrestrial ecosystems, including four broad categories:①land cover classification and vegetation mapping;②estimation of woody plant biomass;③monitoring the extent and timing of inundation and wetland; and④monitoring other temporally-dynamic processes. Finally, the selection of optimal parameters of SAR system for different ecological applications are listed and anzlyzed. It can provide significant reference for ecological applications using SAR data in China.
Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
Big data has been a focus of research in fields such as science, technology, the economy, and society. Many countries already research big data as a national strategy. This paper elaborates the origin, connotation and development momentum of big data from spatial and temporal perspectives. It proposes that scientific big data will become a new solution in scientific research as the paradigm changes from being model driven to data driven. This paper defines the concept of "scientific big data" and strategies for solving "big data problems". Theoretical frameworks and data systems for the digital Earth are discussed with a clear conclusion that the digital Earth is highly featured with scientific big data. Taking spatial cognition of formation mechanism of the "Heihe-Tengchong Line" as an example, big-data computation and analysis are studied for the digital Earth.
By illustrating the relationship between the climate system and the scientific data, a requirement of scientific data for the earth system research has been proposed to be paid more attention to climate change studies. The research progresses of global climate change in China for the recent 10 years have been reviewed and the important role of observation datasets and assimilated production in the global climate change has been pointed out. Furthermore, the meteorological data sharing situation
Land cover change is an important part of ecosystem change and driving factors. In the impacts of the global change and the ecological construction in the 2000s, the land cover of China has changed significantly. Monitoring and analysis of this change not only can support China carbon source/sink evaluation and assessment of carbon budget, but also provide the basic data for the ecological environment evaluation. Supported by object-oriented classification technology, the land cover data of China (ChinaCover) in 2000 and 2010 have been produced using Landsat TM/ETM and HJ-1 satellite data of 30m resolution, combined with a large number of data of field investigation. At the same time, vegetation coverage data has been produced using the dimidiate pixel model with resolution of 250m. This study has analyzed the change of China land cover changes based on the land cover data and vegetation coverage data of 2000 and 2010. Results have showed that:there have been a total of 19×10 4 km 2 land cover changes, accounting for about 2% of the China land area. The areas of woodland and artificial surface have been increased the areas of grassland, wetland and cultivated land have been decreased. The rapid increase of artificial surface and the mass reduction of cultivated land has been the main trend of land cover changes. The area of artificial surface has increased by 28.7%, while the area of cultivated land has decreased by 4.8×10 4 km 2 , 2.7% lower than in 2000. The conversion areas of cropland to artificial surface have been mainly concentrated in Eastern China the conversion areas of cropland to forest and grassland have been mainly distributed in the areas where the "Regulations on Restoring Farmland to Forest" has been carried out Arable land expansion has been mainly occurred in the Sanjiang plain and the Xinjiang oasis. The vegetation coverage changes of forest, shrub and grassland have showed an overall upward trend in 2000s. There have been 47.3%, 58.8% and 55.6% of the forest, shrub and grassland vegetation cover has been improved. But forest quality has had the trend of degradation in the Wenchuan earthquake-stricken area, Hengduan Mountains and Wuyi Mountain areas shrub vegetation coverage has declined around the Tarim basin, eastern Tibet Plateau, Taihang Mountain, and Lüliang Mountain areas grassland has been deteriorated in central Inner Mongolia, southwestern Tibet Plateau, southern Tianshan and Hulun Buir.
To accurately assess the ecological environment and estimate China carbon budget, 2010 land cover data for China has been produced. ChinaCover2010 is based mainly on domestic HJ-1 satellite remote sensing data and its land cover classification consists of two levels: (i) 6 land cover types defined by the Intergovernmental Panel on Climate Change (IPCC) and (ii) 38 land cover types defined by the Land Cover Classification System (LCCS), developed by the UN Food and Agricultural Organization (FAO). The FAO LCCS was chosen for its global application and ability to be used for different mapping scales, land cover types, data sources, and geographic areas. .Efficiency in preprocessing large amounts of remote sensing data was greatly improved by the use of parallel computing methods with supercomputers. For the land cover classification, China’s territory was divided into 835 working blocks; classification was object-based and supported by the use of a sample database populated with in situ data obtained from 85,467 field samples nation-wide. Every sample was an image object in the database with specific object features in terms of spectra, shape, and texture. Radar data was used to optimize the boundaries of artificial surfaces and water areas. For each block, a decision tree of classification was established, after which the blocks were put into a panoramic mosaic for each regional prefecture or province level. Accuracy of ChinaCover 2010 was guaranteed through the use of an independent quality control and accuracy evaluation system. The data was validated with samples collected independently from high spatial resolution images and field work data. Average accuracy was 94% and 86% for the first and second levels respectively. Overall, the classification accuracy for Northwest, North, and East China was above that for Southwest, South, and Northeast China because of the relatively even distribution of land cover classes in the former. Based on user feedback and additional field survey data, the data will continue to be modified in the future to further improve the classification. Analysis of ChinaCover2010 has showed that cropland (not adjusted for cultivation) makes up 18.2% of the total area and is mainly distributed in the various plain areas, such as the Northeast Plain, the North China Plain, the Middle-Lower Yangtze Plain, the Pearl River Delta Plain, and the Sichuan Basin; the cropland areas generally are densely populated areas. The largest area of land cover is formed by woodland, which covers 27.3% of the total area and mainly occurs in mountainous areas with ample sunshine and rainfall, such as the Greater Hinggan, the Lesser Hinggan, and the Changbai Mountain in Northeast China; the Taihang Mountains in North China; Hengduan Mountains in Southwest China; and Nanling Mountains in South China. Grassland (excluding desert) makes up 20.2% of China’s total area and mainly occurs in areas that are relatively colder, such as the western part of Northeast China, the Mongolian Plateau, the Loess Plateau, and the Tibetan Plateau. Human Settlements and wetland are fragmented, making up 2.6% and 3.6% of the total area respectively. Other classes of land cover together make up the remaining 28.1%.
Satellite remote sensing data play an important role in the improvement of climate models forcing field, relevant physical parameters and simulation accuracy. At present, there are many years of satellite remote sensing data and a variety of products about land surface attributes. However, the application of satellite remote sensing data to climate models is still very limited. Fully using satellite remote sensing data is important to improving the simulation ability. In the paper, remote sensing estimates methods of three key land surface parameters including Fractional Vegetation Coverage(FVC), Leaf Area Index(LAI)and surface albedo(Albedo)is reviewed and upor downscaling land surface variables in validation process is analyzed. Secondly, taking WRF(Weather Research and Forecasting)model as an example, three parameters in climate model are described. Finally, the key problems of using remote sensing data in climate models are discussed, which comprise the uncertainties and scales of remote sensing estimation parameters and the future direction is prospected.
卫星遥感资料对于改善气候模式的强迫场,改进相关物理参数,提高数值模式模拟的准确性具有重要作用。目前,全球已经积累了多年的卫星遥感资料,并且已有多种陆面参量遥感产品。然而,卫星遥感资料在气候模式中的应用还非常有限。充分利用卫星遥感资料,对于提高气候模式模拟能力具有重要作用。选择植被覆盖度(Fractional Vegetation Cover,FVC)、叶面积指数(Leaf Area Index,LAI) 和地表反照率(Albedo)3个关键陆面参量的遥感估算方法进行评述,并分析了陆面参量真实性检验的尺度转换问题,还以WRF (Weather Research and Forecasting model)为例,阐述了遥感估算的陆面参量应用于模式的表达方式。最后讨论了关键陆面参量遥感估算的不确定性和遥感参量应用于气候模式的尺度匹配等亟待解决的问题,并对这些问题的未来改进方向进行了展望。
At the present time remote sensing technology, because of its prominent advantages, is playing an important role in land surface processes (LSP)research. Main characteristics of land surface processes research can be summarized as follow: (1)more and more meteorologists pay attention to LSP research;(2)international cooperative research on LSP become very active;(3)interdisciplinary cooperative research between different research fields is being improved to LSP research;(4)remote sensing technology becomes one of necessary tools in LSP research. With the development of remote sensing technology, more and more land surface parameters such as albedo, emissivity, land surface temperature(LST) and soil moisture etc. can be retrieved from satellite remotely sensed data, and the retrieval precise of the parameters become better and better. Optical remote sensing (including visible, near infrared and thermal infrared remote sensing) prove to be effective in retrieving the parameters such as albedo, LST and emissivity, and a lot of retrieval algorithms have been developed. For example, LST, an important land surface parameter, can be estimated well by means of split window algorithms from NOAA/AVHRR data. In contrast to optical remote sensing, microwave remote sensing (both active and passive) has great advantages in retrieving soil moisture. By using the relation between σ 0 ,backscattering coefficient and, soil moisture or the relation between T B, brightness temperature of radiometer and soil moisture, we can estimate the value of soil moisture from microwave remotely sensed data. The capacity of the microwave sensors to penetrate non raining clouds makes them very attractive for use as soil moisture sensors. After reviewing the various algorithms of remote sensing to retrieve land surface parameters and calculate surface energy fluxes and combination of remote sensing with land surface processes models, we concluded that:(1) it is known to all to choose optical or microwave remote sensing according to the feature of the parameter;(2) it becomes a focus that one parameter is derived by various kinds of remote sensing data;(3) studing on combination of remote sensing with LSP models will be improved by the international land surface processes experiments.
The recent program of WCRP/CliC, which represents the current tendency of the international studies on cryopshere, is introduced. Cryopshere is an important water resource in China for maintaining the socioeconomic development in the arid and oasis regions, it also plays an important role in stabilizing the ecological system over the cold regions of western China such as Qinghai Xizang Plateau. With the global warming, the effects of the climate, environment, ecology and water resource by cryospheric decay are becoming more negative and stronger. These effects threat the security of the sustainable development in western China. It suggests that future cryospheric studies in China should focus on the following 5 projects: Processes monitoring, paleo climate and paleo environment records, cryospheric and climatic modeling, relations of cryospheric change and water resources, and impacts assessment and adaptation strategy under various scenarios of cryospheric changes.
The meteorological satellite and satellite meteorology are new monitoring technology and discipline that gained quick development and great success in past decades. At present, the met eorological satellite plays the most important role in the earth-atmosphere monitoring system, whereas satellite meteorology is avery active field in the earth science. This paper reviews that the progress and achievements in the meteorological satellite developments and applications since the 70s of 20 century. (1) The history of China meteorological satellite development is introduced, with the focus being on the launch, operation and basic specifications of orbit and geostationary meteorological satellites. (2) The researches on the theory and data processing method of satellite remote sensing is reviewed, especially on the retrieval of temperature profile, cloud properties, aerosols, precipitation and cloud wind. (3) The achievement on the China satellite applications is described, including those in the weather analysis and forecast, numerical weather prediction, climate monitoring and short range climate fore cast. The recent development on the meteorological sat ellite data assimilation is also introduced.
Zhang Hongmei , Wu Bingfang , Yan Na#cod#x02019;na.
张红梅, 吴炳方, 闫娜娜
Vapor Pressure Deficit (VPD) is an important climatic variable widely used in many ecosystem models to simulate fluxes and states of water and carbon; it plays an important role in fire warning and epidemic disease early warning systems. Accurate estimation of spatio-temporally distributed VPD is critical for ecosystem and climate modeling efforts. In this paper, the available remote sensing datasets for satellitebased VPD estimation are analyzed, the precision and spatial resolution are two important factors for selecting remote sensing data. Then, the principle and advantages of different estimation algorithms are analyzed, which include the regression method and analytic method. The regression method is simple, but requires mass sample data and can not be used in other region before calibration. The analytic method is more complex, but can be used anywhere once established. The near surface air temperature and humidity are two key parameters for estimating VPD, which are usually estimated from the satellite retrieved land surface temperature and total precipitable water vapor. The errors in estimated VPD cloud are further eliminated by improving the accuracy of input remote sensing data and improving estimation algorithms of near surface air temperature and humidity. Finally, the existing problems and the VPD estimation research prospect are discussed. Most research work is limited in clear sky days until now, and VPD estimation under cloudy days is a challenging work, but it is important for many applications. A full VPD map could be achieved by combining several satellite data from different instruments, especially by taking the advantages of optical and microwave remote sensing. The prospects of the satellitebased VPD estimation technologies are presented.
Vegetation,as the principal component of terrestrial ecosystem,plays an important role in sustaining global substance and energy cycle,adjusting carbon balance and alleviating the rise of atmospheric CO 2 concentration and global climate change. Vegetation production of terrestrial ecosystem has been one of the major subjects for the research on global change. The satellite-based model of vegetation productivity has undergone several stages of development,including the initial simple statistical model,the later process model based on light use efficiency principle. Based on remote sensing vegetation data with spatially and temporally continuous distribution,statistical model is crucial in estimating vegetation productivity on the regional and global scale. Statistical model can be classified into two categories: one is direct establishment of the correlation between vegetation index and vegetation productivity,based on which regional estimation is possible; the other is the establishment of regression parameter vector for regional applications,which is realized through the integrated utilization of vegetation indices and other environmental factors and using regression tree,neural network and other complex statistical methods. Light use efficiency model is the major approach to estimating vegetation productivity based on remote sensing data. However,there are large differences on the calculations of the fraction of absorbed photosynthetically active radiation,environmental stress factors,and the model performance also need improve. Future studies should continue to improve model ability,develop multiple model ensemble algorithms and provide simulation uncertainties.
1. National Natural Science Foundation of China, Beijing 100085, China; 2. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China; 3. Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; 4. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;5. Peking University, Beijing 100871, China; 6. China Agricultural University, Beijing 100083, China; 7. Beijing Normal University, Beijing 100875, China; 8. Institute of Policy and Management, Chinese Academy of Sciences, Beijing 100190, China; 9. Lanzhou University, Lanzhou 730000, China;10. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 11. Chinese Academy of Forestry, Beijing 100091, China; 12. Tsinghua University, Beijing 100083, China;13. Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China;14. Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; 15. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
The National Natural Science Foundation of China has launched a major research program entitled “Integrated Study of Eco-hydrological Processes in the Heihe River Basin” (referred to as “Heihe River Program”). It is grounded on the principles of the earth system science, and intended to explore the theory and methods of improving the water use efficiency in the inland river basins of China affected by severe water shortage and ecological deterioration problems. Since the implementation of the Heihe River Program for the past four years, we have established a basin-wide eco-hydrological observation system integrating remote sensing, monitoring and experimentation; developed a comprehensive database and information system; revealed the important coupling mechanism of eco-hydrological processes including glaciers, forests and oases; gained basic understanding of the system characteristics of eco-hydrological units which serve as the basis for computing the basin water cycle and water balance; and quantified the ecological water demand in the lower reaches of the Heihe River as the important constraints for optimal water resources management in the Heihe River Basin. In the next few years, we will integrate comprehensive watershed models supported by high-resolution spatio-temporal data of air, water, biota and economics towards the goal of playing a world-leading role in river science.
Dependable information on large-area agricultural production and production estimation are essential for agricultural markets and the formulation of national and international agricultural policies. It can provide information and technical support for regional or global food security. Factors like worldwide climate change, increasing population and fast changes in land use/cover make the need more urgent. Traditional collection of crop information depends on huge in-situ investigation, which is expensive, time consuming and vulnerable to subjective difference. Along with the development in remote sensing technology and its application to crop information acquirement, some operational crop monitoring systems were developed and put into operation by several countries and international organizations. The development of major crop monitoring systems worldwide (United States, Europe, FAO, Canada, Brazil, Argentina, Russia and India) was reviewed and introduced in detail. The paper points out that the crop acreage estimation, crop yield prediction, crop condition monitoring and drought monitoring are the four primary themes in remote sensing based crop monitoring. In crop acreage monitoring, along with the development of remote sensing technology, the dependence of these systems on field survey has not been reduced, or even increased for some reasons. This is against the primary intention of remote sensing application: to reduce or substitute field survey. The potential of remote sensing in large-area crop monitoring has not been fully exerted. Independent crop yield predicting method with remote sensing is also in great need. How to increase the role of remote sensing will be the major direction for the development of remote sensing based crop monitoring systems.
分析了地图学、遥感、地理信息系统及全球定位系统的发展,为地球信息科学的建立奠定了基础。论述了地球信息科学的内涵、理论基础、技术体系以及地球信息图谱等基本概念,阐述了地球信息科学在资源清查与管理、经济与社会可持续发展规划决策与管理、城市规划与现代化管理、农业规划决策与生产管理、灾害预测与灾情评估、环境污染与生态变化监测、全球变化监测与研究等方面的应用前景。 Abstract: This paper analyses the development of Cartography, Remote Sensing, Geo-information System and GPS for establishing the foundation of Geo-information Science. Some basic concepts about the connotation, theoretical basis, technical system and Geo-information Graphic Analysis (Tupu) are discussed. Furthermore, the application prospects of Geo-information Science concerning resources investigation and management, planning decision-making and management of socioeconomic sustainable development, city planning and modernization management, agriculture planning decision-making and production management, disaster forecast and disaster evaluation, monitoring on environment pollution and ecological change, global change monitor and research etc. are expounded.
Quantitative assessment of carbon budgets at regional scale or in different ecosystems is an important scientific issue in the field of ecosystem and global change, which can provide scientific basis for forecasting climate change and regional carbon management serving for mitigation and adaptation to climate change. Though assessment and authentication of regional carbon budgets could not be fulfilled precisely using current measurements and evaluation methods, many progresses had been made. In this paper, we reviewed the observation technique systems, especially the methods and their uncertainties in evaluating regional carbon budget. To evaluate the carbon sink function of ecosystems, main industries, and projects related to carbon sink and their spatiotemporal patterns quantitatively, it is urgent to build an observation and experiment network based on field platforms and to develop a multi-scale observation system comprised by field platforms, terrestrial transects and ecological networks combined with satellites and aviation observations. The system based on observation data, ecological process model, remote sensing model and GIS spatial analysis is also needed to be built. These systems should be under the guideline of multi-scale observation, multi-method confirmation, multi-process fusion, across-scale cognition and simulation. Meanwhile, cycles of carbon, nitrogen and water in terrestrial ecosystems are coupled by various biological processes, while the knowledge of the coupling mechanisms and their influences on the spatiotemporal patterns of carbon source or sink was limited, so it will be an important aspect and new research hot in the research of ecosystem C cycle and regional carbon budget assessment and authentication.
The paper firstly retrospected the technology progress and developing course of geologic prospecting in our country by the way of illustrating the example of geologic prospecting, including oil, coal, nonferrous metals, uranium, non-metallic minerals and so on. Then it pointed out that the process of remote sensing geological prospecting was tortuous, but it put forward in the innovation and was innovating in the forword, and impelled the continuable developing of geologic prospecting and promoted the discovery of mineral resource in China. Secondly, the paper made a prospect of remote sensing geologic prospecting on the lay of national requirement,appliance field, technology developing and ideaistic updating. The paper particularly emphasized that the country's needs were the power for remote sensing prospecting, the data with high spatial resolution and hyper-spectral resolution brought hope for the direct exploration by the means of remote sensing. Three-dimensional mineral hyperspectral mapping proposed by "Spectral crust" plan has opened up a new avenue to explore the deep exploration by remote sensing technology. And academician Chen stressed that the application of remote sensing should come out from a idea of "technology index", and upgraded to the "scientific level" from the "technical level". At last, based on the comprehensive analysis of technological progress of remote sensing geological prospecting and development prospects, the paper illustrated that the opportunity and challenge contemporary exist at present, furthermore, the opportunity precedes challenge, we must seize the opportunity and rise to the challenge, reshape the new situation of remote sensing geologic prospecting.
Based on the introduction of remote sensing techniques and method as normal optical satellite remote sensing imagery, InSAR, LIDAR and etc, this paper reviews the newly application and development of remote sensing for landslide study. From each of the landslide risk assessment 5 phases: basic topographical data acquisition and extraction, landslide inventory and mapping, monitoring and landslide diagnostic factors mapping and element at risk mapping, this paper states the RS techniques offer a solid technique infrastructure, and exploits its potential development for landslide risk assessment. From the role of RS in landslide study, interpretability, causative condition that influence landslide identification, accuracy assessment and RS data source selection, the author states and discuss some questionable and arguable aspects,and as well presents that: ① the mainly use of remote sensing for landslide study is data and information acquisition and update; ② the interpretability of landslides from remote sensing images depends in the first place on the spatial resolution of the images in relation to the size of the features which are characterizing the slope movement and which can be recognized or identified. The following aspects are key features for recognizing landslides from remote sensing images: temporal resolution, the existing contrast between the slope movement and its background, the ability of stereo imagery acquisition and the interpretability is also influenced by the interpretation method,professional experience of the interpreter;③ the integration of remote sensing imagery,GIS spatial analysis and 3d visualization can enhance the landslide recognition and mapping efficiency and accuracy; ④ the accuracy assessment of landslide interpreted from remote sensing imagery should be objectively assessed from valid, misidentification, omission aspects according to the specific interpretability of the image; ⑤ as for remote sensing data selection for landslide risk assessment, which should follow sufficient is best for the specific application and take cost effective into account.
在对常用的光学遥感卫星影像、InSAR,LiDAR等遥感技术方法介绍的基础上,综述了这些方法在滑坡研究中的最新应用进展,从滑坡风险评估中的基础地形数据获取、滑坡编录与制图、监测、滑坡因素制图、承灾体制图等5个方面阐述遥感技术在滑坡风险中的支撑技术作用与应用前景。从遥感影像在滑坡风险评估中的作用、解译能力、影响解译的因素、精度评价和遥感数据源选择等角度阐述了常用遥感技术在滑坡风险评估应用中存在的问题,认为: ① 遥感技术在滑坡风险评估中的主要作用为数据、信息的获取与更新;② 滑坡的遥感影像解译能力取决于影像空间分辨率与待识别滑坡大小的相对关系,影像的时间分辨率、滑坡与其周边环境的对比度、立体影像的获取能力是利用遥感影像开展滑坡探测、识别与制图的关键要素;解译方法和解译员的专业素质是滑坡遥感解译的重要影响因素;③ 遥感影像与GIS空间分析、3D可视化的综合可有效增强滑坡识别与制图的效率和精度;④ 对于遥感解译滑坡的精度评价应针对具体影像的可解译性从有效解译,错误解译和遗漏解译三个方面予以客观评价;⑤ 滑坡风险评估应针对具体应用,从成本效益比的角度,本着“够用为止”原则合理选用遥感数据源。
This paper focuses on grain production loss caused by Wenchuan Earthquake. The damage of the cultivated area as well as the yield of winter wheat has been assessed. In order to estimate winter wheat acreage damaged by the earthquake, airborne CCD images and IRS P6 LISS4 MN data were used. Damaged arable land were extracted by photo interpretation, while winter wheat proportions were collected by ground survey using GVG instrument for plain area or interpreted from airborne images for mountain area. The winter wheat acreage damaged by the earthquake was calculated using winter wheat proportion multiple the area of damaged arable land and statistic at county scale. To estimate wheat yield, reliable agro-meteorological models were selected by taking into account the disperse distribution of winter wheat in mountain area. The results showed that only about 247.1hm2 of winter wheat were damaged in the twelve main producing counties and the production loss of winter wheat was estimated to 1013778kg. As conclusion, the earthquake did not significantly affect the food production of the whole country. Nevertheless, since all farmers were evacuated in mountain area after the disaster, the problems of harvest in that region producing 220000t of winter wheat need to be addressed.
The 8.0 M s Wenchuan Earthquake in 2008 significantly damaged the local ecosystem of Sichuan Province. In this study, high spatial resolution airborne remote sensing images, spaceborne remote sensing data, and field investigations were used to monitor and analyze agriculture and forestry recovery in Sichuan Province in the five years after the earthquake. The remote sensing images were acquired from the "Wenchuan 5th Anniversary" flight campaign organized by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. For the agricultural aspect, visual interpretation by using high-resolution airborne images acquired from 2008 to 2013 and expert experience were used to determine the status of damaged cultivated areas and to evaluate their recovery. Crop type proportions were collected through ground surveys by using a GVG (GPS, Video, and GIS) instrument over a sampled area, and then, interpolated for regions that were not surveyed. Results revealed that only 17.5% of the 1592 ha damaged arable land could be cultivated five years after the Wenchuan Earthquake. Nearly all usable arable land was cultivated and the cropping structure did not evidently fluctuate after the earthquake. The enthusiasm of local farmers toward their craft was not affected by the unprecedented disaster. This study recommends that the cropping structure must be kept essentially constant to ensure the supply of food in the disaster area. For the forestry aspect, the recovery of three key areas (which are distributed in the dry valley of the Minjiang River area and the montane around the Sichuan Basin area) was monitored via visual interpretation of airborne images. The damage and the recovery status of the entire disaster area were assessed by conducting a time-series change analysis of the normalized difference vegetation index with data from the Moderate-Resolution Imaging Spectroradiometer (MODIS). The results showed that the recovery status of forests in the key areas is relatively good, given that shrubs and young deciduous trees are germinating in most parts of the forests that were destroyed by landslides and mud-rock flows. However, some severely destroyed areas with large slopes and areas that were frequently struck by secondary disasters are still encountering difficulties. In summary, the 46400 ha seriously damaged and the 177000 ha moderately damaged forest areas have fully recovered by 13.52% and 25.84%, respectively, and both have partly recovered by approximately 50%. Some severely destroyed areas, which mainly include the forest areas around Chaping Mountain, require physical intervention to accelerate recovery. A change analysis can directly indicate the damage and recovery status of croplands and forests by using high-resolution airborne images. The airborne remote sensing sensor will continue to play an important role in monitoring ecosystems and in assessing important natural disasters. Meanwhile, a time series analysis can monitor damage and recovery of forests at a large scale by using MODIS data.
This study aims to evaluate the ecological restoration of Wenchuan County after the Wenchuan Earthquake in 2008, and to provide support for further ecological restoration and reconstruction. Simultaneously, this study also focuses on applying remote sensing and Geographic Information System (GIS) technologies to evaluate the ecological environment. Wenchuan County, which was the epicenter of the May 12, 2008 earthquake, was selected for this research, which involved multi-source remote sensing data and other supporting statistical data. An eco-environmental quality evaluation index system was established based on the pressure-state-response framework. The analytic hierarchy process method was used to calculate index weight. The eco-environmental qualities of Wenchuan County in 2007, 2008, and 2013 were evaluated by using the comprehensive index method. The results for the eco-environmental quality evaluation of Wenchuan County in 2007, 2008, and 2013 were obtained. Data gathered on the eco-environmental quality of Wenchuan in 2008 were compared with those obtained in 2007, i.e., before the earthquake. Data on the eco-environmental quality recovery gathered in 2013 were also compared with the data in 2007 (i.e., before the earthquake) and 2008 (i.e., after the earthquake). The result of the analysis showed that 79.4% of Wenchuan County exhibited good eco-environmental quality in 2007. However, the eco-environmental quality of the county was severely damaged by the 2008 earthquake. In particular, the areas near the epicenter suffered from serious destruction. Five years after the earthquake (2013), the eco-environmental quality of Wenchuan County has been successfully restored. In particular, 55.84% of the regional eco-environmental quality of the county has significantly improved compared with that in 2008. The eco-environmental quality of poor regions in the county has also exhibited an obvious improvement. However, the eco-environmental quality in some regions in the county has not fully recovered. Evaluating and analyzing the eco-environmental quality of Wenchuan County in 2007, 2008, and 2013 are feasible by using remote sensing and GIS technologies. Such approaches help determine the space distribution of the eco-environmental quality of Wenchuan Earthquake and evaluate its recovery. This study offers several useful recommendations on protecting and restoring the ecological environment that can be applied in the future.
There were extremely heavy flood disasters in the middle reaches of the Changjiang River and the Nenjiang-Songhuajiang regions in North-East China in summer 1998. In the continuous monitoring and assessment of the historical flood disasters the remote sensing techniques and Geographic Information System have played an important role. During the flood season 38 scenes of satellite radar images have been received, processed and analyzed and all the possible images from meteorological satellite have also been used. With the airborne imaging radars the remote sensing aircraft have been over 20 times taken off and flown over the flooding areas. By using the remote sensing and GIS the flood and the flooding areas have been monitored and assessed.With the satellite and airborne remote sensing the waterlogged areas caused by heavy raining later July 1998 in Wuhan region, the Hubei Province, the flooding areas in the Hunan, Hubei and Jiangxi Provinces of the middle reaches of the Changjiang River, including the Dongting and Poyang Lakes regions and in the Helongjiang, Jilin Provinces and the Inner-Mongolia Autonomous Region have been estimated from the imageries by the flood information extraction. The objective and relative accurate data have been obtained and provided to the agencies related to the disaster fighting and disaster. The practice of the flood monitoring by remote sensing and relevant information technologies has proved its important role. Meanwhile, in this paper some existed problems in the recent conditions hare also been analyzed. In order to increase the ability of the remote sensing some suggestions have been proposed. It is the special importance to strengthen the study on the flood prediction and warning.