Application of Remote Sensing and Geographic Information System in Land Use and Land Cover Change

The integration and application of remote sensing （RS） and geographic in-formation system （GIS） in the study of the Land Use and Land Cover Change （LUCC） were summarized, as wel as researches on the monitoring dynamic changes in LUCC, driving force and application examples of the integration and the application of RS and GIS in simulation research. The methods and technical ap-proaches of RS and GIS in LUCC research were discussed. Views on the existing problems of the integration and the application of RS and GIS were put forward, and the future developing direction of LUCC technology was forecasted.

Remote sensing and geographic information systems techniques in studies on treeline ecotone dynamics

We performed a meta-analysis on over 100 studies applying remote sensing(RS)and geographic information systems(GIS)to understand treeline dynamics.A literature search was performed in multiple online databases,including Web of Knowledge(Thomson Reuters),Scopus(Elsevier),BASE(Bielefeld Academic Search Engine),CAB Direct,and Google Scholar using treeline-related queries.We found that RS and GIS use has steadily increased in treeline studies since 2000.Spatialresolution RS and satellite imaging techniques varied from low-resolution MODIS,moderate-resolution Landsat,to high-resolution WorldView and aerial orthophotos.Most papers published in the 1990s used low to moderate resolution sensors such as Landsat Multispectral Scanner and Thematic Mapper,or SPOT PAN(Panchromatic)and MX(Multispectral)RS images.Subsequently,we observed a rise in high-resolution satellite sensors such as ALOS,GeoEye,IKONOS,and WorldView for mapping current and potential treelines.Furthermore,we noticed a shift in emphasis of treeline studies over time:earlier reports focused on mapping treeline positions,whereas RS and GIS are now used to determine the factors that control treeline variation.

Mapping potential areas for groundwater storage in the High Guir Basin(Morocco):Contribution of remote sensing and geographic information system

Identification of water potential areas in arid regions is a crucial element for the enhancement of their water resources and socio-economic development. In fact, water resources system-planning can be used to make various decisions and implement manage- ment of water resources policies. The purpose of this study is to identify groundwater sto- rage areas in the high Guir Basin by implementing Geographic Information System (GIS) and Remote Sensing methods. The required data for this study can be summarized into five critical factors: Topography (slope), lithology, rainfall, rock fracture and drainage. These critical factors have been converted by the GIS into thematic maps. For each cri- tical parameter, a coefficient with weight was attributed according to its importance. The map of potential groundwater storage areas is obtained by adding the products (coeffi- cient × weight) of the five parameters. The results show that 50% to 64% of the total area of the High Guir Basin is potentially rich in groundwater, where most of fracture systems are intensely developed. The obtained results are validated with specific yield of the aqui- fer in the study area. It is noted that there is a strong positive correlation between excel- lent groundwater potential zones with high flows of water points and it diminishes with low specific yield with poor potential zones.

Remote Sensing Investigation Method on Land Resources by A Geographic Information System

The human living and developing depend on the land. The remote sensing images in Keerqinhouqi, Inner Mongolia Autonomous Region, China, were processed . Supported by a geographical information system, the image map was formed by th e boundary making and overlaying to the precision-corrected remote sensed image . Finally, the current land use types were also classified and outlined. The area s were also calculated. The error is less than 10 precent, compared with the sur vey. Thus the proceduce is considered accepfable.

Corrigendum to "Role of remote sensing,geographic bioinformatics system and bioinformatics in kala-azar epidemiology" [originally published as J Biomed Res 2011,25(6):373-384;doi:10.1016/S1674-8301(11)60050-X]

The author would like to inform the readers that the correct form of title ＂Role of remote sensing, geographic bioinformatics system and bioinformatics in kala-azar epidemiology＂ , content in ab-stract ＂The computational approaches like remote sensing, geographic information system （GIS） and bioinformatics are the key re-sources for the detection and distribution of vectors, patterns, ecologi- cal and environmental factors and genomic and proteomic analysis.＂, and keyword ＂geographical bioinformatics systems （GIS）＂ should be read as follows： title ＂Role of remote sensing, geographical bioinformation system and bioinformatics in kala-azar epidemiology＂, content in abstract ＂The com-putational approaches like remote sensing, geographical information system （GIS） and bioinformat-ics are the key re-sources for the detection and distribution of vectors, patterns, ecological and envi-ronmental factors and genomic and proteomic analysis.＂, and keyword ＂geographical bioinformation system （GIS） ＂.

Quantifying River Bank Erosion and Accretion Patterns along the Gorai River in Kushtia, Bangladesh: A Geospatial Analysis Utilizing GIS and Remote Sensing Techniques

River bank erosion is a natural process that occurs when the water flow of a river exceeds the bank’s ability to withstand it. It is a common phenomenon that causes extensive land damage, displacement of people, loss of crops, and infrastructure damage. The Gorai River, situated on the right bank of the Ganges, is a significant branch of the river that flows into the Bay of Bengal via the Mathumati and Baleswar rivers. The erosion of the banks of the Gorai River in Kushtia district is not a recent occurrence. Local residents have been dealing with this issue for the past hundred years, and according to the elderly members of the community, the erosion has become more severe activities. Therefore, the main objective of this research is to quantify river bank erosion and accretion and bankline shifting from 2003 to 2022 using multi-temporal Landsat images data with GIS and remote sensing technique. Bank-line migration occurs as a result of the interplay and interconnectedness of various factors such as the degree of river-related processes such as erosion, transportation, and deposition, the amount of water in the river during the high season, the geological and soil makeup, and human intervention in the river. The results show that the highest eroded area was 4.6 square kilometers during the period of 2016 to 2019, while the highest accreted area was 7.12 square kilometers during the period of 2013 to 2016. However, the erosion and accretion values fluctuated from year to year.

Basic theory and key technologies for marine geographic information system

Marine geographic information system （MGIS） has great ability to deal with the spatio-temporal problems and has potential superiority when it is applied to oceanography. Using the feature extraction of oceanic phenomena as a case study, the functions of the MGIS are analyzed, and thus the position of MGIS in the oceanography is defined. Comparing the requirement of MGIS with that of the traditional GIS which has been developed in the terrestrial applications in the past four decades, the frame for the functions of MGIS is constructed. According to the established MGIS, some key technologies are discussed in detail with emphasis on the specialities which can distinguish the MGIS from the traditional GIS.

The Development of a Geographic Information System(GIS) Database for Jiuzhaigou National Nature Reserve and Its Application

The objective of this paper is to develop a GIS(Geographic Information System) database for Jiuzhaigou National Nature Reserve(Jiuzhaigou,hereafter) in China and demonstrate its application as a research tool.A cost-effective procedure was developed to compile a variety of geographical and biological data of the study area in terms of popular GIS format such as shape files.These files were further calibrated and validated using field surveys data.The developed GIS database was used to quantify the distributions of the wildlife(amphibians,mammals,and birds) using the distances of the wildlife to the centerline of the bus-tour routes.The Pearson correlation coefficient was used to quantify the correlation in space between pairs of different wildlife using the number of habitats for given space contexts.An ArcObject-based macro was developed to perform the analysis.The results showed the majority of the habitats of wildlife are located in the proximity of the tour-bus routes with an average distance ranging from 564 to 894 m depending on types of wildlife.This indicates a possibility of the disturbance to the wildlife by human activities.The correlation coefficient of the wildlife ranged from 0.36 to 0.64 depending on pairs of wildlife,indicating some correlations in space.However,due to the limited sample size,the statistical significances need to be further investigated.This paper has successfully demonstrated the use of the GIS-based database as a research tool for environmental study.

Quantizing and analyzing the feature information of coastal zone based on high-resolution remote sensing image

On the basis of realization of beach information and its differentiating of high-resolution remote sensing image on coastal zone, extracting objects are carried through RS multi-scale diagnostic analysis, and fast information extraction methods and key technologies are put forward. Meanwhile image segmentation methods are set forth for objects of coastal zone. And through the application of Otsu2D to the segmentation of water area and dock and the applying of Gabor filter to the separation and extraction of construction, some typical applications of high-resolution RS image are presented in the field of coastal zone surface objects＇ recognition. Quantizing high-resolution RS information on the coastal zone proved to be of great scientific and practical significance for coastal development and management.

The research on the remote sensing＇s information tree model of the Nansha coral islets and reef＇s spatial structure

Based on the Nansha coral islets and reef's time-space attributes,and the intension and extension of the remote sensing information, the concept model and concept system of coral islets and reef are proposed.Then twin-tree remote sensing information model for different kinds of reef is constructed by using abstracted islets and reef's primitive, and the structure recognition system for coral islets and reef type is developed.

Separate Analysis of Remote Sensing Information of Structures of Different Geological Periods and Quantitative Study of Corresponding Tectonic Stress Fields

The structural feature shown on a remote sensing image is a synthetic result ofcombination of the deformations produced during the entire geological history of an area.Therefore, the respective tectonic stress field of each of the different stages in the complexdeformation of an area can be reconstructed in three steps: (1) geological structures formed atdifferent times are distinguished in remote sensing image interpretation; (2) structuraldeformation fields at different stages are determined by analyzing relationships betweenmicrostructures (joints and fractures) and the related structures (folds and faults); and (3)tectonic stress fields at different stages are respectively recovered through a study of the featuresof structural deformation fields in different periods. Circular structures and related circlular and radial joints are correlated in space to con-cealed structural rises. The authors propose a new method for establishing a natural model ofthe concealed structural rises and calculating the tectonic stress field by using quantitative dataof the remote sensing information of circular structures and related linear structures.

Spectrum spatial structure characteristic analysis of remote sensing alteration information and interference factors

Based on the statistical characteristics of remote sensing data, the spatial geometric structure characteristics of spectral data and distribution of background, interference and alteration information in characteristic space were researched through the analysis of two-dimensional and three-dimensional scatter diagrams. The results indicate that the hyper-space of remote sensing multi-data aggregation belongs to low-dimensional geometric structure, i.e. hyperplane form, and anomalous point groups including alteration information usually dissociate out of hyperplane. Scatter diagrams of remote sensing data band are mainly presented as two distribution forms of single-ellipse and dual-ellipse. Clarifying the relations of three objects of background, disturbance and alteration information in remote sensing images provides an important technical thought and guidance for accurately detecting and extracting remote sensing alteration information.

The remote sensing composite information entropy and types of Nansha coral reef atolls

In the viempint that the coral reef atolls' growth index of the Nansha Islands is influenced by many factors, the measured remote sensing comopite information including some mutually related factors is divided into 10 geographic events as N1, N2 ..., N10, and the analysis of the atolls' information entropy is made. From the value of theentropy, the closed related factors with the index of the emerged atolls are shown. In proper order, the factors are reeftop's area(0. 319), lagoon's area(0. 324), open-degree of atoll(0. 336), trend of atoll(0. 551 ). On the basis of thiswork, a new description function of the emerged atoll growth index is proposed. This function can be used to identifythe open my of Nansha atoll growth.

THE CLIMATIC STUDY OF CHANGBAI MOUNTAIN BY INTEGRATION OF REMOTE SENSING INFORMATION AND GEO-CODED IMAGES

Ⅰ. INTRODUCTION Changbai Mountain is situated between E127°54′-128°08′, N40°58′-42°06′ about 2700 meters above sea level. It is the typical area of the mountainous climate in the monsoon area of the temperate zone on the globe. The well reserved primeval vertical distribution of natural landscape belts and the Natural Conservation of Changbai Mountains adopted by the UNESCO′s MAB Program cause the worldwide attention of geographers. Beside the complexity of the climatic structure itself, the mechanical effection of the high mountain body also effect the climate in the eastern part of China. In the mountain area where short of meteorological observation data, the climatic study by remote sensing is favorable for discovery and representation of climatic law in large area.

Delineation of groundwater potential zones in Theni district,Tamil Nadu,using remote sensing,GIS and MIF techniques

Integration of remote sensing data and the geographical information system （GIS） for the exploration of groundwater resources has become a breakthrough in the field of groundwater research, which assists in assessing, monitoring, and conserving groundwater resources. In the present paper, various groundwater potential zones for the assessment of groundwater availability in Theni district have been delineated using remote sensing and GIS techniques. Survey of India toposheets and IRS-IC satel- lite imageries are used to prepare various thematic layers viz. lithology, slope, land-use, lineament, drainage, soil, and rainfall were transformed to raster data using feature to raster converter tool in ArcGIS. The raster maps of these factors are allocated a fixed score and weight computed from multi influencing factor （MIF） technique. Moreover, each weighted thematic layer is statistically computed to get the groundwater potential zones. The groundwater potential zones thus obtained were divided into four categories, viz., very poor, poor, good, and very good zones. The result depicts the groundwater potential zones in the study area and found to be helpful in better planning and management of ground- water resonrces.

Agricultural remote sensing big data:Management and applications

Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures. Agricultural remote sensing is one of the backbone technologies for precision agriculture, which considers within-field variability for site-specific management instead of uniform management as in traditional agriculture. The key of agricultural remote sensing is, with global positioning data and geographic information, to produce spatially-varied data for subsequent precision agricultural operations. Agricultural remote sensing data, as general remote sensing data, have all characteristics of big data. The acquisition, processing, storage, analysis and visualization of agricultural remote sensing big data are critical to the success of precision agriculture. This paper overviews available remote sensing data resources, recent development of technologies for remote sensing big data management, and remote sensing data processing and management for precision agriculture. A five-layer-fifteen- level （FLFL） satellite remote sensing data management structure is described and adapted to create a more appropriate four-layer-twelve-level （FLTL） remote sensing data management structure for management and applications of agricultural remote sensing big data for precision agriculture where the sensors are typically on high-resolution satellites, manned aircrafts, unmanned aerial vehicles and ground-based structures. The FLTL structure is the management and application framework of agricultural remote sensing big data for precision agriculture and local farm studies, which outlooks the future coordination of remote sensing big data management and applications at local regional and farm scale.

Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS

Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.

Study on Soil Salinization Information in Arid Region Using Remote Sensing Technique

Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus （ETM＋） image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data. Principal component analysis （PCA） is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help the classification precision of a decision tree to be improved. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. According to the research, the third principal component （PC3） is an effective variable in the decision tree classification for salinized soil information extraction. The research demonstrated that the PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM＋ sensor （TM1） was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk （Tamarix chinensis Lour）; and areas comprising mixed water bodies and vegetation can be identified using the spectral indices MNDWI （modified normalized difference water index） and NDVI （normalized difference vegetation index）. Based upon this analysis, a decision tree classifier was applied to classify landcover types with different levels of soil saline. The results were checked using a statistical accuracy assessment. The overall accuracy of the classification was 94.80%, which suggested that the decision tree model is a simple and effective method with relatively high precision.

Remote Sensing of Ecosystem Services:An Opportunity for Spatially Explicit Assessment

Ecosystem service is an emerging concept that grows to be a hot research area in ecology.Spatially explicit ecosystem service values are important for ecosystem service management.However,it is difficult to quantify ecosystem services.Remote sensing provides images covering Earth surface,which by nature are spatially explicit.Thus,remote sensing can be useful for quantitative assessment of ecosystem services.This paper reviews spatially explicit ecosystem service studies conducted in ecology and remote sensing in order to find out how remote sensing can be used for ecosystem service assessment.Several important areas considered include land cover,biodiversity,and carbon,water and soil related ecosystem services.We found that remote sensing can be used for ecosystem service assessment in three different ways:direct monitoring,indirect monitoring,and combined use with ecosystem models.Some plant and water related ecosystem services can be directly monitored by remote sensing.Most commonly,remote sensing can provide surrogate information on plant and soil characteristics in an ecosystem.For ecosystem process related ecosystem services,remote sensing can help measure spatially explicit parameters.We conclude that acquiring good in-situ measurements and selecting appropriate remote sensor data in terms of resolution are critical for accurate assessment of ecosystem services.

Spatial distribution characteristics of urban thermal conditions: application of GIS and remote sensing

The urban thermal distribution characteristics and its variation are dynamically monitored and synthetically analyzed by using GIS technology. The meteorological satellite data serve as main information source, assisted as auxiliary information sources by the landsat satellite TM data, land use thematic maps and meteorological observed data. A correlated pattern on the ground surface brightness temperatures and air temperatures has been studied and established with good performance of application.