High-Resolution Remote Sensing Imagery for the Recognition of Traditional Villages

Traditional Chinese villages,vital carriers of traditional culture,have faced significant alterations due to urbanization in recent years,urgently necessitating artificial intelligence data updates.This study integrates high spatial resolution remote sensing imagery with deep learning techniques,proposing a novel method for identifying rooftops of traditional Chinese village buildings using high-definition remote sensing images.Using 0.54 m spatial resolution imagery of traditional village areas as the data source,this method analyzes the geometric and spectral image characteristics of village building rooftops.It constructs a deep learning feature sample library tailored to the target types.Employing a semantically enhanced version of the improved Mask R-CNN(Mask Region-based Convolutional Neural Network)for building recognition,the study conducts experiments on localized imagery from different regions.The results demonstrated that the modified Mask R-CNN effectively identifies traditional village building rooftops,achieving an of 0.7520 and an of 0.7400.It improves the current problem of misidentification and missed detection caused by feature heterogeneity.This method offers a viable and effective approach for industrialized data monitoring of traditional villages,contributing to their sustainable development.

A spatial resolution effect analysis of remote sensing bathymetry

A spatial resolution effect of remote sensing bathymetry is an important scientific problem. The in situ measured water depth data and images of Dongdao Island are used to study the effect of water depth inversion from different spatial resolution remote sensing images. The research experiments are divided into five groups including Quick Bird and World View-2 remote sensing images with their original spatial resolution（2.4/2.0 m）and four kinds of reducing spatial resolution（4, 8, 16 and 32 m）, and the water depth control and checking points are set up to carry out remote sensing water depth inversion. The experiment results indicate that the accuracy of the water depth remote sensing inversion increases first as the spatial resolution decreases from 2.4/2.0 to 4, 8 and16 m. And then the accuracy decreases along with the decreasing spatial resolution. When the spatial resolution of the image is 16 m, the inversion error is minimum. In this case, when the spatial resolution of the remote sensing image is 16 m, the mean relative errors（MRE） of Quick Bird and World View-2 bathymetry are 21.2% and 13.1%,compared with the maximum error are decreased by 14.7% and 2.9% respectively; the mean absolute errors（MAE） are 2.0 and 1.4 m, compared with the maximum are decreased by 1.0 and 0.5 m respectively. The results provide an important reference for the selection of remote sensing data in the study and application of the remote sensing bathymetry.

Spatial Differences of Coastal Urban Expansion in China from 1970s to 2013

As the ′economic engines′ of China,coastal cities have developed and expanded considerably since the 1970 s.In this study,information on the urban expansion process of Chinese coastal cities from the 1970 s to 2013 was retrieved.Through the analysis of stage characteristics,spatial expansion modes,influences on land use,centroid shifts,and spatial morphological evolutions,the spatial differences of coastal urban expansion were revealed.Results indicate that 1) the expansion stages of southern coastal cities are more complex than those of northern coastal cities,and the expansion ranges and speeds of the former are far higher than those of the latter;2) the spatial expansion of southern coastal cities mostly adopt a single mode,whereas northern coastal cities mostly adopt a mixed mode;3) significant spatial differences in the occupations of different land sources exist between the south and the north along the coastline;4) the centroid of coastal cities tends to migrate toward the coastline,and the centroid shift distances of southern coastal cities are clearly higher than those of northern coastal cities;and 5) the spatial morphology of southern coastal cities tends to be compact,whereas that of northern coastal cities tends to be loose.Policies have a powerful significance in terms of guiding urban expansion and its spatial differences in coastal cities.Urban expansion in coastal cities will encounter new opportunities and challenges under the guidance of new types of urbanization strategies.

Monitoring of Karst Rocky Desertification Control Projects Based on Remote Sensing Images with Medium and High Spatial Resolution——A Case Study of Disi River Basin in Puan County

[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spatial resolution, KRD control projects in Disi River basin in Puan County were monitored, that is, information of the project construction in the study area was extracted using supervised classification and hu- man-computer interactive interpretation, and the monitoring results were testified with the aid of GPS. [Result] It was feasible to monitor KRD con- trol projects in Disi River basin based on remote sensing images with medium and high resolution, and the monitoring accuracy was satisfactory, reaching above 80% or 90%, so the method is worthy of popularizing. [ Conclusion] Remote sensing images with medium and high resolution can be used to monitor other KRD control Droiects.

Monitoring of Pinus massoniana spatial pattern changes based on RS and GIS techniques

Our research focused on Pinus massoniana information extracted from remote sensing images based on the knowledge detection and decision tree algorithm and established a spatial pattern model, combining quantitative theoretical ecology with remote sensing （RS） and geometric information system （GIS） techniques. Applying information extraction methods and a spatial pattern model, we studied P. massoniana spatial patterns changes before and after the invasion by pine wood nematode （Bursaphelenchus xylophilus） in Fuyang and Zhoushan counties, Zhejiang Province, east China. The P. massoniana spatial patterns are clustering, whether the invasion happened or not. But the degree of clustering is different. Our results show good agreement with field data. Applying the results, we analyzed the relationship between spatial patterns and the invasion level. Then we drew the elementary conclusion that there are two kinds of patterns for pine wood nematode to spread： continuous and discontinuous diffusion. This approach can help monitor and evaluate the changes in ecological systems.

A Written Corpus-Based Semantic Research on the Preposition ＂In＂ of Mongolian English Learners

"In" is one of the most important and difficult prepositions for Chinese Mongolian English learners. Based on the cognitive linguistics theory and corpus method, the thesis analyzes the semantic difference of preposition"in"between Mongolian English learners and native speakers. The results show that(1) Mongolian English learners underuse spatial sense while overuse temporal sense and metaphorical sense.(2) As for ten semantic groups, Mongolian English learners overuse eight semantic groups in which six groups have a significant relationship.

Connected Geomatics in the big data era

The development of global informatization and its integration with industrialization symbolizes that human society has entered into the big data era.This article covers seven new characteristics of Geomatics(i.e.ubiquitous sensor,multi-dimensional dynamics,integration via networking,full automation in real time,from sensing to recognition,crowdsourcing and volunteered geographic information,and serviceoriented science),and puts forward the corresponding critical technical challenges in the construction of integrated space-air-ground geospatial networks.Through the discussions outlined in this paper,we propose a new development stage of Geomatics entitled‘Connected Geomatics,’which is defined as a multi-disciplinary science and technology that uses systematic approaches and integrates methods of spatio-temporal data acquisition,information extraction,network management,knowledge discovery,and spatial sensing and recognition,as well as intelligent location-based services pertaining to any physical objects and human activities on the earth.It is envisioned that the advancement of Geomatics will make a great contribution to human sustainable development.