Xinyuan Wang

Automated Extraction of the Archaeological Tops of Qanat Shafts from VHR Imagery in Google Earth

Qanats in northern Xinjiang of China provide valuable information for agriculturists and anthropologists who seek fundamental understanding of the distribution of qanat water supply systems with regard to water resource utilization, the development of oasis agriculture, and eventually climate change. Only the tops of qanat shafts (TQSs), indicating the course of the qanats, can be observed from space, and their circular archaeological traces can also be seen in very high resolution imagery in Google Earth. The small size of the TQSs, vast search regions, and degraded features make manually extracting them from remote sensing images difficult and costly. This paper proposes an automated TQS extraction method that adopts mathematical morphological processing methods before an edge detecting module is used in the circular Hough transform approach. The accuracy assessment criteria for the proposed method include: (i) extraction percentage (E) = 95.9%, branch factor (B) = 0 and quality percentage (Q) = 95.9% in Site 1; and (ii) extraction percentage (E) = 83.4%, branch factor (B) = 0.058 and quality percentage (Q) = 79.5% in Site 2. Compared with the standard circular Hough transform, the quality percentages (Q) of our proposed method were improved to 95.9% and 79.5% from 86.3% and 65.8% in test sites 1 and 2, respectively. The results demonstrate that wide-area discovery and mapping can be performed much more effectively based on our proposed method.

Large-Area Landslides Monitoring Using Advanced Multi-Temporal InSAR Technique over the Giant Panda Habitat, Sichuan, China

The region near Dujiangyan City and Wenchuan County, Sichuan China, including significant giant panda habitats, was severely impacted by the Wenchuan earthquake. Large-area landslides occurred and seriously threatened the lives of people and giant pandas. In this paper, we report the development of an enhanced multi-temporal interferometric synthetic aperture radar (MTInSAR) methodology to monitor potential post-seismic landslides by analyzing coherent scatterers (CS) and distributed scatterers (DS) points extracted from multi-temporal l-band ALOS/PALSAR data in an integrated manner. Through the integration of phase optimization and mitigation of the orbit and topography-related phase errors, surface deformations in the study area were derived: the rates in the line of sight (LOS) direction ranged from −7 to 1.5 cm/a. Dozens of potential landslides, distributed mainly along the Minjiang River, Longmenshan Fault, and in other the high-altitude areas were detected. These findings matched the distribution of previous landslides. InSAR-derived results demonstrated that some previous landslides were still active; many unstable slopes have developed, and there are significant probabilities of future massive failures. The impact of landslides on the giant panda habitat, however ranged from low to moderate, would continue to be a concern for conservationists for some time in the future.

VHR GeoEye-1 imagery reveals an ancient water landscape at the Longcheng site, northern Chaohu Lake Basin (China)

ABSTRACT This study mainly focuses on revealing an ancient water landscape at the Longcheng site in the northern Chaohu Lake Basin using very high-resolution (VHR) GeoEye-1 imagery. First, prior to classification, the GeoEye-1 image was processed following atmospheric and geometric correction. The supervised classification was carried out in order to show the land-cover situation in the Longcheng area. The overall classification accuracy was 89.98%, with a kappa coefficient of 0.87. The moat system around the city walls was discovered by using rule-based object-oriented segmentation of the postclassified image, and the other walls of ancient Longcheng were manually identified from the pansharpened VHR GeoEye-1 image. Finally, a map of the ancient water landscape containing the ancient city, wall and moat at the Longcheng site was produced. This paper demonstrates that VHR remote sensing has the ability to uncover an ancient water landscape and provide new insights for archaeological and paleoenvironmental studies.

Global detection of large lunar craters based on the CE-1 digital elevation model

Craters, one of the most significant features of the lunar surface, have been widely researched because they offer us the relative age of the surface unit as well as crucial geological information. Research on crater detection algorithms (CDAs) of the Moon and other planetary bodies has concentrated on detecting them from imagery data, but the computational cost of detecting large craters using images makes these CDAs impractical. This paper presents a new approach to crater detection that utilizes a digital elevation model instead of images; this enables fully automatic global detection of large craters. Craters were delineated by terrain attributes, and then thresholding maps of terrain attributes were used to transform topographic data into a binary image, finally craters were detected by using the Hough Transform from the binary image. By using the proposed algorithm, we produced a catalog of all craters ⩾10 km in diameter on the lunar surface and analyzed their distribution and population characteristics.

Auto-Extraction of Linear Archaeological Traces of Tuntian Irrigation Canals in Miran Site (China) from Gaofen-1 Satellite Imagery

This paper describes the use of the Chinese Gaofen-1 (GF-1) satellite imagery to automatically extract tertiary Linear Archaeological Traces of Tuntian Irrigation Canals (LATTICs) located in the Miran site. The site is adjacent to the ancient Loulan Kingdom at the eastern margin of the Taklimakan Desert in western China. GF-1 data were processed following atmospheric and geometric correction, and spectral analyses were carried out for multispectral data. The low values produced by spectral separability index (SSI) indicate that it is difficult to distinguish buried tertiary LATTICs from similar backgrounds using spectral signatures. Thus, based on the textual characteristics of high-resolution GF-1 panchromatic data, this paper proposes an automatic approach that combines joint morphological bottom and hat transformation with a Canny edge operator. The operator was improved by adding stages of geometric filtering and gradient vector direction analysis. Finally, the detected edges of tertiary LATTICs were extracted using the GIS-based draw tool and converted into shapefiles for archaeological mapping within a GIS environment. The proposed automatic approach was verified with an average accuracy of 95.76% for 754 tertiary LATTICs in the entire Miran site and compared with previous manual interpretation results. The results indicate that GF-1 VHR PAN imagery can successfully uncover the ancient tuntian agricultural landscape. Moreover, the proposed method can be generalized and applied to extract linear archaeological traces such as soil and crop marks in other geographic locations.

Improving accuracy of Eutrophication State Index estimation in Chaohu Lake by moderate resolution remote sensing data driven method

Trophic Level Index (TLI) calculated from several water quality monitoring indicators is often used to assess the general eutrophication state of inland-lake. In this paper, we proposed a data driven inland-lake eutrophication mapping method by using artificial neural network (ANN) to build relationship from remote sensing data and in-situ TLI sampling. Low spatial resolution remote sensing data (MODIS, 250-m and 500-m) and moderate spatial resolution remote sensing data (OLI, 30-m) together with in-situ observations are acquired to train the net. Result demonstrates that TLI obtained from medium-resolution remote sensing images is more accurate than which from low resolution remote sensing data, and more accurate than TLI calculated from the water quality factors retrieved from remote sensing images. This method provides an efficient way of mapping the TLI spatial distribution in-inland lake.

An Integrated 3S and Historical Materials Analysis of the Keriya Paleoriver, NW China

Combining analysis of 3S (RS, GIS and GPS) and historical materials (historical records, ancient map and academic and literary writings) allows mapping of the Keriya Paleoriver of Southern Xinjiang, NW China. Keriya Paleoriver, one of the ancient Four Green Corridors which passes through the Taklimakan Desert from south to north in the Tarim Basin, recorded changes of the climate-environment in the ancient Silk Road of the region. According to the archaeological data, historical materials and paleoclimates information, its eco-environment and climate have had great changes since the 1.09Ma B.P., especially during the last 2,000 years, which has led to many famous ancient cities to be abandoned and the route of the ancient Silk Road to be moved southward. Using RS (optical and radar imagery), GIS (mapping and spatial analysis) and GPS (study area investigation), we mapped a major paleodrainage system of Keriya River, which have linked the Kunlun Mountains to the Tienshan Mountains through the Taklimakan Desert, possibly as far back as the early Pleistocene. This study illustrates the capability of the 3S and historical materials, in mapping the Keriya Paleoriver drainage networks and archaeological study on the ancient Silk Road.

Research on the lakes change in Ejin alluvial fan from long time-series landsat images

Inland lakes in the arid and semi-arid areas are sensitive to the climate change and human activities, The long time-series remote sensing data, with a capability to provide valuable information of the distribution and changes of inland water bodies, have become an effective tool for lake study. In this paper, the lakes in Ejin alluvial fan, located in a typical arid region in the west of Inner Mongolia, China, are chosen as study lakes. Twenty years period TM data are used to obtain the long time-series and continental information of the lake change from 1987 to 2008. Climate data and hydrological data are also collected for correlational study. The results show that 1) in latest 20 years, the total area of the studied lakes in Ejin alluvial fan reduced firstly then increased after 2000. 2) The area changes of the four lakes are different. 3) Both the environmental change and the man-kind factors are the drivers of the lake change in Ejin alluvial fan. The latter might exert a main influence.

Mapping of wind energy potential over the Gobi Desert in Northwest China based on multiple sources of data

In recent years, wind energy has been a fastgrowing alternative source of electrical power due to its sustainability. In this paper, the wind energy potential over the Gobi Desert in Northwest China is assessed at the patch scale using geographic information systems (GIS). Data on land cover, topography, and administrative boundaries and 11 years (2000‒2010) of wind speed measurements were collected and used to map and estimate the region’s wind energy potential. Based on the results, it was found that continuous regions of geographical potential (GeoP) are located in the middle of the research area (RA), with scattered areas of similar GeoP found in other regions. The results also show that the technical potential (TecP) levels are about 1.72‒2.67 times (2.20 times on average) higher than the actual levels. It was found that the GeoP patches can be divided into four classes: unsuitable regions, suitable regions, more suitable regions, and the most suitable regions. The GeoP estimation shows that 0.41 billion kW of wind energy are potentially available in the RA. The suitable regions account for 25.49%, the more suitable regions 24.45%, and the most suitable regions for more than half of the RA. It is also shown that Xinjiang and Gansu are more suitable for wind power development than Ningxia.

SAR China Land Mapping Project: Development, Production and Potential Applications

Large-area, seamless synthetic aperture radar (SAR) mosaics can reflect overall environmental conditions and highlight general trends in observed areas from a macroscopic standpoint, and effectively support research at the global scale, which is in high demand now across scientific fields. The SAR China Land Mapping Project (SCLM), supported by the Digital Earth Science Platform Project initiated and managed by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE), is introduced in this paper. This project produced a large-area SAR mosaic dataset and generated the first complete seamless SAR map covering the entire land area of China using EnviSat-ASAR images. The value of the mosaic map is demonstrated by some potential applications in studies of urban distribution, rivers and lakes, geologic structures, geomorphology and paleoenvironmental change.