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Wang J.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Wang J.,Jiangsu Center For Collaborative Innovation In Geographical Information Resource Dev And Applied | Zhou Y.,CAS Beijing Institute of Geographic Sciences and Nature Resources Research | Zhou Y.,Sichuan Province in second Geographic Information Engineering Institute of Surveying and Mapping | And 4 more authors.
Remote Sensing | Year: 2014

Cultivated land resources are an important basis of regional sustainability; thus, it is important to determine the distribution of the cultivated land in the Northeast Asia trans-boundary area of China, Russia and Mongolia, which has a continuous geographic and ecological environment and an uneven population distribution. Extracting information about the cultivated land and determining the spatial and temporal distribution of its features in this large trans-boundary area is a challenge. In this study, we derived information about the cultivated land of the North-South Transect in Northeast Asia by Linear Spectral Mixing Model, using time series data with MODerate resolution Imaging Spectroradiometer (MODIS) in 2000 and 2010. The validation showed more than 98% pixels with a root mean square error less than 0.05. The overall accuracy and spatial consistency coefficients were 81.63% and 0.78 in 2000 and 72.81% and 0.75 in 2010, respectively. The transect analyses indicate the presence of a greater amount of cultivated land in the south and less in the north. China owns most of the cultivated land in the transect area, followed by Mongolia and then Russia. A gradient analysis revealed a decrease of 34.16% of the cultivated land between 2000 and 2010. The amount of cultivated land decreased 22.37%, 58.93%, and 64.73% in China, Russia, and Mongolia, respectively. An analysis shows that the amount of cultivated land is primarily influenced by the various land development and protection policies in the different counties in this trans-boundary area. © 2014 by the authors. Source


Zhu A.X.,Nanjing Normal University | Zhu A.X.,Jiangsu Center For Collaborative Innovation In Geographical Information Resource Dev And Applied | Zhu A.X.,CAS Institute of Geographical Sciences and Natural Resources Research | Zhu A.X.,University of Wisconsin - Madison | And 7 more authors.
European Journal of Soil Science | Year: 2015

Existing predictive soil mapping (PSM) methods often require soil sample data to be sufficient to represent soil-environment relationships throughout the study area. However, in many parts of the world with only a limited quantity of soil sample data to represent the study area, this is still an issue for PSM application. This paper presents a method, named 'individual predictive soil mapping' (iPSM), which can make use of limited soil sample data for PSM. With the assumption that similar environmental conditions have similar soils, iPSM uses the soil-environment relationship at each individual soil sample location to predict soil properties at unvisited locations and estimate prediction uncertainty. Specifically, the environmental similarities of an unvisited location to a set of soil sample locations are used in a weighted average method to integrate the soil-environment relationships at sample locations for prediction and uncertainty estimation. As a case study, iPSM was applied to map soil organic matter (SOM) content (%) in the topsoil layer using two sets of soil samples. Compared with multiple linear regression (MLR), iPSM produced a more accurate SOM map (root mean squared error (RMSE) 1.43, mean absolute error (MAE) 1.16) than MLR (RMSE 8.54, MAE 7.34) the ability of the sample set to represent the study area is limited and achieved a comparable accuracy (RMSE 1.10, MAE 0.69) with MLR (RMSE 1.01, MAE 0.73) when the sample set could represent the study area better. In addition, the prediction uncertainty estimated by iPSM was positively related to prediction residuals in both scenarios. This study demonstrates that iPSM is an effective alternative when existing soil samples are limited in their ability to represent the study area and the prediction uncertainty in iPSM can be used as an indicator of its prediction accuracy. © 2015 British Society of Soil Science. Source


Shen D.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | Shen D.,Nanjing University | Shen D.,Changjiang River Scientific Research Institute | Rui Y.,Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology | And 7 more authors.
Computers and Geosciences | Year: 2015

Flood inundation extent, depth, and duration are important factors affecting flood hazard evaluation. At present, flood inundation analysis is based mainly on a seeded region-growing algorithm, which is an inefficient process because it requires excessive recursive computations and it is incapable of processing massive datasets. To address this problem, we propose a block compressed tracing algorithm for mapping the flood inundation extent, which reads the DEM data in blocks before transferring them to raster compression storage. This allows a smaller computer memory to process a larger amount of data, which solves the problem of the regular seeded region-growing algorithm. In addition, the use of a raster boundary tracing technique allows the algorithm to avoid the time-consuming computations required by the seeded region-growing. Finally, we conduct a comparative evaluation in the Chin-sha River basin, results show that the proposed method solves the problem of flood inundation extent mapping based on massive DEM datasets with higher computational efficiency than the original method, which makes it suitable for practical applications. © 2015 Elsevier Ltd. Source


Xiao J.,Nanjing Normal University | Xiao J.,CAS Nanjing Institute of Geography and Limnology | Xiao J.,Jiangsu Center For Collaborative Innovation In Geographical Information Resource Dev And Applied | Xiao X.,CAS Nanjing Institute of Geography and Limnology | And 3 more authors.
Review of Palaeobotany and Palynology | Year: 2015

A continuous 775-cm-long sediment core (Core B) was collected from the Dajiuhu Basin in the western Shennongjia Forest Region of Central China. The core between 775 and 144. cm in depth spanning the period from 83.4 to 9.6. ka (calibrated age, throughout this study) was studied for pollen analysis. The high-resolution pollen record revealed the histories of the vegetation succession and climate changes from 83.4 to 9.6. ka in the mountainous regions at an altitude of approximately 1,700. m. a.s.l. in Central China. The results show that five evident climate changes disclosed by the pollen record in Core B correspond to MIS (Marine Isotope Stage) 5a, MIS 4, MIS 3, the LGM (Last Glacial Maximum) of MIS 2, and the period from the deglacial of MIS 2 to the early Holocene, respectively. The temperature changes in the Dajiuhu Basin are consistent with the solar insolation in the Northern Hemisphere, the climate records in the Greenland and Guliya ice cores, the stalagmite, and the loess. However, the precipitation changes during the late Quaternary in the study area were roughly reversed with the temperature changes in the Northern Hemisphere. Therefore, the climatic patterns from 83.4 to 9.6. ka in the Dajiuhu Basin are cold and humid conditions and warm and dry conditions, which may be caused by the middle latitude position, the humid monsoon climate, and the steep mountainous geomorphology of the study area. © 2015 Elsevier B.V. Source


Zhang X.,Nanjing University of Information Science and Technology | Chen D.,Queens University | Zhong T.,Nanjing University | Cheng M.,Nanjing University of Information Science and Technology | And 2 more authors.
Clean - Soil, Air, Water | Year: 2015

Lead (Pb) contamination in arable soils is one of the most serious ecological problems due to its high toxicity on human health. Thus, we need to understand the concentration level, contaminated area, and spatial distribution of Pb in arable soils on regional or national scale. This paper reviewed the studies on Pb concentrations throughout Chinese arable soils, based on relevant 537 studies from 2002 to 2014. The results showed that the average Pb concentration was 34.41mg/kg, higher than its background of 23.50mg/kg, indicating that Pb has been introduced into soil from exterior sources. Mining and smelting activities, irrigation by wastewater, and urban development greatly contributed to Pb accumulation in arable soils. North China had lower Pb concentrations than the south, and many hotspots existed on the Pb concentration map due to mining and smelting activities. On the provincial scale, arable soils in Yunnan, Guangxi, and Shaanxi Provinces were moderately polluted by Pb, Gansu and Shaanxi Provinces were slightly affected by Pb, while the other provinces showed relative safe levels. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

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