Cultivated Land Information Extraction and Gradient Analysis for a North-South Transect in Northeast Asia between 2000 and 2010

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

Accuracy Assessment of Multi-Source Gridded Population Distribution Datasets in China

Population is one of the core elements of sustainable development. Quantifying the estimation accuracy of population spatial distribution has been recognized as a critical and challenging task. This study aims to evaluate the data accuracy of four population datasets in China, including three global gridded population datasets, the Gridded Population of the World (GPW), Global Rural and Urban Mapping Project (GRUMP), and WorldPop project (WorldPop), and a Chinese regional gridded population dataset, the China 1 km Gridded Population (CnPop) dataset. These datasets are assessed using a specific method based on a GIS-linked 2000 census dataset at the township level in China. The results indicate that WorldPop had the highest estimation accuracy, estimating about 60% of the total population. CnPop accurately estimated about half of the total population, showing a good mapping performance. The GPW had an acceptable estimation accuracy in a few plain and basin areas, accounting for about 30% of the total population. Compared to the GPW, GRUMP accurately estimated about 40% of the total population. The relative estimation error analysis discovered the disadvantages of the generation strategies of these datasets. The conclusions are expected to serve as a quality reference for potential dataset users and producers, and promote accuracy assessment for population datasets in other regions and globally

Geographical Environment Factors and Risk Assessment of Tick-Borne Encephalitis in Hulunbuir, Northeastern China

Tick-borne encephalitis (TBE) is one of natural foci diseases transmitted by ticks. Its distribution and transmission are closely related to geographic and environmental factors. Identification of environmental determinates of TBE is of great importance to understanding the general distribution of existing and potential TBE natural foci. Hulunbuir, one of the most severe endemic areas of the disease, is selected as the study area. Statistical analysis, global and local spatial autocorrelation analysis, and regression methods were applied to detect the spatiotemporal characteristics, compare the impact degree of associated factors, and model the risk distribution using the heterogeneity. The statistical analysis of gridded geographic and environmental factors and TBE incidence show that the TBE patients mainly occurred during spring and summer and that there is a significant positive spatial autocorrelation between the distribution of TBE cases and environmental characteristics. The impact degree of these factors on TBE risks has the following descending order: temperature, relative humidity, vegetation coverage, precipitation and topography. A high-risk area with a triangle shape was determined in the central part of Hulunbuir; the low-risk area is located in the two belts next to the outside edge of the central triangle. The TBE risk distribution revealed that the impact of the geographic factors changed depending on the heterogeneity