The objective of this study is to develop a novel methodology integrating remote sensing, geographic information system technology and local spatial autocorrelation geo-computation for quick drought assessment. One group of drought indices, based on the condition of the vegetation, includes the Normalized Difference Vegetation Index (NDVI), Anomaly of Normalized Difference Vegetation Index (NDVIA) and Standardized Vegetation Index (SVI). The other group, based on the moisture conditions, includes the Normalized Difference Moisture Index (NDMI) and Standardized Moisture Index (SMI). The local G-statistic (Gi*) provides insight into the spatial relationships of the drought indices for drought risk assessment. Specifically, locations with significant Gi* values indicate spatial clusters where there are differences between the vegetative and hydrological drought indices. The results of spatial co-occurrence analysis indicate the existence of hot spots where the drought indices are spatially stable. This spatial information can be used to identify high drought risk areas as a first step towards helping local administrators improve the allocation of local water resources in arid environments. Finally, the novel methodology, integrating remote sensing, geocomputation and geographic information techniques, is demonstrated. The results indicate its effectiveness for quick drought assessment.

Background: To investigate the prevalence and characteristics of osteoarthritis (OA) in Mongolian middle-aged and senior residents of the Inner Mongolia autonomous region compared with the prevalence of OA in different regions, to understand the OA-associated factors and provide theoretical evidences for intervention and prevention.Objectives: Thereby the prevalence, distribution characteristics and correlative factors of OA in Mongolian middle-aged and senior residents in the Inner Mongolia autonomous region were investigated in this study.Materials and Methods: Rural and urban residents in Hohhot, Baotou and Erdos were selected using stratified, multi-stage and cluster random sampling. 2000 residents aging over 45 filled out questionnaires underwent specialized physical and X-ray examinations. The factors affecting OA were analyzed by the multivariate unconditional logistic regression.Results: Obtained total of 1877 questionnaires were completed. 93% of the residents were unaware of OA-related issues. The prevalence of radiological OA and clinical OA (neck OA: 36.72%; waist OA: 44.02%; knee OA: 12.43%; hand OA: 6.83%) were 62.17% and 56.15%, respectively. Urban residents were more subjected to cervical spine (χ2=8.92, P=0.005) and less to lumbar spine disease (χ2=10.32, P=0.004) compared to rural ones. The prevalence of OA in knees and hands of females (χ2=8.65, P=0.003) was significantly higher than males (χ2=4.37, P=0.042). The prevalence of OA in postmenopausal females was slightly higher than males (χ2=3.86, P=0.052), with no statically significant difference. The risks of OA obviously increased with age. The residents with hypertension, diabetes and atherosclerosis were more subjected to OA.Conclusions: The prevalence of OA in Mongolian middle-aged and senior residents in part of the Inner Mongolia autonomous region was similar to the other ethnic groups. The prevalence of OA was affected by age, gender, location, hypertension, diabetes, atherosclerosis and osteoporosis. The residents need further educations about OA prevention and treatment.