Applications of Spatial Interpolation for Climate Variables Based on Geostatistics: A Case Study in Gansu Province, China

Annals of GIS ◽  
2003 ◽  
Vol 9 (1-2) ◽  
pp. 71-77
Author(s):  
Wenze Yue ◽  
Jianhua Xu ◽  
Hongjuan Liao ◽  
Lihua Xu
Keyword(s):  
Spatial Interpolation ◽  
Gansu Province ◽  
Climate Variables

Happiness in the tropics: climate variables and subjective wellbeing

2021 ◽  
pp. 1-22
Author(s):  
Oscar Zapata
Keyword(s):  
Subjective Wellbeing ◽  
Developed Countries ◽  
Social Characteristics ◽  
Effect Of Temperature ◽  
Climate Variables ◽  
Climate Conditions ◽  
Health And Wellbeing ◽  
The Tropics ◽  
The Relationship

Abstract Changes in climatic patterns are expected to have significant effects on health and wellbeing. However, the literature on the effect of climate on subjective wellbeing remains scant and existing studies focus mostly on developed countries or cross-country analyses. This paper aims to identify the relationship between climate conditions on happiness after controlling for individual and social characteristics. Ecuador, a geographically fragmented country with varying climate conditions across municipalities, constitutes an ideal case study to assess the effect of climate variables on happiness. We employ a cross-section analysis to identify the effect of temperature, precipitation and humidity on happiness. The paper shows that climate conditions constitute an important determinant of people's subjective wellbeing. The results also suggest that income and education attenuate the effect of temperature on happiness and that substantial differences are observed depending on whether places are hot/humid or cold/dry.

scholarly journals Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2757 ◽  
Author(s):  
Kongming Li ◽  
Mingming Feng ◽  
Asim Biswas ◽  
Haohai Su ◽  
Yalin Niu ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Satellite Remote Sensing ◽  
Gansu Province ◽  
Driving Factors ◽  
Driving Mechanism ◽  
Second Stage ◽  
Arid And Semiarid ◽  
Land Use And Cover

Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.

scholarly journals Climate Scenarios and Agricultural Indices: A Case Study for Switzerland

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 535
Author(s):  
Flavian Tschurr ◽  
Iris Feigenwinter ◽  
Andreas M. Fischer ◽  
Sven Kotlarski
Keyword(s):  
21St Century ◽  
Agricultural Sector ◽  
Heat Waves ◽  
Climate Scenario ◽  
Climate Variables ◽  
Climate Scenarios ◽  
High Emission ◽  
Projection Analysis ◽  
Horizontal Pattern

The CH2018 Climate Scenarios for Switzerland are evaluated with respect to the representation of 24 indices with agricultural relevance. Furthermore, future projections of the considered indices until the end of the 21st century are analyzed for two greenhouse gas scenarios (Representative Concentrations Pathways RCP2.6 and RCP8.5). The validation reveals good results for indices that are based on one or two climate variables only and on simple temporal aggregations. Indices that involve multiple climate variables, complex temporal statistics or extreme conditions are less well represented. The climate projection analysis indicates an intensification of temperature-related extreme events such as heat waves. In general, climate change signals in the indices considered are subject to three main patterns: a horizontal pattern across Switzerland, a vertical pattern depending on elevation and a temporal pattern with an intensification of change in the course of the 21st century. Changes are in most cases more pronounced for the high-emission RCP8.5 scenario compared to the mitigation scenario RCP2.6. Overall, the projections indicate a challenging 21st century climate for the agricultural sector. Our findings furthermore show the value and the necessity of a robust validation of climate scenario products to enable trustworthy and valuable impact analyses, especially for more complex indices and models.

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