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(2020) MODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment,

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This study aimed at characterizing the spatial and temporal characteristics of vegetation abundance (represented by At-Sensor Normalized Difference Vegetation Index (ASNDVI) and/or Land Surface Normalized Difference Vegetation Index (LSNDVI)) and surface temperature (represented by At-Sensor Brightness Temperature (ASBT) and/or Land Surface Temperature (LST)) and investigating the types of the relationships between these variables in different seasons in different years using Landsat data in Greater Amman Municipality in Jordan. Correlation analysis using Pearson's correlation coefficient showed that using either ASNDVI or LSNDVI and either ASBT or LST should lead to the same results. Change analysis from 1987-2016 using map algebra showed that the majority of the municipality was subjected to both no change and small increase in vegetation abundance in summer and winter and both no change and small increase in surface temperature in summer and both no change and small decrease in surface temperature in winter. Vegetation abundance variability reflected partly the land cover characteristics of the municipality while surface temperature variability indicated the potential of the presence of an inverted surface urban heat island pattern. Correlation analysis using contingency tables showed the presence of negative relationship in summer and positive relationship in winter between vegetation abundance and surface temperature.

Abstract. This study explores the spatial trends of cutaneous leishmaniasis (CL) and characterises the relationships between the observed spatial patterns and climate in Jordan, Syria, Iraq and Saudi Arabia in 2009. Areal interpolation revealed the presence of four major hotspots of relatively high incidence rates covering most parts of Syria, central parts of Iraq, and north-western, central, south-eastern and south-western parts of Saudi Arabia. The severity of these hotspots was seen to decrease from high to low latitudes. The spatial patterns could be partly linked to precipitation (the higher the precipitation, the higher the incidence rates) and to a lesser degree to temperature (the lower the temperature, the higher the incidence rates). No significant relationship was deduced between the observed spatial patterns of incidence rates and humidity. However, these three climatic factors could be used jointly as explanatory variables (ceteris paribus) to explain part of the spatial variations of the CL incidence rates in the study area by applying geographically weighted regression.