remote sensing Article An Assessment of the Accuracy of MODIS Land Surface Temperature over Egypt Using Ground-Based Measurements Ahmed M. El Kenawy 1,2,* , Mohamed E. Hereher 1,3 and Sayed M. Robaa 4 1 Department of Geography, Sultan Qaboos University, Al Khoud, Muscat 123, Oman 2 Department of Geography, Mansoura University, Mansoura 35516, Egypt 3 Department of Environmental Sciences, Damietta University, New Damietta 34511, Egypt; [email protected] or [email protected] 4 Department of Astronomy, Space Science and Meteorology, Faculty of Science, Cairo University, Cairo 12613, Egypt; [email protected] * Correspondence: [email protected] Received: 30 August 2019; Accepted: 8 October 2019; Published: 12 October 2019 Abstract: Space-based data have provided important advances in understanding climate systems and processes in arid and semi-arid regions, which are hot-spot regions in terms of climate change and variability. This study assessed the performance of land surface temperatures (LSTs), retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS) Aqua platform, over Egypt. Eight-day composites of daytime and nighttime LST data were aggregated and validated against near-surface seasonal and annual observational maximum and minimum air temperatures using data from 34 meteorological stations spanning the period from July 2002 to June 2015. A variety of accuracy metrics were employed to evaluate the performance of LST, including the bias, normalized root-mean-square error (nRMSE), Yule–Kendall (YK) skewness measure, and Spearman’s rho coefficient. The ability of LST to reproduce the seasonal cycle, anomalies, temporal variability, and the distribution of warm and cold tails of observational temperatures was also evaluated. Overall, the results indicate better performance of the nighttime LSTs compared to the daytime LSTs. Specifically, while nighttime LST tended to underestimate the minimum air temperature during winter, spring, and autumn on the order of 1.3, 1.2, and 1.4 C, respectively, daytime LST markedly overestimated the maximum − − − ◦ air temperature in all seasons, with values mostly above 5 ◦C. Importantly, the results indicate that the performance of LST over Egypt varies considerably as a function of season, lithology, and land use. LST performs better during transitional seasons (i.e., spring and autumn) compared to solstices (i.e., winter and summer). The varying interactions and feedbacks between the land surface and the atmosphere, especially the differences between sensible and latent heat fluxes, contribute largely to these seasonal variations. Spatially, LST performs better in areas with sandstone formations and quaternary sediments and, conversely, shows lower accuracy in regions with limestone, igneous, and metamorphic rocks. This behavior can be expected in hybrid arid and semi-arid regions like Egypt, where bare rocks contribute to the majority of the Egyptian territory, with a lack of vegetation cover. The low surface albedo of igneous and limestone rocks may explain the remarkable overestimation of daytime temperature in these regions, compared to the bright formations of higher surface albedo (i.e., sandy deserts and quaternary rocks). Overall, recalling the limited coverage of meteorological stations in Egypt, this study demonstrates that LST obtained from the MODIS product can be trustworthily employed as a surrogate for or a supplementary source to near-surface measurements, particularly for minimum air temperature. On the other hand, some bias correction techniques should be applied to daytime LSTs. In general, the fine space-based climatic information provided by MODIS LST can be used for a detailed spatial assessment of climate variability in Egypt, with important applications in several disciplines such as water resource management, hydrological modeling, agricultural management and planning, urban climate, biodiversity, and energy consumption, amongst others. Remote Sens. 2019, 11, 2369; doi:10.3390/rs11202369 www.mdpi.com/journal/remotesensing Remote Sens. 2019, 11, 2369 2 of 29 Also, this study can contribute to a better understanding of the applications of remote sensing technology in assessing climatic feedbacks and interactions in arid and semi-arid regions, opening new avenues for developing innovative algorithms and applications specifically addressing issues related to these regions. Keywords: air temperature; MODIS; LST; validation; lithology; Egypt 1. Introduction In the era of climate change, an accurate characterization of climate variability and its impacts on natural and human environments requires climatic data at high resolution over space and time [1,2]. Amongst all climatic records, air temperature is an important input variable for both water and energy cycles, being a key indicator of the land surface–atmosphere interactions and feedbacks [3,4]. As such, it has a great importance from the view of various disciplines, including hydrology, agriculture, ecology, ecosystem, health, and energy, among others. Unfortunately, arid and semi-arid environments suffer from a lack of adequate meteorological networks that can properly reflect the main climatological conditions, particularly at the regional and local scales. Specifically, climatic data are often unevenly distributed over space, with temporal discontinuities and inhomogeneities. Furthermore, due to changes in the location of observatories, observers, observation practices, or instruments, climatic records often have a relatively short duration, with frequent gaps, highlighting the limitations of data temporal sampling and spatial coverage. Moreover, in areas of complex topography or high spatial variability of climate, meteorological observatories may fail to capture the high variability of the climate. In developing countries, stationary observation data could have a degree of uncertainty, due to human interference, as most of the meteorological stations are placed in airports under urbanization effects, which could induce records significantly biased from real ambient temperatures [5]. Overall, in data-sparse regions, the quality of climate records is mostly impacted by ageing infrastructure and the inherent costs of manipulating and maintaining observation networks, combined sometimes with a history of unrest, ethnic conflicts, and political and social instability (e.g., Syria, Iraq, Libya, Yemen, and Sudan) [6–8]. In Egypt, the available meteorological records are generally sparse over space and time. Specifically, the majority of the meteorological stations are situated in urbanized settlements close to the Nile and its delta and along the Mediterranean Sea and Red Sea coasts. These areas comprise less than 10% of the total area of the country. From these aspects, the diverse impacts of climate change and the complex interactions between humans and the environment make the current meteorological network inadequate to properly diagnose climate change and its diverse impacts, particularly at detailed spatial scales (i.e., regional and local scales). Within this context, the current meteorological network is not feasible enough to provide solutions that address appropriately the heterogeneity and dynamics of ecosystems across Egypt. In Egypt, high-density climatic information is desired to assess the possible impacts of recent climate change and variability, which are likely to be accelerated under future greenhouse gas emissions, on a wide spectrum of disciplines (e.g., urban climate, agriculture, water resources, food production, health, biodiversity, energy, etc.) [9–12]. Recalling these data limitations, most of the available studies on climate change and variability in Egypt have employed meteorological information from a limited number of meteorological stations and using coarse temporal resolution (i.e., monthly, seasonal, or annual) (e.g., [1,9,13–17]). For instance, based on long-term (1905–2000) records from 18 observatories, the author of [13] assessed intra-decadal variability of winter minimum temperature over Egypt. Also, the authors of [14] assessed temperature variability over Egypt, deploying a monthly data set of only nine time series covering the period 1971–2000. In contrast, a very limited number of investigations have handled climatic data at fine resolution (i.e., daily or sub-daily), which is mandatory for different hydrometeorological applications (e.g., hydrological Remote Sens. 2019, 11, 2369 3 of 29 modeling, natural hazards assessment and forecasting, etc.). One example is [18], the authors of which recently assessed changes in daily temperature extremes over Egypt during the past four decades (1983–2015). Overall, an inspection of these studies highlights the current limitations of meteorological records in Egypt either spatially or temporarily. These challenges strongly constrain any attempts for a reliable diagnosis of climate change and variability and their possible impacts in the country. With the current advancement in Earth observation in general and thermal remote sensing in particular, data retrieved from many sensors have been made freely available for research community, including, for example, the Advanced Very-High-Resolution Radiometer (AVHRR), Moderate-Resolution Imaging Spectroradiometer (MODIS), Spinning Enhanced Visible and Infra-Red Imager (SEVIRI), Meteosat Visible and Infrared Imager (MVIRI), Landsat 4 and 5 TM, Landsat 7 ETM+, Landsat 8 TIRS, Sentinel 2 and 3, and VIIRS. The space-based meteorological data are generally quasi-global, with high spatial