This article summarized the spatiotemporal pattern of land use/land cover (LU/LC) and urban heat island (UHI) dynamics in the Metropolitan city of Tehran between 1988 and 2018. The study showed dynamics of each LU/LC class and their role in influencing the UHI. The impervious surface area expanded by 286.04 (48.27% of total land) and vegetated land was depleted by 42.06 km² (7.10% of total land) during the period of 1988–2018. The mean land surface temperature (LST) has enlarged by approximately 2–3 °C at the city center and 5–7 °C at the periphery between 1988 and 2018 based on the urban–rural gradient analysis. The lower mean LST was experienced by vegetation land (VL) and water body (WB) by approximately 4–5 °C and 5–7 °C, respectively, and the higher mean LST by open land (OL) by 7–11 °C than other LU/LC classes at all time-points during the time period, 1988–2018. The magnitude of mean LST was calculated based on the main LU/LC categories, where impervious land (IL) recorded the higher temperature difference compared to vegetation land (VL) and water bodies (WB). However, open land (OL) recorded the highest mean LST differences with all the other LU/LC categories. In addition to that, there was an overall negative correlation between LST and the normal difference vegetation index (NDVI). By contrast, there was an overall positive correlation between LST and the normal difference built-up index (NDBI). This article, executed through three decadal change analyses from 1988 to 2018 at 10-year intervals, has made a significant contribution to delineating the long records of change dynamics and could have a great influence on policy making to foster environmental sustainability.

Drought has severe impacts on human society and ecosystems. In this study, we used data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) sensors to examine the drought effects on vegetation in Afghanistan from 2001 to 2018. The MODIS data included the 16-day 250-m composites of the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) with Land Surface Temperature (LST) images with 1 km resolution. The TRMM data were monthly rainfalls with 0.1-degree resolution. The relationship between drought and index-defined vegetation variation was examined by using time series, regression analysis, and anomaly calculation. The results showed that the vegetation coverage for the whole country, reaching the lowest levels of 6.2% and 5.5% were observed in drought years 2001 and 2008, respectively. However, there is a huge inter-regional variation in vegetation coverage in the study period with a significant rising trend in Helmand Watershed with R = 0.66 (p value = 0.05). Based on VCI for the same two years (2001 and 2008), 84% and 72% of the country were subject to drought conditions, respectively. Coherently, TRMM data confirm that 2001 and 2008 were the least rainfall years of 108 and 251 mm, respectively. On the other hand, years 2009 and 2010 were registered with the largest vegetation coverage of 16.3% mainly due to lower annual LST than average LST of 14 degrees and partially due to their slightly higher annual rainfalls of 378 and 425 mm, respectively, than the historical average of 327 mm. Based on the derived VCI, 28% and 21% of the study area experienced drought conditions in 2009 and 2010, respectively. It is also found that correlations are relatively high between NDVI and VCI (r = 0.77, p = 0.0002), but slightly lower between NDVI and precipitation (r = 0.51, p = 0.03). In addition, LST played a key role in influencing the value of NDVI. However, both LST and precipitation must be considered together in order to properly capture the correlation between drought and NDVI.

Globally, the urban heat island (UHI) effect is a major problem which leads to urban residents suffering from adverse urban ecological environments and serious health risks. Understanding the impacts of urban landscape features on the thermal environment has been an important focus across various fields of research. The purpose of this study is to analyze the impacts of urban heat source–sink landscape patterns on urban heat islands, using the fast-growing Zhengzhou City in central China as the case study. Landsat data (captured in 1996, 2006, and 2014), various geospatial approaches, and correlation analysis were applied to facilitate the analysis. Based on the contributions of the urban landscape to land surface temperature (LST), we empirically identified the heat sources and heat sinks. Then, the composition and configurations of heat source and sink landscapes were estimated by a series of spatial metrics at the landscape and class levels. The results showed that the overall mean land surface temperature (LST) in the study area increased by 2.72 °C from 1996 to 2014. This observed increasing trend in overall mean LST is consistent with the process of rapid urbanization in the study area, which was evidenced by the dramatic increase in impervious surfaces and the substantial loss in vegetation cover. Generally, as observed, landscape composition has a stronger influence on LST than does landscape configuration. For heat sources, the proportion, size, aggregation, and density of patches have positive effects on LST, while adjusting the spatial distribution and abundance of urban landscape are effective ways to control the UHI effects. In contrast, the percentage, size, density, and aggregation of heat sink patches have negative effects on LST. Additionally, the effects of increasing total patch edges and shape complexity should be considered when mitigating the UHI effect. These findings are beneficial for furthering our understanding of how urban landscape patterns affect UHI, and they can help optimize urban landscape patterns to alleviate the UHI effect and enhance sustainable development in the study area.

Land surface temperature (LST) is a basic parameter in energy exchange between the land and the atmosphere, and is frequently used in many sciences such as climatology, hydrology, agriculture, ecology, etc. Time series of satellite LST data have usually deficient, missing, and unacceptable data caused by the presence of clouds in images, the presence of dust in the atmosphere, and sensor failure. In this study, the singular spectrum analysis (SSA) algorithm was used to resolve the problem of missing and outlier data caused by cloud cover. The region studied in the present research included an image frame of the Moderate Resolution Imaging Spectroradiometer (MODIS) with horizontal number 22 and vertical number 05 (h22v05). This image involved a large part of Iran, Turkmenistan, and the Caspian Sea. In this study, MODIS LST products (MOD11A1) were used during 2015 with approximately 1 km × 1 km spatial resolution and day/night LST data (daily temporal resolution). On average, the data have 36.37% gaps in each pixel profile with 730 day/night LST data. The results of the SSA algorithm in the reconstruction of LST images indicated a root mean square error (RMSE) of 2.95 Kelvin (K) between the original and reconstructed LST time series data in the study region. In general, the findings showed that the SSA algorithm using spatio-temporal interpolation can be effectively used to resolve the problem of missing data caused by cloud cover.

The purpose of this paper is to examine the linkage between rapid urbanization and flood risk in the hinterlands of the Pearl River Delta, P.R. China. Foshan, a typical hinterland city in the Pearl River Delta region, was selected as a case study. Land use and cover change in Foshan during 1988-2003 was analyzed using remote sensing and geographic information system (GIS) techniques. Furthermore, analysis on historical hydrological data during 1962-2005 was performed. Results show that rapid urbanization has resulted in losses of farmland, forest and shrub since 1988. In addition, in order to compensate or offset the loss of farmland due to rapid urban expansion, more than 30 % of the forest and 20 % of the shrub areas were transformed into farmlands. Inevitably, both the urban and agricultural lands increased the pressure on the drainage systems. Furthermore, over the past decades human activities such as dredging up the floodways, excavating sand and building water facilities in the rivers, significantly changed the hydrological conditions, and therefore impaired the rivers’ capacity to buffer floods. Lessons from the Foshan case implied that, in addition to natural processes, human activities driven by socio-economic factors should be considered responsible for the recently increasing level of flood risks. Both economically and environmentally, it is irrational and impractical to encourage encroachment of lands vulnerable to floods. It is also realistic and urgent to effectively prevent and control the adverse ecological consequences of urbanization and economic activities for building their wealth and prominence.