Assessing the extent and impacts of linear infrastructure on Sri Lanka's natural and protected areas: Implications for future development planning.

Linear infrastructure (LI) has varying effects on landscapes depending on different ecosystems' sensitivity and threat levels. Economically developing tropical countries are particularly at risk from LI. Therefore, understanding a country's current LI network and planning future developments to avoid further fragmentation and disturbance is crucial. This study aimed to assess the extent of Sri Lanka's LI network (i.e., roads, railroads, and powerlines), given that it is both a biodiversity hotspot and an economically developing country in the tropics. First, we calculated the average normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) indices and examined their spatial autocorrelation per divisional secretariat division. Then a multivariate cluster analysis was used to determine clusters of natural and protected areas that may receive similar impacts from different LI and their combinations. Results indicated that roads are the most widespread LI type in Sri Lanka, followed by powerlines and railroads. Over 80% of Sri Lanka's total land area falls within 1 km of either a national or a provincial/local road. Areas with high NDVI were primarily manmade habitats, with less than 20% contribution from protected areas. Over 50% of the total protected area of Sri Lanka is being impacted by all three types of LI. Powerlines were the most common LI type in protected areas in proportion to their total network lengths. To minimize environmental impact while achieving development goals, future LI development activities should use a landscape approach to identify development needs and strategies informed by these findings.

Optimization of United States Residential Real Estate Investment through Geospatial Analysis and Market Timing.

In this study, we examined the long-term spatial patterns and trends of home values within the United States from 1996 to 2019. The Zillow Home Value Index (ZHVI) data were obtained from the Zillow's housing data portal. The overall trends indicated both coasts of the United States having the highest concentration of hotspots. The ideal time to sell varied seasonally across the country. We used geo-statistical analysis techniques, such as cluster analysis and emerging hot spot analysis (EHSA), to reveal the average and long-term trends in spatial patterns of home values. Washington was the only state with sporadic hot spots. The Western United States showed consecutive hotspots, most notably in California, but in surrounding states as well. The Northeast, Mid-Atlantic, and Florida were dominated by oscillating hotspots. Texas and the Southeast display new hotspots that signal change, indicative of southward migration of population. Finally, the Midwest has been a historical cold spot, but Cleveland has improved to a diminishing cold spot, pointing to the revitalization of the region. The seasonal level analysis displayed southern and coastal states as those benefiting most from winter home sales, and the colder northern states captured the most value and sold quicker in the summer months. This intuitive analysis of the country's variation in ideal sale month reveals a local view of when to sell rather than a generalized view of the entire United States.

Spatial patterns of malaria case burden and seasonal precipitation in India during 1995-2013.

The majority of malaria cases in Southeast Asia occur in India. It is a major public health problem in India, which accounts for substantial morbidity, mortality, and economic loss. The spatial distribution of malaria widely varies due to geo-ecological diversity, multi-ethnicity, and wide distribution of the different anopheline vectors. The predominant malaria parasites in India for malaria are P. Falciparum (Pf) and P. Vivax (Pv). This study analyzes the spatial patterns of malaria cases, specifically the two dominant malaria vectors, at the regional level and its relation to seasonal precipitation. The results of our study revealed an overall decline in malaria cases in the later years. The spatial spread of malaria cases was more widespread during the normal monsoon years vs drought years, which can be attributed to more conducive environment for mosquitos to breed. The correlation analysis revealed a stronger correlation between malaria case burden and monsoon precipitation. Spatially, the strongest correlation between seasonal and annual precipitation, and malaria case burden were located across the northern plains and northeast India. The results of this research further our understanding of the relationship between seasonal precipitation and malaria case burden at the regional level across India.

Using satellite-based AOD and ground-based measurements to evaluate the impact of the DWH oil spill on coastal air quality.

The 2010 DWH disaster generated atmospheric pollutants of health concern which reached the Gulf Coast. This study evaluated whether changes in coastal air quality due to the disaster were captured by aerosol optical depth (AOD) estimated using satellite data and by ground-based monitoring of air pollution, including fine particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5), benzene and naphthalene. Mean monthly AOD levels were higher in May 2010 [during oil spill time], (mean AOD = 0.355), than for the prior (mean AOD = 0.258) and following years (mean AOD = 0.252) (p < 0.05). PM2.5 concentrations and AOD were significantly correlated (R2 = 0.59, p < 0.05), for one study area. Elevated PM2.5, benzene, and naphthalene concentrations coincided with downwind directions from the location of the oil slicks. A fully-coupled oil fate and transport atmospheric transport model of oil spill emissions, integrated with AOD and more extensive ground-based measurements, is recommended to predict coastal population exposures during oil spills.

Implications of changes in temperature and precipitation on the discharge of Brahmaputra River in the urban watershed of Guwahati, India.

The urban watershed of Guwahati situated on the bank of the Brahmaputra River is one of the fastest growing cities of India. During the last two decades, water security concerns due to climatic variabilities have become a pronounced issue in the urban watershed of Guwahati. Thus, the study aims to calculate the long-term temporal trends of temperature, precipitation, extreme climate indices, and river discharge to assess the variations and patterns of hydro-climatic variations in the urban watershed of Guwahati from 1991 to 2019. Furthermore, the current study also tries to correlate these extreme climatic indices to river discharge to determine the degree of hydro-climatic variations. The Mann-Kendall statistical techniques and Sen's estimator were used to calculate the statistical significance, stability, and averaged magnitude of trends in the hydro-meteorological data. The result shows that the wetness indices, R20 and RX5Day, reported a decline in Guwahati's urban watershed from 1991 to 2019, resulting in a reduction in intensity and duration of heavy rainfalls while the dry spell (CDD) has been more distinct in the study area with a rise in the average temperature by 0.023 °C/year. Similarly, the most significant statistical trend was found in the monsoonal discharge of the Brahmaputra with a negative trend of - 204.16 m3/s/year. The results also show that fluctuations in rainfall patterns have a direct impact on the discharge of the Brahmaputra. These phenomena can affect the quantity of river water resulting in a severe impact on water security in the study area.

Impact of the COVID-19 lockdown on air quality in the Delhi Metropolitan Region.

With the rapid spread of COVID-19 related cases globally, national governments took different lockdown approaches to limit the spread of the virus. Among them, the Government of India imposed a complete nationwide lockdown starting on March 25, 2020. This presented a unique opportunity to explore how a complete standstill in regular daily activities might impact the local environment. In this study, we have analyzed the change in the air quality levels stemming from the reduced anthropogenic activities in one of the most polluted cities in the world, the Delhi Metropolitan Region (DMR). We analyzed station-level changes in particulate matter, PM10 and PM2.5, across the DMR between April 2019 and 2020. The results of our study showed widespread reduction in the levels of both pollutants, with substantial spatial variations. The largest decreases in particulate matter were associated with industrial and commercial areas. Highest levels of PM10 and PM2.5 were observed near sunrise with little change in the time of maximum between 2019 and 2020. The results of our study highlight the role of anthropogenic activities on the air quality at the local level.

Alarming groundwater depletion in the Delhi Metropolitan Region: a long-term assessment.

Groundwater in Delhi Metropolitan Region (DMR) is suffering from multiple catastrophes, viz., asymptotic increases in groundwater withdrawal, reduced recharge due to erratic rainfall, and variable soil type. In this study, we examined long-term trends in groundwater levels across the DMR from 1996 to 2018. Station level data collected by the Central Groundwater Board for 258 stations at the seasonal scale were visualized and interpreted using geospatial analysis. The spatial patterns of the trends in groundwater levels revealed increasing depths of groundwater levels, except the Yamuna River floodplains. The main cause for the decline is related to the rapid growth in population accompanied with high-density impervious urban land uses, leading to lower levels of recharge vs unlimited withdrawal of groundwater for daily needs. In addition, the local geology in the form of clayey soils in northwest DMR also contributed to the lower levels of recharge. The results of the analysis enabled us to establish the trend and delineate the zones of differential recharge. Furthermore, the level of contaminants were analyzed at the district level for fluorides and nitrates. The presence of fluoride contamination was mostly concentrated in the northwestern district, while the nitrate exceedance was more widespread. These findings will help in achieving the 6th Sustainable Development Goal (SDG) of United Nations by 2030 as well as goals identified in Delhi's master plan of 2041.