Chuyuan Wang

Spatio-Temporal Modeling of the Urban Heat Island in the Phoenix Metropolitan Area: Land Use Change Implications

This study examines the spatial and temporal patterns of the surface urban heat island (SUHI) intensity in the Phoenix metropolitan area and the relationship with land use land cover (LULC) change between 2000 and 2014. The objective is to identify specific regions in Phoenix that have been increasingly heated and cooled to further understand how LULC change influences the SUHI intensity. The data employed include MODerate-resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) 8-day composite June imagery, and classified LULC maps generated using 2000 and 2014 Landsat imagery. Results show that the regions that experienced the most significant LST changes during the study period are primarily on the outskirts of the Phoenix metropolitan area for both daytime and nighttime. The conversion to urban, residential, and impervious surfaces from all other LULC types has been identified as the primary cause of the UHI effect in Phoenix. Vegetation cover has been shown to significantly lower LST for both daytime and nighttime due to its strong cooling effect by producing more latent heat flux and less sensible heat flux. We suggest that urban planners, decision-makers, and city managers formulate new policies and regulations that encourage residential, commercial, and industrial developers to include more vegetation when planning new construction.

A Simplified Empirical Line Method of Radiometric Calibration for Small Unmanned Aircraft Systems-Based Remote Sensing

The use of small unmanned aircraft systems (sUAS) to acquire very high-resolution multispectral imagery has attracted growing attention recently; however, no systematic, feasible, and convenient radiometric calibration method has been specifically developed for sUAS remote sensing. In this research, we used a modified color infrared (CIR) digital single-lens reflex (DSLR) camera as the sensor and the DJI S800 hexacopter sUAS as the platform to collect imagery. Results show that the relationship between the natural logarithm of measured surface reflectance and image raw, unprocessed digital numbers (DNs) is linear and the y-intercept of the linear equation can be theoretically interpreted as the minimal possible surface reflectance that can be detected by each sensor waveband. The empirical line calibration equation for every single band image can be built using the y-intercept as one data point, and the natural log-transformed measured reflectance and image DNs of a gray calibration target as another point in the coordinate system. Image raw DNs are therefore converted to reflectance using the calibration equation. The Mann-Whitney U test results suggest that the difference between the measured and the predicted reflectance values of 13 tallgrass sampling quadrats is not statistically significant. The method theory developed in this study can be employed for other sUAS-based remote sensing applications.

Examining the ecosystem health and sustainability of the world's largest mangrove forest using multi-temporal MODIS products.

Sweeping across Bangladesh and India, the Sundarbans forest is the worlds largest contiguous mangrove forest. Although the human population density is high at the edge, Sundarbans has not encountered significant areal transformation in the last four decades. However, we argue that forest degradation can occur discontinuously within the forest without alteration of the entire forest area. In this paper, we used MODIS land products to compare the spatiotemporal ecological dynamics of the Bangladesh and Indian part of this mangrove forest between 2000 and 2010. We used the following 5 ecological parameters for our analysis: the Percent Tree Cover (PTC), Enhanced Vegetation Index (EVI), Net Primary Productivity (NPP), Leaf Area Index (LAI), and Evapotranspiration (ET). Our pixel-based time-series trend analysis for each MODIS image stack, using an ordinary least square (OLS) regression method, showed that forest degradation is happening in fragmented parcels within the forest. The degradation rate is comparatively higher in the Bangladesh part than in the Indian part of Sundarbans. Compartments 8, 10, 12, and 15 in the Bangladesh part, in particular, show high degradation, while compartment 48 and the southern edge of 45 show slight increases in PTC or EVI. Forest degradation in the Indian part of the forest is evident in the National Park and Reserve Forest blocks; however, no substantial degradation is evident in the western section. We have identified certain anthropogenic stressors (i.e., oil pollution, shrimp farming) and natural stressors (i.e., increased salinity, cyclones, forest fire) which might be responsible for the observed degradation. We have provided sustainable planning options and policy transformation alternatives for those areas under pressure from these stressors. We anticipate that our analysis of forest degradation will help management agencies, conservators, and policy makers achieve better management of this worlds largest mangrove forest for a sustainable future.

Environmental Concerns of Deforestation in Myanmar 2001–2010

Deforestation in Myanmar has recently attracted much attention worldwide. This study examined spatio-temporal patterns of deforestation and forest carbon flux in Myanmar from 2001 to 2010 and environmental impacts at the regional scale using land products of the Moderate Resolution Imaging Spectroradiometer (MODIS). The results suggest that the total deforestation area in Myanmar was 21,178.8 km2, with an annual deforestation rate of 0.81%, and that the total forest carbon release was 20.06 million tons, with an annual rate of 0.37%. Mangrove forests had the highest deforestation and carbon release rates, and deciduous forests had both the largest deforestation area and largest amount of carbon release. During the study period, the south and southwestern regions of Myanmar, especially Ayeyarwady and Rakhine, were deforestation hotspots (i.e., the highest deforestation and carbon release rates occurred in these regions). Deforestation caused significant carbon release, reduced evapotranspiration (ET), and increased land surface temperatures (LSTs) in deforested areas in Myanmar during the study period. Constructive policy recommendations are put forward based on these research results.

Landscape determinants of spatio-temporal patterns of aerosol optical depth in the two most polluted metropolitans in the United States

Elevated concentration of atmospheric aerosols during severe urban air pollution episodes necessitates a deep understanding of the underlying determinants for a sustainable urban environment. The 15-year (2001-2015) Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data for the Phoenix and Los Angeles Metropolitan Areas were applied to examine the spatio-temporal patterns and dynamics of urban aerosols. The strongly correlated temporal trends of AOD were observed due to the similar seasonal pattern of aerosol emissions and potential synoptic connections between two areas. Relatively higher mean value and lower decreasing trend of AOD were found in the PMA. Correlations reveal that topography is the predominant factor affecting the spatial pattern of AOD, as compared to the urban land use and vegetation. The effect of urbanization on air pollution varies with preexisting landscape, which apparently alleviates aerosol concentration in the PMA. Vegetation mitigates air pollution despite its emission of fine mode aerosols. As a cross-validation, the ground-measured concentrations of particulate matters (PM2.5 and PM10) were compared against AOD. The abnormal weak positive or strong negative AOD-PM2.5 associations result from the relatively small portion of anthropogenic aerosols and the changing atmospheric boundary layer height.

Modeling Above-Ground Biomass in Tallgrass Prairie Using Ultra-High Spatial Resolution sUAS Imagery

The authors examined the relationship between tallgrass above-ground biomass (AGB) and NDVI from ultra-high spatial resolution multispectral imagery collected by small unmanned aircraft systems (sUAS). This study was conducted at the Tallgrass Prairie National Preserve in Chase County, Kansas. Results show that NDVI values computed from sUAS imagery explained up to 94 percent of the variance (p <0.01) in AGB measurements. The model coefficient of determination (r₂) decreased with increasing aircraft flight altitude suggesting image spatial resolution is a key factor influencing the strength of the relationship. A scaling-up approach from small-scale sUAS imagery to broad-scale, digital aerial imagery collected at 1,200 meters by a piloted aircraft was used to provide AGB model estimates across the entire 4,500 ha of the Preserve. Spectral reflectance data measured by spectroradiometer were also used to identify three optimal regions of the spectrum that have the highest significant correlations with tallgrass AGB.

Empirical modeling and spatio-temporal patterns of urban evapotranspiration for the Phoenix metropolitan area, Arizona

In this study, an empirical model for predicting urban evapotranspiration (ET) is examined for the Phoenix metropolitan area that is in a subtropical desert climate using in situ ET measurements from a local flux tower and remotely sensed moderate-resolution imaging spectroradiometer land products. Annual ET maps of Phoenix are then created for the period from 2001 to 2015 using the empirical model developed. A time-series trend analysis is finally performed using predicted ET maps to discover the spatio-temporal patterns of ET changes during the study period. Results suggest that blue-sky albedo and land surface temperature are two statistically significant variables explanatory to model urban ET for Phoenix. Areas that have experienced significant increases of ET are highly spatially clustered, and are mainly found on the outskirts of the city, while areas of decreasing ET are generally associated with highly developed areas, such as downtown Phoenix.

Fragmentation Patterns in Land Reform Settlements in the Brazilian Amazon

Direct action land reform (DALR) and settlement formation are new drivers of deforestation in the Brazilian Amazon. However, until now no research has paid attention to fragmentation patterns and the social processes that lead to them. This article analyzes two types of settlements, spontaneous and social movement organization-led settlements. The study uses neutral landscape models (NLMs) to compare simulated landscapes with the real fragmentation patterns found in DALR settlements. In sequence, the article uses landscape metrics to analyze the temporal and spatial dynamics of fragmentation patterns in these two types of DALR settlements. Results showed that there are significant differences between real landscape patterns and simulated landscapes using NLMs. In other words, human interferences did play a significant role in shaping deforestation patches in DALR settlements. Our metric results revealed a process in which deforestation patch mean area, shape complexity, and physical connectedness increase over time.