Developed Land Cover Research Articles

Developing Multi-Source Indices to Discriminate between Native Tropical Forests, Oil Palm and Rubber Plantations in Indonesia

Over the last 18 years, Indonesia has experienced significant deforestation due to the expansion of oil palm and rubber plantations. Accurate land cover maps are essential for policymakers to track and manage land change to support sustainable forest management and investment decisions. An automatic digital processing (ADP) method is currently used to develop land cover change maps for Indonesia, based on optical imaging (Landsat). Such maps produce only forest and non-forest classes, and often oil palm and rubber plantations are misclassified as native forests. To improve accuracy of these land cover maps, this study developed oil palm and rubber plantation discrimination indices using the integration of Landsat-8 and synthetic aperture radar Sentinel-1 images. Sentinel-1 VH and VV difference (>7.5 dB) and VH backscatter intensity were used to discriminate oil palm plantations. A combination of Landsat-8 NDVI, NDMI with Sentinel-1 VV and VH were used to discriminate rubber plantations. The improved map produced four land cover classes: native forest, oil palm plantation, rubber plantation, and non-forest. High-resolution SPOT 6/7 imagery and ground truth data were used for validation of the new classified maps. The map had an overall accuracy of 92%; producer’s accuracy for all classes was higher than 90%, except for rubber (65%), and user’s accuracy was over 80% for all classes. These results demonstrate that indices developed from a combination of optical and radar images can improve our ability to discriminate between native forest and oil palm and rubber plantations in the tropics. The new mapping method will help to support Indonesia’s national forest monitoring system and inform monitoring of plantation expansion.

Trends in United States Human Footprint Revealed by New Spatial Metrics of Urbanization and Per Capita Land Change

Accelerations in population growth and urban expansion are transforming landscapes worldwide and represent a major sustainability challenge. In the United States, land conversion to impervious surfaces has outpaced population increases, yet there are few spatial metrics of urbanization and per capita land change available nationwide for assessing local to regional trends in human footprint. We quantified changes (2000–2010) in housing density, imperviousness, per capita land consumption, and land-use efficiency for block groups of the contiguous U.S. and examined national patterns and variation in these metrics along the urban–rural gradient and by megaregion. Growth in housing (+13.6%) and impervious development (+10.7%) resulted in losses of rural lands, primarily due to exurbanization and suburbanization. Mean per capita consumption increased in all density classes but was over 8.5 times greater in rural lands than in exurban, suburban, and urban areas. Urban and suburban areas had significantly lower mean consumption, yet change was unsustainable in 60% of these areas. Megaregions across the sprawling Sun Belt, spanning from Arizona to North Carolina, grew most unsustainably, especially compared to regions in the Pacific Northwest and Front Range. This work establishes 21st-century benchmarks that decision-makers can use to track local and regional per capita land change and sustainable growth in the U.S.; however, these metrics of the form, extent, rate, and efficiency of urbanization can be applied anywhere concurrent built-up area and population data are available over time. Our web mapping application allows anyone to explore spatial and temporal trends in human footprint and download metrics, and it is designed to be easily updatable with future releases of validated developed land cover, protected areas, and decennial Census data.

Future land cover and climate may drive decreases in snow wind‐scour and transpiration, increasing streamflow at a Colorado, USA headwater catchment

AbstractUnderstanding how land cover change will impact water resources in snow‐dominated regions is of critical importance as these locations produce disproportionate runoff relative to their land area. We coupled a land cover evolution model with a spatially explicit, physics‐based, watershed process model to simulate land cover change and its impact on the water balance in a 5.0 km2 headwater catchment spanning the alpine–subalpine transition on the Colorado Front Range. We simulated two potential futures both with greater air temperature (+4°C/century) and more precipitation (+15%/century, MP) or less precipitation (−15%/century, LP) from 2000 to 2100. Forest cover in the catchment increased from 72% in 2000 to 84% and 83% in 2050 and to 95% and 92% in 2100 for MP and LP, respectively. Surprisingly, increases in forest cover led to mean increases in annual streamflow production of 12 mm (6%) and 2 mm (1%) for MP and LP in 2050 with an annual control streamflow of 208 mm. In 2100, mean streamflow production increased by 91 mm (44%) and 61 mm (29%) for MP and LP. This result counters previous work as runoff production increased with forested area due to decreases in snow wind‐scour and increases in drifting leeward of vegetation, highlighting the need to better understand the impacts of forest expansion on the spatial pattern of snow scour, deposition and catchment effective precipitation. Identifying the hydrologic response of mountainous areas to climate warming induced land cover change is critically important due to the potential water resources impacts on downstream regions.

Societal Implications of Forest and Water Body Area Evolution in Czechia and Selected Regions

Land cover evolution is an environmental factor that can be used to characterize forest ecosystem services (FES). This study aims to analyze the change in forest cover and water bodies between 1990 and 2018 in the whole Czech Republic, and in the Central Bohemian and South Moravian regions, and its effects on freshwater provision. Additionally, we attempt to understand the societal implications of water quality, public perception, and environmental investment on natural ecosystems. Forest cover and water body data were obtained from the Corine land cover database, while water quality and investment were compiled from the Czech Statistical Office. Public perceptions on the Czech FES were collected from a national survey. Between 1990 and 2018, forest cover has increased by 3.94% and water bodies by 7.65%; however, from 2014 to 2018, severe droughts were reported that compromised the availability of surface water, presumably on artificial structures, causing an increase in the occupied area. Regarding public perception, respondents with less education, and the older population, obtained an assessment of the low performance of the FES, while the water quality and investment indicate that environmental funding has contributed to improving the quality of outflow water from the wastewater treatment plants, fulfilling all the allowed limits of the urban wastewater treatment directive. Hence, a multidisciplinary approach can help decision makers promote policies that integrate environmental management measures, investment protection, and contribute to sustainable development.

Assessment and forecast of changes in the soil cover of anthropogenically transformed landscapes

Changes in the soil and soil cover under various types of anthropogenic impact are described. Trends of the development of anthropogenically transformed and anthropogenic soil cover patterns that occur in the Northwest of Russia have been studied. Transforming soils, intercomponent links, and natural factors of soil cover differentiation, humans either change their characteristics while maintaining the major trend or open a new branch of the land cover evolution.

Land cover changes on a barrier island: Yearly changes, storm effects, and recovery periods

Ecosystems on barrier islands provide socio-ecological services to terrestrial and aquatic endangered species, as well as human inhabitants. The management of these coastal ecosystems is challenged by changes in annual and storm time scales driven by atmospheric, oceanographic, geologic, and human processes. Thus, the need for data and methods to accurately quantify and assess ecosystem and land cover evolution to inform stakeholders is on the rise. A dataset of high-resolution color infrared images of a U.S. National Wildlife Refuge is used to quantify annual land cover changes at a barrier island scale and to identify the effects of hurricanes and their recovery periods. Geospatial analysis and change matrices depict the interconnection between 13 land cover classes. Vegetation growth over regions of bare sand formed by storms leads to the creation of successional habitats, while the loss of bare sand dune to beach, and beach to water are indicators of erosional processes. Storms passing along the ocean and sound side of a barrier island result in different land cover changes that can last anywhere from 4 to more than 7 years, respectively. Management practices for coastal regions and the presence of infrastructure partially control the expansion of marshes, bare sand, maritime brush, and dunes.

Continuous Monitoring of the Flooding Dynamics in the Albufera Wetland (Spain) by Landsat-8 and Sentinel-2 Datasets

Satellite data are very useful for the continuous monitoring of ever-changing environments, such as wetlands. In this study, we investigated the use of multispectral imagery to monitor the winter evolution of land cover in the Albufera wetland (Spain), using Landsat-8 and Sentinel-2 datasets. With multispectral data, the frequency of observation is limited by the possible presence of clouds. To overcome this problem, the data acquired by the two missions, Landsat-8 and Sentinel-2, were jointly used, thus roughly halving the revisit time. The varied types of land cover were grouped into four classes: (1) open water, (2) mosaic of water, mud and vegetation, (3) bare soil and (4) vegetated soil. The automatic classification of the four classes was obtained through a rule-based method that combined the NDWI, MNDWI and NDVI indices. Point information, provided by geo-located ground pictures, was spatially extended with the help of a very high-resolution image (GeoEye-1). In this way, surfaces with known land cover were obtained and used for the validation of the classification method. The overall accuracy was found to be 0.96 and 0.98 for Landsat-8 and Sentinel-2, respectively. The consistency evaluation between Landsat-8 and Sentinel-2 was performed in six days, in which acquisitions by both missions were available. The observed dynamics of the land cover were highly variable in space. For example, the presence of the open water condition lasted for around 60–80 days in the areas closest to the Albufera lake and progressively decreased towards the boundaries of the park. The study demonstrates the feasibility of using moderate-resolution multispectral images to monitor land cover changes in wetland environments.

Are Land Use Options in Viticulture and Oliviculture in Agreement with Bioclimatic Shifts in Portugal?

Land and climate are strongly connected through multiple interface processes and climate change may lead to significant changes in land use. In this study, high-resolution observational gridded datasets are used to assess modifications in the Köppen–Geiger and Worldwide Bioclimatic (WBCS) Classification Systems, from 1950–1979 to 1990–2019 in Portugal. A compound bioclimatic-shift exposure index (BSEI) is also defined to identify the most exposed regions to recent climatic changes. The temporal evolution of land cover with vineyards and olive groves between 1990 and 2018, as well as correlations with areas with bioclimatic shifts, are analyzed. Results show an increase of CSa Warm Mediterranean climate with hot summer of 18.1%, followed by a decrease in CSb (warm summer) climate of −17.8%. The WBCS Temperate areas also reveal a decrease of −5.11%. Arid and semi-arid ombrotypes areas increased, conversely humid to sub-humid ombrotypes decreased. Thermotypic horizons depict a shift towards warmer classes. BSEI highlights the most significant shifts in northwestern Portugal. Vineyards have been displaced towards regions that are either the coolest/humid, in the northwest, or the warmest/driest, in the south. For oliviculture, the general trend for a relative shift towards cool/humid areas suggests an attempt of the sector to adapt, despite the cover area growth in the south. As vineyards and olive groves in southern Portugal are commonly irrigated, options for the intensification of these crops in this region may threaten the already scarce water resources and challenge the future sustainability of these sectors.

Generalist bird exhibits site-dependent resource selection.

Quantifying resource selection (an organism's disproportionate use of available resources) is essential to infer habitat requirements of a species, develop management recommendations, predict species responses to changing conditions, and improve our understanding of the processes that underlie ecological patterns. Because study sites, even within the same region, can differ in both the amount and the arrangement of cover types, our objective was to determine whether proximal sites can yield markedly different resource selection results for a generalist bird, northern bobwhite (Colinus virginianus). We used 5 years of telemetry locations and newly developed land cover data at two, geographically distinct but relatively close sites in the south‐central semi‐arid prairies of North America. We fit a series of generalized linear mixed models and used an information‐theoretic model comparison approach to identify and compare resource selection patterns at each site. We determined that the importance of different cover types to northern bobwhite is site‐dependent on relatively similar and nearby sites. Specifically, whether bobwhite selected for shrub cover and whether they strongly avoided trees, depended on the study site in focus. Additionally, the spatial scale of selection was nearly an order of magnitude different between the cover types. Our study demonstrates that—even for one of the most intensively studied species in the world—we may oversimplify resource selection by using a single study site approach. Managing the trade‐offs between practical, generalized conclusions and precise but complex conclusions is one of the central challenges in applied ecology. However, we caution against setting recommendations for broad extents based on information gathered at small extents, even for a generalist species at adjacent sites. Before extrapolating information to areas beyond the data collected, managers should account for local differences in the availability, arrangement, and scaling of resources.

Tracing the Long-Term Evolution of Land Cover in an Alpine Valley 1820–2015 in the Light of Climate, Glacier and Land Use Changes

Alpine glacial environments and their fluvial systems are among those landscapes most comprehensively affected by climate change. Typically, studies on the consequences of climate change in such environments, e.g., glacier retreat, cover a maximum of 70 years, reflecting the availability of orthophotos or satellite images. This study addresses the long-term transformation processes in a glaciated catchment and highlights the role of human agency in a changing Alpine environment. In order to identify land cover changes between 1820 and 2015 in the Long-Term Ecosystem Research (LTER) site “Jamtal” (Tyrol, Austria) we apply a “regressive-iterative GIS reconstruction method” combining both historical maps and optical remote sensing data. Below 2,100 m a.s.l. the Jamtal experienced a massive 62% decline of unvegetated debris areas and bedrock outcrops (so-called “wasteland”) that was mainly transformed to grassland and sparsely wooded areas. Forests increased by an outstanding 323% and grassland was replaced by sparsely or densely wooded areas. This primarily reflects the abandonment of agricultural uses at unfavourable remote sites. In the higher (formerly) glaciated subbasin, ice-covered areas declined by 55%, which was associated with a major (82%) growth of exposed wasteland. Concurrently, Alpine grassland expanded by 196% and krumholz even by 304%. Approximately half of the new fluvial system that evolved in deglaciated areas between 1870 and 1921 still existed in 2015. Unconsolidated debris buried almost one fifth of the new channels, and almost one third was colonized by vegetation. Recent data show that the deglaciation process is much faster than the colonization process by Alpine vegetation. Accordingly, the extent of wasteland has expanded and potentially amplifies the sediment supply to the fluvial system. Alterations in high Alpine hydrological and sediment/debris regimes significantly affect human use in lower, more favourable areas of the Alpine region. The long-term investigation of the Alpine landscape reveals that the transformation processes have accelerated in recent decades.

Modeling Distribution of Endemic Bartram’s Bass Micropterus sp. cf. coosae: Disturbance and Proximity to Invasion Source Increase Hybridization with Invasive Alabama Bass

Abstract“Bartram’s Bass” Micropterus sp. cf. coosae is endemic to the upper Savannah River basin of the southeastern United States and is threatened by hybridization with invasive Alabama Bass Micropterus henshalli. Bartram’s Bass have been functionally extirpated from reservoirs, and hybrid individuals have been detected in several tributaries. However, the extent of introgression in tributaries is currently unknown. Our objectives were to (1) assess the distribution of Bartram’s Bass, native Largemouth Bass M. salmoides, invasive Alabama Bass, and their hybrids in streams of the upper Savannah River basin and (2) quantify effects of abiotic variables on the distribution of each species. We sampled 154 locations in 2017 and 2018 and assigned genetic identity using hydrolysis probes and microsatellites. We␣used conditional inference trees to quantify variables affecting the occurrence of each species and hybrids. We observed widespread hybridization across the basin. Pure Bartram’s Bass were collected at 27% (42) of sites, among which only 12 sites contained pure Bartram’s Bass and no other congeners. Thirty sites where pure Bartram’s Bass were collected contained hybrids. In the montane Blue Ridge ecoregion, occurrence of pure Bartram’s Bass was negatively affected by low levels of local‐scale developed land cover. In the lower‐relief Piedmont ecoregion, pure Bartram’s Bass were positively associated with watershed‐scale forest land cover and stream gradient. Distance from a reservoir was positively associated with occurrence of pure Bartram’s Bass in both ecoregions. Pure Bartram’s Bass are likely to occur with high probability in only 16% of nonimpounded stream segments; this represents a conservative estimate, and the true number is likely lower. However, future work accounting for incomplete detection of Bartram’s Bass will help to improve confidence in true extirpations. Conservation efforts may be more successful if implemented on stream segments farther from reservoirs or upstream of dispersal barriers preventing colonization of Alabama Bass.

Factors behind the dynamics of land use evolution: case of Lebanon

sMonitoring and understanding the evolution of land use and land cover is a key factor for many environmental studies as well as for policymakers. Moreover, policymakers are interested in understanding the factors that have a significant impact on land use change. This paper analyses the dynamics of land use change in Lebanon between the years 1984 and 2019 and identifies the main factors behind this process. The use of LandSat satellite images enables the creation of land use maps at several periods and the monitoring of the evolution of built up areas as well as of green areas. Five periods emerge from this analysis, for which it is possible to propose explanatory factors, after an in-depth qualitative analysis. Within the framework of Structural Equation Models, a Confirmatory Factor Analysis is carried out to determine the impacts of several factors related to governance and financial data. Moreover, the urban sprawl is further investigated and explained by cultural, environmental, and infrastructural factors. The main results reveal that the development of built up areas is highly dependent on good funding conditions, whereas banking conditions and weak governance are correlated. The case of Lebanon presents specificities probably linked to historical and cultural considerations that deserve to be studied in future works. In the form of recommendations, new land use policies should be enacted to ensure sustainability in the form of an equilibrium between the urban development, from one side, and the preservation of natural resources and good environmental conditions on the other side. This could comprise the preservation of natural zones; the subsidization of the cultivation profession; and the encouragement of urban densification instead of horizontal sprawl.

Piecing together cities to support bird diversity: Development and forest edge density affect bird richness in urban environments

Urban areas are quickly expanding in the southeastern United States with varying effects on biodiversity. Maintaining bird richness in cities is essential for conserving ecosystem function. In this study, we determined the relative importance of landscape composition and configuration on urban avian richness in the southeastern U.S. We used linear models to explore the influence of the proportion, size, aggregation, and edge density of forests, wetlands, and developed land cover types on urban avian species richness and feeding guild diversity. We found that the proportion of developed land in a city, a composition metric, and forest edge density of cities, a configuration metric, had consistent negative effects on bird richness and feeding guild diversity. These results differ from previous studies that have found landscape configuration to have a minimal influence on bird richness. Urban revegetation should therefore focus on reducing expansion of developed land and reducing edge density of large forest patches.

Interrelated impacts of climate and land-use change on a widespread waterbird.

Together climate and land-use change play a crucial role in determining species distribution and abundance, but measuring the simultaneous impacts of these processes on current and future population trajectories is challenging due to time lags, interactive effects and data limitations. Most approaches that relate multiple global change drivers to population changes have been based on occurrence or count data alone. We leveraged three long-term (1995-2019) datasets to develop a coupled integrated population model-Bayesian population viability analysis (IPM-BPVA) to project future survival and reproductive success for common loons Gavia immer in northern Wisconsin, USA, by explicitly linking vital rates to changes in climate and land use. The winter North Atlantic Oscillation (NAO), a broad-scale climate index, immediately preceding the breeding season and annual changes in developed land cover within breeding areas both had strongly negative influences on adult survival. Local summer rainfall was negatively related to fecundity, though this relationship was mediated by a lagged interaction with the winter NAO, suggesting a compensatory population-level response to climate variability. We compared population viability under 12 future scenarios of annual land-use change, precipitation and NAO conditions. Under all scenarios, the loon population was expected to decline, yet the steepest declines were projected under positive NAO trends, as anticipated with ongoing climate change. Thus, loons breeding in the northern United States are likely to remain affected by climatic processes occurring thousands of miles away in the North Atlantic during the non-breeding period of the annual cycle. Our results reveal that climate and land-use changes are differentially contributing to loon population declines along the southern edge of their breeding range and will continue to do so despite natural compensatory responses. We also demonstrate that concurrent analysis of multiple data types facilitates deeper understanding of the ecological implications of anthropogenic-induced change occurring at multiple spatial scales. Our modelling approach can be used to project demographic responses of populations to varying environmental conditions while accounting for multiple sources of uncertainty, an increasingly pressing need in the face of unprecedented global change.

Use of molecular scatology to assess the diet of feral cats living in urban colonies

Abstract The overpopulation of domestic cats (Felis catus) presents a serious concern for wildlife conservationists, animal welfare advocates, public health officials, and community members alike. In cities, free-ranging, unowned cats often form high-density groups (commonly called ‘colonies’) around human provisioned food sources. While previous diet studies have primarily utilized morphology-based methods, molecular techniques offer a higher resolution alternative. In this study, we used next-generation sequencing techniques to examine the diet composition of feral cats living in five Trap-Neuter-Return colonies located in urban parks on Staten Island, a borough of New York City. We hypothesized that (1) cats living in urban colonies would still consume natural prey despite being regularly fed and (2) that the composition of taxa represented in the diet of each colony would vary, possibly due to differences in prey availability across sites. In total, 16 vertebrate prey taxa were identified in the diet, 13 at the genus level and 3 at the family level. Despite being regularly fed, 58.2% of cat scats contained DNA from natural prey. The diet composition of the cat colonies differed depending on the land cover composition surrounding the colony with the frequency of native prey positively correlated with the proportion of green space and that of non-native prey with developed land cover types. The use of molecular techniques combined with environmental DNA methods offers a promising, non-invasive approach to assessing the diet and consequently, impact of a highly abundant and non-native predator on the persistence of wildlife communities in cities.

Evaluating human–coyote encounters in an urban landscape using citizen science

AbstractCoyotes are ubiquitous in habitats across North America, including in urban areas. Reviews of human–coyote encounters are limited in scope and analysis and predominantly document encounters that tend to be negative, such as human–wildlife conflict, rather than benign experiences. The objective of our study was to use citizen science reports of human–coyote interactions entered into iNaturalist to better understand the range of first person accounts of human–coyote encounters in Madison, WI. We report 398 citizen science accounts of human–coyote encounters in the Madison area between October 2015 and March 2018. Most human–coyote encounters occurred during coyote breeding season and half of all encounters occurred in moderate development land cover. Estimated level of coyote aggressiveness varied significantly, with 90% of citizen scientists scoring estimated coyote aggression as a 0 and 7% scoring estimated aggression as a 1 on a 0–5 scale (with 0 being calm and 5 being aggressive). Our best performing model explaining the estimated distance between the human observer and a coyote (our proxy for a human–coyote encounter) included the variables distance to nearest paved road, biological season of the year relative to coyote life history, and time of day/night. We demonstrate that human–coyote interactions are regularly more benign than negative, with almost all first-hand reported human–coyote encounters being benign. We encourage public outreach focusing on practices that can foster benign encounters when educating the public to facilitate human–coyote coexistence.

Impacts of light detection and ranging (LiDAR) data organization and unit of analysis on land cover classification

ABSTRACT Airborne light detection and ranging (LiDAR) data have been used to generate land cover models for almost two decades. In this paper, three common processing decisions are assessed for their impact on the accuracy and configuration of the resultant land cover models. Using data acquired from a single-wavelength, discrete return system, this study compares six land cover models that investigate (i) the organization of data into tiles or flightstrips, (ii) the unit of analysis as either the individual LiDAR point or as a pixel in a rasterized model of the LiDAR data, and (iii) the use of either pixel- or object-based image analysis. Although the overall accuracies of the land cover models generated in this study are comparable, models disagree on up to 17% of the total study area. Class-specific metrics of recall and precision differ markedly between models, and the configuration of land covers are also affected. Models that employ pixel-based image analysis techniques tend to generate models with smaller, more dispersed patches of land cover. Data organization and choice of unit of analysis also influence the configuration of land cover, although effects differ depending on the land cover class. Comprehensive analyses of accuracy and precision are crucial to developing land cover models. This study demonstrates that it is also important to understand the potential influence of classification methodologies on the configuration of landscape features, especially when interpreting land cover models from an ecological or landscape genetic perspective.

Inter-annual monitoring of land use land cover changes with emphasis on forest reserves under a spatial planning perspective

Monitoring the inter-annual land cover evolution is considered of crucial importance at global level, since it may reveal significant changes across the Earth surface. Primary aim of the paper is to explore the spatiotemporal changes occurred in a highly touristic region which hosts a diversity of high-value natural resources (forests, coastal landscapes, croplands). To this end, a supervised land use image classification has been conducted for two years (2000, 2019) adopting the support vector machine algorithm. The outcomes of the classification have been verified by the overall accuracy (OA) index and kappa coefficient (KC). Both indices indicated high accuracy (over 80% and 0.8 respectively) of correct classification. Next, a matrix and a map of changes were developed to provide a quantitative and qualitative perspective of land use changes. The primary changes occurred were related to the transformation of forest to cropland and vice versa, followed by a mild urban expansion (especially for touristic premises).

Avanço antrópico na bacia hidrográfica do Rio Barigui entre 1999 e 2019 e seu impacto sobre o escoamento superficial avaliado pela alteração da sua curva-número (CN)

The monitoring of anthropic expansion in river basins from the assessment of land cover is very useful for water resources management, as in the case of the CN-SCS rainfall-runoff model, which uses the concept of curve number (CN) to estimate which the rainfall potential to become runoff based on the watershed’s soil and land cover. This research evaluated the evolution of land cover in the Barigui River basin between 1999 and 2019 and its impact on hydrological characteristics based on the variation of their CN. Therefore, Landsat images were classified for the study years and the hydrological types of soil in the basin were defined. The results indicated that there was a significant anthropic advance in the region, with an increase in urbanization (~21 km2) and a reduction in forested areas (~22 km2). However, this advance did not affect significantly the total CN value of the basin, due to the predominant, more impermeable type of soil, and how the changes in land cover occurred, with flooding of wetlands and the consequent increase in permeability in some regions.

Urban Landscape Heterogeneity Influences the Relationship between Tree Canopy and Land Surface Temperature

Urban trees play a key role in alleviating elevated summertime land surface temperatures in cities. However, urban landscape influences the capacity of urban trees to mitigate higher temperatures. We propose that both developed land characteristics and tree cover should be considered to accurately estimate the mitigation effects of canopy cover. We subclassified original land cover based on the canopy cover ratio to capture the within-land cover heterogeneity. We selected two coastal cities with different summertime climatic conditions: Seattle, Washington, USA, and Baltimore, Maryland, USA. We used Landsat-based grid cells (30 m × 30 m) as our spatial analytical unit, with corresponding land surface temperature, canopy area, canopy compactness, population size, and National Land Cover Database (NLCD)-based land cover group. We first used grouped boxplots, Kruskal–Wallis H tests, and post-hoc multiple comparison tests to detect the distribution of land surface temperatures by the land cover group. We then introduced statistical models to test the group effects on the relationship between land surface temperatures and canopy cover variables. We found: (1) land surface temperature increases with level of development, (2) land surface temperature decreases with canopy cover level, (3) the magnitude of the mitigation effects from canopy area differs based on development level and current canopy cover, (4) the differing efficacies of canopy area in decreasing land surface temperature follows a nonlinear threshold relationship, and (5) compactness of canopy cover was not significant in reducing the land surface temperature. These findings suggest the importance of considering heterogeneous canopy cover within developed land cover classes in urban heat island research. Tree planting strategies need to consider the nonlinear relationships between tree canopy cover and land surface temperature alongside environmental equity concerns.