Article asserts that urban tree canopies are a significant sink for atmospheric elemental carbon (EC)--and air pollutant that is a powerful climate-forcing agent and threat to human health. The authors' findings indicate that complex configurations of roads, buildings, and vegetation produce “urban edge trees” that contribute to heterogeneous EC deposition patterns across urban systems, with implications for greenspace planning.

This article is a review examining the effects of forest patches on bees and pollination services to determine how to increase pollination service in agricultural landscapes.

Article exploring the ecology of pollinating bees in urban gardens and farms.

Article presents a study (i) assessing and modeling soil erosion vulnerability based on the Analytic Hierarchy Process (AHP) approach in Hoffenthal and KwaMaye communities within the uThukela Catchment, South Africa; and (ii) identifying the relevant sustainable interventions and remedial strategies to combat soil erosion in the study area.

Article describes how the soil moisture daily diagnostic equation (SMDE) evaluates the relationship between the loss function coefficient and the summation of the weighted average of precipitation. The study has confirmed that using actual solar radiation data in the soil moisture daily diagnostic equation can improve its accuracy.

This article presents a study of urban expansion in the Beijing–Tianjin–Hebei plain based on ALOS Global Digital Surface Model “ALOS World 3D-30 m” (AW3D30 DSM), Shuttle Radar Topography Mission (SRTM) DSM, and Landsat 7 ETM+ images. The method proposed in this paper can provide rapid and large-scale statistics to study urban construction expansion in the world.

Data management plan for the grant, "Multi-Source Irrigation Status and Type Mapping." This grant will quantify the long-term irrigation status and system type changes in the Mississippi Alluvial Valley for an advanced understanding of irrigation-induced water resource changes by integrating multi-source earth observation data, machine learning techniques, artificial intelligence and cloud computing.

Data management plan for the grant, "Collaborative Research: MRA: Particulates in canopy flowpaths: A missing mass flux at the macrosystem scale?" This research will investigate a vital, but currently uncharacterized, macrosystem biogeochemical function within forest canopies at the very start of the terrestrial hydrologic cycle: particulate concentration, flux, and composition in rainwaters draining from forest canopies. We will address three major objectives: (1) Estimate the net rainfall (TF+ SF) water and particulate mass flux across forest types; (2) Characterize the particulate composition (C:N:P, including C components, like total C, organic C, black C, and microplastic C) of TF and SF; and (3) Identify major drivers of macrosystem variability in net rainfall particulate flux and composition.

Article describes how the low-cost sensor has changed the air quality monitoring paradigm with the capacity for efficient network expansion and community engagement. This study comprehensively assessed ten widely used data techniques, namely AdaBoost, Bayesian ridge, gradient tree boosting, K-nearest neighbors, Lasso, multivariable linear regression, neural network, random forest, ridge regression, and support vector machine.

Article discusses how China implemented the first phase of its National Healthy Cities pilot program from 2016-20. Authors recommend aligning the Healthy Cities initiative in China with strategic national and global level agendas such as Healthy China 2030 and the Sustainable Development Goals (SDGs) by providing an integrative governance framework to facilitate a coherent intersectoral program to systemically improve population health.

Article describes the efficient and accurate identification of canopy gaps is the basis of forest ecosystem research, which is of great significance to further forest monitoring and management. One major limitation of the traditional methods of remote sensing to map canopy gaps is that they cannot finely extract the complex edges of canopy gaps in mountainous areas. The authors proposed an object-oriented classification method that integrates multi-source information.