High-resolution population grids built from historical census data can ease the analyses of geographical population changes, at the same time also facilitating the combination of population data with other GIS layers to perform analyses on a wide ran...
Spatially explicit crop yield datasets with continuous long-term series are essential for understanding the spatiotemporal variation of crop yield and the impact of climate change on it. There are several spatial disaggregation methods to generate gr...
In this study, an improved method named spatial disaggregation and detrended bias correction (SDDBC) based on spatial disaggregation and bias correction (SDBC) combined with trend correction was proposed. Using data from meteorological stations over...
Estimation of latent heat flux at the agricultural field scale is required for proper water management. The current generation thermal sensors except Landsat-8 provide data on the order of 1000 m. The aim of this study is to test three approaches bas...
The objective of this study is to develop artificial neural network (ANN) models, including multilayer perceptron (MLP) and Kohonen self-organizing feature map (KSOFM), for spatial disaggregation of areal rainfall in the Wi-stream catchment, an Inte...
Global soil moisture (SM) products are currently available from passive microwave sensors at typically 40 km spatial resolution. Although recent efforts have been made to produce 1 km resolution data from the disaggregation of coarse scale observatio...
A high-resolution population distribution map is crucial for numerous applications such as urban planning, disaster management, public health, and resource allocation, and it plays a pivotal role in evaluating and making decisions to achieve the UN S...
Large-scale crop phenology monitoring is essential for agro-ecosystem policy. Remote sensing helps track crop development but requires high-temporal and spatial resolutions. While datasets with both attributes are now available, their large-scale app...
Urban areas contribute significant carbon emissions. Evaluating and analysing the spatial distribution of carbon emissions are the foundations of low-carbon city development and carbon emissions reduction. In this study, carbon emission inventory was...
In the last decade, technological advances led to the launch of two satellite missions dedicated to measure the Earth’s surface soil moisture (SSM): the ESA’s Soil Moisture and Ocean Salinity (SMOS) launched in 2009, and the NASA’s...
The consequences of climate change are arising in the form of many types of natural disasters, such as flooding, drought, and tropical cyclones. Responding to climate change is a long horizontal run action that requires adaptation and mitigation stra...
Recent years have witnessed growing interest in studying the spatial distribution of cultural and creative industries (CCI), both for their contribution to economic development and for their impact on spatial planning and remodeling of urban structur...
The resolution of current satellite surface soil moisture (SM) estimates is very low, of tens of kilometers, which proves to be insufficient for various agricultural and hydrological applications. Amongst the existing downscaling approaches of remote...
Predicting car ownership patterns at high spatial resolution is key to understanding pathways for decarbonisation—via electrification and demand reduction—of the private vehicle fleet. As the factors widely understood to influence car ownership are h...
Spatial accessibility provides significant policy implications, describing the spatial disparity of access and supporting the decision-making process for placing additional infrastructure at adequate locations. Several previous reviews have covered s...
15 May 2017
Technological innovation in transportation and the related industrial and entrepreneurial ecosystems can reduce urban environmental risks, maintaining urban environments. This study measures inter-county spillovers of the greenhouse gas (GHG) emissio...
Recent surveys have revealed substantial spatial variation in the micronutrient composition of cereals in Ethiopia, where a single national micronutrient concentration values for cereal grains are of limited use for estimating typical micronutrient i...
Ensuring the sustainable management of water and sanitation for all is the primary goal of Sustainable Development Goal 6 (SDG 6). SDG indicator 6.4.2 (level of water stress) is critical for monitoring the progress toward SDG 6. The assessment of the...
Datasets collecting demographic and socio-economic statistics are widely available. Still, the data are often only released for highly aggregated geospatial areas, which can mask important local hotspots. When conducting spatial analysis, one often n...
Data disaggregation (or downscaling) is becoming a recognized modeling framework to improve the spatial resolution of available surface soil moisture satellite products. However, depending on the quality of the scale change modeling and on the uncert...
Thermal data products derived from remotely sensed data play significant roles as key parameters for biophysical phenomena. However, a trade-off between spatial and spectral resolutions has existed in thermal infrared (TIR) remote sensing systems, wi...
A variety of hydrological models is currently available. Many of those employ physically based formulations to account for the complexity and spatial heterogeneity of natural processes. In turn, they require a substantial amount of spatial data, whic...
Owing to low temporal resolution and cloud interference, there is a shortage of high spatial resolution remote sensing data. To address this problem, this study introduces a modified spatial and temporal data fusion approach (MSTDFA) to generate dail...
This paper introduces a modified version of the DisPATCh (Disaggregation based on Physical And Theoretical scale Change) algorithm to disaggregate an SMAP surface soil moisture (SSM) product at a 20 m spatial resolution, through the use of sharpened...
Since 2011, Sargassum seaweed has spread widely outside the Sargasso Sea, causing massive strandings on the coasts of the West Indies and Mexico, causing serious economic, ecological, and health problems. This Atlantic pelagic alga has the characteri...
Through the use of open data portals, cities, districts and countries are increasingly making available energy consumption data. These data have the potential to inform both policymakers and local communities. At the same time, however, these dataset...
Flood risk assessment at the mesoscale requires data that are spatially and thematically detailed enough to provide reliable estimates at the catchment level. However, data availability and suitability are often contradictory: available data are rare...
In this paper we present and develop a new model, which we have calledDynamics of Land Systems (DLS). The DLS model is capable of integrating multiple datasources to simulate the dynamics of a land system. Three main modules are incorporatedin DLS: a...
This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of...
14 June 2024
Background: Social and Environmental Determinants of Health (SEDH) provide us with a conceptual framework to gain insights into possible associations among different human behaviors and the corresponding health outcomes that take place often in and a...
24 January 2026
This study examines the relationship between income and municipal waste generation within the Waste Kuznets Curve (WKC) framework, with a focus on selected disaggregated household waste fractions (paper and cardboard, glass, bulky waste, and biowaste...
6 September 2013
Background: Limited by data availability, most disease maps in the literature are for relatively large and subjectively-defined areal units, which are subject to problems associated with polygon maps. High resolution maps based on objective spatial u...
Temporally and spatially resolved data on wind power generation are very useful for studying the technical and economic aspects of this variable renewable energy at local and regional levels. Due to the lack of disaggregated electricity data from ons...
The determinants of cultural consumption are rarely explored by means of travel demand (i.e., travel cost) models. In this paper, the empirical results are presented in regard to the frequency of attendance to cultural events as an indicator of cultu...
This study proposes an evapotranspiration (ET) disaggregation model based on slope units. Different slope units are first delineated based on digital elevation model data with high spatial resolution. Key factors influencing ET variability across top...
Disaggregated data on electricity generation from bioenergy are very helpful for investigating the economic and technical effects of this form of renewable energy on the German power sector with a high temporal and spatial resolution. But the lack of...
Spatially and temporally resolved data on electricity production from run-of-river plants are very useful to study various aspects of this renewable energy at both the local and regional scale. In the absence of disaggregated feed-in data from such p...
We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA’s Gravity Recovery and Climate Experiment (GRACE). Assimilation...
Areal interpolation is routinely used when spatial data are unavailable at desired geographical units. While many methods are available, few of them were developed specifically for and tested in highly developed urban cores. Even fewer studied subpop...
In this paper, we analyze the labor productivity of “knowledge-intensive services” (KIS) located in the four larger metropolitan areas in Mexico. We discuss the accepted explanation to why big cities concentrate the best and most qualifie...
This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Ra...
Despite the importance of high-resolution population distribution in urban planning, disaster prevention and response, region economic development, and improvement of urban habitant environment, traditional urban investigations mainly focused on larg...
Current land surface temperature (LST) products, estimated by sensors on board satellites, show a trade-off between their spatial and temporal resolution. If the spatial resolution is high (i.e., around 100 m), the LST product is delivered every 2 we...
To meet the demand of regional hydrological and agricultural applications, a new method named near infrared-red (NIR-red) spectra-based disaggregation (NRSD) was proposed to perform a disaggregation of Soil Moisture Active Passive (SMAP) products fro...
In this study, we deal with the application of multiangular data from the Multiangle Imaging Spectroradiometer (MISR) sensor for studying the effect of surface anisotropy and directional information on the classification accuracy for different land c...
The trade-off between spatial and temporal resolutions has led to the disaggregation of remotely sensed land surface temperatures (LSTs) for better applications. The window used for regression is one of the primary factors affecting the disaggregatio...
Geographically fine-grained population information is critical for various urban planning and management tasks. This is especially the case for the Chinese cities that are undergoing rapid development and transformation. However, detailed population...
The current study spatially examines the local variability of robbery rates in the City of Saint Louis, Missouri using both census tract and block group data disaggregated and standardized to the 250- and 500-m raster grid spatial scale. The Spatial...
18 March 2021
The concept of neighborhood contagion focus is defined and justified as a basic spatial unit for epidemiological diagnosis and action, and a specific methodological procedure is provided to detect and map focuses and micro-focuses of contagion withou...
A wide range of disciplines require population data with high spatial resolution. In particular, accessibility instruments for active mobility need data on the building access level. Data availability varies by context. Spatially detailed national ce...
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