Prof. Dr. Tobia Lakes

Profil

• Agricultural Land Markets - Efficiency and Regulation" Teilprojekt SP7 "Quantifizierung der Konzentration an Bodeneigentum und von Zielkonflikten in der Landwirtschaft"

  Quelle ↗

  Förderer: DFG Forschungsgruppe Zeitraum: 03/2021 - 07/2024 Projektleitung: Prof. Dr. Tobia Lakes

• AvH Perez Klimaschutzstipendium

  Quelle ↗

  Förderer: Alexander von Humboldt-Stiftung Zeitraum: 09/2012 - 12/2014 Projektleitung: Prof. Dr. Tobia Lakes

• Building Excellence in Research of Human-Environmental Systems With Geospatial and Earth Observation Technologies (HES-GEO)

  Quelle ↗

  Förderer: Horizon 2020: Coordination and Support Action (CSA) Zeitraum: 01/2021 - 12/2023 Projektleitung: Prof. Dr. Dagmar Haase, Prof. Dr. Tobia Lakes, Prof. Dr. Tobias Kümmerle

• Carbon sequestration, biodiversity and social structures in Southern Amazonia: models and implementation of carbon-optimized land management strategies

  Quelle ↗

  Förderer: Bundesministerium für Wirtschaft und Energie Zeitraum: 06/2011 - 08/2016 Projektleitung: Prof. Dr. Tobia Lakes

• Einfluss des Klimawandels und sozioökonomischer Faktoren auf das Dengue-Vorkommen in Sri Lanka

  Quelle ↗

  Förderer: Alexander von Humboldt-Stiftung Zeitraum: 04/2012 - 12/2014 Projektleitung: Prof. Dr. Tobia Lakes

• Ein räumlich expliziter Ansatz der zellulären Agentenmodellierung basierend auf der Spieltheorie zur Modellierung von Gruppenentscheidungsprozessen in der urbanen Flächennutzungsplanung

  Quelle ↗

  Förderer: DFG sonstige Programme Zeitraum: 03/2020 - 03/2022 Projektleitung: Prof. Dr. Tobia Lakes

• EX: Crimelab Gründerstipendium

  Quelle ↗

  Förderer: Bundesministerium für Wirtschaft und Energie Zeitraum: 08/2011 - 07/2012 Projektleitung: Prof. Dr. Tobia Lakes

• FG 1736/1: Urban Climate and Heat Stress in mid-latitude cities in view of climate change (TP 06)

  Quelle ↗

  Förderer: DFG Forschungsgruppe Zeitraum: 11/2012 - 06/2016 Projektleitung: Prof. Dr. Tobia Lakes

• FOR 2569/1: Agricultural Land Markets – Efficiency and Regulation (TP 07)

  Quelle ↗

  Förderer: DFG Forschungsgruppe Zeitraum: 10/2017 - 01/2021 Projektleitung: Prof. Dr. Tobia Lakes

• GeoLand - Geosciences Go Rural - Geowissenschaftliche Landpartie

  Quelle ↗

  Förderer: Bundesministerium für Forschung, Technologie und Raumfahrt Zeitraum: 02/2022 - 12/2022 Projektleitung: Prof. Dr. Tobia Lakes

• Georg Forster Forschungsstipendium - Forschungskostenzuschuss

  Quelle ↗

  Förderer: Alexander von Humboldt-Stiftung: Forschungskostenzuschuss Zeitraum: 11/2020 - 02/2023 Projektleitung: Prof. Dr. Tobia Lakes

• Geo.X Olabisi Badmos: Developing an agent-based model to predict shrinkage and expansion of slums in Lagos megacity

  Quelle ↗

  Förderer: Helmholtz-Gemeinschaft Zeitraum: 09/2019 - 08/2021 Projektleitung: Prof. Dr. Tobia Lakes

• KliBUp - Klimagesundheit in Lebenswelten - Entwicklung von Strategien und Handlungsansätzen zur Förderung von Resilienz durch Bottom-Up-Ansätze - Teilprojekt Urban Health_räumliche Analyse

  Quelle ↗

  Förderer: Bundesministerium für Forschung, Technologie und Raumfahrt Zeitraum: 02/2025 - 01/2028 Projektleitung: Prof. Dr. Tobia Lakes

• Kohlenstoffspeicherung, Biodiveristät und Sozialstrukturen im südlichen Amazonien: Modellierung und Implementierung eines Kohlenstoff-optimierten Landmanagements

  Quelle ↗

  Förderer: Bundesministerium für Forschung, Technologie und Raumfahrt Zeitraum: 06/2011 - 08/2016 Projektleitung: Prof. Dr. Patrick Hostert, Prof. Dr. Tobia Lakes

• Superdiversität und alternde Städte? Die Konvergenz von wachsender Multiethnizität und einer alternden Bevölkerung

  Quelle ↗

  Förderer: DFG Sachbeihilfe Zeitraum: 02/2017 - 02/2021 Projektleitung: Prof. Dr. Ilse Helbrecht, Prof. Dr. Dagmar Haase, Prof. Dr. Tobia Lakes

• Superdiversität und alternde Städte? Die Konvergenz von wachsender Multiethnizität und einer alternden Bevölkerung.

  Quelle ↗

  Förderer: DFG Sachbeihilfe Zeitraum: 03/2017 - 02/2020 Projektleitung: Prof. Dr. Tobia Lakes, Prof. Dr. Ilse Helbrecht, Prof. Dr. Dagmar Haase

• Superdiversität und alternde Städte? Die Konvergenz von wachsender Multiethnizität und einer alternden Bevölkerung.

  Quelle ↗

  Förderer: DFG Sachbeihilfe Zeitraum: 03/2017 - 02/2020 Projektleitung: Prof. Dr. Dagmar Haase, Prof. Dr. Tobia Lakes, Prof. Dr. Ilse Helbrecht

• Vorbereitungsmodul für ein Einstein Center Climate Change

  Quelle ↗

  Förderer: Einstein Zentrum Zeitraum: 01/2025 - 12/2025 Projektleitung: Prof. Dr. Tobia Lakes

• Mistra Urban Futures

  P

  14 Treffer67.3%
  • Urbane Biodiversität und Ökosystemdienstleistungen
    P

    67.3%

• Schul-Umwelt-Zentrum Berlin Mitte

  PT

  39 Treffer66.8%
  • Gamification for Climate Action
    P

    66.8%

• Grünlandzentrum Niedersachsen/Bremen

  PT

  23 Treffer60.0%
  • GreenGrass – Innovative Nutzung des Grünlands für eine nachhaltige Intensivierung der Landwirtschaft im Landschaftsmaßstab
    P

    60.0%

• Horizont group GmbH

  PT

  30 Treffer59.8%
  • GreenGrass 2: Innovative Nutzung des Grünlands für eine nachhaltige Intensivierung der Landwirtschaft im Landschaftsmaßstab
    P

    59.8%

• Texas Trading GmbH

  PT

  30 Treffer59.8%
  • GreenGrass 2: Innovative Nutzung des Grünlands für eine nachhaltige Intensivierung der Landwirtschaft im Landschaftsmaßstab
    P

    59.8%

• Science & Startups Berlin

  PT

  25 Treffer59.7%
  • Zuwendung im Rahmen des Programms „exist – Existenzgründungen aus der Wissenschaft“ aus dem Bundeshaushalt, Einzelplan 09, Kapitel 02, Titel 68607, Haushaltsjahr 2026, sowie aus Mitteln des Europäischen Strukturfonds (hier Euro-päischer Sozialfonds Plus – ESF Plus) Förderperiode 2021-2027 – Kofinanzierung für das Vorhaben: „exist Women“
    T

    59.7%

• RISC Software GmbH

  P

  12 Treffer58.3%
  • EU: Scattering Amplitudes: From Geometry to EXperiment (SAGEX)
    P

    58.3%

• Versuchszentrum Laimburg

  PT

  33 Treffer58.1%
  • Grasslands for biodiversity: supporting the protection of the biodiversity-rich grasslands and related management practices in the Alps and Carpathians
    P

    58.1%

• National Museum of the Romanian Peasant

  PT

  33 Treffer58.1%
  • Grasslands for biodiversity: supporting the protection of the biodiversity-rich grasslands and related management practices in the Alps and Carpathians
    P

    58.1%

• Centrum biológie rastlín a biodiverzity SAV, v. v. i.

  PT

  33 Treffer58.1%
  • Grasslands for biodiversity: supporting the protection of the biodiversity-rich grasslands and related management practices in the Alps and Carpathians
    P

    58.1%

• Machine learning data-driven approaches for land use/cover mapping and trend analysis using Google Earth Engine

  2021

  Journal of Environmental Planning and Management · 186 Zitationen · DOI

  With the recent advances in earth observation technologies, the increasing availability of data from more and more different satellite sensors as well as progress in semi-automated and automated classification techniques enable the (semi-) automated remote monitoring and analysis of large areas. Online platforms such as Google Earth Engine (GEE) bring data-driven techniques to the desktops of researchers while changing workflows and making excessive data downloads redundant. We present a study that utilizes machine learning algorithms on the GEE cloud computing platform for land use/land cover (LULC) mapping and change detection analysis using a Landsat satellite image time series. We applied different machine learning techniques to data from an environmentally sensitive area in Northern Iran. We tested their efficiency for LULC mapping and change detection analysis using the support vector machine (SVM), random forest (RF) and classification and regression tree (CART). We obtained LULC maps for the years 2000, 2005, 2010, 2015 and 2020. Training data was collected from field operations and historical datasets, and the respective LULC maps were validated using ground control points. In addition, we validated the reliability of the results through a spatial uncertainty analysis using Dempster-Shafer Theory (DST). The resulting accuracies of the classification outcomes varied significantly. SVM performed best with accuracies of 90.25%, 91.84%, 89.02%, 93.35% and 95.65% for 2000, 2005, 2010, 2015 and 2020, respectively. The spatial uncertainty analysis also validated the efficiency of SVM compared to RF and CART. The results confirm the potential of machine learning techniques for time series LULC mapping on the GEE platform while lowering the barriers to analyzing large amounts of satellite data. The results are also critical for decision-makers and authorities for analyzing the LULC changes and developing the respective environmental protection and polices in Northern Iran.

• Restoration in Urban Spaces

  2015

  Environment and Behavior · 184 Zitationen · DOI

  Despite promising experimental findings, few studies have addressed the potential long-term health benefits of frequent contact with different kinds of urban nature. We examine the cross-sectional relations between two kinds of urban nature (neighborhood vegetation visible from the home, use of public green spaces) and health outcomes (life satisfaction, perceived general health, 2-months hair cortisol levels) in a sample population from Berlin ( N = 32) using a mixed-method approach. Participants whose homes had views of high amounts of diverse kinds of vegetation had significantly lower cortisol levels. Moreover, participants who regularly used a vegetated trail along a canal had significantly lower cortisol levels and reported significantly higher life satisfaction than less frequent users. In addition, vegetated routes or paths played an important role in the restorative activities and daily commutes of participants. We discuss directions for future research and recommend more consideration of greenways in urban development.

• Assessing Weather Effects on Dengue Disease in Malaysia

  2013

  International Journal of Environmental Research and Public Health · 184 Zitationen · DOI

  The number of dengue cases has been increasing on a global level in recent years, and particularly so in Malaysia, yet little is known about the effects of weather for identifying the short-term risk of dengue for the population. The aim of this paper is to estimate the weather effects on dengue disease accounting for non-linear temporal effects in Selangor, Kuala Lumpur and Putrajaya, Malaysia, from 2008 to 2010. We selected the weather parameters with a Poisson generalized additive model, and then assessed the effects of minimum temperature, bi-weekly accumulated rainfall and wind speed on dengue cases using a distributed non-linear lag model while adjusting for trend, day-of-week and week of the year. We found that the relative risk of dengue cases is positively associated with increased minimum temperature at a cumulative percentage change of 11.92% (95% CI: 4.41-32.19), from 25.4 °C to 26.5 °C, with the highest effect delayed by 51 days. Increasing bi-weekly accumulated rainfall had a positively strong effect on dengue cases at a cumulative percentage change of 21.45% (95% CI: 8.96, 51.37), from 215 mm to 302 mm, with the highest effect delayed by 26-28 days. The wind speed is negatively associated with dengue cases. The estimated lagged effects can be adapted in the dengue early warning system to assist in vector control and prevention plan.

• Assessment of land use factors associated with dengue cases in Malaysia using Boosted Regression Trees

  2014

  Spatial and Spatio-temporal Epidemiology · 150 Zitationen · DOI

  The transmission of dengue disease is influenced by complex interactions among vector, host and virus. Land use such as water bodies or certain agricultural practices have been identified as likely risk factors for dengue because of the provision of suitable habitats for the vector. Many studies have focused on the land use factors of dengue vector abundance in small areas but have not yet studied the relationship between land use factors and dengue cases for large regions. This study aims to clarify if land use factors other than human settlements, e.g. different types of agricultural land use, water bodies and forest are associated with reported dengue cases from 2008 to 2010 in the state of Selangor, Malaysia. From the correlative relationship, we aim to generate a prediction risk map. We used Boosted Regression Trees (BRT) to account for nonlinearities and interactions between the factors with high predictive accuracies. Our model with a cross-validated performance score (Area Under the Receiver Operator Characteristic Curve, ROC AUC) of 0.81 showed that the most important land use factors are human settlements (model importance of 39.2%), followed by water bodies (16.1%), mixed horticulture (8.7%), open land (7.5%) and neglected grassland (6.7%). A risk map after 100 model runs with a cross-validated ROC AUC mean of 0.81 (±0.001 s.d.) is presented. Our findings may be an important asset for improving surveillance and control interventions for dengue.

• Land‐use change and land degradation on the Mongolian Plateau from 1975 to 2015—A case study from Xilingol, China

  2018

  Land Degradation and Development · 147 Zitationen · DOI

  Abstract Land degradation is a severe environmental problem on a regional and global scale that is often aggravated by intensive land‐use and climate change. The arid to semi‐arid Xilingol in Inner Mongolia, China, is an example of an area that has witnessed continuous land degradation for decades, in spite of numerous attempts to reverse this trend. In this study, land‐use and land‐cover change (LUCC) between 1975 and 2015 was investigated for Xilingol based on multi‐temporal remote sensing images. The aim of the study was to derive detailed information on LUCC over space and time as a basis for assessing ecological and social consequences of land degradation in a bid to develop better strategies for combating land degradation. Two main LUCC processes and two distinct phases were identified: During Phase 1 (1975–2000), the LUCC pattern was dominated by land degradation, affecting 11.4% (22,937 km 2 ) of the total area. During Phase 2 (2000–2015), land restoration increased (12.0% or 24,161 km 2 ) whereas degradation continued, resulting in a further 9.5% (19,124 km 2 ) of degraded land. The transition pattern changed accordingly. Our findings show that, in spite of notable restoration successes in the past, grassland degradation continues to be the main ecological and environmental problem in Xilingol, requiring the continued attention of decision‐makers. Strategic land‐use management has already had a significant influence on LUCC in this area, leading to the expectation that science‐based land‐use strategies can be developed to further reduce land degradation in Xilingol.

• Unsupervised change detection in VHR remote sensing imagery – an object-based clustering approach in a dynamic urban environment

  2016

  International Journal of Applied Earth Observation and Geoinformation · 143 Zitationen · DOI

• Estimation of seismic building structural types using multi-sensor remote sensing and machine learning techniques

  2014

  ISPRS Journal of Photogrammetry and Remote Sensing · 124 Zitationen · DOI

• Policy change, land use, and agriculture: The case of soy production and cattle ranching in Brazil, 2001–2012

  2014

  Applied Geography · 119 Zitationen · DOI

  The Brazilian Amazon has experienced one of the world's highest deforestation rates in the last decades. Cattle ranching and soy expansion constitute the major drivers of deforestation, both through direct conversion and indirectly by land use displacement. However, deforestation rates decreased significantly after the implementation of the action plan to prevent and control deforestation in 2004. The aim of this study is to quantify the contribution of cattle and soy production with deforestation before and after the implementation of the action plan in the two states Mato Grosso and Pará along the BR-163. Specifically, we aim to empirically test for land use displacement processes from soy expansion in Mato Grosso to the deforestation frontier between 2001 and 2012. First, we calculated the relationships between deforestation rate and the change in cattle head and planted soy area respectively for the BR-163 region. Second, we estimated different panel regression models to test the association between processes of land use displacement. Our results indicate a close linkage between cattle ranching and deforestation along the BR-163 between 2001 and 2004. Soy expansion in Mato Grosso was significantly associated with deforestation during this period. However, these relations have diminished after the implementation of the action plan to control and prevent deforestation. With the decrease in deforestation rates in 2005, cattle ranching and deforestation were not directly linked, nor was soy expansion in Mato Grosso and deforestation at the forest frontier. Our analysis hence suggests that there was a close coupling of processes and spatial displacement until 2004 and a decoupling has taken place following the political interventions. These findings improve the understanding of land use displacement processes in Brazil and the methods offer potential for exploring similar processes in different regions of the world.

• Monitoring and forecasting heat island intensity through multi-temporal image analysis and cellular automata-Markov chain modelling: A case of Babol city, Iran

  2018

  Ecological Indicators · 117 Zitationen · DOI

• Property-level direct and indirect deforestation for soybean production in the Amazon region of Mato Grosso, Brazil

  2018

  Land Use Policy · 112 Zitationen · DOI

  Brazil’s Soy Moratorium solidified the world’s largest traders’ commitment to stop soybean purchases from production areas deforested after July 2006. The aim was to remove deforestation from the soybean supply-chain and halt one of the main drivers of forest loss in the Amazon biome. In this study, we investigated changes in deforestation at the property-level for the period 2004 to 2014. The objective was to examine direct and indirect deforestation, defined as on-property displacement and cross-parcel displacement deforestation for soybean expansion in the Amazon region of Mato Grosso, the leading soy-producing state of the Brazilian Amazon. We used publicly available property and land use data to quantify deforestation associated with cropland expansion. Similar to previous studies, we found that direct deforestation for soybean expansion declined following the implementation of the Soy Moratorium. Moreover, our analysis suggest that indirect deforestation occurred already before the implementation of the Soy Moratorium, and decreased following the first period of analyses. However, slight increases of indirect deforestation in the more recent periods, combined with decreasing direct deforestations rendered indirect deforestation to be responsible for more than half of the deforestation associated with soybean expansion. While we acknowledge the overall reduction of deforestation for soybean, our results suggest, given the increasing trends of deforestation in the Brazilian Amazon since 2013, to address indirect deforestation within the Soy Moratorium. This may be achieved by zero-property-deforestation commitments and by strengthening the integration between supply-chain actors, the soybean and beef purchasing companies and the federal policies aiming to control deforestation.

• Multiple environmental burdens and neighborhood-related health of city residents

  2012

  Journal of Environmental Psychology · 112 Zitationen · DOI

• Using Shapley additive explanations to interpret extreme gradient boosting predictions of grassland degradation in Xilingol, China

  2021

  Geoscientific model development · 110 Zitationen · DOI

  Abstract. Machine learning (ML) and data-driven approaches are increasingly used in many research areas. Extreme gradient boosting (XGBoost) is a tree boosting method that has evolved into a state-of-the-art approach for many ML challenges. However, it has rarely been used in simulations of land use change so far. Xilingol, a typical region for research on serious grassland degradation and its drivers, was selected as a case study to test whether XGBoost can provide alternative insights that conventional land-use models are unable to generate. A set of 20 drivers was analysed using XGBoost, involving four alternative sampling strategies, and SHAP (Shapley additive explanations) to interpret the results of the purely data-driven approach. The results indicated that, with three of the sampling strategies (over-balanced, balanced, and imbalanced), XGBoost achieved similar and robust simulation results. SHAP values were useful for analysing the complex relationship between the different drivers of grassland degradation. Four drivers accounted for 99 % of the grassland degradation dynamics in Xilingol. These four drivers were spatially allocated, and a risk map of further degradation was produced. The limitations of using XGBoost to predict future land-use change are discussed.

• Development of an environmental justice index to determine socio-economic disparities of noise pollution and green space in residential areas in Berlin

  2013

  Journal of Environmental Planning and Management · 109 Zitationen · DOI

  The majority of human beings worldwide live in urban areas; hence, methods to assess the quality of the urban environment and its impact on human well-being are of the utmost importance. Particularly relevant are areas with low levels of environmental justice, defined as areas where low biophysical quality meets low socio-economic status, and where resources and strategies for coping are rare. This paper develops and applies an index to assess the patterns of environmental justice in residential areas with a strong focus on stakeholder integration. We concentrate on the relationship between socio-economic disparities of environmental burdens, such as traffic noise, and of environmental benefits, such as vegetation, in residential areas of Berlin, Germany. To develop an environmental justice index, we combined the environmental burdens and benefits with a socio-economic indicator. As a result, we identify city-wide patterns of environmental justice in Berlin. While there was a high positive correlation between vegetation and socio-economic status, the patterns for noise pollution were very heterogeneous. Our approach provides a transparent and modular index allowing an area-wide monitoring of environmental justice in urban areas. Such an analysis is urgently needed to develop adequate decision-making strategies for all inhabitants to make living in a healthier city possible.

• Identifying drivers of land degradation in Xilingol, China, between 1975 and 2015

  2019

  Land Use Policy · 100 Zitationen · DOI

  Land degradation occurs in all kinds of landscapes over the world, but the drivers of land degradation vary from region to region. Identifying these drivers at the appropriate spatial scale is an essential prerequisite for developing and implementing appropriate area-specific policies. In this study, we investigate nine different driving factors in three categories: human disturbance, water condition, and urbanisation. Using partial order theory and the Hasse diagram technique, we analyse the temporal and spatial dynamics of these drivers and identify the major drivers of land degradation at the county level in the Xilingol League, China. Our findings indicate that: (i) in eight out of the region’s 12 counties, human disturbance was the dominant driver responsible for land degradation up to 2000, followed by water conditions, while urbanisation was the dominant driver in only four counties; (ii) the effects resulting from human disturbance and water availability decreased after 2000, while urbanisation became the dominant driver for land degradation in seven counties. The influence of human disturbance in this region has decreased, which suggests that ecological protection policies that were designed to control population and livestock numbers have worked as intended for this region. However, land degradation has continued and new policy measures are required to ease the effect of urbanisation.

• An automated deep learning convolutional neural network algorithm applied for soil salinity distribution mapping in Lake Urmia, Iran

  2021

  The Science of The Total Environment · 88 Zitationen · DOI

• A deep learning convolutional neural network algorithm for detecting saline flow sources and mapping the environmental impacts of the Urmia Lake drought in Iran

  2021

  CATENA · 81 Zitationen · DOI

• The urban environmental indicator “Biotope Area Ratio”—An enhanced approach to assess and manage the urban ecosystem services using high resolution remote-sensing

  2011

  Ecological Indicators · 81 Zitationen · DOI

• Cropland change in southern Romania: a comparison of logistic regressions and artificial neural networks

  2009

  Landscape Ecology · 77 Zitationen · DOI

• Quantification of heat-stress related mortality hazard, vulnerability and risk in Berlin, Germany

  2013

  SHILAP Revista de lepidopterología · 74 Zitationen · DOI

  Many studies have addressed the challenge of heat stress for human health in recent years. However, appropriate concepts and methods for quantifying heat-stress hazards, vulnerabilities and risks are yet under development. The objective of this study is to test the applicability of a risk concept and associated event-based risk-analysis method for quantifying heat-stress related mortality. The study reveals that about 5 % of all deaths between 2001 and 2010 in Ber­lin can statistically be related to elevated air temperatures. Most of the affected people are 65 years or older, while the mortality of people below 65 years shows only weak statistical correlation to air temperature. Mean daily air tempera­ture was best suitable for risk analysis. The results demonstrate that the novel approach for quantitative risk analysis delivers statistically highly significant results on the city scale when analysing heat stress on an event basis. Performing the risk analysis on a spatially distributed data basis for city districts would allow to account for spatial variations of ur­ban climates and demographic properties. Using indoor climate data is expected to provide new insight into heat-stress related mortality risks, particularly for highly vulnerable persons like elderly persons or patients residing in hospitals.

• Scenario-based analysis of the impacts of lake drying on food production in the Lake Urmia Basin of Northern Iran

  2022

  Scientific Reports · 64 Zitationen · DOI

  In many parts of the world, lake drying is caused by water management failures, while the phenomenon is exacerbated by climate change. Lake Urmia in Northern Iran is drying up at such an alarming rate that it is considered to be a dying lake, which has dire consequences for the whole region. While salinization caused by a dying lake is well understood and known to influence the local and regional food production, other potential impacts by dying lakes are as yet unknown. The food production in the Urmia region is predominantly regional and relies on local water sources. To explore the current and projected impacts of the dying lake on food production, we investigated changes in the climatic conditions, land use, and land degradation for the period 1990-2020. We examined the environmental impacts of lake drought on food production using an integrated scenario-based geoinformation framework. The results show that the lake drought has significantly affected and reduced food production over the past three decades. Based on a combination of cellular automaton and Markov modeling, we project the food production for the next 30 years and predict it will reduce further. The results of this study emphasize the critical environmental impacts of the Urmia Lake drought on food production in the region. We hope that the results will encourage authorities and environmental planners to counteract these issues and take steps to support food production. As our proposed integrated geoinformation approach considers both the extensive impacts of global climate change and the factors associated with dying lakes, we consider it to be suitable to investigate the relationships between environmental degradation and scenario-based food production in other regions with dying lakes around the world.

• Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014

  2016

  BMC Public Health · 64 Zitationen · DOI

  This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

• A scenario-based approach for urban water management in the context of the COVID-19 pandemic and a case study for the Tabriz metropolitan area, Iran

  2021

  The Science of The Total Environment · 63 Zitationen · DOI

• An efficient GIS-based approach for sustainability assessment of urban drinking water consumption patterns: A study in Tabriz city, Iran

  2020

  Sustainable Cities and Society · 63 Zitationen · DOI

• Aerial and surface rivers: downwind impacts on water availability from land use changes in Amazonia

  2018

  Hydrology and earth system sciences · 62 Zitationen · DOI

  Abstract. The abundant evapotranspiration provided by the Amazon forests is an important component of the hydrological cycle, both regionally and globally. Since the last century, deforestation and expanding agricultural activities have been changing the ecosystem and its provision of moisture to the atmosphere. However, it remains uncertain how the ongoing land use change will influence rainfall, runoff, and water availability as findings from previous studies differ. Using moisture tracking experiments based on observational data, we provide a spatially detailed analysis recognizing potential teleconnection between source and sink regions of atmospheric moisture. We apply land use scenarios in upwind moisture sources and quantify the corresponding rainfall and runoff changes in downwind moisture sinks. We find spatially varying responses of water regimes to land use changes, which may explain the diverse results from previous studies. Parts of the Peruvian Amazon and western Bolivia are identified as the sink areas most sensitive to land use change in the Amazon and we highlight the current water stress by Amazonian land use change on these areas in terms of the water availability. Furthermore, we also identify the influential source areas where land use change may considerably reduce a given target sink's water reception (from our example of the Ucayali River basin outlet, rainfall by 5–12 % and runoff by 19–50 % according to scenarios). Sensitive sinks and influential sources are therefore suggested as hotspots for achieving sustainable land–water management.

• Urban heat stress: novel survey suggests health and fitness as future avenue for research and adaptation strategies

  2017

  Environmental Research Letters · 62 Zitationen · DOI

  Extreme heat has tremendous adverse effects on human health. Heat stress is expected to further increase due to urbanization, an aging population, and global warming. Previous research has identified correlations between extreme heat and mortality. However, the underlying physical, behavioral, environmental, and social risk factors remain largely unknown and comprehensive quantitative investigation on an individual level is lacking. We conducted a new cross-sectional household questionnaire survey to analyze individual heat impairment (self-assessed and reported symptoms) and a large set of potential risk factors in the city of Berlin, Germany. This unique dataset (n = 474) allows for the investigation of new relationships, especially between health/fitness and urban heat stress. Our analysis found previously undocumented associations, leading us to generate new hypotheses for future research: various health/fitness variables returned the strongest associations with individual heat stress. Our primary hypothesis is that age, the most commonly used risk factor, is outperformed by health/fitness as a dominant risk factor. Related variables seem to more accurately represent humans' cardiovascular capacity to handle elevated temperature. Among them, active travel was associated with reduced heat stress. We observed statistical associations for heat exposure regarding the individual living space but not for the neighborhood environment. Heat stress research should further investigate individual risk factors of heat stress using quantitative methodologies. It should focus more on health and fitness and systematically explore their role in adaptation strategies. The potential of health and fitness to reduce urban heat stress risk means that encouraging active travel could be an effective adaptation strategy. Through reduced CO2 emissions from urban transport, societies could reap double rewards by addressing two root causes of urban heat stress: population health and global warming.

• Alice Salomon Hochschule Berlin

  KliBUp - Klimagesundheit in Lebenswelten - Entwicklung von Strategien und Handlungsansätzen zur Förderung von Resilienz durch Bottom-Up-Ansätze - Teilprojekt Urban Health_räumliche Analyse

  other

• Charité – Universitätsmedizin Berlin

  KliBUp - Klimagesundheit in Lebenswelten - Entwicklung von Strategien und Handlungsansätzen zur Förderung von Resilienz durch Bottom-Up-Ansätze - Teilprojekt Urban Health_räumliche Analyse

  university

• Freie Universität Berlin

  Vorbereitungsmodul für ein Einstein Center Climate Change

  university

• Georg-August-Universität Göttingen

  Agricultural Land Markets - Efficiency and Regulation" Teilprojekt SP7 "Quantifizierung der Konzentration an Bodeneigentum und von Zielkonflikten in der Landwirtschaft"

  university

• Hochschule Esslingen

  KliBUp - Klimagesundheit in Lebenswelten - Entwicklung von Strategien und Handlungsansätzen zur Förderung von Resilienz durch Bottom-Up-Ansätze - Teilprojekt Urban Health_räumliche Analyse

  other

• Hochschule Magdeburg-Stendal

  KliBUp - Klimagesundheit in Lebenswelten - Entwicklung von Strategien und Handlungsansätzen zur Förderung von Resilienz durch Bottom-Up-Ansätze - Teilprojekt Urban Health_räumliche Analyse

  other

• K.N. Toosi University of Technology Tehran

  Ein räumlich expliziter Ansatz der zellulären Agentenmodellierung basierend auf der Spieltheorie zur Modellierung von Gruppenentscheidungsprozessen in der urbanen Flächennutzungsplanung

  university

• Leibniz-Institut für Agrarentwicklung in Transformationsökonomien

  Agricultural Land Markets - Efficiency and Regulation" Teilprojekt SP7 "Quantifizierung der Konzentration an Bodeneigentum und von Zielkonflikten in der Landwirtschaft"

  other

• Potsdam-Institut für Klimafolgenforschung e.V.

  FG 1736/1: Urban Climate and Heat Stress in mid-latitude cities in view of climate change (TP 06)

  other

• Rheinische Friedrich-Wilhelms-Universität Bonn

  Agricultural Land Markets - Efficiency and Regulation" Teilprojekt SP7 "Quantifizierung der Konzentration an Bodeneigentum und von Zielkonflikten in der Landwirtschaft"

  university

• Technische Universität Berlin

  Vorbereitungsmodul für ein Einstein Center Climate Change

  university

• Universität der Künste Berlin

  Vorbereitungsmodul für ein Einstein Center Climate Change

  university

• Universität für Bodenkultur Wien

  Agricultural Land Markets - Efficiency and Regulation" Teilprojekt SP7 "Quantifizierung der Konzentration an Bodeneigentum und von Zielkonflikten in der Landwirtschaft"

  university

• Universitätsklinikum Essen

  KliBUp - Klimagesundheit in Lebenswelten - Entwicklung von Strategien und Handlungsansätzen zur Förderung von Resilienz durch Bottom-Up-Ansätze - Teilprojekt Urban Health_räumliche Analyse

  other

Name

Prof. Dr. Tobia Lakes

Titel

Prof. Dr.

Fakultät

Mathematisch-Naturwissenschaftliche Fakultät

Institut

Geographisches Institut

Arbeitsgruppe

Angewandte Geoinformationsverarbeitung

Telefon

+49 30 2093-6873

HU-FIS-Profil

Quelle ↗

Zuletzt gescrapt

26.4.2026, 01:08:16