Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.Ihmisen toiminnan seurauksena ympäristön tila on heikentynyt kiihtyvällä vauhdilla. Ilmasto lämpenee, metsähakkuut ja metsäpalot lisääntyvät ja luonnon monimuotoisuus on katoamassa. Ympäristöongelmia ja -uhkia voidaan tutkia ja mallintaa geoinformatiikan menetelmin ja metodein: kaukokartoituksen, paikkatietojärjestelmien (GIS) sekä spatiaalis-tilastollisten ennustemallien avulla. Väitöskirjassa tutkittiin geoinformatiikan menetelmin geospatiaalista aineistoa hyväksi käyttäen: (i) Täpläverkkoperhosen (Melitaea cinxia) esiintymistä Ahvenanmaalla; (ii) Lehtimittarin (Scopulini moths; Lepidoptera: Geometridae, Sterrhinae) esiintymisen spatiaalis-temporaalista levinneisyyttä ja diversiteettiä globaalissa mittakaavassa; (iii) alkuperäismetsien häviämistä ja (iv) asutuksen levinneisyyttä Taita Hills -ylänköalueella Keniassa, sekä (v ja vi) savannipalojen esiintymistä ja paloarpien laajuuden arviointia Itä-Kaprivilla, Namibiassa. Tulokset: (i) Ahvenanmaalla esiintyvälle Täpläverkkoperhoselle luotiin paikkatietokanta, jonka avulla selvitettiin lajin metapopulaation spatiaalis-temporaalisia tekijöitä. Tärkein tulos todisti että paikallisilmaston vaikutus on yksi merkittävimmistä tekijöistä Täpläverkkoperhosen populaatioiden koon vaihtelussa. (ii) Paikkatietomenetelmin pystyttiin selvittämään Lehtimittarin (Scopulini moths; Lepidoptera: Geometridae, Sterrhinae) globaali maantieteellinen levinneisyys ja diversiteetti. Lajia tavataan ympäri maailmaa paitsi arktisilla alueilla. Pääosa lajeista on löydetty troppisilta alueilta. Diversiteetti on erityisen runsasta Saharan eteläpuoleisessa Afrikassa. (iii) Taita Hills ylänköalueella alkuperäismetsät ovat vähentyneet 50% (260 hehtaaria) vuodesta 1955 vuoteen 2004. Kuitenkin metsäpinta-ala oli Taita Hillsin ylänköalueella pienentynyt vain 2% johtuen metsänistutuksista. Maankäytön muutostulkintaan perustuen Taita Hills ylänköalueen alkuperäismetsät ovat pääosin muuttuneet maatalousmaaksi. Alkuperäismetsien tilalle on myös istutettu ns. eksoottisia lajikkeita kuten eukalyptusta, joka on heikentänyt metsien laatua, jolla on haitalliset vaikutukset mm. eliölajien monimuotoisuuteen Taita Hillsin alueella. (iv) Taita Hills ylänköalueen asutuksen levinneisyyttä voidaan mallintaa geospatiaalisilla karttatasoilla ja spatiaalis-tilastollisilla ennustemenetelmillä. Tutkimuksessa ilmeni, että satelliittikuvalta saadut ensimmäisen asteen tilastolliset tekstuuripiirteet ja toisen asteen tilastolliset tekstuuripiirteet, jotka perustuvat ns. Haralickin tekstuuripiirteiden yhtenevyysmatriisiin, olivat parhaita muuttujia selittämään asutuksen levinneisyyttä. Tutkimus paljasti että asutuksen mallintamiseen ei välttämättä tarvita satelliittikuvalta luokiteltua maankäyttökarttatasoa, sillä ensimmäisen ja toisen asteen tilastolliset tekstuuripiirteet olivat parempia selittäviä muuttujia ennustemalleissa. (v) Itä-Kaprivilla spatiaalis-tilastollisella ennustemallilla; yleistetty lineaarinen regressio (generalized linear model, GLM) voidaan arvioida paloalueiden laajuus paikallistasolla tarkemmin kuin käyttämällä olemassa olevaa MODIS satelliittiin perustuvaa (MCD45A1) globaalia paloaluemallia. Spatiaalis-tilastollisissa malleissa on kuitenkin huomioitava palojen spatiaalinen autokorrelaatio kalibrointiprosessissa. (vi) Kahdeksaa eri spatiaalis-tilastollista ennustemallinnusmenetelmää verrattiin palojen esiintymisen ja paloalueiden laajuuden analyysissä Itä-Kaprivilla. GBM (Generalized boosting methods) -menetelmä osoittautui parhaaksi sekä palojen esiintymisen ja paloalueiden laajuuden mallintamisessa. Ennustemalleilla pystyttiin arvioimaan paloalueiden laajuus ja paloriskialueet tarkemmin kuin käyttämällä olemassa olevaa MODIS satelliittiin perustuvaa (MCD45A1) globaalia paloaluemallia

Utilizing geographic information systems tools for risk-informed maritime search and rescue performance evaluation

In many sea areas there is significant recreational activity, with many sailing vessels and motor boats navigating, especially in coastal areas. Search and Rescue (SAR) organizations ensure the safety of people at sea, and are relatively frequently called to perform rescue or assistance missions to people in distress. Apart from the importance of adequate operational planning and training, rescue organizations benefit from establishing a robust, effective and cost-efficient response system. Risk-informed capacity planning can serve as a decision-support tool for determining the number and location of the required search and rescue units (SRUs). The purpose of this paper is to present such a risk-informed approach, which combines analysis of historic accident and incident data of recreational boating with information derived from Geographic Information System (GIS) methods. The method is applied to a case study focusing on the risk-informed capacity evaluation of the voluntary search and rescue services in the Finnish part of the Gulf of Finland. Results indicate that the response performance for recreational boating incidents is very good in most areas.Peer reviewe

Assessment of Urban Sprawl, Land Use and Land Cover Changes in Voi Town, Kenya Using Remote Sensing and Landscape Metrics

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Habitat suitability modelling to improve conservation status of two critically endangered endemic Afromontane forest bird species in Taita Hills, Kenya

Tropical montane forests are known to support many endemic species with restricted geographic ranges. Many of these species are however, faced with numerous threats, most notably from habitat loss and degradation, invasive alien species, and climate change. Examples include Taita Apalis and Taita Thrush. Taita Apalis (Apalis fuscigularis) and Taita Thrush (Turdus helleri) are species of birds listed as Critically Endangered by the Government of Kenya and the International Union for Conservation of Nature (IUCN). They are endemic to Taita Hills' cloud forests in southeastern Kenya and protected under Wildlife Conservation and Management Act. As they face high risk of extinction, exploring their habitat suitability is imperative for their protection. To determine the current spatial distribution and the key ecogeographical explanatory factors and conditions affecting species distribution and indirect effects on species survival and reproduction, we employed Maximum Entropy (MaxEnt) modelling. This study was conducted in Ngangao and Vuria forests in June and July 2019 and 2020. Ngangao forest is gazetted as forest reserve and managed by the Kenya Forest Service whereas Vuria is nongazetted and thus remains without official protection status. Ecogeographical explanatory variables; climatic, remote sensing-, LIDAR-, topography-and landscape-based variables were used in modelling and separate models were produced. 23 occurrence records of Taita Apalis and 30 of Taita Thrush from Ngangao and 21 of Taita Apalis from Vuria forests were used in the modelling. According to the models, less than 7% of the total area of Ngangao and Vuria forests was predicted as suitable habitat for Taita Apalis and Taita Thrush. This shows that these two species are more vulnerable to extinction from demographic stochasticity. Consequently, managing their habitats is critical for their long-term persistence. LIDAR-based canopy height range and elevation greatly influenced Taita Apalis distribution in Ngangao forest, with areas of high elevation (1620-1750 m a.s.l.) and having open middle-storey preferred. Elevation, slope and topographic wetness index (twi) were the major determinants of Taita Thrush distribution in Ngangao, where gentle sloping areas with moderately dry surfaces within high elevation (1620-1730 m a.s.l.) were favoured. Mean annual temperature, Euclidean distance to the forest edge, slope and land cover type greatly influenced the distribution of Taita Apalis in Vuria, with gentle sloping areas within forest interior made up of indigenous vegetation preferred. This study proposes reforesting open and degraded sites next to areas predicted as highly suitable for the two species; establishment of agroforestry belts based on indigenous trees on the boundaries of the two forests to reduce grazing and firewood collection pressure and enhance resilience to the edge effects; and enhancing forest protection through Participatory Forest Management.Peer reviewe

Testing the Potential Application of Simulated Multispectral Data in Discriminating Tree Species in Taita Hills

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A predictive modelling technique for human population distribution and abundance estimation using remote sensing and geospatial data in a rural mountainous area in Kenya

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Spatiotemporal clustering patterns and sociodemographic determinants of COVID-19 (SARS-CoV-2) infections in Helsinki, Finland,

This study aims to elucidate the variations in spatiotemporal patterns and sociodemographic determinants of SARS-CoV-2 infections in Helsinki, Finland. Global and local spatial autocorrelation were inspected with Moran's I and LISA statistics, and Getis-Ord Gi* statistics was used to identify the hot spot areas. Space-time statistics were used to detect clusters of high relative risk and regression models were implemented to explain sociodemographic determinants for the clusters. The findings revealed the presence of spatial autocorrelation and clustering of COVID-19 cases. High–high clusters and high relative risk areas emerged primarily in Helsinki's eastern neighborhoods, which are socioeconomically vulnerable, with a few exceptions revealing local outbreaks in other areas. The variation in COVID-19 rates was largely explained by median income and the number of foreign citizens in the population. Furthermore, the use of multiple spatiotemporal analysis methods are recommended to gain deeper insights into the complex spatiotemporal clustering patterns and sociodemographic determinants of the COVID-19 cases.Peer reviewe

Potential tree species extinction, colonization and recruitment in Afromontane forest relicts

Tree species regeneration determines future forest structure and composition, but is often severely hampered in small forest relicts. To study succession, long-term field observations or simulation models are used but data, knowledge or resources to run such models are often scarce in tropical areas. We propose and implement a species accounting equation, which includes the co-occurring events extinction, colonization and recruitment and which can be solved by using data from a single inventory. We solved this species accounting equation for the 12 remaining Afromontane cloud forest relicts in Taita Hills, Kenya by comparing the tree species present among the seedling, sapling and mature tree layer in 82 plots. A simultaneous ordination of the seedling, sapling and mature tree layer data revealed that potential species extinctions, colonizations and recruitments may induce future species shifts. On landscape level, the potential extinction debt amounted to 9% (7 species) of the regional species pool. On forest relict level, the smallest relicts harbored an important proportion of the tree species diversity in the regeneration layer. The average potential recruitment credit, defined as species only present as seedling or sapling, was 3 and 6 species for large and small forest relicts, while the average potential extinction debt was 12 and 4 species, respectively. In total, both large and small relicts are expected to lose approximately 20% of their current local tree species pool. The species accounting equations provide a time and resource effective tool and give an improved understanding of the conservation status and possible future succession dynamics of forest relicts, which can be particularly useful in a context of participatory monitoring

Assessment of human–elephant conflicts in multifunctional landscapes of Taita Taveta County, Kenya

People and wildlife have co-occurred, sharing resources for thousands of years, however, over the last four decades records of human–wildlife conflict have increasingly emerged. Human–elephant conflict is a form of such conflict, resulting from negative interactions between people and elephants. Human–elephant conflict affects local community livelihood and the success of elephant conservation. Tsavo East and Tsavo West National Parks, which cover about 60% of the Taita Taveta County land area, host the single largest elephant population in Kenya. We analysed human–elephant conflict incident data over 15 years (2004–2018) in Taita Taveta County, which forms part of the Tsavo ecosystem in south-eastern Kenya. We identified eight forms of human–elephant conflict comprising elephant threat, crop raiding, property damage, injury to people, human death, elephant death, elephant injury, and livestock death. Three forms of conflict accounted for 97% of the reported incidents, namely elephant threat to humans, constituting the highest number of incidents (62.46%), followed by crop raiding (32.46%) and property damage (2.33%). Conflicts occurred throughout the year, with June to July having the highest number of incidents. Rainfall, distance from the Tsavo national parks, and human population density were used as covariates to explain HEC patterns. This study seeks to provide a detailed evaluation of the spatial–temporal patterns of human–elephant conflict in Taita Taveta County and to yield information useful for human–elephant conflict mitigation and elephant conservation.Peer reviewe

Tropical stream diatom communities – the importance of headwater streams for regional diversity

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