Land cover change from national to global scales:A spatiotemporal assessment of trajectories, transitions and drivers

Changes in global land cover (LC) have significant consequences for global environmental change, impacting the sustainability of biogeochemical cycles, ecosystem services, biodiversity, and food security. Different forms of LC change have taken place across the world in recent decades due to a combination of natural and anthropogenic drivers, however, the types of change and rates of change have traditionally been hard to quantify. This thesis exploits the properties of the recently released ESA-CCI-LC product – an internally consistent, high-resolution annual time-series of global LC extending from 1992 to 2018. Specifically, this thesis uses a combination of trajectories and transition maps to quantify LC changes over time at national, continental and global scales, in order to develop a deeper understanding of what, where and when significant changes in LC have taken place and relates these to natural and anthropogenic drivers. This thesis presents three analytical chapters that contribute to achieving the objectives and the overarching aim of the thesis. The first analytical chapter initially focuses on the Nile Delta region of Egypt, one of the most densely populated and rapidly urbanising regions globally, to quantify historic rates of urbanisation across the fertile agricultural land, before modelling a series of alternative futures in which these lands are largely protected from future urban expansion. The results show that 74,600 hectares of fertile agricultural land in the Nile Delta (Old Lands) was lost to urban expansion between 1992 and 2015. Furthermore, a scenario that encouraged urban expansion into the desert and adjacent to areas of existing high population density could be achieved, hence preserving large areas of fertile agricultural land within the Nile Delta. The second analytical chapter goes on to examine LC changes across sub-Saharan Africa (SSA), a complex and diverse environment, through the joint lenses of political regions and ecoregions, differentiating between natural and anthropogenic signals of change and relating to likely drivers. The results reveal key LC change processes at a range of spatial scales, and identify hotspots of LC change. The major five key LC change processes were: (i) “gain of dry forests” covered the largest extent and was distributed across the whole of SSA; (ii) “greening of deserts” found adjacent to desert areas (e.g., the Sahel belt); (iii) “loss of tree-dominated savanna” extending mainly across South-eastern Africa; (iv) “loss of shrub-dominated savanna” stretching across West Africa, and “loss of tropical rainforests” unexpectedly covering the smallest extent, mainly in the DRC, West Africa and Madagascar. The final analytical chapter considers LC change at the global scale, providing a comprehensive assessment of LC gains and losses, trajectories and transitions, including a complete assessment of associated uncertainties. This chapter highlights variability between continents and identifies locations of high LC dynamism, recognising global hotspots for sustainability challenges. At the national scale, the chapter identifies the top 10 countries with the largest percentages of forest loss and urban expansion globally. The results show that the majority of these countries have stabilised their forest losses, however, urban expansion was consistently on the rise in all countries. The thesis concludes with recommendations for future research as global LC products become more refined (spatially, temporally and thematically) allowing deeper insights into the causes and consequences of global LC change to be determined

Mapping and Analyzing Urban Growth: A Study to Identify Drivers of Urban Growth in West Africa

Urban area expansion is one of the most powerful anthropogenic forces changing the earth‘s surface. Such changes are happening at much faster rates in African and Asian cities. Several interconnected but distinct processes like increase in population concentration and extensive alteration of the landscape are associated with urban area expansion. Therefore, understanding the urban area expansion and its drivers is a key task to devise a plan for sustainable urban development. In this study we mapped and analyzed urban area growth of six mid to large size cities of West Africa. In land cover studies, growth in urban land use are characterized by the declines in cropland. So, firstly we evaluated twelve freely available, remotely sensed land cover and land use (LCLU) datasets at the eco-region, country, and pixel levels in West Africa to estimate croplands. The result shows a very high variability of estimated cropland at all levels. Despite this variability, datasets having a finer spatial resolution and representing a similar time period—specifically data from the International Institute for Applied Systems Analysis-International Food Policy Research Institute (IIASA-IFPRI), Global Land Cover-SHARE(GLC-SHARE), Moderate Resolution Imaging Spectroradiometer-UMD (MODIS-UMD), Global Cropland Extent, Moderate Resolution Imaging Spectroradiometer-UMD (MODIS-IGBP), and GLOBCOVER (GlobCover V23)—estimated comparable cropland areas at eco-region and country levels. The countrywide cropland area, obtained from the selected datasets, when compared with the sum of arable land and permanent crop area obtained from the Food and Agriculture Organization (FAO), showed high coefficient of determination (R2>0.95) for IIASA-IFPRI, and GLC-SHARE. At the pixel level, at the original resolution, the newer datasets have a comparable user’s accuracy (UA>53%) and producer’s accuracy (PA>46%), except for the Global Cropland Extent data. Overall, two datasets – IIASA-IFPRI and GLC-SHARE– performed better in the region to estimate the cropland area at all levels. Next, we used Landsat MSS, TM and ETM+ images to map the urban land area in six West African cities for four different time steps from the early-1970s to 2010. The selected cities are Kumasi of Ghana, Daloa of Cote d’Ivoire, Abuja and Kano in Nigeria, Kindia of Guinea, and Ouagadougou of Burkina Faso. They also represent three different eco-regions: Eastern Guinean Forest, Guinean Forest-Savanna Mosaic, and West Sudanian Savanna of West Africa. We found that all the cities, except Daloa, have a large number of non-urban pixel converted to urban in the past three to four decades. The growth of the urban areas was high, 13 to 54%, but the growth trajectories were not consistent. For example, the rate of urban growth has been declining in Abuja and Ouagadougou in recent years while Kumasi has been growing consistently at a much higher rate since 1975 and was still growing about 13% annually, between 2005 and 2010. Also, most of the cities have shown a higher rate of growth of urban land use than population except Abuja and Ouagadougou. These cities revealed higher population growth, (10.7 to 15.8%) than urban land use growth, which varies from 3.0 to 4.5%. We did not observe any similarities in the growth of cities from the same eco-region. Finally, we identified that Normalized Difference Vegetation Index (NDVI) and distance to the urban area showed strong associations with the growth of six cities in West Africa. The six cities include Kumasi, Daloa, Abuja, Kindia, Ouagadougou, and Kano. We found that none of the factors showed a consistent association with urban land use. Out of the six cities, Ouagadougou and Kano showed some level of agreement in associating the urban growth with NDVI at different time periods. In the rest of the cities, proximity parameters such as distance to the nearest urban area and distance to the core city area showed some level of association to urban growth. These findings shows that the process of conversion of urban land use is unique for a city at a given time period

Abundance and Diversity of Trees Species Under Different Land Uses in the Sudan Savannah Ecological Zone of Ghana, West Africa

Knowledge on tree species abundance and diversity is critical for sustainable land management and biodiversity conservation. The aim of the study was to assess tree species abundance and diversity across different land uses and sites in the Sudan savannah ecological zone of Ghana, a total of 64 plots of 3600 m2 (60 m x 60 m) were laid out in three land use types (Forest reserve, cropland and rangeland) in four sites (Bawku, Binduri, Garu and Pusiga). All standing trees and shrubs species encountered in the setting plot were recorded including dendrometry parameters. Alpha diversity was measured using Simpson, Shannon-Wiener and Evenness indices whereas similarity in species composition between land use types and sites were measured using Sorenson’s index. The results showed that there were more species in the lower diameter classes (0 to 20 cm) than the higher diameter classes (>20 cm). the greatest value of tree diversity was recorded in forest land in the four sites compared to the other land use types. The highest similarity (53%) in tree species composition was recorded between cropland in Binduri and Garu. the current study revealed that forest land recorded the highest value of tree species richness in each site compared to the other two land use types (cropland and rangeland) in the same site

The WASCAL hydrometeorological observatory in the Sudan Savanna of Burkina Faso and Ghana

Watersheds with rich hydrometeorological equipment are still very limited in West Africa but are essential for an improved analysis of environmental changes and their impacts in this region. This study gives an overview of a novel hydrometeorological observatory that was established for two mesoscale watersheds in the Sudan Savanna of Southern Burkina Faso and Northern Ghana as part of the West African Science Service Centre on Climate Change and Adapted Land Use (WASCAL) program. The study area is characterized by severe land cover changes due to a strongly increasing demand of agricultural land. The observatory is designed for long-term measurements of >30 hydrometeorological variables in subhourly resolution and further variables such as CO2. This information is complemented by long-term daily measurements from national meteorological and hydrological networks, among several other datasets recently established for this region. A unique component of the observatory is a micrometeorological field experiment using eddy covariance stations implemented at three contrasting sites (near-natural, cropland, and degraded grassland) to assess the impact of land cover changes on water, energy, and CO2 fluxes. The datasets of the observatory are needed by many modeling and field studies conducted in this region and are made available via the WASCAL database. Moreover, the observatory forms an excellent platform for future investigations and can be used as observational foundation for environmental observatories for an improved assessment of environmental changes and their socioeconomic impacts for the savanna regions of West Africa

Climatic impacts of vegetation dynamics in Eastern Africa

The climate system responds to changes in the structure and physiology of vegetation. These changes can be induced by seasonal growing cycles, anthropogenic land cover changes (LCCs), and precipitation extremes. The extent to which vegetation changes impact the climate depends on the type of ecosystem, the season, and the intensity of perturbations from LCCs and precipitation extremes. Under the growing impacts of climate change and human modification of natural vegetation cover, understanding and monitoring the underlying biogeophysical processes through which vegetation affects the climate are central to the development and implementation of effective land use plans and mitigation measures. In Eastern Africa (EA) the vegetation is characterized by multiple growing cycles and affected by agricultural expansion as well as recurrent and severe drought events. Nonetheless, the degrees to which vegetation changes affect the surface energy budget and land surface temperature (LST) remain uncertain. Moreover, the relative contributions of various biogeophysical mechanisms to land surface warming or cooling across biomes, seasons, and scales (regional to local) are unknown. The objective of this thesis was to analyze and quantify the climatic impacts of land changes induced by vegetation seasonal dynamics, agricultural expansion, and precipitation extremes in EA. In particular, this thesis investigated these impacts across biomes and spatio-temporal scales. To address this objective, satellite observation and meteorological data were utilized along with empirical models, observation-based metrics, and statistical methods. The results showed that rainfall–vegetation interaction had a strong impact on LST seasonality across ecoregions and rainfall modality patterns. Furthermore, seasonal LST dynamics were largely controlled by evapotranspiration (ET) changes that offset the albedo impact on the surface radiation balance. Forest loss disturbed the LST dynamics and increased local LST consistently and notably during dry seasons, whereas during the wet season its impact was limited because of strong rainfall–vegetation interaction. Moreover, drought events affected LST anomalies; however, the impact of droughts on temperature anomalies was highly regulated by vegetation greening. In addition, the conversion of forest to cropland generated the highest net warming (1.3 K) compared with other conversion types (savanna, shrubland, grassland, and cropland). Warming from the reduction of ET and surface roughness was up to ~10 times stronger than the cooling effect from albedo increases (−0.12 K). Furthermore, large scale analysis revealed a comparable warming magnitude during bushland-to-cropland conversion associated with the dominant impact of latent heat (LE) flux reduction, which outweighed the albedo effect by up to ~5 times. A similar mechanism dominated the surface feedback during precipitation extremes; where LE flux anomalies dominated the energy exchange causing the strongest LST anomaly in grassland, followed by savanna. By contrast, the impact was negligible in forest ecosystems. In conclusion, the results of this thesis clarify the mechanics and magnitude of the impacts of vegetation dynamics on LST across biomes and seasons. These results are crucial for guiding land use planning and climate change mitigation efforts in EA. The methods and results of this thesis can assist in the development of ecosystem-based mitigation strategies that are tailored to EA biomes. Moreover, they can be used for assessing the performance of climate models and observation-based global scale studies that focus on the biogeophysical impacts of LCCs. Keywords: LST seasonality; Land cover change; Bushland (Acacia-Commiphora); Biophysical effects; Precipitation extremes; Satellite observation.Ilmastojärjestelmä reagoi kasvillisuuden rakenteen ja fysiologian muutoksiin. Muutokset voivat johtua kasvukauden vaiheesta, ihmistoiminnan vaikutuksesta maanpeitteeseen ja sään ääri-ilmiöistä. Se missä määrin kasvillisuuden muutokset vaikuttavat ilmastoon riippuu ekosysteemistä ja vuodenajasta sekä maanpeitemuutosten ja sään ääri-ilmiöiden voimakkuudesta. Ilmastonmuutoksen ja maanpeitteen muokkaamisen vaikutusten voimistuessa on keskeistä ymmärtää ja seurata biogeofysikaalisia prosesseja, joiden kautta kasvillisuus vaikuttaa ilmastoon. Tällä tiedolla on keskeinen rooli tehokkaiden maankäyttösuunnitelmien kehittämisessä ja toteuttamisessa sekä ilmastonmuutoksen hillinnässä. Itä-Afrikassa kasvillisuudella on ominaisesti useita kasvukausia ja siihen vaikuttavat maatalouden laajentuminen sekä toistuvat ja vakavat kuivuusjaksot. Siitä huolimatta kasvillisuuden muutosten vaikutus energiataseeseen ja maanpinnan lämpötilaan on edelleen epävarmaa. Lisäksi eri biogeofysikaalisten mekanismien suhteellista vaikutusta maanpinnan lämpenemiseen tai jäähtymiseen eri biomien, vuodenaikojen ja mittakaavojen (alueellinen ja paikallinen) välillä ei tunneta. Tämän tutkielman tavoitteena oli analysoida ja kvantifioida kasvillisuuden vuodenaikaisvaihtelun, maatalouden laajentumisen ja sademäärän ääri-ilmiöiden aiheuttamien muutosten ilmastovaikutuksia Itä-Afrikassa. Erityisesti tutkielmassa tarkasteltiin vaikutuksia eri biomien ja mittakaavojen välillä. Tutkielmassa hyödynnettiin satelliittihavaintoja ja meteorologisia tietoja sekä empiirisiä malleja, havaintopohjaisia indeksejä ja tilastollisia menetelmiä. Tulokset osoittivat, että sademäärän ja kasvillisuuden vuorovaikutuksella oli voimakas vaikutus maanpinnan lämpötilan vuodenaikaisvaihteluun kasvillisuustyyppien ja sademoodien välillä. Maanpinnan lämpötilaa säätelivät suurelta osin evapotranspiraation muutokset, jotka kompensoivat albedon vaikutuksia pinnan säteilytasapainoon. Metsän häviäminen häiritsi maanpinnan lämpötilan dynamiikkaa ja lisäsi sitä paikallisesti, etenkin kuivina vuodenaikoina, kun taas sadekauden aikana sen vaikutus oli vähäinen sateen ja kasvillisuuden voimakkaan vuorovaikutuksen vuoksi. Lisäksi kuivuus vaikutti lämpötilan poikkeavuuksiin; kuivuuden vaikutusta sääteli kuitenkin voimakkaasti kasvillisuuden vihertyminen. Metsän muuntaminen viljelysmaaksi aiheutti suurimman nettolämmityksen (1.3 K) verrattuna muihin muutostyyppeihin (savanni, pensaikko, ruohostomaat ja viljelymaat). Evapotranspiraation vähenemisestä ja pinnan epätasaisuudesta aiheutuva lämpeneminen oli jopa noin 10 kertaa voimakkaampi kuin albedon jäähdytysvaikutus (−0.12 K). Lisäksi pensaikon muuntaminen viljelysmaaksi aiheutti vastaavan lämpenemisen. Lämpeneminen liittyi latentin lämpövuon merkityksen vähentymiseen, joka ylitti albedovaikutuksen jopa noin viisinkertaisesti. Samanlainen mekanismi hallitsi sademäärän ääripäiden aikana, jolloin latentin lämpövuon poikkeavuudet hallitsivat energianvaihtoa aiheuttaen voimakkaimman maanpinnan lämpötilan poikkeavuuden ruohostomailla ja savanneilla. Sitä vastoin metsissä vaikutus oli vähäinen. Yhteenvetona voidaan todeta, että tutkielman tulokset selventävät kasvillisuuden dynamiikan vaikutusten mekanismeja ja suuruutta maanpinnan lämpötilaan biomien ja vuodenaikojen välillä. Tulokset ovat tärkeitä Itä-Afrikan maankäytön suunnittelun ja ilmastonmuutoksen hillitsemistoimien ohjaamisessa. Tutkielman menetelmät ja tulokset voivat auttaa kehittämään Itä-Afrikan biomeille räätälöityjä ekosysteemipohjaisia lieventämisstrategioita. Lisäksi niitä voidaan käyttää arvioimaan ilmastomalleja ja havaintopohjaisia globaalin mittakaavan tutkimuksia, jotka keskittyvät maanpeitemuutosten biogeofysikaalisiin vaikutuksiin. Avainsanat: Maanpinnan lämpötilan vuodenaikaisvaihtelu; Maanpeitteen muutos; Pensaikko (AcaciaCommiphora); Biofysikaaliset vaikutukset; Sademäärä; Satelliittikaukokartoitus

Potential of satellite and reanalysis evaporation datasets for hydrological modelling under various model calibration strategies

Twelve actual evaporation datasets are evaluated for their ability to improve the performance of the fully distributed mesoscale Hydrologic Model (mHM). The datasets consist of satellite-based diagnostic models (MOD16A2, SSEBop, ALEXI, CMRSET, SEBS), satellite-based prognostic models (GLEAM v3.2a, GLEAM v3.3a, GLEAM v3.2b, GLEAM v3.3b), and reanalysis (ERA5, MERRA-2, JRA-55). Four distinct multivariate calibration strategies (basin-average, pixel-wise, spatial bias-accounting and spatial bias-insensitive) using actual evaporation and streamflow are implemented, resulting in 48 scenarios whose results are compared with a benchmark model calibrated solely with streamflow data. A process-diagnostic approach is adopted to evaluate the model responses with in-situ data of streamflow and independent remotely sensed data of soil moisture from ESA-CCI and terrestrial water storage from GRACE. The method is implemented in the Volta River basin, which is a data scarce region in West Africa, for the period from 2003 to 2012. Results show that the evaporation datasets have a good potential for improving model calibration, but this is dependent on the calibration strategy. All the multivariate calibration strategies outperform the streamflow-only calibration. The highest improvement in the overall model performance is obtained with the spatial bias-accounting strategy (+29%), followed by the spatial bias-insensitive strategy (+26%) and the pixel-wise strategy (+24%), while the basin-average strategy (+20%) gives the lowest improvement. On average, using evaporation data in addition to streamflow for model calibration decreases the model performance for streamflow (-7%), which is counterbalance by the increase in the performance of the terrestrial water storage (+11%), temporal dynamics of soil moisture (+6%) and spatial patterns of soil moisture (+89%). In general, the top three best performing evaporation datasets are MERRA-2, GLEAM v3.3a and SSEBop, while the bottom three datasets are MOD16A2, SEBS and ERA5. However, performances of the evaporation products diverge according to model responses and across climatic zones. These findings open up avenues for improving process representation of hydrological models and advancing the spatiotemporal prediction of floods and droughts under climate and land use changes

Estimating the Extent of Degradation in the Bounfum Forest Reserve, Ghana, Using Historical Remotely Sensed Data and Landscape Fragmentation Indices

Land use and land cover changes, especially deforestation and forest degradation and its driving factors, are key factors hindering sustainable forest management. Currently, there is limited knowledge concerning the detection of the extent and interpretation of the spatial and temporal pattern of forest cover dynamics in the Bounfum Forest Reserve, which when available will inform sustainable policies. Using the Landsat TM image of 1986, Landsat ETM+ image of 2002 and Landsat 8 OLI image of 2014, the study identified and quantified the forest cover dynamics in the Bounfum Forest Reserve from 1986 to 2014. The ERDAS maximum likelihood classification algorithm was used to classify the pixels into five major land cover classes namely, bare/built areas, farmlands, closed forest, open forest and shrub/grassland. The Kappa coefficients of 0.83 (1986), 0.72 (2002) and 0.75 (2014) respectively were obtained for the classified images. The findings showed that the closed forests decreased by 3.5% (563.90 ha) per annum whilst the open forests and farm lands increased by 19.5% (385.60 ha) and 2.9% (65.00 ha) per annum within the 28-year period. This implies that the Bounfum forest reserve has been highly degraded over the past 28 years, evident through the trends of its patch densities and the number of patches. Collaborative forest management is required in the management of the forest reserve to conserve the socio-ecological and economic benefits derived from the resource on sustainable basis. Keywords: Land use and land cover change, Bounfum forest reserve, deforestation, forest degradation, remote sensing, sustainable forest managemen

Spatio-temporal mixed pixel analysis of savanna ecosystems : a review

Reliable estimates of savanna vegetation constituents (i.e., woody and herbaceous vegetation) are essential as they are both responders and drivers of global change. The savanna is a highly heterogenous biome with high variability in land cover types while also being very dynamic at both temporal and spatial scales. To understand the spatial-temporal dynamics of savannas, using Earth Observation (EO) data for mixed-pixel analysis is crucial. Mixed pixel analysis provides detailed land cover data at a sub-pixel level which are essential for conservation purposes, understanding food supply for herbivores, quantifying environmental change, such as bush encroachment, and fuel availability essential for understanding fire dynamics, and for accurate estimation of savanna biomass. This review paper consulted 197 studies employing mixed-pixel analysis in savanna ecosystems. The review indicates that studies have so far attempted to resolve the savanna mixed-pixel issues by using mainly coarse resolution data, such as Terra-Aqua MODIS and AVHRR and medium resolution Landsat, to provide fractional cover data. Hence, there is a lack of spatio-temporal mixed-pixel analysis for savannas at high spatial resolutions. Methods used for mixed-pixel analysis include parametric and non-parametric methods which range from pixel-unmixing models, such as linear spectral mixture analysis (SMA), time series decomposition, empirical methods to link the green vegetation parameters with Vegetation Indices (VIs), and machine learning methods, such as regression trees (RT) and random forests (RF). Most studies were undertaken at local and regional scale, highlighting a research gap for savanna mixed pixel studies at national, continental, and global level. Parametric methods for modeling spatio-temporal mixed pixel analysis were preferred for coarse to medium resolution remote sensing data, while non-parametric methods were preferred for very high to high spatial resolution data. The review indicates a gap for long time series spatio-temporal mixed-pixel analysis of savannas using high resolution data at various scales. There is potential to harmonize the available low resolution EO data with new high-resolution sensors to provide long time series of the savanna mixed pixel, which, according to this review, is missing.The Deutscher Akademischer Austauschdienst and the Federal Ministry of Education and Research (BMBF) within the framework of the Strategy “Research for Sustainability” (FONA).http://www.mdpi.com/journal/remotesensingpm2022Geography, Geoinformatics and Meteorolog

Multiscale Study of the Interactions between Climate, Land Use, and Agricultural Productivity in Western Sahel: A Case Study of Chad

Title from PDF of title page, viewed on June 1, 2015Thesis advisor: Jimmy O. AdegokeVitaIncludes bibliographic references (pages 127-139)Thesis (M.S.)--Department of Geosciences. University of Missouri--Kansas City, 2014This study employed an integrated approach to investigate drivers and impacts of environmental change from the 1980s to 2012 using geospatial and statistical analyses of atmospheric, climate, land use land cover, and socio-economic data. The atmospheric and climate data were obtained from the NASA Giovanni web-portal (GES DISC) for area covering all of Southern Chad and extending to the neighboring countries of Cameroon, Central African Republic, Niger, Nigeria, and Sudan. The geographic coordinates of that area are: North 14.403, West 10.815, East 24.219, and South 7.328. Agricultural productivity country summary data for Chad was obtained from the Food and Agriculture Organization (FAO) of the United Nations. Other data sets, including the Landsat imagery used for deriving land use and land cover information focusing on the transition areas between desert in the Northern Chad and Sahel/Savanna areas to the South. These transition areas are ecologically sensitive and especially vulnerable to changes in climate variables. The geostatistical analyses revealed gradients of precipitation, soil moisture, and NDVI that are positively highly correlated with each other and negatively correlated with the temperature. Cloud fraction amounts, specific humidity, aerosol optical depth, soil moisture, and NDVI values are higher in wetter years than in dryer years; in contrary, wind speeds and surface air temperature are lower during wetter years. The land use land cover analysis of the lake Fitri region shows that the areas covered by natural vegetation such as forest, savanna, and steppe has been decreasing since 1986. Alongside, farm and grasslands have been increasing during that same period of time. In multiple linear regression analysis, it has been shown a positive correlation between precipitation and crops such as sorghum (0.53), maize (0.5), and rice paddy (0.54) and livestock such as sheep (0.43), goat (0.5), and cattle (0.40). But these correlations are higher with population than with precipitationOverview -- Literature review -- Data and methodology -- Data analysis and results -- Discussion -- Conclusion -- Annexes: Accuracy assessment table