Spectral cross-calibration of VIIRS enhanced vegetation index with MODIS: A case study using year-long global data

© 2015 by the authors; licensee MDPI, Basel, Switzerland. In this study, the Visible Infrared Imaging Radiometer Suite (VIIRS) Enhanced Vegetation Index (EVI) was spectrally cross-calibrated with the Moderate Resolution Imaging Spectroradiometer (MODIS) EVI using a year-long, global VIIRS-MODIS dataset at the climate modeling grid (CMG) resolution of 0.05°-by-0.05°. Our cross-calibration approach was to utilize a MODIS-compatible VIIRS EVI equation derived in a previous study [Obata et al., J. Appl. Remote Sens., vol.7, 2013] and optimize the coefficients contained in this EVI equation for global conditions. The calibrated/optimized MODIS-compatible VIIRS EVI was evaluated using another global VIIRS-MODIS CMG dataset of which acquisition dates did not overlap with those used in the calibration. The calibrated VIIRS EVI showed much higher compatibility with the MODIS EVI than the original VIIRS EVI, where the mean error (MODIS minus VIIRS) and the root mean square error decreased from -0.021 to -0.003 EVI units and from 0.029 to 0.020 EVI units, respectively. Error reductions on the calibrated VIIRS EVI were observed across nearly all view zenith and relative azimuth angle ranges, EVI dynamic range, and land cover types. The performance of the MODIS-compatible VIIRS EVI calibration appeared limited for high EVI values (i.e., EVI > 0.5) due likely to the maturity of the VIIRS dataset used in calibration/optimization. The cross-calibration methodology introduced in this study is expected to be useful for other spectral indices such as the normalized difference vegetation index and two-band EVI

Analysis of surface variables and parameterization of surface processes in HIRLAM. Part I: Approach and verification by parallel runs

The analysis of surface variables and parameterization of surface processes of the reference HIRLAM system is described. Special emphasis has been put on the treatment of surface heterogeneity making that surface uxes of heat and momentum inherit such high spacial variability. The so called “tiling" approach has been adopted to prevent the problems associated with the use of efective parameters in case of strongly changing surface conditions. The tiles are defined by coupling independently each homogeneous patch or “tile" of a grid square to the lowest level of the model. Tiles interact each other only through the atmosphere. Average surface uxes are then computed by averaging surface uxes over each land-use tile weighted by their fractional area. The model allows up to five diferent tiles (water, sea ice, bare ground, low vegetation, forest) within each grid square. Fractional snow cover is also allowed within each tile. The ISBA scheme has been selected to model land surface processes. The surface analysis initializes the following surface variables: sea surface temperature (SST), fraction of water and ice, snow depth, 2-metre temperature, 2-metre relative humidity, surface soil temperature, mean soil temperature, surface soil water content and total soil water content. The algorithm is able to cope with the tiled structure by averaging some variables only over land tiles. SST and snow depth analyses are based on the successive correction method. 2-metre temperature and relative humidity analyses are based on the optimal interpolation method. Finally, soil water content analysis is based on the sequential method, which corrects water content depending on 2-metre temperature and relative humidity forecast errors, only in those synoptic cases where screen variables are strongly inuenced by the surface beneath. A comprehensive list of parallel runs covering all seasons of the year have been conducted to demonstrate the superiority of the new package against the previous surface treatment. Special emphasis has been put on summer time and midlatitude regions were the inuence of soil wáter content on screen temperature and humidity is extremely high

Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards

Accurate estimates of sensible (H) and latent (LE) heat fluxes and actual evapotranspiration (ET) are required for monitoring vegetation growth and improved agricultural water management. A large aperture scintillometer (LAS) was used to provide these estimates with the objective of quantifying the effects of surface heterogeneity due to soil moisture and vegetation growth variability. The study was conducted over drip-irrigated vineyards located in a semi-arid region in Albacete, Spain during summer 2007. Surface heterogeneity was characterized by integrating eddy covariance (EC) observations of H, LE and ET; land surface temperature (LST) and normalized difference vegetation index (NDVI) data from Landsat and MODIS sensors; LST from an infrared thermometer (IRT); a data fusion model; and a two-source surface energy balance model. The EC observations showed 16% lack of closure during unstable atmospheric conditions and was corrected using the residual method. The comparison between the LAS and EC measurements of H, LE, and ET showed root mean square difference (RMSD) of 25 W m−2, 19 W m−2, and 0.41 mm day−1, respectively. LAS overestimated H and underestimated both LE and ET by 24 W m−2, 34 W m−2, and 0.36 mm day−1, respectively. The effects of soil moisture on LAS measurement of H was evaluated using the Bowen ratio, β. Discrepancies between HLAS and HEC were higher at β ≤ 0.5 but improved at 1 ≥ β \u3e 0.5 and β \u3e 1.0 with R2 of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVILAS compared to that of the EC (NDVIEC) by ~0.022. Surface heterogeneity increased during wetter periods, as characterized by the LST–NDVI space and temperature vegetation dryness index (TVDI). As TVDI increased (decreased) during drier (wetter) conditions, the discrepancies between HLAS and HEC, as well as LELAS and LEEC Re decreased (increased). Thresholds of TVDI of 0.3, 0.25, and 0.5 were identified, above which better agreements between LAS and EC estimates of H, LE, and ET, respectively, were obtained. These findings highlight the effectiveness and ability of LAS in monitoring vegetation growth over heterogonous areas with variable soil moisture, its potential use in supporting irrigation scheduling and agricultural water management over large regions

Classification of Vegetation and Analysis of its Recent Trends at Camp Williams, Utah Using Remote Sensing and Geographic Information System Techniques

Current vegetation classes were generated from remotely sensed data to provide coarse-level information for an ecosystem management plan developed at Camp Williams, Utah. Vegetation trend from 1973 - 1993 was also examined via satellite imagery. The data set consisted of Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) images from July or August of 1973, 1975, 1980, 1988, and 1993. Two approaches were used to detect vegetation change. The first approach determined overall and cover type trend from standard digital image differencing of soil-adjusted vegetation index (SAVI) images. The second approach used an unsupervised classification of a composite SAVI image of all dates. The first approach defined areas of increase, decrease, and no significant change in SAVI and differences in trend for tree versus shrub cover types. The second approach resulted in an ecological classification that defined new environmental patterns based on vegetation trend

Generating global products of LAI and FPAR from SNPP-VIIRS data: theoretical background and implementation

Leaf area index (LAI) and fraction of photosynthetically active radiation (FPAR) absorbed by vegetation have been successfully generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) data since early 2000. As the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard, the Suomi National Polar-orbiting Partnership (SNPP) has inherited the scientific role of MODIS, and the development of a continuous, consistent, and well-characterized VIIRS LAI/FPAR data set is critical to continue the MODIS time series. In this paper, we build the radiative transfer-based VIIRS-specific lookup tables by achieving minimal difference with the MODIS data set and maximal spatial coverage of retrievals from the main algorithm. The theory of spectral invariants provides the configurable physical parameters, i.e., single scattering albedos (SSAs) that are optimized for VIIRS-specific characteristics. The effort finds a set of smaller red-band SSA and larger near-infraredband SSA for VIIRS compared with the MODIS heritage. The VIIRS LAI/FPAR is evaluated through comparisons with one year of MODIS product in terms of both spatial and temporal patterns. Further validation efforts are still necessary to ensure the product quality. Current results, however, imbue confidence in the VIIRS data set and suggest that the efforts described here meet the goal of achieving the operationally consistent multisensor LAI/FPAR data sets. Moreover, the strategies of parametric adjustment and LAI/FPAR evaluation applied to SNPP-VIIRS can also be employed to the subsequent Joint Polar Satellite System VIIRS or other instruments.Accepted manuscrip

The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0

Climate change and increased fire are eroding the resilience of boreal forests. This is problematic because boreal vegetation and the cold soils underneath store approximately 30 % of all terrestrial carbon. Society urgently needs projections of where, when, and why boreal forests are likely to change. Permafrost (i.e., subsurface material that remains frozen for at least two consecutive years) and the thick soil-surface organic layers (SOLs) that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and SOL module that operates at fine spatial (1 ha) and temporal (daily) resolutions. The module mechanistically simulates daily changes in depth to permafrost, annual SOL accumulation, and their complex effects on boreal forest structure and functions. We coupled the module to an established forest landscape model, iLand, and benchmarked the model in interior Alaska at spatial scales of stands (1 ha) to landscapes (61,000 ha) and over temporal scales of days to centuries. The coupled model could generate intra- and inter-annual patterns of snow accumulation and active layer depth (portion of soil column that thaws throughout the year) consistent with independent observations in 17 instrumented forest stands. The model was also skilled at representing the distribution of near-surface permafrost presence in a topographically complex landscape. We simulated 34.6 % of forested area in the landscape as underlain by permafrost; a close match to the estimated 33.4 % from the benchmarking product. We further determined that the model could accurately simulate moss biomass, SOL accumulation, fire activity, tree-species composition, and stand structure at the landscape scale. Modular and flexible representations of key biophysical processes that underpin 21st-century ecological change are an essential next step in vegetation simulation to reduce uncertainty in future projections and to support innovative environmental decision making. We show that coupling a new permafrost and SOL module to an existing forest landscape model increases the model&rsquo;s utility for projecting forest futures at high latitudes. Process-based models that represent relevant dynamics will catalyze opportunities to address previously intractable questions about boreal forest resilience, biogeochemical cycling, and feedbacks to regional and global climate.&emsp;</p

Proposing an improved surface dryness index to estimate soil moisture based on the temperature vegetation dryness index

Master of ArtsDepartment of GeographyDouglas GoodinIn this thesis, I proposed a new surface dryness index based on the slope of soil moisture isolines in the Land Surface Temperature/Normalized Difference Vegetation Index (LST/NDVI) feature space. This index, referred to here as Dryness Slope Index (DSI), overcomes the problem of Temperature Vegetation Dryness Index (TVDI) having different basis when calculating TVDI values across different images. This problem is rooted in the definition of TVDI whose calculation depends on the position of the “dry edge” and “wet edge” of pixels’ values in the LST/NDVI space of a specific image. The “wet edge” has a fairly stable physical meaning, which represents soil at field capacity or above, and it remains stable across a time series of images. However, the position of “dry edge” represents the driest condition in the image, which does not necessarily mean that the soil is completely dry. Therefore, the value of TVDI calculated from different images is not based on an invariant dry edge value as its baseline, and it is therefore likely to lead to incorrect conclusion if used without extra examination. This problem manifests itself when comparing TVDI values from different images with meteorological data. Results from similar analyses done with DSI showed more reasonable match with the validation data, indicating DSI is a more robust surface dryness index than TVDI. Having verified DSI can be effectively used in estimating soil moisture, I applied DSI on Landsat5 TM to study the relationship between soil moisture and land cover, slope, aspect, and relative elevation. Results showed that land cover accounts the most for variations of estimated soil moisture. I also applied DSI on a long time-series (2000 to 2014) of MODIS data trying to explore the temporal evolution of soil moisture in the entire Flint Hills ecoregion. Results showed little correlation between time and estimated soil moisture, indicating that no noticeable changes in soil moisture has been found through all these years

An integrated study of earth resources in the state of California using remote sensing techniques

There are no author-identified significant results in this report

Partitioning of carbon dioxide exchange in rapidly and slowly changing ecosystems

Im Hinblick auf den aktuellen Klimawandel besteht die Frage, wie die Biosphäre auf den Globalen Wandel und die daraus hervorgehende lokale Landnutzungsänderung bezüglich ihres Kohlenstoffkreislaufes reagiert. Die Landoberfläche ist zum gegenwärtigen Zeitpunkt eine Senke für anthropogene Emissionen von Kohlenstoffdioxid (CO2), jedoch wird gleich-zeitig durch Landnutzungsänderungen zusätzliches CO2 freigesetzt. Nach wie vor ist nicht eindeutig geklärt, wie sensitiv die photosynthetische CO2-Aufnahme und die atmungsbedingte CO2-Freisetzung eines Ökosystems gegenüber Umweltparametern reagieren. Eine Möglichkeit, den vertikalen Fluss der Treibhausgase in ihre Quellen und Senken aufzuspalten, bietet das sogenannte Source-Partitioning. Hierbei werden z. B. vertikale CO2-Flüsse in Photosynthese und Respiration oder im Fall von Wasserdampfflüssen (H2O) in Evaporation und Transpiration aufgetrennt. Derzeitig existieren mehrere Ansätze und Verfahren für das Source-Partitioning, jedoch besitzt jede Methode auch gewisse Nachteile und läßt Raum für Erweiterungen und Verbesserungen. In dieser Arbeit wird zum einen ein Ansatz getestet, der sogenannte Zusatzmessungen benötigt und zum anderen eine analytische Partitionierungsmethode aufgegriffen. Beide Ansätze werden anhand von Fallbeispielen in Agrar- und Waldökosystemen demonstriert und untersucht. Zuerst wird der Prototyp einer mobilen Liftanlage präsentiert, mit der zeitlich sowie räumlich hochaufgelöste Messung von CO2-, H2O-, Temperatur- und Windgeschwindigkeitsprofilen zwischen der Bodenoberfläche und der erdnahen atmosphärischen Grenzschicht über der Pflanzenoberfläche eines Ackers durchgeführt wurden. Die vertikale Verteilung der Konzentrationen von CO2 und H2O kann somit qualitativ für einen dichten Pflanzenbestand bestimmt werden. Dafür wurden zwischen Frühjahr 2015 und Herbst 2016 Kampagnenmessungen in Winterweizen, Wintergerste und einer Zwischenfruchtmischung während verschiedenen Stadien der Pflanzenentwicklung und zu unterschiedlichen Tageszeiten durchgeführt. Mit Hilfe eines Gasanalysators wurden kontinuierlich über eine Profilhöhe von 2 m die Konzentrationen mit einer Frequenz von 20 s-1 aufgezeichnet. Wir demonstrieren die Nachbearbeitung der Messungen (z. B. die Korrektur von Zeitverzögerungen) und zeigen die resultierenden vertikalen Profile als 30-minütige Mittel mit einer Auflösung von 0.025 m. Die Profile zeigen innerhalb des Planzenbestandes deutlich die Effekte der Bodenatmung und der photosynthetischen Kohlenstoffaufnahme, die sowohl innerhalb der Tageszeiten als auch während der Vegetationsperiode variieren. Mit Hilfe der Monin-Obukhov'schen Ähnlichkeitstheorie wurden Messungen über unbewachsenem Boden und einer niedrigen Pflanzendecke analysiert, um die Validität der Profilmessungen und der Rohdatenverarbeitung zu überprüfen. Die abgeleiteten Flüsse von CO2, latente und sensible Wärme und Impuls zeigen eine gute Übereinstimmung zu den parallel durchgeführten Eddy-Kovarianz-Messungen. Während die Kohlenstoffbilanz einer Ackerfläche im Laufe einer Vegetationsperiode zwischen Quelle und Senke wechselt, dauert dieser Prozess in bewirtschafteten Waldökosystemen meist Jahrzehnte. Im Allgemeinen nehmen Wälder in Mitteleuropa im Jahresmittel mehr CO2 auf, als sie abgeben und stellen somit eine Senke für atmosphärisches CO2 dar. Diese Situation kann sich ändern, sobald ein Eingriff in das Waldökosystem stattfindet. Ein Extrembeispiel eines solchen Eingriffs sind flächenhafte Kahlschläge, die den Wald nach der Abholzung von einer ehemaligen Senke zu einer Quelle für CO2 umwandeln. In dieser Arbeit präsentiert werden sieben Jahre CO2-Flussmessungen über einer rund 70 Jahre alten Fichten-Monokulturfläche im Nationalpark Eifel, von der rund 20% drei Jahre nach Beginn der Messung abgeholzt wurden. Ein Eddy-Kovarianz-System, das auf einem 37.8 m hohen Turm innerhalb des Waldes montiert wurde, erfasste kontinuierlich Flüsse sensibler und latenter Wärme, CO2 und Impuls. Nach der teilweisen Entfichtung wurde eine zweite EC-Station innerhalb der Entfichtungsfläche installiert und parallel zur Waldstation betrieben. Komplette Zeitreihen und jährliche Kohlenstoffbilanzen des Netto-Ökosystemaustauschs von CO2 (NEE) und seiner Komponenten Brutto-Primärproduktion (GPP) und Ökosystematmung (Reco) wurden mit Hilfe von Gapfilling- und Source-Partition-ing Methoden berechnet. Daneben wird die gemessene Bodenatmung berücksichtigt und dich sich gegenüberstehenden Klimaeffekte der durch die Entfichtung veränderten CO2-Sequestrierung und dem biophysikalischen Effekt der geänderten Albedo betrachtet. Im Gegensatz zur abgeholzten Fläche zeigten die über dem Wald gemessenen jährlichen NEE-Summen eine starke Kohlenstoffsenke mit geringer zwischenjährlicher Variabilität. Ein Jahr nach der Entfichtung bestand die Vegetation auf der abgeholzten Fläche hauptsächlich aus Gräsern und Sträuchern; ab dem zweiten Jahr konnte ein vermehrter Zuwachs neuer Bäume (vorwiegend Eberesche) beobachtet werden. Die wiederaufkommende Vegetation spiegelte sich in den jährlichen Summen des NEE wieder, so entwickelte sich die Entfichtungsfläche von einer Kohlenstoffquelle (ca. 500 g C m-2 y-1) innerhalb der betrachteten vier Jahre aufgrund der Zunahme photosynthetischer Aktivitäten zunehmend zu einem CO2 neutralen Zustand. Im anschließenden Kapitel wird die Kohlenstoffbilanz eines Ackers über eine drei Jahre andauernde Fruchtwechselfolge untersucht. Der Versuchsstandort Selhausen befindet sich in einer landwirtschaftlich intensiv genutzen Region innerhalb der Niederrheinischen Bucht. Rund 34% der Fläche Deutschlands war im Jahr 2015 durch Landwirtschaft genutzt (FAO, 2015). Die Fähigkeit von landwirtschaftlichen Flächen Kohlenstoff zu binden, aber auch zu emittieren, ist von großer Bedeutung für den lokalen und globalen Kohlenstoffkreislauf. Um eine lokale Kohlenstoffbilanz für ein Agrarökosystem aufstellen und modellieren zu können, benötigt man neben dem gemessenen vertikalen Netto-Ökosystemaustausch zusätzliche Informationen bezüglich seiner Zusammensetzung aus Brutto-Primärproduktion und Ökosystematmung. Die in Ökosystemstudien am häufigsten genutzten Partitionierung-Methoden sind die sogenannten datenbasierenden nichtlinearen Funktionen (NLR). Sie beschreiben den nichtlinearen Zusammenhang zwischen dem gemessenen NEE und Umgebungsvariablen wie Lufttemperatur oder solare Strahlung, die maßgeblich Atmungs- und Photosyntheseprozesse steuern. In der hier vorgestellten Studie wird für die Aufteilung der gemessenen NEE über einer 3-jährigen Fruchtwechselfolge, bestehend aus Winterweizen / Wintergerste / Zwischenfrucht und Zuckerrübe, der Ansatz einer reinen Nacht- (NT) und einer größtenteils Tagdaten (DT) basierenden NLR benutzt. Zusätzlich wurde ein eigener Algorithmus entwickelt und implementiert, der NLR ohne eine vorangehende Aufteilung in Tag- und Nachtdaten berechnet. Der Verlauf der saisonalen und zwischenjährlichen Flüsse von NEE, GPP und Reco zeigten typische Muster und Größenordnungen einer landwirtschaftlich genutzen Fläche innerhalb Mitteleuropas. Die kumulierten Tagessummen der NEE variierten je nach angebauter Frucht und Jahreszeit zwischen +10 und -14 g C m-2 d-1. Die höchste CO2-Aufnahme fand zwischen Mai und Juni im Winterweizen statt. Die höchsten Emissionen wurden nach der Ernte von Wintergerste beobachtet, wobei vermutlich untergepflügte Erntereste im Boden einen Anstieg der Bodenatmung durch Dekompositionsvorgänge begünstigt haben. Über die komplette Fruchtwechselfolge und bei reiner Betrachtung des vertikalen CO2-Flusses zeigte das Ökosystem, je nach verwendetem Partitionierungsmodell, eine Netto-CO2-Aufnahme von -1.3 bis -1,6 kg C m-2 und stellte somit eine Senke für Kohlenstoff dar. Werden zusätzlich zum NEE der Kohlenstoffeintrag und -austrag durch Sähen und Ernte, sowie die Emissionen aus Feldbewirtschaftungsmaßnahmen in der Kohlenstoffbilanzierung berücksichtigt, wird der Acker eine Kohlenstoffquelle (0.7 bis 1.0 kg C m-2). Beim Vergleich der unterschiedlichen NLR fiel auf, dass die Anwendung, die ausschließlich auf Nachtdaten basiert, grundsätzlich höhere Werte der Ökosystematmung ermittelt, als die anderen verwendeten Methoden. So kam es in den kummulierten Flüssen zu Abweichungen von 16%, 6% und 15% zwischen NEE, GPP und Reco im Vergleich zwischen NT und DT. Geringer fielen die Unterschiede zwischen NT und der eigenen Methode aus. Auch andere Studien berichten von Diskrepanzen in der Partitionierung von NEE bei der Verwendung der oben beschriebenen Methoden. Diese und auch unsere Arbeit zeigen, dass weiterhin Forschungsbedarf hinsichtlich der Anwendung von Source-Partitioning besteht.A key question in times of climate change is, how the biosphere responds to global change and the local land use management in regard to its carbon cycle. At the present time, the land surface acts as a sink for anthropogenic carbon dioxide (CO2) emissions. However, additional CO2 is released simultaneously by land use change. There is still no clear understanding of the sensitivity of photosynthetic CO2 uptake and respiratory CO2 release to environmental parameters. One possible way to disentangle the flux of greenhouse gases is source-partitioning, e.g. into photosynthesis and respiration (CO2) or into evaporation and transpiration (H2O). Currently, there are a number of procedures for source-partitioning, however, each method has its disadvantages and allows for extensions and improvements. In this thesis, one instrumental and a data-driven partitioning approaches are taken up and demonstrated by examples of an agro- and forest ecosystem. First, we present the prototype of a portable elevator based device for measuring temporal and spatial high-resolution profiles of CO2, H2O, temperature and wind velocity between the soil surface and the atmospheric surface layer above crop canopies. The vertical distribution of CO2 and H2O concentrations can thus be determined qualitatively for dense crop stands. Between spring 2015 and autumn 2016, campaign measurements were carried out in winter wheat, winter barley, and in an intercrop mixture during different plant development stage and at different times of day. A gas analyzer continuously records the concentrations at a frequency of 20 s-1 over a 2 m profile height. We present a post-processing technique of the measurements (e.g. the correction of time lags) and show the resulting vertical profiles as 30-minute averages over height steps of 0.025 m. The profiles clearly show the effects of soil respiration and photosynthetic carbon uptake within the plant stand, which vary both during the time of day and during the vegetation period. Using the Monin-Obukhov similarity theory, measurements over bare soil and a short plant canopy were analyzed to check the validity of the elevator measurements and the raw data processing. It was found that the derived fluxes of CO2, latent and sensible heat, and momentum correlated well with eddy-covariance (EC) measurements. While the carbon balance of an agricultural area alternates between source and sink during a vegetation period, this process usually requires decades for the management of forest ecosystems. In general, forests in Central Europe assimilate more CO2 on an annual average than they emit and thus are a sink for atmospheric CO2. This may change as soon as the forest ecosystem is intervened. An extreme example of such an intervention is clear cutting. After deforestation, the forest changes from a former sink to a source of CO2. We present seven years of CO2 flux measurements over a 70 year old spruce monoculture in the Eifel National Park, from which about 20% were deforested three-years after beginning of the observation period. An EC system mounted on top of a 37.8 m high tower within the forest, continuously collects fluxes of sensible and latent heat, CO2 and momentum. After partial deforestation, a second EC station was installed within the deforested area and was running parallel to the forest station. Complete time series and annual carbon budgets of the net ecosystem exchange (NEE) of CO2 and its components, gross primary production (GPP) and ecosystem respiration (Reco), were calculated using gap-filling and source-partitioning methods. In addition, local chamber measurements of soil respiration are taken into account and the climatic effects of the changed CO2 sequestration and the biophysical effect of changed albedo are compared. In contrast to the deforested area, the annual sums of NEE measured above the forest show a strong carbon sink with low inter-annual variability. One year after deforestation, the vegetation on the deforested area consisted mainly of grasses and shrubs; from the second year onwards, an increased growth of new trees (mainly mountain ash) could be observed. The recovering vegetation is reflected in the annual sums of NEE, which decreased from a carbon source (500 g C m-2 y-1) towards neutral over the past four years, due to an increase in the photosynthetic activities. In the last chapter, the carbon balance of a three-year crop rotation cycle was examined. The study site Selhausen is located in an intensively managed agricultural region within the Lower Rhine Embayment. About 34% of the area of Germany was covered by agriculture in 2015 (FAO, 2015). The ability of agricultural areas to sequester or also to emit carbon gives them an important role in the local and global carbon cycle. In order to calculate or to model the local carbon balance for an agroecosystem, information about the measured NEE and its components GPP and Reco are needed. The most frequently used partitioning methods in ecosystem studies are the so-called data-based nonlinear regression functions (NLR). NLR describes the nonlinear relationship between the measured NEE and environmental variables, such as air temperature or solar radiation, which are the main drivers of respiration and photosynthetic processes. The study presented here uses a nighttime (NT) and daytime data based (DT) NLR approach for the partitioning of measured NEE in a 3-year crop rotation cycle, consisting of winter wheat / winter barley / catch-crop and sugar beet. In addition, an own algorithm was developed and implemented that calculates NLR without a previous separation of the dataset into day- and nighttime data. The seasonal and inter-annual fluxes of NEE, GPP and Reco showed typical patterns and orders of magnitude of an agroecosystem within Central Europe. The cumulated daily sums of the NEE varied between +10 and -14 g C m-2 d-1 depending on the cultivated crop and season. The highest CO2 uptake took place between May and June in winter wheat. The highest emissions were observed after harvest of winter barley, when crop residues in the soil favoring an increase in soil respiration due to decomposition processes. Over the 3-year crop rotation, the ecosystem acted as a carbon source with a release of 0.7 to 1.0 kg C m-2, depending on the used source-partitioning model. Comparing the different NLR methods, it became apparent that the NT based application overestimated Reco compared to the other methods, resulting in deviations in NT vs. DT of 16%, 6% and 15% between the cumulated fluxes of NEE, GPP and Reco. The differences between NT and the own method were in general smaller. Other studies also reported discrepancies in the partitioning of NEE using the methods described above. Their and our work shows that there is still a need for further investigation regarding source-partitioning strategies