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Dr. Marion Stellmes
Freie Universität Berlin, Remote Sensing and Geoinformatics

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Research Keywords & Expertise

0 Landsat time series (LTS)
0 land use / land cover change
0 Remote Sensing & Gis
0 Wild fires
0 MODIS and Landsat phenology and other time series analysis

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land use / land cover change
Remote Sensing & Gis
MODIS and Landsat phenology and other time series analysis
Landsat time series (LTS)
Wild fires

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Journal article
Published: 01 April 2021 in Sustainability
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Different slums exhibit different levels of resilience against the threat of eviction. However, little is known about the role of the social capital of the slum community in this context. This study investigates the factors contributing to slum resilience in the Lagos Metropolis, Nigeria, through a social capital lens. This study first investigates land allocation in slums, then the available social capital, and subsequently how this capital influences resilience to the threat of eviction in slums. Data were collected in two slum communities, in Lagos, through in-depth interviews and focus groups discussion. This study shows that land allocation is done by the traditional heads, contrarily to the mandate of the Nigeria Land Use Act of 1978. Furthermore, there is a form of structural social capital through the presence of government registered community development associations in the slums; however, their activities, decision-making process and the perception of the residents’ towards their respective associations, differs. This led to differences in trust, social cohesion and bonding ties among residents of the slum, thereby influencing resilience to the threat of eviction in slums. Since community group associations, through the appointed executives, drive the efficient utilization of social capital in slums, this study therefore recommends their restructuring in order to support a sustainable solution to the threat of eviction in slums in Lagos.

ACS Style

Olabisi Obaitor; Taibat Lawanson; Marion Stellmes; Tobia Lakes. Social Capital: Higher Resilience in Slums in the Lagos Metropolis. Sustainability 2021, 13, 3879 .

AMA Style

Olabisi Obaitor, Taibat Lawanson, Marion Stellmes, Tobia Lakes. Social Capital: Higher Resilience in Slums in the Lagos Metropolis. Sustainability. 2021; 13 (7):3879.

Chicago/Turabian Style

Olabisi Obaitor; Taibat Lawanson; Marion Stellmes; Tobia Lakes. 2021. "Social Capital: Higher Resilience in Slums in the Lagos Metropolis." Sustainability 13, no. 7: 3879.

Journal article
Published: 07 December 2020 in IEEE Transactions on Geoscience and Remote Sensing
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Many studies analyzing spaceborne hyperspectral images (HSIs) have so far struggled to deal with a lack of pure pixels due to complex mixtures of urban surface materials. Recently, an alternative concept of gradients in urban surface material composition has been proposed and successfully applied to map cities with spaceborne HSIs without the requirement for a previous determination of pure pixels. The gradient concept treats all pixels as mixed and aims to describe and quantify gradual transitions in the cover fractions of surface materials. This concept presents a promising approach to tackle urban mapping using spaceborne HSIs. However, since gradients are determined in a data-driven way, their transferability within urban areas needs to be investigated. For this purpose, we analyze the robustness of urban surface material gradients and their dependence across six systematic and three simple random sampling schemes. The results show high similarity between nine sampling schemes in the primary gradient feature space (Pspace) and individual gradient feature spaces (Ispaces). Comparing the Pspace with the Ispaces, the Mantel statistics show the resemblance of samples' distribution in the Pspace, and each Ispace is rather strong with high credibility, as the significance level is P < 0.01. Therefore, it can be concluded that the material gradients defined in the test area are independent of the specific sampling scheme. This study paves the way for subsequent analysis of the stability of urban surface material gradients and the interpretation of material gradients in other urban environments.

ACS Style

Chaonan Ji; Marianne Jilge; Uta Heiden; Marion Stellmes; Hannes Feilhauer. Sampling Robustness in Gradient Analysis of Urban Material Mixtures. IEEE Transactions on Geoscience and Remote Sensing 2020, PP, 1 -11.

AMA Style

Chaonan Ji, Marianne Jilge, Uta Heiden, Marion Stellmes, Hannes Feilhauer. Sampling Robustness in Gradient Analysis of Urban Material Mixtures. IEEE Transactions on Geoscience and Remote Sensing. 2020; PP (99):1-11.

Chicago/Turabian Style

Chaonan Ji; Marianne Jilge; Uta Heiden; Marion Stellmes; Hannes Feilhauer. 2020. "Sampling Robustness in Gradient Analysis of Urban Material Mixtures." IEEE Transactions on Geoscience and Remote Sensing PP, no. 99: 1-11.

Journal article
Published: 03 January 2020 in International Journal of Applied Earth Observation and Geoinformation
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Mapping heathland habitats is generally challenging due to fine-scale habitats as well as spectral ambiguities between different classes. A multi-seasonal time-series of multispectral RapidEye data from several phenological stages was analysed towards the classification of different vegetation communities. A 3-level hierarchical dependent classification using Import Vector Machines was tested, based on the assumption that a probabilistic output per class would help the mapping. The first level of the hierarchical classification was related to the moisture gradient, which was derived from Ellenberg’s moisture indicative value. The second level aimed to separate plant alliances; the third level differentiated individual plant associations. For the final integration of the three classification levels, two approaches were implemented: (i) the F1-score and (ii) the maximum classification probability. The overall classification accuracies of both methods were found to be similar, around 0.7. Nevertheless, based on our expert knowledge we found the probabilistic approach to provide a more realistic picture and to be more practical compared to the result using the F1-score from the management point of view. In addition, the overall performance of the maximum probabilistic approach is better in the sense that the same accuracy of 0.7 was achieved with a differentiation of 33 classes instead of only 13 classes for the F1-score, meaning that the method is able to separate more spectral classes at a more detailed level providing the same accuracy.

ACS Style

Kristin Fenske; Hannes Feilhauer; Michael Förster; Marion Stellmes; Björn Waske. Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series. International Journal of Applied Earth Observation and Geoinformation 2020, 87, 102036 .

AMA Style

Kristin Fenske, Hannes Feilhauer, Michael Förster, Marion Stellmes, Björn Waske. Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series. International Journal of Applied Earth Observation and Geoinformation. 2020; 87 ():102036.

Chicago/Turabian Style

Kristin Fenske; Hannes Feilhauer; Michael Förster; Marion Stellmes; Björn Waske. 2020. "Hierarchical classification with subsequent aggregation of heathland habitats using an intra-annual RapidEye time-series." International Journal of Applied Earth Observation and Geoinformation 87, no. : 102036.

Journal article
Published: 28 January 2019 in Remote Sensing
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Analysis Ready Data (ARD) have undergone the most relevant pre-processing steps to satisfy most user demands. The freely available software FORCE (Framework for Operational Radiometric Correction for Environmental monitoring) is capable of generating Landsat ARD. An essential step of generating ARD is atmospheric correction, which requires water vapor data. FORCE relies on a water vapor database obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). However, two major drawbacks arise from this strategy: (1) The database has to be compiled for each study area prior to generating ARD; and (2) MODIS and Landsat commissioning dates are not well aligned. We have therefore compiled an application-ready global water vapor database to significantly increase the operational readiness of ARD production. The free dataset comprises daily water vapor data for February 2000 to July 2018 as well as a monthly climatology that is used if no daily value is available. We systematically assessed the impact of using this climatology on surface reflectance outputs. A global random sample of Landsat 5/7/8 imagery was processed twice (i) using daily water vapor (reference) and (ii) using the climatology (estimate), followed by computing accuracy, precision, and uncertainty (APU) metrics. All APU measures were well below specification, thus the fallback usage of the climatology is generally a sound strategy. Still, the tests revealed that some considerations need to be taken into account to help quantify which sensor, band, climate, and season are most or least affected by using a fallback climatology. The highest uncertainty and bias is found for Landsat 5, with progressive improvements towards newer sensors. The bias increases from dry to humid climates, whereas uncertainty increases from dry and tropic to temperate climates. Uncertainty is smallest during seasons with low variability, and is highest when atmospheric conditions progress from a dry to a wet season (and vice versa).

ACS Style

David Frantz; Marion Stellmes; Patrick Hostert. A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery. Remote Sensing 2019, 11, 257 .

AMA Style

David Frantz, Marion Stellmes, Patrick Hostert. A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery. Remote Sensing. 2019; 11 (3):257.

Chicago/Turabian Style

David Frantz; Marion Stellmes; Patrick Hostert. 2019. "A Global MODIS Water Vapor Database for the Operational Atmospheric Correction of Historic and Recent Landsat Imagery." Remote Sensing 11, no. 3: 257.

Journal article
Published: 14 April 2018 in Biodiversity & Ecology
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ACS Style

Achim Röder; Marion Stellmes; David Frantz; Joachim Hill. Remote sensing-based environmental assessment and monitoring - generation of operational baseline and enhanced experimental products in southern Africa. Biodiversity & Ecology 2018, 6, 344 -354.

AMA Style

Achim Röder, Marion Stellmes, David Frantz, Joachim Hill. Remote sensing-based environmental assessment and monitoring - generation of operational baseline and enhanced experimental products in southern Africa. Biodiversity & Ecology. 2018; 6 ():344-354.

Chicago/Turabian Style

Achim Röder; Marion Stellmes; David Frantz; Joachim Hill. 2018. "Remote sensing-based environmental assessment and monitoring - generation of operational baseline and enhanced experimental products in southern Africa." Biodiversity & Ecology 6, no. : 344-354.

Journal article
Published: 14 April 2018 in Biodiversity & Ecology
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ACS Style

Anne Schneibel; Achim Röder; Marion Stellmes; David Frantz. Long-term land use change analysis in south-central Angola. Assessing the trade-off between major ecosystem services with remote sensing data. Biodiversity & Ecology 2018, 6, 360 -367.

AMA Style

Anne Schneibel, Achim Röder, Marion Stellmes, David Frantz. Long-term land use change analysis in south-central Angola. Assessing the trade-off between major ecosystem services with remote sensing data. Biodiversity & Ecology. 2018; 6 ():360-367.

Chicago/Turabian Style

Anne Schneibel; Achim Röder; Marion Stellmes; David Frantz. 2018. "Long-term land use change analysis in south-central Angola. Assessing the trade-off between major ecosystem services with remote sensing data." Biodiversity & Ecology 6, no. : 360-367.

Journal article
Published: 31 August 2017 in Remote Sensing
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Dry tropical forests undergo massive conversion and degradation processes. This also holds true for the extensive Miombo forests that cover large parts of Southern Africa. While the largest proportional area can be found in Angola, the country still struggles with food shortages, insufficient medical and educational supplies, as well as the ongoing reconstruction of infrastructure after 27 years of civil war. Especially in rural areas, the local population is therefore still heavily dependent on the consumption of natural resources, as well as subsistence agriculture. This leads, on one hand, to large areas of Miombo forests being converted for cultivation purposes, but on the other hand, to degradation processes due to the selective use of forest resources. While forest conversion in south-central rural Angola has already been quantitatively described, information about forest degradation is not yet available. This is due to the history of conflicts and the therewith connected research difficulties, as well as the remote location of this area. We apply an annual time series approach using Landsat data in south-central Angola not only to assess the current degradation status of the Miombo forests, but also to derive past developments reaching back to times of armed conflicts. We use the Disturbance Index based on tasseled cap transformation to exclude external influences like inter-annual variation of rainfall. Based on this time series, linear regression is calculated for forest areas unaffected by conversion, but also for the pre-conversion period of those areas that were used for cultivation purposes during the observation time. Metrics derived from linear regression are used to classify the study area according to their dominant modification processes. We compare our results to MODIS latent integral trends and to further products to derive information on underlying drivers. Around 13% of the Miombo forests are affected by degradation processes, especially along streets, in villages, and close to existing agriculture. However, areas in presumably remote and dense forest areas are also affected to a significant extent. A comparison with MODIS derived fire ignition data shows that they are most likely affected by recurring fires and less by selective timber extraction. We confirm that areas that are used for agriculture are more heavily disturbed by selective use beforehand than those that remain unaffected by conversion. The results can be substantiated by the MODIS latent integral trends and we also show that due to extent and location, the assessment of forest conversion is most likely not sufficient to provide good estimates for the loss of natural resources.

ACS Style

Anne Schneibel; David Frantz; Achim Röder; Marion Stellmes; Kim Fischer; Joachim Hill. Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola. Remote Sensing 2017, 9, 905 .

AMA Style

Anne Schneibel, David Frantz, Achim Röder, Marion Stellmes, Kim Fischer, Joachim Hill. Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola. Remote Sensing. 2017; 9 (9):905.

Chicago/Turabian Style

Anne Schneibel; David Frantz; Achim Röder; Marion Stellmes; Kim Fischer; Joachim Hill. 2017. "Using Annual Landsat Time Series for the Detection of Dry Forest Degradation Processes in South-Central Angola." Remote Sensing 9, no. 9: 905.

Journal article
Published: 01 May 2016 in Land Use Policy
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The Okavango catchment is a hot spot of accelerating land use change. In particular, climate predictions, demographic developments and a growing utilization of ecosystem services and functions are expected to increase pressure on resources and land. Land use conflicts, the sustenance of precarious livelihoods, deforestation of woodland savannahs, upstream–downstream water issues and human–wildlife conflicts are among the processes that are characteristic of policy and management challenges in the region. In the Eastern and Western Kavango regions of Namibia and the Cuando-Cubango province of Angola, a unique cross-border situation exists that allows assessing how the combination of local traditions, regional land management and national policies determines spatial patterns of land use and land cover transformation processes. To map major land use types and change processes we used a set of multi-temporal Landsat-5 TM and Landsat-7 ETM+ data sets, support vector machine (SVM) classification and iterative spectral mixture analysis (ISMA) on images covering the period from 1990 to 2010. Integrating satellite imagery with literature reviews, interviews, census and household survey data, we assessed the contrasting development of resource utilization on both sides of the Okavango River. We investigated if and how policies and regulations at different levels drive land use decisions, and how these decisions manifest spatially. We found a strong and interconnected urban growth on both sides of the river. The area around Rundu has constantly been evolving to become Namibia's second largest city, also functioning as a hub of development and transborder commerce with opposing Calai. This trend was found to affect adjacent settlement areas and cause widespread conversion of woodland savannahs to agricultural land or their utilization for timber extraction. The conversion of woodland savannah to arable land was by far the dominant land use change process on both sides of the river, with a total conversion area of 460 km2 (Namibia) and 293 km2 (Angola) observed during the observation period. Strong spatial change gradients occurred in relation to determining factors, such as accessibility, proximity to water, urban centres, etc., while relations to settlements where less obvious. Assessing results by country illustrated the difference in land use intensity and resource consumption between Angola and Namibia, which relate directly to historical developments, with a long period of stability in Namibia standing opposed to the recent and ongoing recovery from civil war in Angola. These are added to by statutory and traditional policy frameworks, the national endowment with natural capital (e.g. oil, uranium, diamonds, zinc) and the integration into global markets, which strongly affects national economies of both countries at large. Underlying land use decisions were found to be largely driven by individualized perspectives on growth ideologies, consumerism and wealth-aspirations connected to globalization processes. However, at present the result of these perspectives is still mainly a small-structured conversion to rainfed agriculture as a component of subsistence strategies of local livelihoods, and thus stands opposed to other regions of the world, where change processes are much more driven by large companies or follow national regulations and result in more intensive uses.

ACS Style

Achim Röder; Michael Pröpper; Marion Stellmes; Anne Schneibel; Joachim Hill. Reprint of “Assessing urban growth and rural land use transformations in a cross-border situation in Northern Namibia and Southern Angola”. Land Use Policy 2016, 53, 97 -111.

AMA Style

Achim Röder, Michael Pröpper, Marion Stellmes, Anne Schneibel, Joachim Hill. Reprint of “Assessing urban growth and rural land use transformations in a cross-border situation in Northern Namibia and Southern Angola”. Land Use Policy. 2016; 53 ():97-111.

Chicago/Turabian Style

Achim Röder; Michael Pröpper; Marion Stellmes; Anne Schneibel; Joachim Hill. 2016. "Reprint of “Assessing urban growth and rural land use transformations in a cross-border situation in Northern Namibia and Southern Angola”." Land Use Policy 53, no. : 97-111.

Journal article
Published: 29 April 2016 in Remote Sensing
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In many parts of Africa, spatially-explicit information on plant α-diversity, i.e., the number of species in a given area, is missing as baseline information for spatial planning. We present an approach on how to combine vegetation-plot databases and remotely-sensed land surface phenology (LSP) metrics to predict plant α-diversity on a regional scale. We gathered data on plant α-diversity, measured as species density, from 999 vegetation plots sized 20 m × 50 m covering all major vegetation units of the Okavango basin in the countries of Angola, Namibia and Botswana. As predictor variables, we used MODIS LSP metrics averaged over 12 years (250-m spatial resolution) and three topographic attributes calculated from the SRTM digital elevation model. Furthermore, we tested whether additional climatic data could improve predictions. We tested three predictor subsets: (1) remote sensing variables; (2) climatic variables; and (3) all variables combined. We used two statistical modeling approaches, random forests and boosted regression trees, to predict vascular plant α-diversity. The resulting maps showed that the Miombo woodlands of the Angolan Central Plateau featured the highest diversity, and the lowest values were predicted for the thornbush savanna in the Okavango Delta area. Models built on the entire dataset exhibited the best performance followed by climate-only models and remote sensing-only models. However, models including climate data showed artifacts. In spite of lower model performance, models based only on LSP metrics produced the most realistic maps. Furthermore, they revealed local differences in plant diversity of the landscape mosaic that were blurred by homogenous belts as predicted by climate-based models. This study pinpoints the high potential of LSP metrics used in conjunction with biodiversity data derived from vegetation-plot databases to produce spatial information on a regional scale that is urgently needed for basic natural resource management applications.

ACS Style

Rasmus Revermann; Manfred Finckh; Marion Stellmes; Ben J. Strohbach; David Frantz; Jens Oldeland. Linking Land Surface Phenology and Vegetation-Plot Databases to Model Terrestrial Plant α-Diversity of the Okavango Basin. Remote Sensing 2016, 8, 370 .

AMA Style

Rasmus Revermann, Manfred Finckh, Marion Stellmes, Ben J. Strohbach, David Frantz, Jens Oldeland. Linking Land Surface Phenology and Vegetation-Plot Databases to Model Terrestrial Plant α-Diversity of the Okavango Basin. Remote Sensing. 2016; 8 (5):370.

Chicago/Turabian Style

Rasmus Revermann; Manfred Finckh; Marion Stellmes; Ben J. Strohbach; David Frantz; Jens Oldeland. 2016. "Linking Land Surface Phenology and Vegetation-Plot Databases to Model Terrestrial Plant α-Diversity of the Okavango Basin." Remote Sensing 8, no. 5: 370.

Journal article
Published: 14 April 2016 in IEEE Transactions on Geoscience and Remote Sensing
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Satellite-derived land surface phenology (LSP) serves as a valuable input source for many environmental applications such as land cover classifications and global change studies. Commonly, LSP is derived from coarse-resolution (CR) sensors due to their well-suited temporal resolution. However, LSP is increasingly demanded at medium resolution (MR), but inferring LSP directly from MR imagery remains a challenging task (e.g., due to acquisition frequency). As such, we present a methodology that directly predicts MR LSP on the basis of the respective CR LSP and MR reflectance imagery. The approach considers information from the local pixel neighborhood at both resolutions by utilizing several prediction proxies, including spectral distance and multiscale heterogeneity metrics. The prediction performs well with simulated data $(R^{2} = 0.84)$, and the approach substantially reduces noise. The size of the smallest reliably predicted object coincides with the effective CR pixel size (i.e., field-of-view). Nevertheless, even subpixel objects can be reliably predicted provided that pure CR pixels are located within the search radius. The application to real MODIS LSP and Landsat reflectance well preserves the phenological landscape composition, and the spatial refinement is especially striking in heterogeneous agricultural areas, where, for example, the circular shape of center pivot irrigation schemes is successfully restored at MR.

ACS Style

David Frantz; Marion Stellmes; Achim Roder; Thomas Udelhoven; Sebastian Mader; Joachim Hill. Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs. IEEE Transactions on Geoscience and Remote Sensing 2016, 54, 4153 -4164.

AMA Style

David Frantz, Marion Stellmes, Achim Roder, Thomas Udelhoven, Sebastian Mader, Joachim Hill. Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs. IEEE Transactions on Geoscience and Remote Sensing. 2016; 54 (7):4153-4164.

Chicago/Turabian Style

David Frantz; Marion Stellmes; Achim Roder; Thomas Udelhoven; Sebastian Mader; Joachim Hill. 2016. "Improving the Spatial Resolution of Land Surface Phenology by Fusing Medium- and Coarse-Resolution Inputs." IEEE Transactions on Geoscience and Remote Sensing 54, no. 7: 4153-4164.

Journal article
Published: 01 April 2016 in Science of The Total Environment
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The repopulation of abandoned areas in Angola after 27 years of civil war led to a fast and extensive expansion of agricultural fields to meet the rising food demand. Yet, the increase in crop production at the expense of natural resources carries an inherent potential for conflicts since the demand for timber and wood extraction are also supposed to rise. We use the concept of ecosystem services to evaluate the trade-off between food and woody biomass. Our study area is located in central Angola, in the highlands of the upper Okavango catchment. We used Landsat data (spatial resolution: 30 × 30 m) with a bi-temporal and multi-seasonal change detection approach for five time steps between 1989 and 2013 to estimate the conversion area from woodland to agriculture. Overall accuracy is 95%, user's accuracy varies from 89–95% and producer's accuracy ranges between 92–99%. To quantify the trade-off between woody biomass and the amount of food, this information was combined with indicator values and we furthermore assessed biomass regrowth on fallows. Our results reveal a constant rise in agricultural expansion from 1989–2013 with the mean annual deforestation rate increasing from roughly 5300 ha up to about 12,000 ha. Overall, 5.6% of the forested areas were converted to agriculture, whereas the FAO states a national deforestation rate for Angola of 5% from 1990–2010 (FAO, 2010). In the last time step 961,000 t per year of woodland were cleared to potentially produce 1240 t per year of maize. Current global agro-economical projections forecast increasing pressure on tropical dry forests from large-scale agriculture schemes (Gasparri et al., 2015; Searchinger and Heimlich, 2015). Our study underlines the importance of considering subsistence-related change processes, which may contribute significantly to negative effects associated with deforestation and degradation of these forest ecosystems.

ACS Style

Anne Schneibel; Marion Stellmes; Achim Röder; Manfred Finckh; Rasmus Revermann; David Frantz; Joachim Hill. Evaluating the trade-off between food and timber resulting from the conversion of Miombo forests to agricultural land in Angola using multi-temporal Landsat data. Science of The Total Environment 2016, 548-549, 390 -401.

AMA Style

Anne Schneibel, Marion Stellmes, Achim Röder, Manfred Finckh, Rasmus Revermann, David Frantz, Joachim Hill. Evaluating the trade-off between food and timber resulting from the conversion of Miombo forests to agricultural land in Angola using multi-temporal Landsat data. Science of The Total Environment. 2016; 548-549 ():390-401.

Chicago/Turabian Style

Anne Schneibel; Marion Stellmes; Achim Röder; Manfred Finckh; Rasmus Revermann; David Frantz; Joachim Hill. 2016. "Evaluating the trade-off between food and timber resulting from the conversion of Miombo forests to agricultural land in Angola using multi-temporal Landsat data." Science of The Total Environment 548-549, no. : 390-401.

Journal article
Published: 07 March 2016 in IEEE Transactions on Geoscience and Remote Sensing
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We developed a large-area preprocessing framework for multisensor Landsat data, capable of processing large data volumes. Cloud and cloud shadow detection is performed by a modified Fmask code. Surface reflectance is inferred from Tanré's formulation of the radiative transfer, including adjacency effect correction. A precompiled MODIS water vapor database provides daily or climatological fallback estimates. Aerosol optical depth (AOD) is estimated over dark objects (DOs) that are identified in a combined database and image-based approach, where information on their temporal persistency is utilized. AOD is inferred with consideration of the actual target reflectance and background contamination effect. In case of absent DOs in bright scenes, a fallback approach with a modeled AOD climatology is used instead. Topographic normalization is performed by a modified C-correction. The data are projected into a single coordinate system and are organized in a gridded data structure for simplified pixel-based access. We based the assessment of the produced data set on an exhaustive analysis of overlapping pixels: 98.8% of the redundant overlaps are in the range of the expected ±2.5% overall radiometric algorithm accuracy. AOD is in very good agreement with Aerosol Robotic Network sunphotometer data (R 2 : 0.72 to 0.79, low intercepts, and slopes near unity). The uncertainty in using the water vapor fallback climatology is approximately ±2.8% for the TM SWIR1 band in the wet season. The topographic correction was considered successful by an investigation of the nonrelationship between the illumination angle and the corrected radiance.

ACS Style

David Frantz; Achim Röder; Marion Stellmes; Joachim Hill. An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications. IEEE Transactions on Geoscience and Remote Sensing 2016, 54, 3928 -3943.

AMA Style

David Frantz, Achim Röder, Marion Stellmes, Joachim Hill. An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications. IEEE Transactions on Geoscience and Remote Sensing. 2016; 54 (7):3928-3943.

Chicago/Turabian Style

David Frantz; Achim Röder; Marion Stellmes; Joachim Hill. 2016. "An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications." IEEE Transactions on Geoscience and Remote Sensing 54, no. 7: 3928-3943.

Original articles
Published: 13 July 2015 in Remote Sensing Letters
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We developed a spatio-temporal path reflectance climatology for use in atmospheric corrections for a Landsat pre-processing framework. The climatology is intended as a fallback strategy for aerosol estimation in bright Southern African savannah ecosystems where the rarity of dark objects decreases the applicability of common image-based aerosol estimation strategies and the widespread burning prohibits the use of a fixed aerosol loading. We predicted the climatological path reflectance surface by applying a multivariate regression model to all available path reflectance retrievals on basis of the geolocation and the days of the year on which the data were acquired. The resulting predictions are able to successfully model major spatio-temporal gradients of the path reflectance distribution. The prediction error (weighted root mean squared Error at 0.483 µm) was less than 1% reflectance while the prediction itself varied by 4.6% reflectance. Thus, using the modelled climatology for atmospheric correction is favourable compared to a fixed aerosol content.

ACS Style

David Frantz; A. Röder; Marion Stellmes; J. Hill. On the derivation of a spatially distributed aerosol climatology for its incorporation in a radiometric Landsat pre-processing framework. Remote Sensing Letters 2015, 6, 647 -656.

AMA Style

David Frantz, A. Röder, Marion Stellmes, J. Hill. On the derivation of a spatially distributed aerosol climatology for its incorporation in a radiometric Landsat pre-processing framework. Remote Sensing Letters. 2015; 6 (8):647-656.

Chicago/Turabian Style

David Frantz; A. Röder; Marion Stellmes; J. Hill. 2015. "On the derivation of a spatially distributed aerosol climatology for its incorporation in a radiometric Landsat pre-processing framework." Remote Sensing Letters 6, no. 8: 647-656.

Journal article
Published: 01 January 2015 in Land Use Policy
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ACS Style

Achim Röder; Michael Pröpper; Marion Stellmes; Anne Schneibel; Joachim Hill. Assessing urban growth and rural land use transformations in a cross-border situation in Northern Namibia and Southern Angola. Land Use Policy 2015, 42, 340 -354.

AMA Style

Achim Röder, Michael Pröpper, Marion Stellmes, Anne Schneibel, Joachim Hill. Assessing urban growth and rural land use transformations in a cross-border situation in Northern Namibia and Southern Angola. Land Use Policy. 2015; 42 ():340-354.

Chicago/Turabian Style

Achim Röder; Michael Pröpper; Marion Stellmes; Anne Schneibel; Joachim Hill. 2015. "Assessing urban growth and rural land use transformations in a cross-border situation in Northern Namibia and Southern Angola." Land Use Policy 42, no. : 340-354.

Book chapter
Published: 27 January 2014 in Remote Sensing and Digital Image Processing
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Understanding the impact of land transformation processes on ecosystem services (ESS) is an essential prerequisite for drafting and implementing sustainable land management concepts. This study presents an analysis of land transformation processes in Horqin Sandy Lands, one of the dry areas in Inner Mongolia (China). It aims at demonstrating the impacts of governmental management policies on land use change and its impact on the long-term availability of important ecosystem services. Spectral mixture analysis is applied to a calibrated time series of Landsat-TM/ETM+ images which covers a period of 20 years (1987–2007); the mixture model comprises three spectral end-members (Green Vegetation, Mobile Sand, Water) which are conceived as surrogates for important ecosystem services. Changing land surface conditions are identified through linear trend analysis of end-member proportions and by mapping the spatial extension of specific surface types at subsequent dates within the observation period. For translating the derived change rates into readjustments of selected ESS-indicators a simple linear model is proposed. Fuelled by long-term satellite observations, the synoptic representation of changing ecosystem services forms the basis for addressing synergies and trade-offs between ecological and societal well-being. The case of Horqin Sandy Lands, where new land use concepts are implemented by promoting selected ecosystem services at the cost of others, provides a striking example for these mechanisms.

ACS Style

Joachim Hill; Marion Stellmes; Changyao Wang. Land Transformation Processes in NE China: Tracking Trade-Offs in Ecosystem Services Across Several Decades with Landsat-TM/ETM+ time Series. Remote Sensing and Digital Image Processing 2014, 383 -409.

AMA Style

Joachim Hill, Marion Stellmes, Changyao Wang. Land Transformation Processes in NE China: Tracking Trade-Offs in Ecosystem Services Across Several Decades with Landsat-TM/ETM+ time Series. Remote Sensing and Digital Image Processing. 2014; ():383-409.

Chicago/Turabian Style

Joachim Hill; Marion Stellmes; Changyao Wang. 2014. "Land Transformation Processes in NE China: Tracking Trade-Offs in Ecosystem Services Across Several Decades with Landsat-TM/ETM+ time Series." Remote Sensing and Digital Image Processing , no. : 383-409.

Journal article
Published: 31 December 2013 in Biodiversity and Ecology
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Biodiversity & Ecology (B&E) - University of Hamburg - Biocenter Klein Flottbek and Botanical Garden

ACS Style

Marion Stellmes. Fire frequency, fire seasonality and fire intensity within the Okavango region derived from MODIS fire products. Biodiversity and Ecology 2013, 5, 351 .

AMA Style

Marion Stellmes. Fire frequency, fire seasonality and fire intensity within the Okavango region derived from MODIS fire products. Biodiversity and Ecology. 2013; 5 ():351.

Chicago/Turabian Style

Marion Stellmes. 2013. "Fire frequency, fire seasonality and fire intensity within the Okavango region derived from MODIS fire products." Biodiversity and Ecology 5, no. : 351.

Journal article
Published: 31 December 2013 in Biodiversity & Ecology
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ACS Style

Marion Stellmes. Okavango Basin - Earth Observation. Biodiversity & Ecology 2013, 5, 23 .

AMA Style

Marion Stellmes. Okavango Basin - Earth Observation. Biodiversity & Ecology. 2013; 5 ():23.

Chicago/Turabian Style

Marion Stellmes. 2013. "Okavango Basin - Earth Observation." Biodiversity & Ecology 5, no. : 23.

Journal article
Published: 01 January 2013 in Land Use Policy
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Marion Stellmes; Achim Röder; T. Udelhoven; J. Hill. Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data. Land Use Policy 2013, 30, 685 -702.

AMA Style

Marion Stellmes, Achim Röder, T. Udelhoven, J. Hill. Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data. Land Use Policy. 2013; 30 (1):685-702.

Chicago/Turabian Style

Marion Stellmes; Achim Röder; T. Udelhoven; J. Hill. 2013. "Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data." Land Use Policy 30, no. 1: 685-702.

Journal article
Published: 26 November 2012 in Remote Sensing
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In order to monitor dryness stress under controlled conditions, we set up an experiment with beech seedlings in plant pots and built a platform for observing the seedlings with field imaging spectroscopy. This serves as a preparation for multi-temporal hyperspectral air- and space-borne data expected to be available in coming years. Half of the trees were watered throughout the year; the other half were cut off from water supply for a five-week period in late summer. Plant health and soil, as well as leaf water status, were monitored. Moreover, hyperspectral images of the trees were acquired four times during the experiment. Results show that the experimental imaging setup is well suited for recording hyperspectral images of objects, like the beech pots, under natural illumination conditions. The high spatial resolution makes it feasible to discern between background, soil, wood, green leaves and brown leaves. Furthermore, it could be shown that dryness stress is detectable from an early stage even in the limited spectral range considered. The decline of leaf chlorophyll over time was also well monitored using imaging spectroscopy data.

ACS Style

Henning Buddenbaum; Oksana Stern; Marion Stellmes; Johannes Stoffels; Pyare Pueschel; Joachim Hill; Willy Werner. Field Imaging Spectroscopy of Beech Seedlings under Dryness Stress. Remote Sensing 2012, 4, 3721 -3740.

AMA Style

Henning Buddenbaum, Oksana Stern, Marion Stellmes, Johannes Stoffels, Pyare Pueschel, Joachim Hill, Willy Werner. Field Imaging Spectroscopy of Beech Seedlings under Dryness Stress. Remote Sensing. 2012; 4 (12):3721-3740.

Chicago/Turabian Style

Henning Buddenbaum; Oksana Stern; Marion Stellmes; Johannes Stoffels; Pyare Pueschel; Joachim Hill; Willy Werner. 2012. "Field Imaging Spectroscopy of Beech Seedlings under Dryness Stress." Remote Sensing 4, no. 12: 3721-3740.

Journal article
Published: 15 June 2011 in Remote Sensing of Environment
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Drylands cover about 41% of the globe's surface and provide important ecosystem services, but land use and climate change exert considerable pressure on these ecosystems. Both of these drivers frequently result in gradual vegetation change and landscape-scale trend analysis based on yearly vegetation estimates can capture such changes. Such trend analyses based on high-resolution time series of satellite imagery have so far not widely been used and existing studies in drylands relied on different vegetation measures. Spectral mixture analysis (SMA) has been chosen due to its superiority to simpler vegetation estimates in quantifying vegetation cover in single-date studies, however SMA can be challenging to implement for large areas. Here, we quantify the trade-off involved when using simple vegetation estimates instead of SMA fractions for subsequent trend analyses. We calculated NDVI, SAVI and Tasseled Cap Greenness, as well as SMA green vegetation fractions for a time series of Landsat images from 1984–2005 for a study region in Crete. Linear trend analysis showed that trend coefficients and the spatial patterns of trends were similar across all vegetation estimates and the entire study region, especially for areas where vegetation changed gradually. On average, trends based on simple measures differed less than 5% from SMA-based trends with decreasing similarity in trend results from Tasseled Cap Greenness to SAVI and NDVI. Vegetation estimates differed markedly in their response to disturbance events such as fires. Trend analyses based on qualitative measures can easily be applied across very large areas and using multi-sensor time series based on high-resolution data. While the subtle differences between vegetation estimates may still be important for some applications, the robustness of trend analyses regarding the choice of vegetation estimate bears considerable promise to reconstruct fine-scale vegetation dynamics and land use histories and to assess climate change impacts on the world's drylands.

ACS Style

Ruth Sonnenschein; Tobias Kuemmerle; Thomas Udelhoven; Marion Stellmes; Patrick Hostert. Differences in Landsat-based trend analyses in drylands due to the choice of vegetation estimate. Remote Sensing of Environment 2011, 115, 1408 -1420.

AMA Style

Ruth Sonnenschein, Tobias Kuemmerle, Thomas Udelhoven, Marion Stellmes, Patrick Hostert. Differences in Landsat-based trend analyses in drylands due to the choice of vegetation estimate. Remote Sensing of Environment. 2011; 115 (6):1408-1420.

Chicago/Turabian Style

Ruth Sonnenschein; Tobias Kuemmerle; Thomas Udelhoven; Marion Stellmes; Patrick Hostert. 2011. "Differences in Landsat-based trend analyses in drylands due to the choice of vegetation estimate." Remote Sensing of Environment 115, no. 6: 1408-1420.