Kartographie, GIS und Fernerkundung

Was wir hier machen...


Die Abteilung Kartographie, GIS & Fernerkundung des Geographischen Instituts arbeitet an den Herausforderungen, die sich durch den Globalen Wandel und Klimawandel ergeben. Durch Auflösung der Grenze zwischen gesellschaftlichen und naturwissenschaftlichen Forschungsansätzen erforscht die Abteilung das Ausmaß des menschlichen Einflusses auf den Globalen Wandel. Unser Ziel ist es, die Landoberflächenprozesse der Erde sowie die Landschaftsdynamik besser zu verstehen und die Art und Weise wie die Menschen damit interagieren. Die Entwicklung von integrativen Methoden zur räumlich verteilten Analyse von wechselwirkenden Prozessen an der Erdoberfläche spielen in unserer Forschung und Ausbildung eine zentrale Rolle. Dabei versuchen wir das Verständniss räumlicher Interaktion durch prozessorientierte Modelle und durch die Nutzung von modernen Monitoringtechniken (z.B. Fernerkundung) und Methoden zur Erfassung und Verarbeitung von Umweltinformation (z.B. GIS) zu verbessern.


Aktuelle Publikationen

Negussie, K. G., Wyss, D., Knox, N., Vallejo Orti, M., Corral-Pazos-de-Provens, E., & Kappas, M. (2022). Evaluating SWAT model for streamflow estimation in the semi-arid Okavango-Omatako catchment, Namibia. African Journal of Environmental Science and Technology , 16(11), 385-403.
https://doi.org/10.5897/AJEST2022.3155

Xue, L., Kappas, M., Wyss, D., Putzenlechner, B. (2022): Assessing the Drought Variability in Northeast China over Multiple Temporal and Spatial Scales. Atmosphere 13(9). https://doi.org/10.3390/atmos13091506

Erdanaev, E.; Kappas, M.; Wyss, D. Irrigated Crop Types Mapping in Tashkent Province of Uzbekistan with Remote Sensing-Based Classification Methods (2022). Sensors 22, 5683.
https://doi.org/10.3390/s22155683

Chand, D., Berg, L. K., Tagestad, J., Putzenlechner, B., Yang, Z., Tai, S., Fast, J. D. (2022). Fine Scale Variability in Green Vegetation Fraction Over the Southern Great Plains Using Sentinel-2 Satellite: A Case Study. Remote Sensing Applications: Society and Environment https://doi.org/10.1016/j.rsase.2022.100799

Wyss, D., Negussie, K., Staacke, A., Karnagel, A., Engelhardt, M., & Kappas, M. (2022). A comparative analysis of MODIS-derived drought indices for Northern and Central Namibia. African Journal of Environmental Science and Technology , 16(5), 173-191. https://doi.org/10.5897/AJEST2022.3096

Xue, L., Kappas, M., Wyss, D., Wang, C., Putzenlechner, B., Thi, N. P., Chen, J. (2022). Assessment of Climate Change and Human Activities on Vegetation Development in Northeast China. Sensors 22(7) https://doi.org/10.3390/s22072509

Jiquan Chen, Ranjeet John, Jing Yuan, Elizabeth A Mack, Pavel Groisman, Ginger Allington, Jianguo (Jingle) Wu, Peilei Fan, Kirsten M de Beurs, Arnon Karnieli, Garik Gutman, Martin Kappas, Gang Dong, Fangyuan Zhao, Zutao Ouyang, Amber L Pearson, Beyza Şat, Norman A Graham, Changliang Shao, Anna K Graham, Geoffrey M Henebry, Zhichao Xue, Amarjargal Amartuvshin, Luping Qu, Hogeun Park, Xiaoping Xin, Jingyan Chen, Li Tian, Colt Knight, Maira Kussainova, Fei Li, Christine Fürst and Jiaguo Qi. (2022). Sustainability challenges for the social-environmental systems across the Asian drylands belt. Environ. Research Letters.
https://doi.org/10.1088/1748-9326/ac472f.

Putzenlechner, B., Marzahn, P., Koal, P., Sanchez-Azofeifa, A. (2022). Fractional vegetation cover derived from UAV and Sentinel-2 imagery as a proxy for in situ FAPAR in a dense mixed-coniferous forest? Remote Sensing 14(2): 380. https://doi.org/10.3390/rs14020380

Chunyan Xu, Martin Kappas, Stefan Hohnwald, Daniel Wyss, José Daniel Lencinas, Diegeo Mohr-Bell (2021). Monitoring Forest Fire Severity Using Time Series Of Landsat Data – A Case Study Of Lago Epuyén In Patagonia, Argentinia. GEOÖKO, Volume/Band XLII, 5 - 38, Göttingen 2021.

Xue, Z.; Kappas, M.; Wyss, D. (2021). Spatio-Temporal Grassland Development in Inner Mongolia after Implementation of the First Comprehensive Nation-Wide Grassland Conservation Program. Land 2021, 10, 38. https://doi.org/10.3390/land10010038

Pham Thi, N.; Kappas, M.; Faust, H. Impacts of Agricultural Land Acquisition for Urbanization on Agricultural Activities of affected Households: A Case Study in Huong Thuy Town, Thua Thien Hue Province, Vietnam. Sustainability 2021, 13, 8559. https://doi.org/10.3390/su13158559

Oyudari Vova, Martin Kappas, Tsolmon Renchin, Steven R. Fassnacht. (2020). Extreme Climate Event and Its Impact on Landscape Resilience in Gobi Region of Mongolia. Remote Sens. 2020, 12, 2881; doi:10.3390/rs12182881

The Dung Nguyen, Kappas, M. (2020). "Estimating the Aboveground Biomass of an Evergreen Broadleaf Forest in Xuan Lien Nature Reserve, Thanh Hoa, Vietnam, Using SPOT-6 Data and the Random Forest Algorithm," International Journal of Forestry Research, Vol. 2020, Article ID 4216160, 2020. https://doi.org/10.1155/2020/4216160

Fierke, J., Kappas, M., Wyss, D. (2020). Quantifying forest cover at Mount Kenya: Use of Sentinel-2 for a discrimination of tropical tree composites. African Journal of Environmental Science and Technology, Vol. 14(6), pp. 159 176, June 2020, Article Number: 7C896DC64182; ISSN: 1996 0786, DOI: 10.5897/AJEST2020.2832

Malena Andernach, Daniel Wyss and Martin Kappas (2020). An Evaluation of the Land Cover Classification Product Sentinel 2 Prototype Land Cover 20 m Map of Africa 2016 for Namibia. Namibian Journal of the Environment (NJE) 4 A: 1-12

Oyudari Vova, Martin Kappas, Ammar Rafiei Emmam. (2019). Comparison of Satellite Soil Moisture Products in Mongolia and Their Relation to Grassland Condition. Land 2019, 8, 142; doi:10.3390/land8090142

Rafiei Emam A., Kappas M., Fassnacht S., LINH N.H.K. (2018) Uncertainty analysis of hydrological modeling in a tropical area using different algorithms, Front. Earth Sci. (2018).

Tung GiaPham, Hung Trong Nguyen, Martin Kappas (2018) Assessment of soil quality indicators under different agricultural land uses and topographic aspects in Central Vietnam. International Soil and Water Conservation Research. https://doi.org/10.1016/j.iswcr.2018.08.001

Thanh Noi, P., Kappas, M. (2018): Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery. Sensors 2018 (1), 18, 18; doi:10.3390/s18010018