Search

Your search keyword '"Kleinschmit, Birgit"' showing total 345 results
Start Over Author "Kleinschmit, Birgit"
345 results on '"Kleinschmit, Birgit"'

3. Weakly Supervised Semantic Segmentation of Remote Sensing Images for Tree Species Classification Based on Explanation Methods

Author

Ahlswede, Steve, Thekke-Madam, Nimisha, Schulz, Christian, Kleinschmit, Birgit, and Demir, Begüm

Subjects
Computer Science - Computer Vision and Pattern Recognition, I.4.6, I.5.3
Abstract

The collection of a high number of pixel-based labeled training samples for tree species identification is time consuming and costly in operational forestry applications. To address this problem, in this paper we investigate the effectiveness of explanation methods for deep neural networks in performing weakly supervised semantic segmentation using only image-level labels. Specifically, we consider four methods:i) class activation maps (CAM); ii) gradient-based CAM; iii) pixel correlation module; and iv) self-enhancing maps (SEM). We compare these methods with each other using both quantitative and qualitative measures of their segmentation accuracy, as well as their computational requirements. Experimental results obtained on an aerial image archive show that:i) considered explanation techniques are highly relevant for the identification of tree species with weak supervision; and ii) the SEM outperforms the other considered methods. The code for this paper is publicly available at https://git.tu-berlin.de/rsim/rs_wsss., Comment: 4 pages, 1 figure, submitted to IEEE Geosciences and Remote Sensing Symposium (2022)

Published
2022

17. Relating soil moisture and Sentinel-2 vegetation index patterns to spruce bark beetle infestations prior to outbreak.

Author

Xu, Chunyan, Förster, Michael, Gränzig, Tobias, May, Johannes, and Kleinschmit, Birgit

Subjects
BARK beetles, SOIL moisture, VEGETATION patterns, SILVER fir, REMOTE sensing, NORWAY spruce
Abstract

Central Europe experienced severe droughts from 2018 to 2020, which led to bark beetle infestations in Norway spruce (Picea abies L.). While recent studies have identified these droughts as a major factor in the dieback of spruces, the exact mechanism through which drought stress influences spruce vitality and increases vulnerability to infestations is not well understood. To gain insights into the spatial and temporal relations between infestations and drought stress, this study compared soil moisture index (SMI) data for the entire soil layer from the German Drought Monitor and Sentinel-2 satellite time series for healthy and bark beetle infested spruce stands preceding the infestation. The study used t-tests to compare pre-infestation monthly sums of SMI and vegetation indices (VIs) for healthy and infested stands. Yearly trajectories of six VIs were used to compare the separability between infested and healthy plots. The results showed that the monthly sum values of SMI for healthy spruce plots were statistically significantly higher than the infested plots from May 2017 to January 2018, while the monthly sum values of Inverted Red Edge Chlorophyll Index of healthy spruce plots were significantly higher than infested plots during growing seasons. With these findings, the study provides useful information for the understanding of the relation of soil moisture and remote sensing VIs patterns in relation to bark beetle infestations. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

29. Towards an automatic segmentation and classification of multi-source point clouds for Arctic to boreal permafrost ecosystem analysis

Author

Döpper, Veronika, primary, Jackisch, Robert, additional, Gloy, Josias, additional, Rettelbach, Tabea, additional, Boike, Julia, additional, Grünberg, Inge, additional, Nitze, Ingmar, additional, Runge, Alexandra, additional, Inauen, Cornelia, additional, Barth, Sophia, additional, Helm, Veit, additional, Enguehard, Léa, additional, Kleinschmit, Birgit, additional, Herzschuh, Ulrike, additional, Heim, Birgit, additional, Grosse, Guido, additional, and Kruse, Stefan, additional

Published
2023
Full Text
View/download PDF

32. TreeSatAI Benchmark Archive : a multi-sensor, multi-label dataset for tree species classification in remote sensing

Author

Ahlswede, Steve, Schulz, Christian, Gava, Christiano, Helber, Patrick, Bischke, Benjamin, Förster, Michael, Arias, Florencia, Hees, Jörn, Demir, Begüm, Kleinschmit, Birgit, Ahlswede, Steve, Schulz, Christian, Gava, Christiano, Helber, Patrick, Bischke, Benjamin, Förster, Michael, Arias, Florencia, Hees, Jörn, Demir, Begüm, and Kleinschmit, Birgit

Abstract

Airborne and spaceborne platforms are the primary data sources for large-scale forest mapping, but visual interpretation for individual species determination is labor-intensive. Hence, various studies focusing on forests have investigated the benefits of multiple sensors for automated tree species classification. However, transferable deep learning approaches for large-scale applications are still lacking. This gap motivated us to create a novel dataset for tree species classification in central Europe based on multi-sensor data from aerial, Sentinel-1 and Sentinel-2 imagery. In this paper, we introduce the TreeSatAI Benchmark Archive, which contains labels of 20 European tree species (i.e., 15 tree genera) derived from forest administration data of the federal state of Lower Saxony, Germany. We propose models and guidelines for the application of the latest machine learning techniques for the task of tree species classification with multi-label data. Finally, we provide various benchmark experiments showcasing the information which can be derived from the different sensors including artificial neural networks and tree-based machine learning methods. We found that residual neural networks (ResNet) perform sufficiently well with weighted precision scores up to 79 % only by using the RGB bands of aerial imagery. This result indicates that the spatial content present within the 0.2 m resolution data is very informative for tree species classification. With the incorporation of Sentinel-1 and Sentinel-2 imagery, performance improved marginally. However, the sole use of Sentinel-2 still allows for weighted precision scores of up to 74 % using either multi-layer perceptron (MLP) or Light Gradient Boosting Machine (LightGBM) models. Since the dataset is derived from real-world reference data, it contains high class imbalances. We found that this dataset attribute negatively affects the models' performances for many of the underrepresented classes (i.e., scarce tree species

Published
2023

39. Mehr als 'Gute fachliche Praxis'

Author

Dieter, Matthias, Schraml, Ulrich, Möhring, Bernhard, Bauhus, Jürgen, Endres, Ewald, Lang, Friederike, Seeling, Ute, Farwig, Nina, Hafner, Annette, Kätzel, Ralf, Kleinschmit, Birgit, Lindner, Marcus, Müller, Jörg, Niekisch, Manfred, and Richter, Klaus

Abstract

Um Wälder und ihre Ökosystemleistungen auch unter den Bedingungen des globalen Wandels zu erhalten und nachhaltig nutzen zu können, wird im Kontext der geplanten Novellierung des Bundeswaldgesetzes unter dem Begriff der Guten fachlichen Praxis (GfP) die Konkretisierung von Mindeststandards für die Waldwirtschaft diskutiert. Dies trifft insbesonder auf naturschutzfachliche Mindeststandards zu. Im deutschen Forstrecht wird der Begriff der Guten fachlichen Praxis bisher nur selten verwandt und wenn, dann als abstrakte politische Leitlinie. Er ist inhaltlich ähnlich besetzt wie die sogenannte ordnungsgemäße Forstwirtschaft. Bisher erschwert eine mangelnde Konkretisierung der Guten fachlichen Praxis eine rechtssichere Umsetzung. Der Wissenschaftliche Beirat für Waldpolitik (WBW) schlägt zur Bewältigung der Herausforderungen des globalen Wandels als Alternative zur Guten fachlichen Praxis ein umfassenderes Konzept für eine anpassungsfähige forstliche Governance vor. Es zielt auf eine neue Lastenverteilung zwischen Waldeigentümern und Gesellschaft ab und basiert auf einem breiten Instrumentenmix, um eine „Gesellschaftlich erwünschte forstliche Praxis“ zu erreichen. Das Fundament der anpassungsfähigen forstlichen Governance bilden die zwingend erforderlichen, sanktionsbewährten rechtlichen Mindeststandards der Waldbewirtschaftung, die sich aus der Gemeinwohlverpflichtung des Eigentums ergeben. Dazu gehören beispielsweise die Pflicht zur Walderhaltung oder das Betretungsrecht. Weitere Bestandteile des Instrumentenmixes sind, neben den klassischen ordnungsrechtlichen Instrumenten, verschiedene Förderinstrumente (bspw. zur Honorierung von Klimaschutz- oder Biodiversitätsleistungen), strukturelle Instrumente (bspw. zur Stärkung forstlicher Zusammenschlüsse), die Bereitstellung geeigneter Information inklusive der dafür erforderlichen Forschung sowie die Schaffung von Rahmenbedingungen, um Kooperationen mit und zwischen privaten Institutionen zu ermöglichen. Der WBW empfiehlt der Bundesregierung, dieses Stufen-Konzept zur Erreichung der „Gesellschaftlich erwünschten forstlichen Praxis“ bei der Novellierung des Bundeswaldgesetzes zu verankern., Berichte über Landwirtschaft - Zeitschrift für Agrarpolitik und Landwirtschaft, Sonderheft 235 - Januar 2023

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results