Dr. Dirk Pflugmacher
Profil
Zusammenfassung
Dr. Dirk Pflugmacher entwickelt Methoden zur Fernerkundung von Waldökosystemen und Landnutzungsveränderungen. Er nutzt Satellitendaten (insbesondere Landsat und Sentinel) und zeitliche Datenreihen, um Waldgesundheit, Baumartenzusammensetzung, Störungen wie Waldbrände und Waldsterben sowie Landnutzungswandel großflächig zu erfassen und zu modellieren. Seine Expertise ermöglicht es Unternehmen und Behörden, Waldbestände, Agrarflächen und Ökosystemveränderungen systematisch zu überwachen und Risiken wie Waldbrandgefahr vorherzusagen.
Skills
Stammdaten
Identität, Organisation und Kontakt aus HU-FIS.
Forschungsthemen1
Verbundvorhaben: Kartierung der Waldbrandgefahr mit fernerkundlichen und meteorologischen Daten; Teilvorhaben 2: Satellitengestützte Erfassung und Charakterisierung historischer und aktueller Waldbrände für die Modellierung der Waldbrandgefahr
Quelle ↗Förderer: Bundesministerium für Landwirtschaft, Ernährung und Heimat Zeitraum: 07/2020 - 12/2022 Projektleitung: Dr. Dirk Pflugmacher
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Publikationen25
Top 25 nach Zitationen — Quelle: OpenAlex (BAAI/bge-m3 embedded für Matching).
Frontiers in Ecology and the Environment · 384 Zitationen · DOI
When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote‐sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser‐scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, long‐term trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.
Remote Sensing of Environment · 378 Zitationen · DOI
Monitoring agricultural systems becomes increasingly important in the context of global challenges like climate change, biodiversity loss, population growth, and the rising demand for agricultural products. High-resolution, national-scale maps of agricultural land are needed to develop strategies for future sustainable agriculture. However, the characterization of agricultural land cover over large areas and for multiple years remains challenging due to the locally diverse and temporally variable characteristics of cultivated land. We here propose a workflow for generating national agricultural land cover maps on a yearly basis that accounts for varying environmental conditions. We tested the approach by mapping 24 agricultural land cover classes in Germany for the three years 2017, 2018, and 2019, in which the meteorological conditions strongly differed. We used a random forest classifier and dense time series data from Sentinel-2 and Landsat 8 in combination with monthly Sentinel-1 composites and environmental data and evaluated the relative importance of optical, radar, and environmental data. Our results show high overall accuracy and plausible class accuracies for the most dominant crop types across different years despite the strong inter-annual meteorological variability and the presence of drought and non-drought years. The maps show high spatial consistency and good delineation of field parcels. Combining optical, SAR, and environmental data increased overall accuracies by 6% to 10% compared to single sensor approaches, in which optical data outperformed SAR. Overall accuracy ranged between 78% and 80%, and the mapped areas aligned well with agricultural statistics at the regional and national level. Based on the multi-year dataset we mapped major crop sequences of cereals and leaf crops. Most crop sequences were dominated by winter cereals followed by summer cereals. Monocultures of summer cereals were mainly revealed in the Northwest of Germany. We showcased that high spatial and thematic detail in combination with annual mapping will stimulate research on crop cycles and studies to assess the impact of environmental policies on management decisions. Our results demonstrate the capabilities of integrated optical time series and SAR data in combination with variables describing local and seasonal environmental conditions for annual large-area crop type mapping.
Nature Communications · 370 Zitationen · DOI
Abstract Mortality is a key indicator of forest health, and increasing mortality can serve as bellwether for the impacts of global change on forest ecosystems. Here we analyze trends in forest canopy mortality between 1984 and 2016 over more than 30 Mill. ha of temperate forests in Europe, based on a unique dataset of 24,000 visually interpreted spectral trajectories from the Landsat archive. On average, 0.79% of the forest area was affected by natural or human-induced mortality annually. Canopy mortality increased by +2.40% year –1 , doubling the forest area affected by mortality since 1984. Areas experiencing low-severity mortality increased more strongly than areas affected by stand-replacing mortality events. Changes in climate and land-use are likely causes of large-scale forest mortality increase. Our findings reveal profound changes in recent forest dynamics with important implications for carbon storage and biodiversity conservation, highlighting the importance of improved monitoring of forest mortality.
Kooperationen1
Bestätigte Forscher↔Partner-Paare aus HU-FIS — Gold-Standard-Positive für das Matching.
Verbundvorhaben: Kartierung der Waldbrandgefahr mit fernerkundlichen und meteorologischen Daten; Teilvorhaben 2: Satellitengestützte Erfassung und Charakterisierung historischer und aktueller Waldbrände für die Modellierung der Waldbrandgefahr
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