Früher|Nächster

Studie zur Anwendbarkeit räumlicher Herunterskalierungsmethoden für Nachtlichtbilder städtischer Seen im Jangtse-Einzugsgebiet (NPP-VIIRS-NTL)

  • role： First author第一作者
  • Affiliation：

    School of Geography and Environment/Key Laboratory of Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China

  • Email：zhawx@jxnu.edu.cn
  • Introduction：查文娴，研究方向为环境遥感。E-mail：zhawx@jxnu.edu.cn
ZHA Wenxian1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geography and Environment/Key Laboratory of Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China

  • Email：zhm8012@jxnu.edu.cn
  • Introduction：赵红梅，研究方向为环境遥感。E-mail：zhm8012@jxnu.edu.cn
ZHAO Hongmei1*,  
  • Affiliation：

    School of Information and Software Engineering, East China Jiaotong University, Nanchang 330013, China

DENG Zhigang2,  
  • Affiliation：

    State Key Laboratory of Tropical Oceanography & Guangdong Key Laboratory of Ocean Remote Sensing, South China Sea Institute of Oceanology Chinese Academy of Sciences, Guangzhou 510000, China

LI Wenkai3

Resümee

Nachtsichtfernerkundungsbilder werden umfassend in den Bereichen der städtischen Umwelt, sozialen Wirtschaft, ökologischen Schutz und der Bewertung nach bewaffneten Konflikten eingesetzt. Aufgrund des Fehlens langfristiger, hochauflösender Nachtsichtfernerkundungsdaten ist die Bewertung der städtischen Gewässerumgebung in der Nachtsichtfernerkundungsforschung jedoch relativ begrenzt. Diese Studie zielt darauf ab, die Lücke in der Forschung der Binnengewässerumgebung durch Nachtsichtfernerkundungsdaten zu schließen, indem städtische Seen unterschiedlicher Form mit einer Fläche von mehr als 3 km² im Einzugsgebiet des Jangtse untersucht werden. Es werden Parameter der Fernerkundungsbewertung der Wasserumgebung kombiniert, darunter die Seebrightness-Temperatur LBT, der schwebende Algenindex FAI und der Wasserfarbenindex FUI. Dabei werden für thermisch-infrarotbasierte Fernerkundungsdaten geeignete räumliche Herunterskalierungsmethoden wie DisTrad, geographisch gewichtete Regression GWR und Random Forest RF verwendet. Durch Einführung objektsorientierter Theorien und korrelative statistische Methoden wird die beste räumliche Herunterskalierungsmethode für die Nachtlichtbilder (NTL) des Suomi-NPP-Satelliten mit dem Visible Infrared Imaging Radiometer Suite (VIIRS) untersucht. Die Ergebnisse zeigen, dass die objektsorientierte DisTrad-Methode (OD-TA) basierend auf LBT und FAI eine gewisse Stabilität aufweist, während die objektsorientierte geographisch gewichtete Regression (OGWR-TU) basierend auf LBT und FUI bei großen (>10 km²), in der Form komplexen (PARA>65) städtischen Seen wie Dian-See und Chao-See ausgezeichnete Leistungen zeigt; die räumliche Morphologie der Seen und die sozial-kulturellen Merkmale der nächtlichen Beleuchtung am Ufer sind die Hauptfaktoren, die die Anwendbarkeit der räumlichen Herunterskalierungsmethoden beeinflussen. Die Ergebnisse dieser Studie schließen nicht nur die Lücke an langfristigen hochauflösenden NTL-Bildern für Wassergebiete, sondern bieten auch methodische und datenbasierte Unterstützung für die Bewertung der Lichtverschmutzung in städtischen Seen und die Analyse der sozial-kulturellen Umwelt an den Seenrändern.

Schlüsselwort

Nachtlicht;Brightness-Temperatur;räumliche Herunterskalierung;NPP-VIIRS;städtische Seen

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