TY - JOUR A1 - Luft, Laura A1 - Neumann, C. A1 - Itzerott, S. A1 - Lausch, A. A1 - Doktor, D. A1 - Freude, M. A1 - Blaum, Niels A1 - Jeltsch, Florian T1 - Digital and real-habitat modeling of Hipparchia statilinus based on hyper spectral remote sensing data JF - International journal of environmental science and technology N2 - The abandonment of military areas leads to succession processes affecting valuable open-land habitats and is considered to be a major threat for European butterflies. We assessed the ability of hyper spectral remote sensing data to spatially predict the occurrence of one of the most endangered butterfly species (Hipparchia statilinus) in Brandenburg (Germany) on the basis of habitat characteristics at a former military training area. Presence-absence data were sampled on a total area of 36 km(2), and N = 65 adult individuals of Hipparchia statilinus could be detected. The floristic composition within the study area was modeled in a three-dimensional ordination space. Occurrence probabilities for the target species were predicted as niches between ordinated floristic gradients by using Regression Kriging of Indicators. Habitat variance could be explained by up to 81 % with spectral variables at a spatial resolution of 2 x 2 m by transferring PLSR models to imagery. Ordinated ecological niche of Hipparchia statilinus was tested against environmental predictor variables. N = 6 variables could be detected to be significantly correlated with habitat preferences of Hipparchia statilinus. They show that Hipparchia statilinus can serve as a valuable indicator for the evaluation of the conservation status of Natura 2000 habitat type 2330 (inland dunes with open Corynephorus and Agrostis grasslands) protected by the Habitat Directive (Council Directive 92/43/EEC). The authors of this approach, conducted in August 2013 at Doberitzer Heide Germany, aim to increase the value of remote sensing as an important tool for questions of biodiversity research and conservation. KW - Habitat gradients KW - Military areas KW - Natura 2000 KW - hyper spectral KW - Vegetation continuum KW - Kriging Y1 - 2016 U6 - https://doi.org/10.1007/s13762-015-0859-1 SN - 1735-1472 SN - 1735-2630 VL - 13 SP - 187 EP - 200 PB - Springer CY - New York ER - TY - JOUR A1 - Luft, Laura A1 - Neumann, Carsten A1 - Freude, Matthias A1 - Blaum, Niels A1 - Jeltsch, Florian T1 - Hyperspectral modeling of ecological indicators - A new approach for monitoring former military training areas JF - Ecological indicators : integrating monitoring, assessment and management N2 - Military areas are valuable habitats and refuges for rare and endangered plants and animals. We developed a new approach applying innovative methods of hyperspectral remote sensing to bridge the existing gap between remote sensing technology and the demands of the nature conservation community. Remote sensing has already proven to be a valuable monitoring instrument. However, the approaches lack the consideration of the demands of applied nature conservation which includes the legal demands of the EU Habitat Directive. Following the idea of the Vital Signs Monitoring in the USA, we identified a subset of the highest priority monitoring indicators for our study area. We analyzed continuous spectral response curves and tested the measurability of N=19 indicators on the basis of complexity levels aggregated from extensive vegetation assemblages. The spectral differentiability for the floristic as well as faunistic indicators revealed values up to 100% accuracy. We point out difficulties when it comes to distinguishing faunistic habitat requirements of several species adapted to dry open landscapes, which in this case results in OVERALL ACCURACY of 67, 87-95, and 35% in the error matrix. In summary, we provide an applicable and feasible method to facilitating monitoring military areas by hyperspectral remote sensing in the following. (C) 2014 Elsevier Ltd. All rights reserved. KW - Ecological health KW - Fauna KW - Flora KW - Hyperspectral remote sensing KW - Military conversion KW - Natura 2000 monitoring Y1 - 2014 U6 - https://doi.org/10.1016/j.ecolind.2014.06.025 SN - 1470-160X SN - 1872-7034 VL - 46 SP - 264 EP - 285 PB - Elsevier CY - Amsterdam ER -