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Network for Habitat Monitoring by Airborne-supported Field work – An innovative and effective process in implementation of the Habitat Directive

Final Report Summary - CHANGEHABITATS 2 (Network for Habitat Monitoring by Airborne-supported Field work – An innovative and effective process in implementation of the Habitat Directive)

Executive Summary
The goal of CHANGEHABITATS 2 was the establishment of a long-lasting intersectoral and international network in the field of environmental monitoring between industry and academia. Its aim was to develop operable, time and cost-effective procedures, and (software) solutions for monitoring habitats using innovative airborne data acquisition techniques.
Within the project two complementary remote sensing (RS) data acquisition methods which are currently becoming established in the market were concentrated on: airborne laser scanning (ALS) and airborne hyperspectral imagery (HS), with a major emphasis on ALS. These methods were evaluated and their potential for manual and automatic derivation of habitat parameters was investigated for selected sites. Tight integration of data producers, data processors and end users, building the network both from industry and academia, allowed to develop a fast and efficient automatic software workflow for vegetation classification and mapping, categorizing grassland vegetation by ALS and mapping of grass species by HS, estimation of deadwood and vegetation layers in forests by ALS, and habitat quality monitoring of alkali grasslands by ALS.
Habitat types of relevance in various (Central) European ecoregions (mainly forests and grasslands) were studied both by airborne data acquisition techniques (ALS and HS) and field work. During a total of 10 flight campaigns ALS data were collected by RIEGL in a steppe forest, alkali grasslands and floodplain forests in Eastern Hungary and beech forests in Western Hungary and East Germany. Hyperspectral data were investigated in Western Hungary. Field work on habitat mapping including important habitat characteristics both from a nature conservation and remote sensing point of view was carried out in parallel at these sites. Aerial data processing concentrated on the development of a stepwise detection process for deadwood and vegetation layers in forests, identification of different grassland types and microtopography in alkali grasslands. Structural parameters from aerial survey were correlated with habitat features from field-work (e.g. deadwood, habitat trees, invasive species...) for automatic deduction of habitat parameters. Thus an automatic forest layer identification from ALS data according to Natura 2000 specification was implemented and verified to reliably predict field observations. In the alkali grasslands of Agota-puszta a relationship between fine-scale differences in vertical position and vegetation patterns could be established and eight grassland associations based on micro-relief derived from ALS data could be classified. These findings show that ALS measurements can be used for the classification of open mosaic landscapes, especially those influenced by elevation where ALS has a distinct advantage over other remotely sensed data. ALS data from the Pannonic salt steppe were also used to develop an automated method for calculating Natura 2000 conservation status. Both ecological variables and conservation status, as generated from ALS point rasters by machine learning and fuzzy categorization, were successfully applied in a GIS processing model following the national Hungarian Natura 2000 manual. Thus it could be shown that results from ALS and HS data for habitat assessment are compatible with the current field-based approach.
As a result, ChangeHabitats2 has generated new inputs to rapidly developing data processing and interpretation technologies for complex land cover. The state-of-the-art of habitat monitoring in the EU is expensive and laborious field work. Categorizing vegetation in complex terrain using micro-topographic features derived from ALS point clouds, or estimation of deadwood and vegetation layers in forests by ALS, will not only reduce time for fieldwork, but reduce intersubjective bias in field-work. The new approach for habitat quality assessment by ALS derived parameters yielded in a RS-derived conservation status map that meets the requirements of Natura 2000 monitoring.
Due to the feasibility of supporting time-demanding and expensive field-work in Natura 2000 habitat monitoring by airborne data, we expect that annual costs of at least 0.9 Billion Euros could be saved. In the private and the scientific sector, and across the disciplines of Earth observation and ecology, a network of multi-disciplinary oriented individuals was established that continues to push the frontiers of science forward and transfer the knowledge to the private sector.

Project Website:

Contact details:
Prof. Dr. Hermann Heilmeier
Interdisziplinäres Ökologisches Zentrum (IÖZ), AG Biologie/Ökologie
TU Bergakademie Freiberg, Leipziger Str. 29, D-09599 Freiberg (Germany)
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