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Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia / Loïc Paul Dutrieux in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 112 - 125 Titre : Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia Type de document : Article/Communication Auteurs : Loïc Paul Dutrieux, Auteur ; Jan Verbesselt, Auteur ; Lammert Kooistra, Auteur ; Martin Herold, Auteur Année de publication : 2015 Article en page(s) : pp 112 - 125 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Bolivie [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] forêt tropicale [Termes IGN] image Terra-MODIS [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] sécheresse [Termes IGN] série temporelle [Termes IGN] variabilité Résumé : (auteur) Automatically detecting forest disturbances as they occur can be extremely challenging for certain types of environments, particularly those presenting strong natural variations. Here, we use a generic structural break detection framework (BFAST) to improve the monitoring of forest cover loss by combining multiple data streams. Forest change monitoring is performed using Landsat data in combination with MODIS or rainfall data to further improve the modelling and monitoring. We tested the use of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) with varying spatial aggregation window sizes as well as a rainfall derived index as external regressors. The method was evaluated on a dry tropical forest area in lowland Bolivia where forest cover loss is known to occur, and we validated the results against a set of ground truth samples manually interpreted using the TimeSync environment. We found that the addition of an external regressor allows to take advantage of the difference in spatial extent between human induced and naturally induced variations and only detect the processes of interest. Of all configurations, we found the 13 by 13 km MODIS NDVI window to be the most successful, with an overall accuracy of 87%. Compared with a single pixel approach, the proposed method produced better time-series model fits resulting in increases of overall accuracy (from 82% to 87%), and decrease in omission and commission errors (from 33% to 24% and from 3% to 0% respectively). The presented approach seems particularly relevant for areas with high inter-annual natural variability, such as forests regularly experiencing exceptional drought events. Numéro de notice : A2015-726 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.03.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.03.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78378 [article]

Mapping a priori defined plant associations using remotely sensed vegetation characteristics / Hans D. Rölofsen in Remote sensing of environment, vol 140 (January 2014)  

Public [article]  inRemote sensing of environment > vol 140 (January 2014) . - pp 639 - 651 Titre : Mapping a priori defined plant associations using remotely sensed vegetation characteristics Type de document : Article/Communication Auteurs : Hans D. Rölofsen, Auteur ; Lammert Kooistra, Auteur ; Peter M. van Bodegom, Auteur ; Jochem Verrelst, Auteur ; Johan Krol, Auteur ; Jan-Philip M. Witte, Auteur Année de publication : 2014 Article en page(s) : pp 639 - 651 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] caractérisation [Termes IGN] classification [Termes IGN] humidité du sol [Termes IGN] image aérienne [Termes IGN] image multibande [Termes IGN] nutriment végétal [Termes IGN] Pays-Bas [Termes IGN] phytosociologie [Termes IGN] placette d'échantillonnage [Termes IGN] répartition géographique [Termes IGN] salinité [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Incorporation of a priori defined plant associations into remote sensing products is a major challenge that has only recently been confronted by the remote sensing community. We present an approach to map the spatial distribution of such associations by using plant indicator values (IVs) for salinity, moisture and nutrients as an intermediate between spectral reflectance and association occurrences. For a 12 km2 study site in the Netherlands, the relations between observed IVs at local vegetation plots and visible and near-infrared (VNIR) and short-wave infrared (SWIR) airborne reflectance data were modelled using Gaussian Process Regression (GPR) (R2 0.73, 0.64 and 0.76 for salinity, moisture and nutrients, respectively). These relations were applied to map IVs for the complete study site. Association occurrence probabilities were modelled as function of IVs using a large database of vegetation plots with known association and IVs. Using the mapped IVs, we calculated occurrence probabilities of 19 associations for each pixel, resulting in both a crisp association map with the most likely occurring association per pixel, as well as occurrence probability maps per association. Association occurrence predictions were assessed by a local vegetation expert, which revealed that the occurrences of associations situated at frequently predicted indicator value combinations were over predicted. This seems primarily due to biases in the GPR predicted IVs, resulting in associations with envelopes located in extreme ends of IVs being scarcely predicted. Although the results of this particular study were not fully satisfactory, the method potentially offers several advantages compared to current vegetation classification techniques, like site-independent calibration of association probabilities, site-independent selection of associations and the provision of IV maps and occurrence probabilities per association. If the prediction of IVs can be improved, this method may thus provide a viable roadmap to bring a priori defined plant associations into the domain of remote sensing. Numéro de notice : A2014-796 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2013.09.030 En ligne : https://doi.org/10.1016/j.rse.2013.09.030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81015 [article]

Integrating remote sensing in Natura 2000 habitat monitoring: Prospects on the way forward / Jeroen Vanden Borre in Journal for nature conservation, vol 19 n° 2 (May 2011)

Public [article]  inJournal for nature conservation > vol 19 n° 2 (May 2011) . - pp 116 - 125 Titre : Integrating remote sensing in Natura 2000 habitat monitoring: Prospects on the way forward Type de document : Article/Communication Auteurs : Jeroen Vanden Borre, Auteur ; Desiré Paelinckx, Auteur ; Caspar A. Mücher, Auteur ; Lammert Kooistra, Auteur ; Birgen Haest, Auteur ; Geert De Blust, Auteur ; Anne M. Schmidt, Auteur Année de publication : 2011 Article en page(s) : pp 116 - 125 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] habitat (nature) [Termes IGN] image satellite [Termes IGN] site Natura 2000 [Termes IGN] télédétection électromagnétique [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Monitoring and reporting on the state of nature gained increasing importance in the European Union with the implementation of the Habitats Directive and the Natura 2000 network. Reporting habitat conservation status requires detailed knowledge on many aspects of habitats at different spatial levels. Remote sensing is recognised as a powerful tool to acquire synoptic data on habitats, but to date, its use for Natura 2000 monitoring and reporting is still very limited. One reason for this appears to be the knowledge gap between the nature conservation agencies and the remote sensing community. We conducted a review of legal monitoring and reporting requirements on Natura 2000 habitats, looked into the current use of remote sensing in habitat reporting, and consulted monitoring experts in nature conservation administrations to find out about their attitude and expectations towards remote sensing. In this paper, we disclose and summarise the real data needs behind the legal requirements for Natura 2000 habitat monitoring and reporting, analyse opportunities and constraints for remote sensing, and highlight bottlenecks and pathways to resolve them. Monitoring experts are not unwilling to use remote sensing data, but they are unsure of whether remote sensing can suit their needs in a cost-effective way. They look upon remote sensing as a one-way process of data deliverance and fail to see the importance of their active cooperation. Based on our findings, we argue that the integration of remote sensing into Natura 2000 habitat monitoring could benefit from (1) harmonising and standardising approaches, (2) focusing on data at hand to develop readily useful products, (3) a proper validation of both traditional and remote sensing methods, and (4) an enhanced sharing and exchange of ideas and results between the different research communities involved. Numéro de notice : A2011-025 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81071 [article]