Propastin, Pavel A.

[["dc.bibliographiccitation.firstpage","138"],["dc.bibliographiccitation.issue","2"],["dc.bibliographiccitation.journal","Basic and Applied Dryland Research"],["dc.bibliographiccitation.lastpage","154"],["dc.bibliographiccitation.volume","1"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Kappas, Martin"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Muratova, Nadia R."],["dc.date.accessioned","2020-05-12T08:32:47Z"],["dc.date.available","2020-05-12T08:32:47Z"],["dc.date.issued","2007"],["dc.description.abstract","We combined Normalized Difference Vegetation Index (NDVI) datasets derived from the Advanced Very High Resolution Radiometer (AVHRR) and climate records to analyse within-season temporal relationships between vegetation activity and two eco-climatic parameters (precipitation and temperature) in an arid region of Central Kazakhstan. Assessments of these relationships were performed by calculating correlation coefficients between 10-day values of NDVI and the both climatic parameters throughout the growing season (April-October). The correlations were calculated for every pixel as well as for the aggregated datasets representing different land cover types and the entire study area. The results indicate that strong significant positive correlations exist between NDVI and each of the explanatory climatic parameters at all spatial scales. Temperature was considered to be the leading climatic factor controlling intra-annual NDVI dynamics. The correlation coefficients between NDVI-rainfall and NDVI-temperature exhibit a clear structure in terms of spatial distribution. The results indicate that the response of vegetation to climatic factors increases in order from shrubs and desert vegetation to semi-desert, short grassland and to steppe vegetation."],["dc.description.abstract","Die Arbeit untersucht zeitliche Zusammenhänge zwischen Vegetationsdynamik und Dynamik von Klimaelementen (Temperatur und Niederschlag) in einem Trockengebiet des Zentral-Kasachstans. Die Datengrundlagen der Arbeit umfassten den Normalized Difference Vegetation Index (NDVI) von dem Advanced Very High Resolution Radiometer (AVHRR) sowie Messwerten der Klimastationen für Niederschlag und Temperatur. Die Schätzung der Stärke des Zusammenhanges erfolgte durch Berechnung des Koeffizienten der Korrelation und Kreuzkorrelation zwischen den Zeitreihen der Dekadenwerte der NDVI und der beiden Klimaelemente während der Pflanzenwachstumsperiode. Die statistischen Zusammenhänge wurden auf verschiedenen Skalen räumlicher Generalisierung betrachtet: von dem gesamten Gebiet bis zu einzelnem Pixel. Die Ergebnisse beweisen, dass auf allen Betrachtungsskalen strenge Interrelationen zwischen der Dynamik des NDVI auf einer Seite und den beiden Klimaelementen auf der anderen Seite bestehen. Temperatur erwies sich als der Hauptfaktor für die Kontrolle der Vegetationsdynamik durch das Klima. Die räumliche Verbreitung der Werte des Korrelationskoeffizienten zeigte ein deutliches Muster. Dieses Muster spiegelt die Unterschiede zwischen einzelnen Vegetationstypen in bezug auf ihre Reaktionskraft und Reaktionsgeschwindigkeit zu der Einwirkung der Klimaelemente wider."],["dc.identifier.doi","10.1127/badr/1/2007/138"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65138"],["dc.language.iso","en"],["dc.relation.issn","1864-3191"],["dc.title","Remote sensing based study on intra-annual dynamics of vegetation and climate in drylands of Kazakhastan"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","6612"],["dc.bibliographiccitation.issue","24"],["dc.bibliographiccitation.journal","Journal of Climate"],["dc.bibliographiccitation.lastpage","6623"],["dc.bibliographiccitation.volume","22"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Propastin, Pavel A."],["dc.contributor.author","Kappas, Martin W."],["dc.contributor.author","Panferov, Oleg I."],["dc.date.accessioned","2018-11-07T11:21:33Z"],["dc.date.accessioned","2020-05-08T08:40:09Z"],["dc.date.available","2018-11-07T11:21:33Z"],["dc.date.available","2020-05-08T08:40:09Z"],["dc.date.issued","2009"],["dc.description.abstract","The present study is based on the assumption that vegetation in Indonesia is significantly affected by climate anomalies that are related to El Nino-Southern Oscillation (ENSO) warm phases (El Nino) during the past decades. The analysis builds upon a monthly time series from the normalized difference vegetation index (NDVI) gridded data from the Advanced Very High Resolution Radiometer (AVHRR) and two ENSO proxies, namely, sea surface temperature anomalies (SSTa) and Southern Oscillation index (SOI), and aims at the analysis of the spatially explicit dimension of ENSO impact on vegetation on the Indonesian archipelago. A time series correlation analysis between NDVI anomalies and ENSO proxies for the most recent ENSO warm events (1982-2006) showed that, in general, anomalies in vegetation productivity over Indonesia can be related to an anomalous increase of SST in the eastern equatorial Pacific and to decreases in SOI, respectively. The net effect of these variations is a significant decrease in NDVI values throughout the affected areas during the ENSO warm phases. The 1982/83 ENSO warm episode was rather short but-in terms of ENSO indices-the most extreme one within the study period. The 1997/98 El Nino lasted longer but was weaker. Both events had significant impact on vegetation in terms of negative NDVI anomalies. Compared to these two major warm events, the other investigated events (1987/88, 1991/92, 1994/95, and 2002/03) had no significant effect on vegetation in the investigated region. The land cover-type specific sensitivity of vegetation to ENSO anomalies revealed thresholds of vegetation response to ENSO warm events. The results for the 1997/98 ENSO warm event confirm the hypothesis that the vulnerability of vegetated tropical land surfaces to drought conditions is considerably affected by land use intensity. In particular, it could be shown that natural forest areas are more resistant to drought stress than degraded forest areas or cropland. Comparing the spatially explicit patterns of El Nino-related vegetation variation during the major El Nino phases, the spatial distribution of affected areas reveals distinct core regions of ENSO drought impact on vegetation for Indonesia that coincide with forest conversion and agricultural intensification hot spots."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft (DFG) [SFB-552]"],["dc.identifier.doi","10.1175/2009JCLI2460.1"],["dc.identifier.isi","000273359000007"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/5931"],["dc.identifier.scopus","2-s2.0-77649334436"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/55798"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-77649334436&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.eissn","1520-0442"],["dc.relation.issn","0894-8755"],["dc.relation.orgunit","Abteilung Bioklimatologie"],["dc.rights","Goescholar"],["dc.rights.uri","https://goescholar.uni-goettingen.de/licenses"],["dc.title","Spatial patterns of NDVI variation over Indonesia and their relationship to ENSO warm events during the period 1982-2006"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","47"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","International Journal of Applied Earth Observation and Geoinformation"],["dc.bibliographiccitation.lastpage","59"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Propastin, Pavel A."],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2018-11-07T08:46:17Z"],["dc.date.accessioned","2020-05-11T13:19:05Z"],["dc.date.available","2018-11-07T08:46:17Z"],["dc.date.available","2020-05-11T13:19:05Z"],["dc.date.issued","2010"],["dc.description.abstract","A time series of leaf area index (LAI) has been developed based on 16-day normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m resolution (MOD250_LAI). The MOD250_LAI product uses a physical radiative transfer model which establishes a relationship between LAI, fraction of vegetation cover (FVC) and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. In situ measurements of LAI and FVC made at 166 plots using hemispherical photography served for calibration of model parameters and validation of modelling results. Optical properties of vegetation cover, summarized by the light extinction coefficient, were computed at the local (pixel) level based on empirical models between ground-measured tree crown architecture at 85 sampling plots and spectral values in Landsat ETM+ bands. Influence of view-illumination conditions on optical properties of canopy was simulated by a view angle geometry model incorporating the solar zenith angle and the sensor viewing angle. The results revealed high compatibility of the produced MOD250-LAI data set with ground truth information and the 30 m resolution Landsat ETM+ LAI estimated using the similar algorithm. The produced MOD250_LAI was also compared with the global MODIS 1000-m LAI product (MOD15A2 LAI). Results show good consistency of the spatial distribution and temporal dynamics between the two LAI products. However, the results also showed that the annual LAI amplitude by the MODI 5A2 product is significantly higher than by the MOD250_LAI. This higher amplitude is caused by a considerable underestimation of the tropical rainforest LAI by the MOD15A2 during the seasonal phases of low leaf production. (C) 2009 Elsevier B.V. All rights reserved."],["dc.description.sponsorship","German Research Foundation (DFG)"],["dc.identifier.doi","10.1016/j.jag.2009.09.013"],["dc.identifier.isi","000272894800006"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/20653"],["dc.language.iso","en"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","Najko"],["dc.relation.issn","0303-2434"],["dc.title","A physically based approach to model LAI from MODIS 250m data in a tropical region"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","269"],["dc.bibliographiccitation.lastpage","291"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Ardiansyah, Muhammad"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Huete, Alfredo"],["dc.date.accessioned","2020-05-11T13:16:34Z"],["dc.date.available","2020-05-11T13:16:34Z"],["dc.date.issued","2010"],["dc.description.abstract","The current state of tropical forest cover and its change have been identified as key variables in modelling and measuring the consequences of human action on ecosystems. The conversion of tropical forest cover to any other land cover (deforestation) directly contributes to the two main environmental threats of the recent past: 1) the alteration of the global climate by the emission of carbon to the atmosphere and 2) the decline in tropical biodiversity by land use intensification and habitat conversion. The sub-continent of Southeast Asia exhibits one of the highest rates of forest loss and comprises one of the regions with the highest amount and diversity of flora and fauna species, worldwide. The knowledge of the spatial and temporal trends in the variation of forest cover in tropical regions is a prerequisite for the development and establishment of mitigation strategies from the global to the regional level. However, there is considerable disagreement in recent estimates of tropical forest cover change ranging from continuing and intensified decline in forest loss to a distinct decrease in deforestation rates and up to stagnation in other cases. Against this background, the present study aims at a review and comparison of recently available global forest cover estimates for the region of Southeast Asia. In a case study, the results at the national level will be compared to an analysis at the regional level for the island of Sulawesi, Indonesia. The outcome of the study provides recommendations for future remote sensing based forest assessments in tropical regions."],["dc.identifier.doi","10.1007/978-3-642-00493-3_12"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65012"],["dc.language.iso","en"],["dc.publisher","Springer Science + Business Media"],["dc.relation.eisbn","978-3-642-00493-3"],["dc.relation.isbn","978-3-642-00492-6"],["dc.relation.ispartof","Environmental Science and Engineering"],["dc.title","Spatiotemporal trends of forest cover change in Southeast Asia"],["dc.type","book_chapter"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","73"],["dc.bibliographiccitation.issue","Special Issue GI-Days, Münster, 2007"],["dc.bibliographiccitation.journal","International Journal of Spatial Data Infrastructures Research"],["dc.bibliographiccitation.lastpage","94"],["dc.bibliographiccitation.volume","3"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Kappas, Martin"],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2020-05-11T09:24:03Z"],["dc.date.available","2020-05-11T09:24:03Z"],["dc.date.issued","2007"],["dc.description.abstract","Scale-dependence of spatial relationship between vegetation and rainfall in Central Sulawesi has been modelled using Normalized Difference Vegetation Index (NDVI) and rainfall data from weather stations. The modelling based on application of two statistical approaches: conventional ordinary least squares (OLS) regression, and geographically weighted regression (GWR). The analysis scales ranged from the entire study region to spatial unities with a size of 750 750 m. The analysis revealed the presence of spatial non-stationarity for the NDVI-precipitation relationship. The results support the assumption that dealing with spatial non-stationarity and scaling down from regional to local modelling significantly improves the model’s accuracy and prediction power. The local approach also provides a better solution to the problem of spatially autocorrelated errors in spatial modelling."],["dc.identifier.doi","10.2902/1725-0463.2008.03.art6"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/64997"],["dc.language.iso","en"],["dc.relation.issn","1725-0463"],["dc.title","Application of Geographically Weighted Regression to Investigate the Impact of Scale on Prediction Uncertainty by Modelling Relationship between Vegetation and Climate"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","252"],["dc.bibliographiccitation.journal","Remote Sensing of Environment"],["dc.bibliographiccitation.lastpage","260"],["dc.bibliographiccitation.volume","121"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Ibrom, Andreas"],["dc.contributor.author","Knohl, Alexander"],["dc.contributor.author","Erasmi, Stefan"],["dc.date.accessioned","2017-09-07T11:49:08Z"],["dc.date.accessioned","2020-05-11T13:16:48Z"],["dc.date.available","2017-09-07T11:49:08Z"],["dc.date.available","2020-05-11T13:16:48Z"],["dc.date.issued","2012"],["dc.description.abstract","The Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) product (GPPMOD17A2) was evaluated against GPP from the eddy covariance flux measurements (GPPm) at a CO2 flux tower test site in a tropical rainforest in Sulawesi, Indonesia. The dynamics of 8-day GPPMOD17A2 averages generally showed similarities with observed values for the period 2004–2005 (r-value is 0.66, RMSE = 1.31 g C m− 2 d− 1). However, the results revealed some underestimation of GPP by the MOD17A2 product during phases of low photosynthetic production while it overestimated GPP during phases with clear sky conditions. Obviously, these seasonal differences are caused by too large seasonal amplitudes in GPPMOD17A2. The observed inconsistencies of the GPPMOD17A2with GPPm were traced to the inputs of the MODIS GPP algorithm, including fraction of absorbed photosynthetically active radiation (fAPAR) and light use efficiency (εg). This showed that underestimation of low values is caused by several uncertainties in the MODIS fAPAR input, whereas overestimation at high irradiance is caused by the MODIS light use efficiency approach which does not account for saturation of canopy photosynthesis under clear sky conditions. The performance of the MODIS GPP algorithm has been improved through the use of a site-validated fAPAR data set and a novel approach for εg adjustment which allows for saturation of gross photosynthesis at high irradiance. Our study revealed a weakness of a commonly used light use efficiency approach to estimate global GPP at the example of a moist tropical rain forest in Indonesia and demonstrated a potential need for MOD17 enhancement."],["dc.identifier.doi","10.1016/j.rse.2012.02.005"],["dc.identifier.gro","3147099"],["dc.identifier.scopus","2-s2.0-84857748453"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/4816"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/65014"],["dc.identifier.url","http://www.scopus.com/inward/record.url?eid=2-s2.0-84857748453&partnerID=MN8TOARS"],["dc.language.iso","en"],["dc.notes.status","public"],["dc.notes.submitter","chake"],["dc.relation.issn","0034-4257"],["dc.relation.orgunit","Abteilung Bioklimatologie"],["dc.title","Effects of canopy photosynthesis saturation on the estimation of gross primary productivity from MODIS data in a tropical forest"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","1515"],["dc.bibliographiccitation.issue","5"],["dc.bibliographiccitation.journal","Global Change Biology"],["dc.bibliographiccitation.lastpage","1530"],["dc.bibliographiccitation.volume","16"],["dc.contributor.author","Schwendenmann, Luitgard"],["dc.contributor.author","Veldkamp, Edzo"],["dc.contributor.author","Moser, Gerald"],["dc.contributor.author","Hölscher, Dirk"],["dc.contributor.author","Köhler, Michael"],["dc.contributor.author","Clough, Yann"],["dc.contributor.author","Anas, Iswandi"],["dc.contributor.author","Djajakirana, Gunawan"],["dc.contributor.author","Erasmi, Stefan"],["dc.contributor.author","Hertel, Dietrich"],["dc.contributor.author","Leitner, Daniela"],["dc.contributor.author","Leuschner, Christoph"],["dc.contributor.author","Michalzik, Beate"],["dc.contributor.author","Propastin, Pavel"],["dc.contributor.author","Tjoa, Aiyen"],["dc.contributor.author","van Straaten, Oliver"],["dc.date.accessioned","2017-08-25T10:13:31Z"],["dc.date.accessioned","2020-05-11T13:19:25Z"],["dc.date.available","2017-08-25T10:13:31Z"],["dc.date.available","2020-05-11T13:19:25Z"],["dc.date.issued","2010"],["dc.description.abstract","Agroforestry systems may play a critical role in reducing the vulnerability of farmers' livelihood to droughts as tree-based systems provide several mechanisms that can mitigate the impacts from extreme weather events. Here, we use a replicated throughfall reduction experiment to study the drought response of a cacao/Gliricidia stand over a 13-month period. Soil water content was successfully reduced down to a soil depth of at least 2.5 m. Contrary to our expectations we measured only relatively small nonsignificant changes in cacao (−11%) and Gliricidia (−12%) sap flux densities, cacao leaf litterfall (+8%), Gliricidia leaf litterfall (−2%), soil carbon dioxide efflux (−14%), and cacao yield (−10%) during roof closure. However, cacao bean yield in roof plots was substantially lower (−45%) compared with control plots during the main harvest following the period when soil water content was lowest. This indicates that cacao bean yield was more sensitive to drought than other ecosystem functions. We found evidence in this agroforest that there is complementary use of soil water resources through vertical partitioning of water uptake between cacao and Gliricidia. This, in combination with acclimation may have helped cacao trees to cope with the induced drought. Cacao agroforests may thus play an important role as a drought-tolerant land use in those (sub-) tropical regions where the frequency and severity of droughts is projected to increase."],["dc.identifier.doi","10.1111/j.1365-2486.2009.02034.x"],["dc.identifier.gro","3150086"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/6815"],["dc.language.iso","en"],["dc.notes.status","final"],["dc.relation.issn","1354-1013"],["dc.subject","cacao yield; CO2 efflux; fine root biomass; leaf litterfall; plant water uptake; sap flux; shade trees; soil water; throughfall reduction"],["dc.title","Effects of an experimental drought on the functioning of a cacao agroforestry system, Sulawesi, Indonesia"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","no"],["dspace.entity.type","Publication"]]