2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)最新文献

Generation of 250m MODIS LAI time series by temporal regression 用时间回归生成250m MODIS LAI时间序列

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005059

R. Colditz, R. Llamas

引用次数: 0

Low and high spatial resolution time series fusion for improved land cover map production 低、高空间分辨率时间序列融合改进土地覆盖图制作

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005052

J. Inglada, O. Hagolle, G. Dedieu

引用次数: 7

Urbanization analysis by mutual information based change detection between SPOT 5 panchromatic images 基于互信息的spot5全色图像变化检测的城市化分析

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005072

L. Gueguen, M. Pesaresi, D. Ehrlich, Linlin Lu

引用次数: 7

Monitoring a fuzzy object: The case of Lake Naivasha 监测一个模糊的对象:奈瓦沙湖的案例

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005071

W. Bijker, N. Hamm, Julian Ijumulana, Misganaw Kebede Wole

引用次数: 4

Analysis of LULC changes and urban expansion of the resort city of Al Ain using remote sensing and GIS 基于遥感和GIS的度假城市Al Ain土地利用价值变化与城市扩张分析

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005094

S. M. Issa, A. Al Shuwaihi

引用次数: 3

Multi-temporal analysis of a mangrove ecosystem in Southeastern Brazil using object-based classification applied to IKONOS II data IKONOS II数据中基于对象分类的巴西东南部红树林生态系统多时相分析

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005075

Adriano de Oliveira Vasconcelos, L. Landau, Fernando Pellon de Miranda

引用次数: 2

Multitemporal fusion of Landsat and MERIS images Landsat和MERIS图像的多时相融合

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005053

J. Amorós-López, L. Gómez-Chova, L. Guanter, L. Alonso, J. Moreno, Gustau Camps-Valls

{"title":"Multitemporal fusion of Landsat and MERIS images","authors":"J. Amorós-López, L. Gómez-Chova, L. Guanter, L. Alonso, J. Moreno, Gustau Camps-Valls","doi":"10.1109/MULTI-TEMP.2011.6005053","DOIUrl":"https://doi.org/10.1109/MULTI-TEMP.2011.6005053","url":null,"abstract":"Monitoring Earth dynamics from current and future observation satellites is one of the most important objectives for the remote sensing community. In this regard, the exploitation of image time series from sensors with different characteristics provides an opportunity to increase the knowledge about environmental changes, which are needed in many operational applications, such as monitoring vegetation dynamics and land cover/use changes. Many studies in the literature have proven that high spatial resolution sensors like Landsat are very useful for monitoring land cover changes. However, the cloud cover probability of many areas and the 15-days temporal resolution restrict its use to monitor rapid variation phenomena. On the contrary, sensors with coarser spatial resolution like MERIS acquire images every 1-3 days. In this paper, Landsat/TM and ENVISAT/MERIS sensors are combined in a synergistic manner to enhance image time series at high spatial resolution using the temporal information provided by the MERIS sensor. The capabilities of the proposed methodology are illustrated using a temporal image series of both sensors acquired over Albacete (Spain) in 2004. Additionally, the temporal profile of the NDVI is selected as demonstrative application of agricultural monitoring.","PeriodicalId":254778,"journal":{"name":"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125733008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The impact of inter-annual variability in remote sensing time series on modeling tree species distributions 遥感时间序列年际变率对树种分布建模的影响

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005078

A. Cord, D. Klein, S. Dech

{"title":"The impact of inter-annual variability in remote sensing time series on modeling tree species distributions","authors":"A. Cord, D. Klein, S. Dech","doi":"10.1109/MULTI-TEMP.2011.6005078","DOIUrl":"https://doi.org/10.1109/MULTI-TEMP.2011.6005078","url":null,"abstract":"Predictions of species occurrence as indicators of ecosystem integrity are of high relevance for decision-makers in conservation biology, invasive species' management, and climate change research. Remote sensing data can serve as valuable input for Species Distribution Models (SDMs) since they provide information on current habitat conditions and disturbance factors besides bioclimatic suitability which is commonly derived from climatic data. However, little is known about the usefulness of multi-temporal remote sensing data in general for modeling species distributions and the related effects of inter-annual variability on the extent and accuracy of modeled distribution ranges. This study investigates the above-mentioned questions for two tropical tree species, Brosimum alicastrum and Liquidambar macrophylla, in Mexico. From the MODIS 16-day vegetation index product (MOD13A2), 18 annual phenological metrics (time-related, NPP-related and seasonality-related) were computed for the period from 2001 to 2009 and combined to a set of multi-year average values (covering 3, 5, 7, and 9 years). The results show that inter-annual variability has a significant impact on model predictions and that models based on longer composite periods show less deviance from observed species presence-absence field data.","PeriodicalId":254778,"journal":{"name":"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122279167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Spectral-Temporal Analysis by Response Surface applied to detect deforestation in the Brazilian Amazon 响应面光谱-时相分析用于检测巴西亚马逊地区的森林砍伐

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005055

M. P. Mello, F. Martins, L. Sato, R. Cantinho, D. A. Aguiar, B. Rudorff, Rafael Santos

引用次数: 5

Snow cover monitoring in alpine regions with COSMO-SkyMed images by using a multitemporal approach and depolarization ratio COSMO-SkyMed遥感高寒地区积雪监测的多时相方法和去极化比

2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Pub Date : 2011-07-12 DOI: 10.1109/MULTI-TEMP.2011.6005065

B. Ventura, T. Schellenberger, C. Notarnicola, M. Zebisch, T. Nagler, H. Rott, V. Maddalena, R. Ratti, L. Tampellini

{"title":"Snow cover monitoring in alpine regions with COSMO-SkyMed images by using a multitemporal approach and depolarization ratio","authors":"B. Ventura, T. Schellenberger, C. Notarnicola, M. Zebisch, T. Nagler, H. Rott, V. Maddalena, R. Ratti, L. Tampellini","doi":"10.1109/MULTI-TEMP.2011.6005065","DOIUrl":"https://doi.org/10.1109/MULTI-TEMP.2011.6005065","url":null,"abstract":"The multi-temporal technique for the detection of wet snow, based on the different response of snow and no-snow area was applied to COSMO-SkyMed (CSK) images acquired over South Tyrol (Northern Italy) during the first year of activity in the project “SNOX — snow cover and glacier monitoring in alpine areas with COSMO-SkyMed X-band data” funded by the Italian Space Agency. A standard threshold value of −3 dB and a less restrictive threshold of −2.3 dB are compared for an improved distinction of the snow and no-snow distributions. The application of these two different thresholds determines a variation of snow cover area (SCA) between 2% and 8%. Furthermore, it has been proved that the choice of the reference image for the no-snow areas is critical and can determine a variability in the resulting SCA up to 10%. The depolarization factor, σ0VH/σ0VV, is also exploited to evaluate its contribution to the identification of snow covered areas. Preliminary results indicate that the contribution of the depolarization factor to the SCA detection is very limited.","PeriodicalId":254778,"journal":{"name":"2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134014428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4