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Modeling of Spring Phenology of Boreal Forest by Coupling Machine Learning and Diurnal Temperature Indicators

Chinese Geographical Science 2025年第1期35卷 38-54页

作者： DENG Guorong ZHANG Hongyan HONG Ying GUO Xiaoyi YI Zhihua EHSAN BINIYAZ School of Hydraulic Engineering Nanchang Institute of TechnologyNanchang 330099China Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains Ministry of EducationSchool of Geographical SciencesNortheast Normal UniversityChangchun 130024China Urban remote sensing Application Innovation Center School of Geographical SciencesNortheast Normal UniversityChangchun 130024China School of Geographical Sciences Inner Mongolia Normal UniversityHohhot 010022China landscape Ecology and Geoinformation Science Department of GeographyKiel UniversityKiel 24118Germany

The roles of diurnal temperature in providing heat accumulation and chilling requirements for vegetation spring phenology *** previous studies have established a stronger correlation between leaf onset and diurnal temperature than between leaf onset and average temperature,current research on modeling spring phenology based on diurnal temperature indicators remains *** this study,we confirmed the start of the growing season(SOS)sensitivity to diurnal temperature and average temperature in boreal *** estimation of SOS was carried out by employing K-Nearest Neighbor Regression(KNR-TDN)model,Random Forest Regres-sion(RFR-TDN)model,eXtreme Gradient Boosting(XGB-TDN)model and Light Gradient Boosting Machine model(LightGBM-TDN)driven by diurnal temperature indicators during 1982-2015,and the SOS was projected from 2015 to 2100 based on the Coupled Model Intercomparison Project Phase 6(CMIP6)climate scenario *** sensitivity of boreal forest SOS to daytime temperature is greater than that to average temperature and nighttime *** LightGBM-TDN model perform best across all vegetation types,exhibiting the lowest RMSE and bias compared to the KNR-TDN model,RFR-TDN model and XGB-TDN *** incorporating diurn-al temperature indicators instead of relying only on average temperature indicators to simulate spring phenology,an improvement in the accuracy of the model is ***,the preseason accumulated daytime temperature,daytime temperature and snow cover end date emerged as significant drivers of the SOS simulation in the study *** simulation results based on LightGBM-TDN model exhibit a trend of advancing SOS followed by stabilization under future climate *** study underscores the potential of diurn-al temperature indicators as a viable alternative to average temperature indicators in driving spring phenology models,offering a prom-ising new method for simulating spring phenology.

关键词： spring phenology diurnal temperature machine learning future climate scenarios boreal forest

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Spatial distribution of the potential forest biomass availability in Europe

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Forest Ecosystems 2019年第1期6卷 56-66页

作者： Pieter Johannes Verkerk Joanne Brighid Fitzgerald Pawan Datta Matthias Dees Geerten Martijn Hengeveld Marcus Lindner Sergey Zudin European Forest Institute University of Freiburg-Institute of Forest Sciences-Chair of remote sensing and landscape information systems Wageningen University and Research

Background: European forests are considered a crucial resource for supplying biomass to a growing bio-economy in Europe. This study aimed to assess the potential availability of forest biomass from European forests and its spatial distribution. We tried to answer the questions(i) how is the potential forest biomass availability spatially distributed across Europe and(ii) where are hotspots of potential forest biomass availability located?Methods: The spatial distribution of woody biomass potentials was assessed for 2020 for stemwood, residues(branches and harvest losses) and stumps for 39 European countries. Using the European Forest information SCENario(EFISCEN) model and international forest statistics, we estimated the theoretical amount of biomass that could be available based on the current and future development of the forest age-structure, growing stock and increment and forest management regimes. We combined these estimates with a set of environmental(site productivity, soil and water protection and biodiversity protection) and technical(recovery rate, soil bearing capacity) constraints, which reduced the amount of woody biomass that could potentially be available. We mapped the potential biomass availability at the level of administrative units and at the 10 km × 10 km grid level to gain insight into the spatial distribution of the woody biomass ***: According to our results, the total availability of forest biomass ranges between 357 and 551 Tg dry matter per year. The largest potential supply of woody biomass per unit of land can be found in northern Europe(southern Finland and Sweden, Estonia and Latvia), central Europe(Austria, Czech Republic, and southern Germany),Slovenia, southwest France and Portugal. However, large parts of these potentials are already used to produce materials and energy. The distribution of biomass potentials that are currently unused only partially coincides with regions that currently have high levels of wood pro

关键词： Forest biomass EFISCEN Europe Potential supply Spatial distribution

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Modelling stratified forest attributes using optical/LiDAR features in a central European landscape

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International Journal of Digital Earth 2012年第2期5卷 106-132页

作者： Hooman Latifi Arne Nothdurft Christoph Straub Barbara Koch department of remote sensing and landscape information systems University of FreiburgTennenbacherstraßeFreiburgGermany department of Biometry and Informatics Forest Research Institute Baden WurttembergWonnhaldestraßeFreiburgGermany

Improvements in the acquisition of three-dimensional(3D)information from the Airborne Laser Scanner(ALS)increase its applications for studying Earth’s *** use of ALS data in natural resource inventories is still in an experimental stage in central ***,a survey was completed in Germany,where plot-level features from LANDSAT Thematic Mapper and ALS data were *** automated process was developed for forest stratification using orthoimages.A genetic algorithm was applied for variable *** subsets of different sizes were employed for simultaneous predictions of structural forest attributes using the‘Random Forest’(RF)*** was assessed by leave-one-out cross-validations on bootstrap resample *** indicate that the stratification of forest notably improved the results of *** improvements were more obvious for the strata-related *** was enhanced as the number of selected variables ***,parsimonious models are still essentially required for practical *** RF errors were slightly greater than those from least squares regression,as the non-parametric methods do not share the same mix of error components as *** the combination of remote sensing and modelling,we conclude that our results are helpful for bridging the gap between regional earth observation and on-the-ground forest structure.

关键词： spatial prediction natural resource inventory ALS Digital Earth data fusion remote sensing

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Evaluation on the Two Filling Functions for the Recovery of Forest information in Mountainous Shadows on Landsat ETM + Image

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Journal of Mountain Science 2011年第3期8卷 414-426页

作者： SHAHTAHMASSEBI Amir reza MOORE Nathan Institute of Agriculture remote sensing and information Technology Zhejiang University Key Laboratory of Agricultural remote sensing and information System of Zhejiang Province department of Geography Michigan State University

In general,topographic shadow may reduce performance of forest mapping over mountainous regions in remotely sensed *** this paper,information in shadow was synthesized by using two filling techniques,namely,roifill and imfill,in order to improve the accuracy of forest mapping over mountainous *** two methods were applied to Landsat Enhanced Thematic Mapper (ETM +) multispectral image from Dong Yang County,Zhejiang Province,*** performance of these methods was compared with two conventional techniques,including cosine correction and multisource *** results showed that by applying filling approaches,average overall accuracy of classification was improved by 14 ***,through conventional methods this value increased only by 9 *** results also revealed that estimated forest area on the basis of shadow-corrected images by 'roifill' technique was much closer to the survey data compared to traditional *** from this finding,our finding indicated that topographic shadow was an accentuated problem in medium resolution images such as Landsat ETM+ over mountainous regions.

关键词： Shadow Imfill: Roifill: Landsat ETM+

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Importance of community containment measures in combating the COVID-19 epidemic:From the perspective of urban planning

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Geo-Spatial information Science 2021年第3期24卷 363-371页

作者： Xin Huang Qiquan Yang Junjing Yang School of remote sensing and information Engineering Wuhan UniversityWuhanChina State Key Laboratory of information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina

To contain the outbreak of COVID-19 in Wuhan,unprecedented interventions,including city lockdown and community closure,have been ***,most of the current studies focused on evaluation of the city lockdown,but paid limited attention to the impacts of the community containment measures within the *** research addressed this important issue from the perspective of urban planning,based on the epidemic and remote sensing data of 194 communities of *** found that the number of confirmed cases of communities is highly related to urban planning factors,*** percentage of buildings and density of neighboring *** factors are relevant to the residents’activity patterns,which therefore impact the mode of virus *** research confirmed the effectiveness of the community-oriented control strategies,provided a valuable reference for other cities that are suffering from the epidemic,and exhibited new thoughts into future urban planning.

关键词： SARS-Cov-2 close-off transmission remote sensing landscape city layouts infection disease healthy city

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Orthogonal waveform design with fractional programming on the ambiguity suppression of SAR systems

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Science China(information Sciences) 2024年第9期67卷 263-279页

作者： Yunkai DENG Yongwei ZHANG Zhimin ZHANG Wei WANG Heng ZHANG department of Space Microwave remote sensing System Aerospace Information Research InstituteChinese Academy of Sciences

Waveform diversity(WD) represents a dynamic and transformative technology widely used in radar systems to enhance sensitivity and discrimination capabilities. Recently, WD techniques have been extensively explored for their potential ambiguity suppression within synthetic aperture radar(SAR) *** these, the alternate transmitting mode combined with orthogonal waveforms emerges as a particularly promising solution. This study focuses on optimizing the power spectrum density(PSD) of signals to design and generate an orthogonal waveform pair that achieves both a low cross-correlation-to-autocorrelation ratio(CAR) and satisfactory imaging performance. Initially, we construct a fractional programming model with convex constraints to minimize the CAR. To address this challenge, we introduce an iterative optimization procedure for the PSD variable, which sequentially reduces the CAR. Each optimization step can be efficiently solved using a quadratically constrained quadratic program, ensuring that the resulting computational complexity remains low. Building on the optimized PSD, we established a parametric piecewise linear model to generate an orthogonal waveform pair. This model not only maintains a low CAR but achieves satisfactory imaging performance in real-time applications. Consequently, this orthogonal waveform pair effectively suppresses range ambiguity in SAR systems. Finally, we demonstrated the practicability and effectiveness of the proposed orthogonal waveforms through detailed simulation experiments, specifically targeting ambiguity suppression in conventional quad-polarization SAR systems.

关键词： synthetic aperture radar (SAR) waveform diversity (WD) ambiguity suppression orthogonal waveform fractional programming power spectrum density (PSD)

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Deep learning-based local climate zone classification using Sentinel-1 SAR and Sentinel-2 multispectral imagery

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Geo-Spatial information Science 2022年第3期25卷 383-398页

作者： Lin Zhou Zhenfeng Shao Shugen Wang Xiao Huang School of remote sensing and information Engineering Wuhan UniversityWuhanChina State Key Laboratory of information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina department of Geosciences University of ArkansasFayettevilleNCUSA

As a newly developed classification system,the LCZ scheme provides a research framework for Urban Heat Island(UHI)studies and standardizes the worldwide urban temperature *** the growing popularity of deep learning,deep learning-based approaches have shown great potential in LCZ *** major cities in China are selected as the study *** this study,we design a deep convolutional neural network architecture,named Residual combined Squeeze-and-Excitation and Non-local Network(RSNNet),that consists of the Squeeze-and-Excitation(SE)block and non-local block to classify LCZ using freely available Sentinel-1 SAR and Sentinel-2 multispectral *** Accuracy(OA)of 0.9202,0.9524 and 0.9004 for three selected cities are obtained by applying RSNNet and training data of individual city,and OA of 0.9328 is obtained by training RSNNet with data from all three *** outperforms other popular Convolutional Neural Networks(CNNs)in terms of LCZ mapping *** further design a series of experiments to investigate the effect of different characteristics of Sentinel-1 SAR data on the performance of RSNNet in LCZ *** results suggest that the combination of SAR and multispectral data can improve the accuracy of LCZ *** proposed RSNNet achieves an OA of 0.9425 when integrat-ing the three decomposed components with Sentinel-2 multispectral images,2.44%higher than using Sentinel-2 images alone.

关键词： Local Climate Zone(LCZ) deep learning Sentinel-1 Sentinel-2

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Unsupervised hyperspectral unmixing based on robust nonnegative dictionary learning

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Journal of systems Engineering and Electronics 2022年第2期33卷 294-304页

作者： LI Yang JIANG Bitao LI Xiaobin TIAN Jing SONG Xiaorui department of Space information Space Engineering UniversityBeijing 101400China Beijing Institute of remote sensing information Beijing 100192China

Considering the sparsity of hyperspectral images(HSIs),dictionary learning frameworks have been widely used in the field of unsupervised spectral ***,it is worth mentioning here that existing dictionary learning method-based unmixing methods are found to be short of robustness in noisy *** improve the performance,this study specifically puts forward a new unsupervised spectral unmixing *** the reason that the solution only functions in a condition that both endmembers and the abundances meet non-negative con-straints,a model is built to solve the unsupervised spectral un-mixing problem on the account of the dictionary learning *** raise the screening accuracy of final members,a new form of the target function is introduced into dictionary learning practice,which is conducive to the growing robustness of noisy HSI ***,by introducing the total variation(TV)terms into the proposed spectral unmixing based on robust nonnega-tive dictionary learning(RNDLSU),the context information under HSI space is to be cited as prior knowledge to compute the abundances when performing sparse unmixing ***-cording to the final results of the experiment,this method makes favorable performance under varying noise conditions,which is especially true under low signal to noise conditions.

关键词： hyperspectral image(HSI) nonnegative dictionary learning norm loss function unsupervised unmixing

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Water erosion risk mapping using derived parameters from digital elevation model and remotely sensed data

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Geo-Spatial information Science 2012年第3期15卷 157-169页

作者： Soufiane MAIMOUNI Abderrazak EL-HARTI Abderrazak BANNARI El-Mostafa BACHAOUI remote sensing and Geographical information systems Laboratory Faculty of Science and TechniquesUniversity of Sultan Moulay SlimaneBeniMellalMorocco remote sensing and Geomatics of the Environment Laboratory Department of GeographyUniversity of OttawaOntarioCanada

The aim of this study is to map the areas exposed to water erosion risks in the High Atlas Mountains of Morocco around the Hassan-I *** methodology is based on the analysis of the water power index(WPI)as a hydrological parameter,the vegetation cover,and the litho-logical *** WPI was derived from a Digital Elevation Model(DEM)and the litho-logical units and vegetation cover were derived from Advanced Land Imager sensor on the Earth Observing-1 satellite *** image was corrected from radiometric and atmospheric effects,and geometrically rectified using a DEM and grounds control *** variables were integrated in a Geographical information systems environment,and Multi-Criteria Analyses were used to derive the water erosion risks map pointing out the most exposed areas requiring the implementation of suitable conservation *** validation of the obtained results shows the simplicity and the potential of this approach for water erosion risks mapping.

关键词： water erosion risks GIS remote sensing vegetation cover litho-logical units hydrological parameter

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From digital Earth to smart Earth

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Chinese Science Bulletin 2014年第8期59卷 722-733页

作者： Deren Li Yuan Yao Zhenfeng Shao Le Wang School of remote sensing and information Engineering Wuhan University State Key Laboratory of information Engineering in Surveying Mapping and Remote Sensing Wuhan University department of Geography The State University of New York at Buffalo

This article will analyze the achievements of the digital Earth concept and further introduce two key technologies,the internet of things and cloud *** these technologies are accelerating the development of digital Earth toward a new concept—smart *** objective of this article is to discuss the architecture,infrastructure,and typical applications for smart Earth and to elaborate on trends of the movement from digital Earth to smart Earth.

关键词：数字地球智慧地球概念典型应用基础设施发展趋势物联网技术

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