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Assessment of forest dieback on the Moroccan Central Plateau using spectral vegetation indices

Journal of Forestry Research 2023年第3期34卷 793-808页

作者： Youssef Dallahi Amal Boujraf Modeste Meliho Collins Ashianga Orlando Laboratory of Microbial Biotechnologies Agrosciences and Environment(BioMAgE)Faculty of Sciences SemlaliaCadi Ayyad UniversityMarrakechMorocco Laboratoire des Productions Végétale Animales et Agro-industrieEquipe de BotaniqueBiotechnologie et Protection des PlantesFacultédes SciencesUniversitéIbn TofailKenitraMorocco Sociétés TerritoiresHistoires et PatrimoinesFacultédes Lettres et des Sciences HumainesUniversitéMohammed VRabatMorocco Rabat Morocco

Cork oak forests in Morocco are rich in resources and services thanks to their great biological diversity,playing an important ecological and socioeconomic *** degradation of the forests has been accentuated in recent years by signifi cant human pressure and eff ects of climate change;hence,the health of the stands needs to be *** this study,the Google Engine Earth platform was leveraged to extract the normalized diff erence vegetation index(NDVI)and soil-adjusted vegetation index,from Landsat 8 OLI/TIRS satellite images between 2015 and 2017 to assess the health of the Sibara Forest in *** results highlight the importance of interannual variations in NDVI in forest monitoring;the variations had a signifi cantly high relationship(p<0.001)with dieback *** was positively and negatively correlated with mean annual precipitation and mean annual temperature with respective coeffi cients of 0.49 and−0.67,highlighting its ability to predict phenotypic changes in forest *** interannual variation in NDVI between 2016 and 2017 seemed to confi rm fi eld observations of cork oak dieback in 2018,with the largest decreases in NDVI(up to−38%)in December in the most-aff ected *** of the infl uence of ecological factors on dieback highlighted the role of substrate as a driver of dieback,with the most severely aff ected plots characterized by granite-granodiorite substrates.

关键词： Forest health monitoring Remote sensing Dieback vegetation indices Sibara forest

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Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

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The Crop Journal 2020年第1期8卷 87-97页

作者： Xiuliang Jin Zhenhai Li Haikuan Feng Zhibin Ren Shaokun Li Institute of Crop Sciences Chinese Academy of Agricultural SciencesKey Laboratory of Crop Physiology and EcologyMinistry of AgricultureBeijing 100081China Beijing Research Center for Information Technology in Agriculture Beijing Academy of Agriculture and Forestry SciencesBeijing 100097China Northeast Institute of Geography and Agroecology Chinese Academy of SciencesChangchun 130102JilinChina

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop *** is also a key trait in increasing grain yield by crop *** aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)*** results showed that biomass was associated with all vegetation *** three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%*** was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and *** estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of *** provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.

关键词： Biomass estimation Maize vegetation indices Deep neural network algorithm LAI

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Effects of RapidEye Imagery's Red-edge Band and vegetation indices on Land Cover Classification in an Arid Region

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Chinese Geographical Science 2017年第5期27卷 827-835页

作者： LI Xianju CHEN Gang LIU Jingyi CHEN Weitao CHENG Xinwen LIAO Yiwei College of Computer Science and Hubei Key Laboratory of Intelligent Geo-Information Processing China University of GeosciencesWuhan 430074China College of Marine Science and Technology China University of GeosciencesWuhan 430074China Laboratory of Geographic Information and Spatial Analysis Department of Geography and PlanningQueen's UniversityKingston ON K7L3N6Canada Faculty of Information Engineering China University of GeosciencesWuhan 430074China School of Electrical and Electronic Engineering Huazhong University of Science and TechnologyWuhan 430074China

Land cover classification(LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidE ye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidE ye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement(3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.

关键词： arid region land cover classification RapidEye red-edge band vegetation indices random forest Dunhuang Basin

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Estimating aboveground biomass in Mu Us Sandy Land using Landsat spectral derived vegetation indices over the past 30 years

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Journal of Arid Land 2013年第4期5卷 521-530页

作者： Feng YAN Bo WU YanJiao WANG Institute of Desertification Studies Chinese Academy of Forestry National Climate Center China Meteorological Administration

Remote sensing is a valuable and effective tool for monitoring and estimating aboveground biomass （AGB） in large *** current international research on biomass estimation by remote sensing technique mainly focused on forests,grasslands and crops,with relatively few applications for desert *** this paper,Landsat Thematic Mapper （TM）/Enhanced Thematic Mapper Plus （ETM＋） images from 1988 to 2007 and the data of 283 AGB samples in August 2007 were used to estimate the AGB for Mu Us Sandy Land over the past 30 ***,temporal and spatial distribution characteristics of AGB and influencing factors of climate and underlying surface were also *** show that：（1） Differences of correlations exist in the fitted equations between AGB and different vegetation indices in desert *** modified soil adjusted vegetation index （MSAVI） and soil adjusted vegetation index （SAVI） show relatively higher correlations with AGB,while the correlation between normalized difference vegetation index （NDVI） and AGB is relatively *** testing shows that the AGB-MSAVI model established can be used to accurately estimate AGB of Mu Us Sandy Land in August.（2） AGB in Mu Us Sandy Land shows the fluctuant characteristics over the past 30 years,which decreased from the 1980s to the 1990s,and increased from the 1990s to *** in 2007 had the highest value,with a total AGB of 3.352×106 ***,in the 1990s,AGB had the lowest value with a total AGB of 2.328×106 t.（3） AGB with relatively higher values was mainly located in the middle and southern parts of Mu Us Sandy Land in the *** was low in the whole area in the1990s,and relatively higher AGB values were mainly located in the southern parts of *** 2007,AGB in the whole area was relatively higher than those of the last twenty years,and higher AGB values were mainly located in the northern,western and middle parts of Mu Us Sandy Land.

关键词： aboveground biomass (AGB) linear regression vegetation indices Mu Us Sandy Land

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Drought Impacts on vegetation indices and Productivity of Terrestrial Ecosystems in Southwestern China During 2001–2012

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Chinese Geographical Science 2018年第5期28卷 784-796页

作者： ZHOU Lei WANG Shaoqiang CHI Yonggang WANG Junbang College of Geography and Environmental Sciences Zhejiang Normal University Key Laboratory of Ecosystem Network Observation and Modelling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of Sciences School of Earth & Atmospheric Sciences Georgia Institute of Technology

Drought, as a recurring extreme climate event, affects the structure, function, and process of terrestrial ecosystems. Despite the increasing occurrence and intensity of the drought in the past decade in Southwestern China, the impacts of continuous drought events on vegetation in this region remain unclear. During 2001–2012, Southwestern China experienced the severe drought events from 2009 to 2011. Our aim is to characterize drought conditions in the Southwestern China and explore the impacts on the vegetation condition and terrestrial ecosystem productivity. The Standardized Precipitation Index(SPI) was used to characterize drought area and intensity and a light-use efficiency model was used to explore the effect of drought on the terrestrial ecosystem productivity with Moderate Resolution Imaging Spectrometer(MODIS) data. The SPI captured the major drought events in Southwestern China during the study period, indicated that the 12-year period of this study included both ‘normal' precipitation years and two severe drought events in 2009–2010 and 2011. Results showed that vegetation greenness(Normalized Difference vegetation Index, NDVI and Enhanced vegetation Index, EVI) both declined in 2009/2010 drought, but the 2011 drought resulted in less declines of vegetation greenness and productivity due to shorten drought duration and rising temperature. Meanwhile, it was about 5 months lapse between drought events and maximum declines in vegetation greenness for 2009/2010 drought events. In addition, forest, grassland and cropland revealed significant different ecosystem responses to drought. It indicated that grassland showed an early sensitivity to drought, while cropland was the most sensitive to water deficit and forest was more resilient to drought. This study suggests that it is necessary to detect the difference responses of ecosystem to drought in a regional area with satellite data and ecosystem model.

关键词： drought Standardized Precipitation Index(SPI) vegetation indices Net Primary Productivity(NPP) Southwestern China

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Measuring cotton water status using water-related vegetation indices at leaf and canopy levels

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Journal of Arid Land 2012年第3期4卷 310-319页

作者： QiuXiang YI AnMing BAO Yi LUO Jin ZHAO Xinjiang Institute of Ecology and Geography Chinese Academy of SciencesUrumqi 830011China

Drought is one of the major environmental threats in the world. In recent years, the damage from droughts to the environment and economies of some countries has been extensive, and drought monitoring has caused widespread concerns. Remote sensing has a proven ability to provide spatial and temporal measurements of surface properties, and it offers an opportunity for the quantitative assessment of drought indicators such as the vegetation water content at different levels. In this study, sites of cotton field in Shihezi, Xinjiang, Northwest China were sampled. Four classical water content parameters, namely the leaf equivalent water thickness （EWT^e,f）, the fuel moisture content （FMC）, the canopy equivalent water thickness （EVVmcanopy） and vegetation water content （VWC） were evaluated against seven widely-used water-related vegetation indices, namely the NDII （normalized difference infrared index）, NDWI2130 （normalized difference water index）, NDVI （normalized difference vegetation index）, MSI （moisture stress index）, SRWI （simple ratio water index）, NOWI1240 （normalized difference water index） and WI （water index）, respectively. The results proved that the relationships between the water-related vegetation indices and EWTleaf were much better than that with FMC, and the relationships between vegetation indices and EWTcanopy were better than that with VWC. Furthermore, comparing the significance of all seven water-related vegetation in- dices, WI and NDII proved to be the best candidates for EWT detecting at leaf and canopy levels, with R2 of 0.262 and 0.306 for EWTlear-WI and EWTcanopy-NDII linear models, respectively. Besides, the prediction power of linear regression technique （LR） and artificial neural network （ANN） were compared using calibration and validation dataset, respectively. The results indicated that the performance of ANN as a predictive tool for water status meas- uring was as good as LR. The study should further our understanding of the relationship

关键词： artificial neural network cotton linear regression vegetation indices water parameters

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Reclamation areas and their development studied by vegetation indices

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International Journal of Digital Earth 2008年第1期1卷 155-164,I0011页

作者： L.Halounova Remote Sensing Laboratory Faculty of Civil Engineering Czech Technical University in PragueTha´kurova 716629 Prague 6Czech Republic

Large areas in the Czech Republic were used for open casts of brown coal *** of them have been already *** of them and of their dumps is the next step intheir *** is possible to divide used reclamations into the forest,hydrologic,agricultural and other onesroads,*** age varies from 45 years to as yet *** areas are documented in reclamation *** about age and land use determined groups of these areas to be evaluated by vegetation indices.100 areas with forest type were *** vegetation indices(NDVI,DVI,RVI,PVI,SAVI,MSAVI,TSAVI and EVI)were calculated and their average value in each area in 1988,1992 and 1998 Thematic Mapper data were *** over years showed close relation to precipitations of previous *** relation was confirmed by evaluation of forest areas situated near reclamation ***/negative changes of vegetation indices were different for different groups and different vegetation *** overview of results of vegetation indices is presented for individual areas whose land use comprised at least partly forest *** in a 4-year period(19881992)were in many areas by many indices negative,changes in 10 years were in most areas by most vegetation indices ***,minimum values and maximum values in groups were *** of vegetation indices brought again various *** vegetation index is not sufficient to prove improvement/deterioration of vegetation *** state before measurement should be *** shortage of precipitation can cause vegetation cover deterioration,which is also only *** best development derived from vegetation indices evaluation was found at forest reclamation with mixed tree stand that was 1020 years *** method was derived as a tool for post-finishing control of vegetation development of reclamations performed in several year periods.

关键词： reclaimed area Thematic Mapper vegetation indices time change

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Application of vegetation indices for Detection and Monitoring Oil Spills in Ahoada West Local Government Area of Rivers State,Nigeria

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Journal of Geographical Research 2023年第3期6卷 29-41页

作者： Jonathan Lisa Erebi Egirani E.Davidson Department of Geology Niger Delta UniversityWilberforce IslandBayelsa State560103Nigeria

The study evaluated the environmental effects of an oil spill in Joinkrama 4 and Akimima Ahoada West LGA,Rivers State,Nigeria,using various vegetation *** data for the spill were obtained from the Nigeria Oil Spill Detection and Response Agency,and Landsat imagery was acquired from the United States Geological *** soil samples were collected from the affected area,and their analysis included measuring total petroleum hydrocarbons(TPH),total hydrocarbons(THC),and polycyclic aromatic hydrocarbons(PAH).The obtained data were processed with ArcGIS software,utilizing different vegetation indices such as the Normalized Difference vegetation Index(NDVI),Atmospheric Resistant vegetation Index(ARVI),Soil Adjusted vegetation Index(SAVI),Green Short Wave Infrared(GSWIR),and Green Near Infrared(GNIR).Statistical analysis was performed using SPSS and Microsoft *** results consistently indicated a negative impact on the environment resulting from the oil spill.A comparison of spectral reflectance values between the oil spill site and the non-oil spill site showed lower values at the oil spill site across all vegetation indices(NDVI 0.0665-0.2622,ARVI-0.0495-0.1268,SAVI 0.0333-0.1311,GSWIR-0.183-0.0517,GNIR-0.0104--0.1980),indicating damage to ***,the study examined the correlation between vegetation indices and environmental parameters associated with the oil spill,revealing significant relationships with TPH,THC,and PAH.A t-test with a significance level of pvegetation index values at the non-oil spill site compared to the oil spill site,suggesting a potential disparity in vegetation health between the two ***,this study emphasizes the harmful effect of oil spills on vegetation and highlights the importance of utilizing vegetation indices and spectral reflectance analysis to detect and monitor the impact of oil spills on vegetation.

关键词： vegetation indices TPH PAH THC Oil spill Impact Rivers State Nigeria

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High-throughput phenotyping of two plant-size traits of Eucalyptus species using neural networks

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Journal of Forestry Research 2022年第2期33卷 591-599页

作者： Marcus Vinicius Vieira Borges Janielle de Oliveira Garcia Tays Silva Batista Alexsandra Nogueira Martins Silva Fabio Henrique Rojo Baio Carlos Antônio da Silva Junior Gileno Brito de Azevedo Glauce Taís de Oliveira Sousa Azevedo Larissa Pereira Ribeiro Teodoro Paulo Eduardo Teodoro Federal University of Mato Grosso Do Sul(UFMS) Chapadão Do SulMato Grosso Do Sul 79560000Brazil Department of Geography State University of Mato Grosso(UNEMAT)SinopMato Grosso 78555000Brazil

In forest modeling to estimate the volume of wood,artificial intelligence has been shown to be quite effi-cient,especially using artificial neural networks(ANNs).Here we tested whether diameter at breast height(DBH)and the total plant height(Ht)of eucalyptus can be pre-dicted at the stand level using spectral bands measured by an unmanned aerial vehicle(UAV)multispectral sensor and vegetation *** do so,using the data obtained by the UAV as input variables,we tested different configurations(number of hidden layers and number of neurons in each layer)of ANNs for predicting DBH and Ht at stand level for different Eucalyptus *** experimental design was randomized blocks with four replicates,with 20 trees in each experimental *** treatments comprised five Eucalyptus species(***,***,***,***-dis,and ***)and Corymbria *** and Ht for each plot at the stand level were measured seven times in separate overflights by the UAV,so that the multispectral sensor could obtain spectral bands to calculate vegetation indices(VIs).ANNs were then constructed using spectral bands and VIs as input layers,in addition to the categorical variable (species), to predict DBH and Ht at the stand level simultaneously. This report represents one of the first appli-cations of high-throughput phenotyping for plant size traits in Eucalyptus species. In general, ANNs containing three hidden layers gave better statistical performance (higher esti-mated r, lower estimated root mean squared error-RMSE) due to their greater capacity for self-learning. Among these ANNs, the best contained eight neurons in the first layer, seven in the second, and five in the third (8 − 7 − 5). The results reported here reveal the potential of using the gener-ated models to perform accurate forest inventories based on spectral bands and VIs obtained with a UAV multispectral sensor and ANNs, reducing labor and time.

关键词： Computational intelligence Diameter at breast height Forest inventory Remote sensing vegetation indices

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Coastal wetland vegetation features and digital Change Detection Mapping based on remotely sensed imagery:El-Burullus Lake, Egypt

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International Soil and Water Conservation Research 2020年第1期8卷 66-79页

作者： Asmaa Nasser Mohamed Eid C.O.Olatubara T.A.Ewemoje Haitham Farouk Mohamed Talaat El-Hennawy Department of Environmental Management The Pan African University for Earth and Life Sciences Including Health and AgricultureUniversity of IbadanIbadanNigeria Department of Computer Science Faculty of Computers and InformationSuez UniversitySuezEgypt Nature Conservation Sector of the Ministry of Environment Egypt

El-Burullus Lake is one of the four Egyptian Ramsar sites that constitute internationally important wetlands as they contain a rich biodiversity and have a large number of water bird *** the valuable resources in El-Burullus Lake and its surrounding area have faced various threats to wetlands over recent *** study was carried out to evaluate the dynamics of land cover change using three change scenes of recent and past satellite data from 1990 to *** study utilized ArcGIS10.7,ERDAS Imagine 14,Landsat TM(1990,1999,and 2010),Landsat OLI-TIRS(2019)to analyze the land-use/land-cover(LULC)of El-Burullus *** Difference vegetation Index(NDVI)and Normal-ized Difference Water Index(NDWI)were employed to assess the change scenario of the *** indicated that vegetated land has increased significantly with a concomitant shrinkage in the water body and open soil during the study *** 53 km^2(7.0%)of water body and 8.7 km^2(1.3%)of open soil were lost,while vegetation areas expanded to approximately 29.9 km^2(7.4%).Factors that underpin the observed changes in the area are;reclamation projects and fish-farms which are creating the danger of drying up of the southern coastal parts of the lake,as well as spreading of reed beds(mainly:Phragmites australis)that covers about 20%of El-Burullus lake which led to dry up the lake ***,the study suggests the need for urgent attention on conservation of remaining wetland resources for sustainable utilization for the next generation.

关键词： El-burullus natural wetlands LULC NDVI NDWI Remote sensing vegetation indices

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