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REGIONAL PATTERNS OF normalized difference vegetation index IN NORTH-AMERICAN SHRUBLANDS AND GRASSLANDS

ECOLOGY 1995年第6期76卷 1888-1898页

作者： PARUELO, JM LAUENROTH, WK Dep. Rangeland Ecosyst. Sci. Colorado State Univ. Fort Collins CO 80523 USA

We characterized the seasonal pattern of the normalized difference vegetation index (NDVI) of 49 grassland and shrubland sites corresponding to areas with low human impact. Each site was characterized as a vector of 21 elements, where each element corresponded to the average NDVI for one date. We used the integral of the NDVI as an estimate of the total production, and the difference between the maximum and minimum NDVI over the year as a measure of the seasonality. Based on a Principal Component Analysis, the integral of the NDVI accounted for 63% of the variability of the SITEXDATE matrix. The difference between the maximum and minimum NDVI throughout the year accounted for 19%. Mean annual precipitation explained 67% of the variability of the integral of the NDVI curves (P < 0.01). The slope of the relationship between precipitation and integrated NDVI was significantly steeper for grasslands than for shrublands. The difference between the extreme values of NDVI increased with mean annual precipitation and the thermal amplitude, and decreased with mean annual temperature (P < 0.01).

关键词： ABOVEGROUND NET PRIMARY PRODUCTION AVNRR/NOAA CLIMATIC CONTROLS GLOBAL CHANGE GRASSLANDS MULTIVARIATE ANALYSIS normalized difference vegetation index REGIONAL ANALYSIS SEASONALITY SHRUBLANDS

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Multi-temporal characterization of land surface temperature and its relationships with normalized difference vegetation index and soil moisture content in the Yellow River Delta, China

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GLOBAL ECOLOGY AND CONSERVATION 2020年 23卷

作者： Chi, Yuan Sun, Jingkuan Sun, Yonggen Liu, Shengjing Fu, Zhanyong Minist Nat Resources Inst Oceanog 1 Qingdao 266061 Shandong Peoples R China Minist Nat Resources Key Lab Coastal Zone Exploitat & Protect Nanjing 210024 Jiangsu Peoples R China Binzhou Univ Shandong Key Lab Ecoenvironm Sci Yellow River Del 391Huanghewu Rd Binzhou 256600 Shandong Peoples R China Nanjing Univ Sch Geog & Ocean Sci Nanjing 210023 Jiangsu Peoples R China China Univ Min & Technol Sch Chem & Environm Engn Beijing 100083 Peoples R China

Land surface temperature (LST) is an important indicator of resource and environment changes in coastal wetlands and exhibits considerable spatiotemporal variations under multiple influences of intensive landesea interaction and various human activities. Revealing the multi-temporal characteristics of LST and its relationships with normalized difference vegetation index (NDVI) and soil moisture content (MC) in coastal wetlands is important for identifying the LST variations under complex factors, the heat effects of different human exploitations, and the corresponding changes in vegetation and soil water conditions. The Yellow River Delta, a typical and important coastal wetland in China, was selected to demonstrate the study. Remote sensing and field investigation served as the data source, and the LST spatiotemporal patterns and their intrinsic correlations with NDVI and MC in the last 30 years and across different seasons were analyzed. Results indicated that LST spatial distributions varied in different years and seasons. In 1987, LST was low along the Yellow River and high in alongshore areas;in 2016, LST was distinctly low in most of the alongshore areas and high in urban and industrial areas. Across seasons, LST differences between alongshore and inner areas were more distinct in spring that in the other seasons, and LST in urban and industrial areas was especially higher than that in other areas in summer. Among different land covers, salt pond generated cool island effect, whereas urban and industrial areas generated heat island effect. Significant correlations were observed between LST and NDVI at regional scale and among LST, NDVI, and MC at site scale, and their relationships varied in different land cover types across different times. The changes in shorelines, land covers, and vegetation and soil conditions jointly determined the LST spatiotemporal patterns, and human activity has been the main driving factor. (c) 2020 The Authors. Published by Elsevie

关键词： Land surface temperature Coastal wetland Spatiotemporal pattern Seasonality normalized difference vegetation index Moisture content

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Use of time series normalized difference vegetation index (NDVI) to monitor fall armyworm (Spodoptera frugiperda) damage on maize production systems in Africa

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GEOCARTO INTERNATIONAL 2023年第1期38卷 Article: 2186492页

作者： Adan, Marian Tonnang, Henri E. Z. Greve, Klaus Borgemeister, Christian Goergen, Georg Univ Bonn Ctr Dev Res ZEF Bonn Germany Int Ctr Insect Physiol & Ecol ICIPE Nairobi Kenya Tri Postal Int Inst Trop Agr IITA Cotonou Benin

Fall armyworm (FAW) Spodoptera frugiperda (J.E. Smith), damage was monitored at a regional scale using time series data in Western and Southern African countries. The study employed the normalized difference vegetation index (NDVI) computed from Landsat 8 imagery using the Google Earth Engine (GEE) using image composites for the years 2013 to 2020 for the study areas. The index was then reclassified based on the NDVI threshold values into low, sparse, moderate, and dense classes. FAW prevalence data were then utilized to validate the correlation between the FAW infestation and NDVI values. FAW was associated with a decrease in vegetation productivity between the years 2016, 2017, and 2018 when the pest infestation was reported in the study areas. The validation results showed that there is a correlation between FAW infestation and NDVI (R(2)0.83). Our study highlighted that NDVI can be used as a proxy to quantify pest damage to vegetation productivity.

关键词： Landsat 8 Google Earth Engine (GEE) vegetation productivity fall armyworm normalized difference vegetation index

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Spatiotemporal Changes in Actual Evapotranspiration, Soil Moisture, the normalized difference vegetation index, and Land Use/Land Cover in the Gedeo Coffee–Based Agroforestry System of Southern Ethiopia

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Journal of Chinese Soil and Water Conservation 2024年第2期55卷 94-105页

作者： Getahun, Tedla Mamo, Girma Haile, Getahun Markos, Daniel Tesfaye, Gebremedhin Dilla University Department of Natural Resource Management for Sustainable Agriculture P.O.Box 419 Dilla Ethiopia Ethiopian Institute of Agricultural Research P.O.Box-2003 Addis Ababa Ethiopia Hawassa Agricultural Research Center P.O.Box-06 Hawassa Ethiopia

Mapping and quantifying changes in land use/land cover (LULC) and their drivers guides the identification of areas vulnerable to change and the design of sustainable land management strategies. In the Gedeo zone of Southern Ethiopia, policies and strategies are required to protect coffee-based agroforestry from the destabilizing effects of climate change, a declining resource base, and unplanned changes in land use. Accordingly, this study analyzed trends in LULC, soil moisture, actual evapotranspiration, and the normalized difference vegetation index (NDVI) over the preceding 30 years by using remote sensing, geographic information systems, and secondary data. Using Landsat images from the years 1993, 2008, and 2023, we mapped six major LULC types: wetlands, grassland, settlements, bare land, forest land, and cultivated land including crop lands and agroforestry systems. The NDVI exhibited a significant decreasing trend in the regions of Dilla, Raphe, and Wonago, indicating hot spots of LULC changes. Cultivated land and forest land underwent the most extensive LULC changes, with rates of 45.1% and −22%, respectively. LULC types with high environmental importance, namely grassland and wetlands, decreased annually by 10.8% and 4.3%, respectively. Settlements increased by 12.2% at the expense of coffee-based agroforestry systems, which have been the backbone of the local economy. The preceding three decades have seen rapid urban growth and development at the cost of sustainable quality coffee production in and around the study area. The root causes underlying LULC changes have been urbanization, climate change, population growth, and a lack of public awareness regarding the consequences of LULC changes. LULC changes, including the conversion of wetlands to cultivated land and uncontrolled settlements along the finest coffee belt, have threatened food and income security and have undermined ecological sustainability initiatives, as evidenced by the decreasing NDVI thro

关键词： Agroforestry Coffee Land use normalized difference vegetation index Settlement

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Detection of large-scale climate signals in spring vegetation index (normalized difference vegetation index) over the Northern Hemisphere

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JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 2003年第D16期108卷

作者： Gong, DY Ho, CH Beijing Normal Univ Key Lab Environm Change & Nat Disaster Inst Resources Sci Beijing 100875 Peoples R China Seoul Natl Univ Sch Earth & Environm Sci Seoul 151742 South Korea

Climate is one of the determinants driving ecosystems on both local and global scales. During the last two decades, there has occurred a dramatic temperature increase in the northern midlatitudes to high latitudes. The rapid warming has resulted in the promotion of bioactivity and an early growing season. However, the temperature and vegetation changes are not uniform in geographical distribution. In the present study, we analyze the spatial features in the normalized difference vegetation index (NDVI)-temperature relationship over Eurasia and North America in spring for the period 1982-2000. The NDVI data are derived from the Earth Observing System Pathfinder advanced very high resolution radiometer data sets. A singular value decomposition analysis is applied to the covariance matrix of the NDVI and temperature. Most of the squared covariance, 91.6%, is captured by the first seven paired modes. The result clearly indicates that the temperature is a focal factor influencing vegetation activity. Furthermore, those seven paired modes show large-scale features and well-defined patterns. The atmospheric circulation systems, such as the Southern Oscillation, North Atlantic Oscillation/Arctic Oscillation, Pacific/North American pattern, Eurasian pattern, western Pacific pattern, western Atlantic pattern, eastern Atlantic pattern, and North Pacific index, are found to be associated with that. The time coefficient corresponding to the first paired modes, centered on western Siberia, is correlated significantly with the Eurasian teleconnection pattern. Their correlation coefficients are 0.72 and 0.78 for vegetation and temperature, respectively, for the data period. Other modes are also correlated with one or more circulation indices. This implies that the large-scale circulation is essential for understanding the regional response of vegetation to global climate change. Taking all nine circulation indices and time lags into account, a large portion (71%) of the satellite-s

关键词： normalized difference vegetation index climate impact atmospheric circulation teleconnection vegetation change

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Implications Atmospheric Correction for normalized difference vegetation index (NDVI) Analysis in Multispectral Camera LAPAN A3

Implications Atmospheric Correction for Normalized Differenc...

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IEEE International Conference on Aerospace Electronics and Remote Sensing Technology (ICARES)

作者： Ega Asti Anggari Sigit Heru Murti Wahyudi Hasbi Department of Information Geographic Science Universitas Gadjah Mada Yogyakarta Indonesia Research Center for Satellite Technology National Research and Innovation Agency Yogyakarta Indonesia Research Center for Satellite Technology National Research and Innovation Agency Bogor Indonesia

ISBN: (数字)9798331542016

ISBN: (纸本)9798331542023

Lapan A3 images encode their pixel values as digital numbers (DN). To conduct index analysis using these images, it is necessary to convert the DN values into surface reflectance values, which requires atmospheric correction. This study focuses on performing atmospheric correction on Lapan A3 imagery, specifically over the Batu Jamus rubber plantation and its surroundings in Karanganyar Regency, Central Java. Three atmospheric correction methods were employed: histogram adjustment, FLAASH, and 6S. The corrected reflectance values were subsequently utilized to calculate the normalized difference vegetation index (NDVI). The analysis demonstrated that atmospheric correction generally led to a reduction in reflectance values in the red and near-infrared (NIR) bands. Moreover, NDVI calculations revealed notable changes in values before and after correction. Histogram adjustment yielded a median NDVI value of 0.772, higher than the pre-correction value, while the FLAASH and 6S methods resulted in reduced median NDVI values of 0.256 and 0.462, respectively. Pearson correlation analysis indicated a strong positive correlation between pre- and post-correction NDVI values, with correlation coefficients exceeding 0.87. In the FLAASH and 6S methods, there are two land cover types that exhibit similar reference NDVI values. Therefore, the recommended atmospheric correction methods for calculating NDVI values using LAPAN A3 data are the FLAASH and 6S methods.

关键词： Reflectivity Correlation coefficient Histograms normalized difference vegetation index Correlation Shape Plantations Land surface Rubber Remote sensing

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Microcontrolled System to Map and Monitor normalized difference vegetation index (NDVI) in Pasture Areas

Microcontrolled System to Map and Monitor Normalized Differe...

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International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT)

作者： Victório Mariani Roque Tiago Oliveira Weber Altamiro Amadeu Susin Electrical Engineering Graduate Program University Federal of Rio Grande do Sul Porto Alegre Brazil

ISBN: (数字)9798350350869

ISBN: (纸本)9798350350876

The vast territorial extension of Brazil is also a positive factor, but there is room for improvement through technological implementations. This work proposes monitoring the vegetation index (NDVI) by mapping the state of the pasture during the cattle's stay in the field. Measurements obtained with a commercial Greenseeker device are compared and integrated with values extracted from satellite images from the Satveg tool, which has a periodicity of 16 days and a resolution of 250 meters. A function is created to predict the NDVI in the total area based on points collected locally and from the satellite, using the KNN and Kriging algorithms for data fusion and interpolation. The article foresees contributions to the efficiency of agricultural production, allowing correct livestock management based on NDVI mapping. Additionally, results from previous simulations of analog circuits are presented for developing the NDVI measuring instrument. Future work aims to use the embedded system to automatically collect NDVI data and generate the Map presented here.

关键词： Meters normalized difference vegetation index vegetation mapping Data visualization Data integration Production Cows Analog circuits Satellite images Monitoring

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A NOVEL METHOD TO RECONSTRUCT normalized difference vegetation index TIME SERIES BASED ON TEMPORAL-SPATIAL ITERATION ESTIMATION

A NOVEL METHOD TO RECONSTRUCT NORMALIZED DIFFERENCE VEGETATI...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Lili Xu Baolin Li Yecheng Yuan Tao Zhang State Key Lab of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research CAS

ISBN: (纸本)9781479979301

Reconstructing normalized difference vegetation index (NDVI) time series datasets is essential for monitoring long-term changes of the terrestrial surface. Here, a temporal-spatial iteration (TSI) method was developed to estimate the NDVIs of contaminated MODIS13Q1 pixels based on reliable MODIS13Q1 data. NDVIs of contaminated pixels were firstly computed through linear interpolation of adjacent high-quality pixels in the temporal series. Then, undetermined NDVIs of contaminated pixels were derived using the NDVI of the high-quality pixel that reflected the most similar land cover within the same ecological region, based on the weighted trajectory distance algorithm. These two steps were repeated iteratively, taking the estimated NDVIs as high-quality NDVIs to estimate other undetermined NDVIs of contaminated pixels until all NDVIs of contaminated pixels were estimated. The accuracies of estimated NDVIs using TSI were clearly higher than the asymmetric Gaussian, Savitzky-Golay, and window-regression methods;root mean square error and mean absolute percent error decreased by 14.0-104.8% and 19.4-47.3%, respectively. Furthermore, the TSI method performed better over a variety of environmental conditions. Variation of performance by the compared methods was 8.8-17.0 times than that of the TSI method. The TSI method will be most applicable when large amount of contaminated pixels exist.

关键词： Reconstruction Time-series NDVI Trajectory Distance Temporal-Spatial Correlation normalized difference vegetation index pixel Thyroid-Stimulating Immunoglobulins Reconstructive Surgical Procedures land cover Time series iterative methods Reconstructions linearly independant

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Elk distributions relative to spring normalized difference vegetation index values

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International Journal of Ecology 2010年第unknown期2010卷 1-10页

作者： Smallidge, Samuel T. Baker, Terrell T. Vanleeuwen, Dawn Gould, William R. Thompson, Bruce C. College of Agricultural Consumer and Environmental Sciences New Mexico State University MSC 3AE Las Cruces NM 88003 P.O. Box 30003 United States University Statistics Center New Mexico State University MSC 3CQ Las Cruces NM 88003 P.O. Box 30003 United States New Mexico Energy Minerals and Natural Resources Department Santa Fe NM 87505 1220 South St. Francis Dr. United States

Rocky Mountain elk (Cervus elaphus) that winter near San Antonio Mountain in northern New Mexico provide important recreational and economic benefits while creating management challenges related to temporospatial variation in their spring movements. Our objective was to examine spring distributions of elk in relation to vegetative emergence as it progresses across the landscape as measured by remote sensing. Spring distributions of elk were closely associated with greater photosynthetic activity of spring vegetation in 2 of 3 years as determined using NDVI values derived from AVHRR datasets. Observed elk locations were up to 271% greater than expected in the category representing the most photosynthetic activity. This association was not observed when analyses at a finer geographic scale were conducted. Managers facing challenges involving human-wildlife interactions and land-use issues should consider environmental conditions that may influence variation in elk association with greener portions of the landscape. © 2010 Samuel T. Smallidge et al.

关键词： normalized difference vegetation index manager Spring season Category Economic benefits human-wildlife relations Elaphurus davidianus landscapes New Mexico

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Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics

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JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2025年第3期17卷

作者： Xia, Yushu Sanderman, Jonathan Watts, Jennifer D. Machmuller, Megan B. Mullen, Andrew L. Rivard, Charlotte Endsley, Arthur Hernandez, Haydee Kimball, John Ewing, Stephanie A. Litvak, Marcy Duman, Tomer Krishnan, Praveena Meyers, Tilden Brunsell, Nathaniel A. Mohanty, Binayak Liu, Heping Gao, Zhongming Chen, Jiquan Abraha, Michael Scott, Russell L. Flerchinger, Gerald N. Clark, Patrick E. Stoy, Paul C. Khan, Anam M. Brookshire, E. N. Jack Zhang, Quan Cook, David R. Thienelt, Thomas Mitra, Bhaskar Mauritz-Tozer, Marguerite Tweedie, Craig E. Torn, Margaret S. Billesbach, Dave Woodwell Climate Res Ctr Falmouth MA USA Columbia Univ Lamont Doherty Earth Observ Palisades NY USA Montana State Univ Dept Land Resources & Environm Sci Bozeman MT USA Colorado State Univ Nat Resources Ecol Lab Ft Collins CO 80523 USA Brookings Inst Ctr Sustainable Dev Washington DC USA Univ Montana WA Franke Coll Forestry & Conservat Missoula MT USA Colorado Field Off Nat Conservancy Boulder CO USA Univ New Mexico Albuquerque NM USA NOAA Atmospher Turbulence & Diffus Div Oak Ridge TN USA Univ Kansas Dept Geog & Atmospher Sci Lawrence KS USA Texas A&M Univ Biol & Agr Engn Dept College Stn TX USA Washington State Univ Dept Civil & Environm Engn Pullman WA 99164 USA Sun Yat Sen Univ Sch Atmospher Sci Zhuhai Peoples R China Michigan State Univ Dept Geog Environm & Spatial Sci E Lansing MI USA USDA ARS Southwest Watershed Res Ctr Tucson AZ USA USDA ARS Northwest Watershed Res Ctr Boise ID USA Univ Wisconsin Madison Dept Biol Syst Engn Madison WI USA Univ Wisconsin Madison Dept Forest & Wildlife Ecol Madison WI USA Indiana Univ Sch Publ & Environm Affairs Indianapolis IN USA Wuhan Univ Renmin Hosp Wuhan Peoples R China Argonne Natl Lab Div Environm Sci Lemont IL USA Martin Luther Univ Halle Wittenberg Dept Geoecol Wittenberg Germany James Hutton Inst Informat & Computat Sci Aberdeen Scotland Univ Texas El Paso Dept Biol Sci El Paso TX 79968 USA Lawrence Berkeley Natl Lab Climate & Ecosyst Sci Div Berkeley CA USA Univ Nebraska Lincoln Dept Biol Syst Engn Lincoln NE USA

Rangelands provide significant environmental benefits through many ecosystem services, which may include soil organic carbon (SOC) sequestration. However, quantifying SOC stocks and monitoring carbon (C) fluxes in rangelands are challenging due to the considerable spatial and temporal variability tied to rangeland C dynamics as well as limited data availability. We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long-term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C-cycle processes. Bayesian calibration was conducted using quality-controlled C flux data sets obtained from 61 Ameriflux and NEON flux tower sites from Western and Midwestern US rangelands to parameterize the model according to dominant vegetation classes (perennial and/or annual grass, grass-shrub mixture, and grass-tree mixture). The resulting RCTM system produced higher model accuracy for estimating annual cumulative gross primary productivity (GPP) (R-2 > 0.6, RMSE <390 g C m(-2)) relative to net ecosystem exchange of CO2 (NEE) (R-2 > 0.4, RMSE <180 g C m(-2)). Model performance in estimating rangeland C fluxes varied by season and vegetation type. The RCTM captured the spatial variability of SOC stocks with R-2 = 0.6 when validated against SOC measurements across 13 NEON sites. Model simulations indicated slightly enhanced SOC stocks for the flux tower sites during the past decade, which is mainly driven by an increase in precipitation. Future efforts to refine the RCTM system will benefit from long-term network-based monitoring of vegetation biomass, C fluxes, and SOC stocks.

关键词： gross primary productivity net ecosystem exchange soil organic carbon rangeland flux towers modeling C carbon DNDC Denitrification-Decomposition DSM digital soil mapping fPAR fraction of absorbed photosynthetically active radiation GEE Google Earth Engine GPP Gross Primary Productivity HOC humus organic carbon L4C Level 4 Carbon LOOCV leave-one-out cross-validation LUE light use efficiency MBE mean bias error NDVI normalized difference vegetation index NEE net ecosystem exchange of carbon dioxide NEON National Ecological Observatory Network NIR near infrared band NLCD National Land Cover Database NLDAS North American Land Data Assimilation System NPP net primary productivity nRMSE normalized Root Mean Square Error PI principal investigator POC particulate organic carbon QC quality control RAP Rangeland Analysis Platform RB relative bias RCTM Rangeland Carbon Tracking and Management RECO ecosystem respiration RMSE Root Mean Square Error ROC resistant organic carbon RothC Rothamsted Carbon RS remote sensing SMAP Soil Moisture Active-Passive SMLR stepwise multiple linear regression SOC SOM soil organic matter STARFM Spatial and Temporal Adaptive Reflectance Fusion Model VPD vapor pressure deficit

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