Phenologically-Tuned MODIS NDVI-Based Time Series  (2000-2012) For Monitoring Of Vegetation and Climate Change in North-Eastern Punjab, Pakistan

Phenologically-Tuned MODIS NDVI-Based Time Series (2000-2012) For Monitoring Of Vegetation and Climate Change in North-Eastern Punjab, Pakistan

Dr. Farooq Ahmad

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University of the Punjab

Phenologically-Tuned MODIS NDVI-Based Time Series (2000-2012) For Monitoring Of Vegetation and Climate Change in North-Eastern Punjab, Pakistan

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Abstract

One of the main factors determining the daily variation of the active surface temperature is the state of the vegetation cover. It can well be characterized by the Normalized Difference Vegetation Index (NDVI). The NDVI has the potential ability to signal the vegetation features of different eco-regions and provides valuable information as a remote sensing tool in studying vegetation phenology cycles. The vegetation phenology is the expression of the seasonal cycles of plant processes and contributes vital current information on vegetation conditions and their connections to climate change. The NDVI is computed using near-infrared and red reflectances, and thus has both an accuracy and precision. A gapless time series of MODIS NDVI (MOD13A1) composite raster data from 18th February, 2000 to 16th November, 2012 with a spatial resolution of 500 m was utilized. Time-series terrestrial parameters derived from NDVI have been extensively applied to global climate change, since it analyzes each pixel individually without the setting of thresholds to detect change within a time series.

References

129 Cites in Article

Reference Format

J Aber,S Ollinger,C Federer,P Reich,M Goulden,D Kicklighter,J Melillo,R Lathrop (1995). Predicting the effects of climate change on water yield and forest production in the northeastern United States.
S Ackerman,K Strabala,W Menzel,R Frey,C Moeller,L Gumley,B Baum,S Seemann,Z Hong (2006). Discriminating clear sky from clouds with MODIS, Algorithm theoretical basis document.
S Ackerman,K Strabala,W Menzel,R Frey,C Moeller,L Gumley (1998). Discriminating clear sky from clouds with MODIS.
Cristina Aguilar,Julie Zinnert,María Polo,Donald Young (2012). NDVI as an indicator for changes in water availability to woody vegetation.
F Ahmad (2012). NOAA AVHRR satellite data for evaluation of climatic variation and vegetation change in the Punjab Province, Pakistan.
F Ahmad (2012). A review of remote sensing data change detection: Comparison of Faisalabad and Multan Districts, Punjab Province, Pakistan.
Farooq Ahmad (2012). Detection of change in vegetation cover using multi-spectral and multi-temporal information for district Sargodha, Pakistan.
T Akiyama,K Kawamura,A Fukuo,Z Chen (2002). Sustainable grassland management using GIS, GPS and remote sensing data in Inner Mongolia.
A Akkartala,O Türüdüa,F Erbekb (2004). Analysis of changes in vegetation biomass using multitemporal and multisensor satellite data.
A Anyamba,J Eastman (1996). Interannual variability of NDVI over Africa and its relation to El Niño/Southern Oscillation.
Germán Baldi,José Paruelo (2008). Land-Use and Land Cover Dynamics in South American Temperate Grasslands.
G Baldi,M Nosetto,R Aragón,F Aversa,J Paruelo,E Jobbágy (2008). Long-term satellite NDVI datasets: Evaluating their ability to detect ecosystem functional changes in South America.
D Baldocchi,T Black,P Curtis,E Falge,J Fuentes,A Granier,L Gu,A Knohl,K Pilegaard,H Schmid,R Valentini,K Wilson,S Wofsy,L Xu,S Yamamoto (2005). Predicting the onset of net carbon uptake by deciduous forests with soil temperature and climate data: a synthesis of FLUXNET data.
F Baret,G Guyot (1991). Potentials and limits of vegetation indices for LAI and APAR assessment.
William Barnes,Vincent Salomonson (1993). MODIS: a global imaging spectroradiometer for the Earth Observing System.
W Barnes,T Pagano,V Salomonson (1998). Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1.
M Budde,G Tappan,J Rowland,J Lewis,L Tieszen (2004). Assessing land cover References Références Referencias.
Phenologically-Tuned MODIS NDVI-Based Time Series (2000-2012) for Monitoring of Vegetation and Climate Change in North-Eastern Punjab, Pakistan performance in Senegal, West Africa using 1-km integrated NDVI and local variance analysis.
Graciela Canziani,Rosana Ferrati,Claudio Rossi,Diego Ruiz-Moreno (2006). The influence of climate and dam construction on the Ibera wetlands, Argentina.
J Campbell (1987). Introduction to remote sensing.
Hugo Carrão,Paulo Gonçalves,Mário Caetano (2008). Contribution of multispectral and multitemporal information from MODIS images to land cover classification.
Varun Chandola,Dafeng Hui,Lianhong Gu,Budhendra Bhaduri,Ranga Vatsavai (2010). Using Time Series Segmentation for Deriving Vegetation Phenology Indices from MODIS NDVI Data.
Pei-Yu Chen,Gunar Fedosejevs,Mario Tiscareño-López,Jeffrey Arnold (2006). Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI Composite Data Using Agricultural Measurements: An Example at Corn Fields in Western Mexico.
P Chen,R Srinivasan,G Fedosejevs,A Báez-González,P Gong (2002). Assessment of NDVI composite using merged NOAA-14 and NOAA-15 AVHRR data.
Robert Charbonneau,G Kondolf (1993). Land use change in California, USA: Nonpoint source water quality impacts.
Bhaskar Choudhury (1987). Relationships between vegetation indices, radiation absorption, and net photosynthesis evaluated by a sensitivity analysis.
C Chris,E Molly (2006). Intra-seasonal NDVI change projections in semi-arid Africa.
E Chuvieco,I Aguado,D Cocero,D Riano (2003). Design of an empirical index to estimate fuel moisture content from NOAA-AVHRR images in forest fire danger studies.
Linda Cyr,Ferdinand Bonn,Alain Pesant (1995). Vegetation indices derived from remote sensing for an estimation of soil protection against water erosion.
K Dabrowska-Zielinska,F Kogan,A Ciolkosz,M Gruszczynska,W Kowalik (2002). Modelling of crop growth conditions and crop yield in Poland using AVHRR-based indices.
Philip Dennison,Dar Roberts (2003). The effects of vegetation phenology on endmember selection and species mapping in southern California chaparral.
Jiarui Dong,Robert Kaufmann,Ranga Myneni,Compton Tucker,Pekka Kauppi,Jari Liski,Wolfgang Buermann,V Alexeyev,Malcolm Hughes (2003). Remote sensing estimates of boreal and temperate forest woody biomass: carbon pools, sources, and sinks.
J Dorman,P Sellers (1989). A Global climatology of albedo, roughness length and stomatal resistance for atmospheric general circulation models as represented by the Simple Biosphere Model (SiB).
Umar Farooq,Munir Ahmad,Abdul Jasra (2007). Natural Resource Conservation, Poverty Alleviation, and Farmer Partnership.
P Fearnside (2005). Deforestation in Brazilian Amazonia: History, rates, and consequences.
F Fontana (2009). From single pixel to continental scale: using AVHRR and MODIS to study land surface parameters in mountain regions.
D Fuller (1998). Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987-1993.
B Gao (1996). NDWI -A normalized difference water index for remote sensing of vegetation liquid water from space.
E Glenn,A Huete,P Nagler,S Nelson (2008). Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape.
H Grau,N Gasparri,T Aide (2005). Agriculture expansion and deforestation in seasonally dry forests of north-west Argentina.
B Guenther,G Godden,X Xiong,E Knight,S Qiu,H Montgomery,M Hopkins,M Khayat,Z Hao (1998). Prelaunch algorithm and data format for the level 1 calibration products for the EOS-AM1 Moderate Resolution Imaging Spectroradiometer (MODIS).
X Guo (2003). Relationships between NDVI and climatological variability in the Prairie ecozone of Canada.
Sandra Hamel,Mathieu Garel,Marco Festa‐bianchet,Jean‐michel Gaillard,Steeve Côté (2009). Spring Normalized Difference Vegetation Index (NDVI) predicts annual variation in timing of peak faecal crude protein in mountain ungulates.
S Hashemi (2010). Evaluating phenological events of shrubs land by AVHRR data.
C Huang,S Kim,A Altstatt,J Townshend,P Davis,K Song,C Tucker,O Rodas,A Yanosky,R Clay,J Musinsky (2007). Rapid loss of Paraguay's Atlantic forest and the status of protected areas: A Landsat assessment.
A Huete,K Didan,T Miura,E Rodriguez,X Gao,L Ferreira (2002). Overview of the radiometric and biophysical performance of the MODIS vegetation indices.
Alfredo Huete,Kamel Didan,Yosio Shimabukuro,Piyachat Ratana,Scott Saleska,Lucy Hutyra,Wenze Yang,Ramakrishna Nemani,Ranga Myneni (2006). Amazon rainforests green‐up with sunlight in dry season.
A Huete,C Justice,Van Leeuwen (1999). MODIS vegetation index (MOD 13) algorithm theoretical basis document version 3.
Alice Isaacman,Gary Toller,William Barnes,Bruce Guenther,Xiaoxiong Xiong (2003). MODIS Level 1B calibration and data products.
Mark Jakubauskas,David Legates,Jude Kastens (2002). Crop identification using harmonic analysis of time-series AVHRR NDVI data.
J Jenkins,B Braswell,S Frolking,J Aber (2002). Detecting and predicting spatial and interannual patterns of temperate forest springtime phenology in the eastern U.S..
J Jensen (2005). Introductory digital image processing: A remote sensing perspective. 3 rd Edition.
L Ji,A Peters (2003). Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices.
Suming Jin,Steven Sader (2005). MODIS time-series imagery for forest disturbance detection and quantification of patch size effects.
A Huete (2005). Global variability of terrestrial surface properties derived from MODIS visible to thermal-infrared measurements.
(2003). MODIS technical specifications.
K Hufkens,M Friedl,A Richardson,T Milliman,M Migliavacca (2010). Vegetation phenology from MODIS/AVHRR/PhenoCam: Scaling and validation possibilities.
G Jianya,S Haigang,Ma Guorui,Z Qiming (2008). Processing of multitemporal data and change detection.
C Justice,E Vermote,J Townshend,R Defries,D Roy,D Hall,V Salomonson,J Privette,G Riggs,A Strahler,W Lucht,R Myneni,Y Knyazikhin,S Running,R Nemani,Zhengming Wan,A Huete,W Van Leeuwen,R Wolfe,L Giglio,J Muller,P Lewis,M Barnsley (1985). The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research.
C Justice,J Townshend,E Vermote,E Masuoka,R Wolfe,N Saleous,D Roy,J Morisette (2002). An overview of MODIS land data processing and product status.
A Karaburun (2010). Estimation of C factor for soil erosion modeling using NDVI in Büyükçekmece watershed.
A Kawabata,K Ichii,Y Yamaguchi (2001). Global monitoring of interannual changes in vegetation activities using NDVI and its relationships to temperature and precipitation.
J Khan (1993). The Climate of Pakistan.
K Khlopenkov,A Trishchenko (2008). Implementation and Evaluation of Concurrent Gradient Search Method for Reprojection of MODIS Level 1B Imagery.
F Kogan (1987). Vegetation index for areal analysis of crop conditions.
Felix Kogan (1997). Global Drought Watch from Space.
Zhaoqin Li,Xulin Guo (2012). Detecting Climate Effects on Vegetation in Northern Mixed Prairie Using NOAA AVHRR 1-km Time-Series NDVI Data.
H Liu,A Huete (1995). A feedback based modification of the NDV I to minimize canopy background and atmospheric noise.
D Lloyd (1990). A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery.
T Logan (1999). EOS/AM-1 Digital Elevation Model (DEM) Data Sets: DEM and DEM auxiliary datasets in support of the EOS/Terra platform.
S Los,P North,W Grey,M Barnsley (2005). A method to convert AVHRR Normalized Difference Vegetation Index time series to a standard viewing and illumination geometry.
Wolfgang Lucht,I Prentice,Ranga Myneni,Stephen Sitch,Pierre Friedlingstein,Wolfgang Cramer,Philippe Bousquet,Wolfgang Buermann,Benjamin Smith (2002). Climatic Control of the High-Latitude Vegetation Greening Trend and Pinatubo Effect.
Ada Malo,Sharon Nicholson (1990). A study of rainfall and vegetation dynamics in the African Sahel using normalized difference vegetation index.
C Meneses-Tovar (2011). NDVI as indicator of degradation.
A Menzel,N Estrella,P Fabian (2001). Spatial and temporal variability of the phenological seasons in Germany from 1951 to 1996.
M Moran,Ray Jackson,Philip Slater,Philippe Teillet (1992). Evaluation of simplified procedures for retrieval of land surface reflectance factors from satellite sensor output.
S Moulin,L Kergoat,N Viovy,G Dedieu (1997). Global-Scale Assessment of Vegetation Phenology Using NOAA/AVHRR Satellite Measurements.
V Musande,A Kumar,K Kale,P Roy (2012). TEMPORAL INDICES DATA FOR SPECIFIC CROP DISCRIMINATION USING FUZZY BASED NOISE CLASSIFIER.
R Myneni,G Asrar (1994). Atmospheric effects and spectral vegetation indices.
R Myneni,C Keeling,C Tucker,G Asrar,R Nemani (1997). Increased plant growth in the northern high latitudes from 1981 to 1991.
Wei Ouyang,Fanghua Hao,Andrew Skidmore,Thomas Groen,A Toxopeus,Tiejun Wang (2012). Integration of multi-sensor data to assess grassland dynamics in a Yellow River sub-watershed.
José Paruelo,Howard Epstein,William Lauenroth,Ingrid Burke (1997). ANPP ESTIMATES FROM NDVI FOR THE CENTRAL GRASSLAND REGION OF THE UNITED STATES.
Aníbal Pauchard,Mauricio Aguayo,Eduardo Peña,Roberto Urrutia (2006). Multiple effects of urbanization on the biodiversity of developing countries: The case of a fast-growing metropolitan area (Concepción, Chile).
Nathalie Pettorelli,Jon Vik,Atle Mysterud,Jean-Michel Gaillard,Compton Tucker,Nils Stenseth (2005). Using the satellite-derived NDVI to assess ecological responses to environmental change.
S Piao,A Mohammat,J Fang,Q Cai,J Feng (2006). NDVI-based increase in growth of temperate grasslands and its responses to climate changes in China.
S Piao,J Fang,J He (2006). Variations in vegetation net primary production in the Qinghai-Xizang Plateau, China, from 1982 to 1999.
S Piao,J Fang,L Zhou,Q Guo,M Henderson,W Ji,Y Li,S Tao (2003). Interannual variations of monthly and seasonal NDVI in China from 1982 to 1999.
Christopher Potter,James Randerson,Christopher Field,Pamela Matson,Peter Vitousek,Harold Mooney,Steven Klooster (1993). Terrestrial ecosystem production: A process model based on global satellite and surface data.
Anup Prasad,Sudipta Sarkar,Ramesh Singh,Menas Kafatos (2007). Inter-annual variability of vegetation cover and rainfall over india.
J Nightingale,W Esaias,R Wolfe,J Nickeson,P Ma (2008). Assessing Honey Bee Equilibrium Range and Forage Supply using Satelite-Derived Phenology.
Md Rahman,A Islam,Md Rahman (2004). NDVI derived sugarcane area identification and crop condition assessment.
A Richardson,D Hollinger,D Dail,J Lee,J Munger,J O'keefe (2009). Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests.
Hugo Romero,Fernando Ordenes (2004). Emerging Urbanization in the Southern Andes.
J Rouse,R Haas,J Schell,D Deering (1973). Monitoring vegetation systems in the Great Plains with ERTS.
Ramesh Singh,Sudipa Roy,F Kogan (2002). Vegetation and temperature condition indices from NOAA AVHRR data for drought monitoring over India.
Application on remote sensing technology for the management of agricultural resources.
T Sakamoto,M Yokozawa,H Toritani,M Shibayama,N Ishitsuka,H Ohno (2005). A crop phenology detection method using time-series MODIS data.
Vincent Salomonson,David Toll (1991). Execution phase (C/D) spectral band characteristics of the EOS moderate resolution imaging spectrometer-Nadir (MODIS-N) facility instrument.
G Senseman,C Bagley,S Tweddale (1996). Integrating Landsat TM and SRTM-DEM derived variables with decision trees for habitat classification and change detection in complex neotropical environments.
R Stöckli,P Vidale (2004). European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset.
Bradley Reed,Jesslyn Brown,Darrel Vanderzee,Thomas Loveland,James Merchant,Donald Ohlen (1994). Measuring phenological variability from satellite imagery.
Phenologically-Tuned MODIS NDVI-Based Time Series (2000-2012) for Monitoring of Vegetation and Climate Change in North-Eastern Punjab.
Bin Tan,Jeffrey Morisette,Robert Wolfe,Feng Gao,Gregory Ederer,Joanne Nightingale,Jeffrey Pedelty (2008). Vegetation Phenology Metrics Derived from Temporally Smoothed and Gap-Filled MODIS Data.
David Thomas,H Leason (2005). Dunefield activity response to climate variability in the southwest Kalahari.
J Townshend (1992). Improved Global Data for Land Applications: A proposal for a new high resolution data Set.
J Townshend,C Justice (1988). Selecting the spatial resolution of satellite sensors required for global monitoring of land transformations.
J Tarpley,S Schnieder,R Money (1984). Effects of spectral response function on surface reflectance and NDVI measured with moderate resolution satellite sensors.
C Tucker (1979). Red and photographic infrared linear combinations for monitoring vegetation.
C Tucker,H Dregne,W Newcomb (1991). Expansion and contraction of the Sahara Desert from 1980 to 1990.
C Tucker,J Gatlin,S Schnieder,M Kuchinos (1982). Monitoring large scale vegetation dynamics in the Nile delta and river valley from NOAA AVHRR data.
C Tucker,D Slayback,J Pinzon,S Los,R Myneni,M Taylor,R Hyndman,A Zeileis,D Culvenor (2001). Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999.
Ricardo Villalba,Hector Grau,Jose Boninsegna,Gordon Jacoby,Alberto Ripalta (1998). Tree‐ring evidence for long‐term precipitation changes in subtropical South America.
R Villalba,A Lara,J Boninsegna,M Masiokas,S Delgado,J Aravena,F Roig,A Schmelter,A Wolodarsky,A Ripalta (2003). Large-scale temperature changes across the southern Andes: 20 th century variations in the context of the past 400 years.
Zhengming Wan (2003). Monitoring thermal status of ecosystems with MODIS land-surface temperature and vegetation index products.
J Wang,P Rich,K Price (2003). Assessment of status and trends of olive farming intensity in EU-Mediterranean countries using remote sensing time series and land cover data.
Konrad Wessels,Karen Steenkamp,Graham Von Maltitz,Sally Archibald (2011). Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa.
R Wolfe,J Storey,E Masuoka,A Fleig (1995). MODIS Level 1A Earth location algorithm theoretical basis document.
Robert Wolfe,Masahiro Nishihama,Albert Fleig,James Kuyper,David Roy,James Storey,Fred Patt (2002). Achieving sub-pixel geolocation accuracy in support of MODIS land science.
X Xiao,S Boles,S Frolking,W Salas,B Moore,C Li,L He,R Zhao (2002). Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data.
X Xiong,V Salomonson,J Kuyper,L Tan,K Chiang,J Sun,W Barnes (2005). Status of the MODIS level 1B algorithms and calibration tables.
Xiaoxiong Xiong,K Chiang,Bruce Guenther,William Barnes (2003). MODIS thermal emissive bands calibration algorithm and on-orbit performance.
Xiaoxiong Xiong,Jun-Qiang Sun,Joseph Esposito,Bruce Guenther,William Barnes (2003). MODIS reflective solar bands calibration algorithm and on-orbit performance.
L Yang,B Wylie,L Tieszen,B Reed (1998). An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the US northern and central Great Plains.
W Yang,L Yang,J Merchant (1997). An assessment of AVHRR/NDVI-ecoclimatological relations in Nebraska, U.S.A..
Z Yang,P Willis,R Mueller (2008). Impact of band-ratio enhanced AWIFS image to crop classification accuracy.
Bin Zhao,Yaner Yan,Haiqiang Guo,Meimei He,Yongjian Gu,Bo Li (2009). Monitoring rapid vegetation succession in estuarine wetland using time series MODIS-based indicators: An application in the Yangtze River Delta area.
Maosheng Zhao,Faith Heinsch,Ramakrishna Nemani,Steven Running (2003). Improvements of the MODIS terrestrial gross and net primary production global data set.
Liming Zhou,Compton Tucker,Robert Kaufmann,Daniel Slayback,Nikolay Shabanov,Ranga Myneni (2001). Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999.
M Zoran,S Stefan (2006). Analysis of climatic and anthropogenic changes effects on spectral vegetation indices in forest areas derived from satellite data.

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How to Cite This Article

Dr. Farooq Ahmad. 2013. \u201cPhenologically-Tuned MODIS NDVI-Based Time Series (2000-2012) For Monitoring Of Vegetation and Climate Change in North-Eastern Punjab, Pakistan\u201d. Global Journal of Human-Social Science - B: Geography, Environmental Science & Disaster Management GJHSS-B Volume 12 (GJHSS Volume 12 Issue B13): .

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GJHSS Volume 12 Issue B13
Pg. 37- 54

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Crossref Journal DOI 10.17406/GJHSS

Print ISSN 0975-587X

e-ISSN 2249-460X

Keywords

Climate MODIS NDVI Remote Sensing time series vegetation phenology

Submission ReceivedJune 9, 2012
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Accepted July 5, 2012
Published July 15, 2012

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Country: Pakistan

Subject: Global Journal of Human-Social Science - B: Geography, Environmental Science & Disaster Management

Authors: Dr. Farooq Ahmad (PhD/Dr. count: 1)

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