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Application of Landscape Metrics and Object-Oriented Remote Sensing to Detect the Spatial Arrangement of Agricultural Land

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Abraham K., 2015. Detecting shifts in agricultural landscape patterns of Hawassa, Ethiopia: An assessment of land cover change between 1984–2014 using object-based image analysis and landscape metrics. Centre for Geo-Information Thesis Report GIRS-2015-11, Wageningen University and Research Centre 115 p.AbrahamK.2015Detecting shifts in agricultural landscape patterns of Hawassa, Ethiopia: An assessment of land cover change between 1984–2014 using object-based image analysis and landscape metricsCentre for Geo-Information Thesis Report GIRS-2015-11,Wageningen University and Research Centre115 p.Search in Google Scholar

Aguilar M.A., Vallario A., Aguilar F.J., Lorca A.G., Parente C., 2015. Object-based greenhouse horticultural crop identification from multi-temporal satellite imagery: A case study in Almeria, Spain. Remote Sensing 7(6): 7378–7401. DOI 10.3390/rs70607378.AguilarM.A.VallarioA.AguilarF.J.LorcaA.G.ParenteC.2015Object-based greenhouse horticultural crop identification from multi-temporal satellite imagery: A case study in Almeria, SpainRemote Sensing767378740110.3390/rs70607378Open DOISearch in Google Scholar

Anders N., Seijmonsbergen A.C., Bouten W., 2013. Geomorphological change detection using object-based feature extraction from multi-temporal LiDAR data. IEEE Geoscience and Remote Sensing Letters 10(6): 1587–1591. DOI 10.1109/LGRS.2013.2262317.AndersN.SeijmonsbergenA.C.BoutenW.2013Geomorphological change detection using object-based feature extraction from multi-temporal LiDAR dataIEEE Geoscience and Remote Sensing Letters1061587159110.1109/LGRS.2013.2262317Open DOISearch in Google Scholar

Aronoff S., 2005. Remote sensing for GIS managers. Esri Press, Redlands CA: 487.AronoffS.2005Remote sensing for GIS managersEsri PressRedlands CA487Search in Google Scholar

Asgarian A., Soffianian A., Pourmanafi S., 2016. Crop type mapping in a highly fragmented and heterogeneous agricultural landscape: A case of central Iran using multi-temporal Landsat 8 imagery. Computers and Electronics in Agriculture 127: 531–540. DOI 10.1016/j.compag.2016.07.019.AsgarianA.SoffianianA.PourmanafiS.2016Crop type mapping in a highly fragmented and heterogeneous agricultural landscape: A case of central Iran using multi-temporal Landsat 8 imageryComputers and Electronics in Agriculture12753154010.1016/j.compag.2016.07.019Open DOISearch in Google Scholar

Baatz M., and Schäpe A., 2000. Multi resolution Segmentation: An optimum approach for high quality multi scale image segmentation. In: J.Strobl, T.Blaschke, G.Griesbner (Eds.), Angewandte Geographische Informations-Verarbeitung, XII, Wichmann Verlag, Karlsruhe, Germany, 12–23.BaatzM.SchäpeA.2000Multi resolution Segmentation: An optimum approach for high quality multi scale image segmentationIn:StroblJ.BlaschkeT.GriesbnerG.(Eds.),Angewandte Geographische Informations-Verarbeitung, XIIWichmann VerlagKarlsruhe, Germany1223Search in Google Scholar

Bandyopadhyay S., Jaiswal R., Hegde V., Jayaraman V., 2009. Assessment of land suitability potentials for agriculture using a remote sensing and GIS based approach. International Journal of Remote Sensing 30(4): 879–895. DOI 10.1080/01431160802395235.BandyopadhyayS.JaiswalR.HegdeV.JayaramanV.2009Assessment of land suitability potentials for agriculture using a remote sensing and GIS based approachInternational Journal of Remote Sensing30487989510.1080/01431160802395235Open DOISearch in Google Scholar

Bedada W., Lemenih M., Karltun E., 2016. Soil nutrient build-up, input interaction effects and plot level N and P balances under long-term addition of compost and NP fertilizer. Agriculture, Ecosystems & Environment 218: 220–231. DOI 10.1016/j.agee.2015.11.024.BedadaW.LemenihM.KarltunE.2016Soil nutrient build-up, input interaction effects and plot level N and P balances under long-term addition of compost and NP fertilizerAgriculture, Ecosystems & Environment21822023110.1016/j.agee.2015.11.024Open DOISearch in Google Scholar

Bihamta Toosi N., Soffianian A.R., Fakheran S., Pourmanafi S., Ginzler C., Waser L.T, 2020. Land cover classification in mangrove ecosystems based on VHR satellite data and machine learning – An upscaling approach. Remote Sensing 12(17): 2684. DOI 10.3390/rs12172684.Bihamta ToosiN.SoffianianA.R.FakheranS.PourmanafiS.GinzlerC.WaserL.T2020Land cover classification in mangrove ecosystems based on VHR satellite data and machine learning – An upscaling approachRemote Sensing1217268410.3390/rs12172684Open DOISearch in Google Scholar

Blaschke T., 2010. Object based image analysis for remote sensing. ISPRS journal of Photogrammetry and Remote Sensing 65(1): 2–16. DOI 10.1016/j.isprsjprs.2009.06.004.BlaschkeT.2010Object based image analysis for remote sensingISPRS journal of Photogrammetry and Remote Sensing65121610.1016/j.isprsjprs.2009.06.004Open DOISearch in Google Scholar

Bolton D.K., Friedl M.A., 2013. Forecasting crop yield using remotely sensed vegetation indices and crop phenology metrics. Agricultural and Forest Meteorology 173: 74–84. DOI 10.1016/j.agrformet.2013.01.007.BoltonD.K.FriedlM.A.2013Forecasting crop yield using remotely sensed vegetation indices and crop phenology metricsAgricultural and Forest Meteorology173748410.1016/j.agrformet.2013.01.007Open DOISearch in Google Scholar

Bozorgi M., Moein M., Nejadkoorki F., Toosi N.B. 2020. Assessing the effect of water scarcity on crop selection and spatial pattern of croplands in central Iran. Computers and Electronics in Agriculture 178: 1–10. DOI 10.1016/j.compag.2020.105743.BozorgiM.MoeinM.NejadkoorkiF.ToosiN.B.2020Assessing the effect of water scarcity on crop selection and spatial pattern of croplands in central IranComputers and Electronics in Agriculture17811010.1016/j.compag.2020.105743Open DOISearch in Google Scholar

Chavez P.S., 1996. Image-based atmospheric corrections-revisited and improved. Photogrammetric Engineering and Remote Sensing 62(9): 1025–1035.ChavezP.S.1996Image-based atmospheric corrections-revisited and improvedPhotogrammetric Engineering and Remote Sensing62910251035Search in Google Scholar

Chen H., Yi Z.F., Schmidt-Vogt D., Ahrends A., Beckschäfer P., Kleinn C., Ranjitkar S., Xu J., 2016. Pushing the limits: The pattern and dynamics of rubber monoculture expansion in Xishuangbanna, SW China. PLoS One 11(2): e0150062. DOI 10.1371/journal.pone.0150062.ChenH.YiZ.F.Schmidt-VogtD.AhrendsA.BeckschäferP.KleinnC.RanjitkarS.XuJ.2016Pushing the limits: The pattern and dynamics of rubber monoculture expansion in Xishuangbanna, SW ChinaPLoS One112e015006210.1371/journal.pone.0150062476433726907479Open DOISearch in Google Scholar

Collier P.M., 2015. Accounting for managers: Interpreting accounting information for decision making. John Wiley & Sons: 544 p.CollierP.M.2015Accounting for managers: Interpreting accounting information for decision makingJohn Wiley & Sons544 p.Search in Google Scholar

Ding L., Cheng Z., Guo S., Zhang R., Huang C., 2007. Effect of regulated deficit irrigation on water use efficiency and yield of broad bean. Journal of Gansu Agricultural University 42: 123–126.DingL.ChengZ.GuoS.ZhangR.HuangC.2007Effect of regulated deficit irrigation on water use efficiency and yield of broad beanJournal of Gansu Agricultural University42123126Search in Google Scholar

Dutrieux L.P., Jakovac C.C., Latifah S.H., Kooistra L., 2016. Reconstructing land use history from Landsat time-series: Case study of a swidden agriculture system in Brazil. International Journal of Applied Earth Observation and Geoinformation 47: 112–124. DOI 10.4236/ojmh.2013.34028.DutrieuxL.P.JakovacC.C.LatifahS.H.KooistraL.2016Reconstructing land use history from Landsat time-series: Case study of a swidden agriculture system in BrazilInternational Journal of Applied Earth Observation and Geoinformation4711212410.4236/ojmh.2013.34028Open DOISearch in Google Scholar

Farina A., 2008. Principles and methods in landscape ecology: Towards a science of the landscape. Springer Science & Business Media: 412 p.FarinaA.2008Principles and methods in landscape ecology: Towards a science of the landscapeSpringer Science & Business Media412 p.Search in Google Scholar

Farkhondeh M., 2013. Landscaping foundation. Institute of Printing and Publishing, University of Tehran. Tehran: 289. (In Persian).FarkhondehM.2013Landscaping foundationInstitute of Printing and Publishing, University of TehranTehran289. (In Persian).Search in Google Scholar

Foerster S., Kaden K., Foerster M., Itzerott S., 2012. Crop type mapping using spectral–temporal profiles and phenological information. Computers and Electronics in Agriculture 89: 30–40. DOI 10.1016/j.compag.2012.07.015.FoersterS.KadenK.FoersterM.ItzerottS.2012Crop type mapping using spectral–temporal profiles and phenological informationComputers and Electronics in Agriculture89304010.1016/j.compag.2012.07.015Open DOISearch in Google Scholar

Godschalk D.R., 2004. Land use planning challenges: Coping with conflicts in visions of sustainable development and livable communities. Journal of the American Planning Association 70(1): 5–13. DOI 10.1080/01944360408976334.GodschalkD.R.2004Land use planning challenges: Coping with conflicts in visions of sustainable development and livable communitiesJournal of the American Planning Association70151310.1080/01944360408976334Open DOISearch in Google Scholar

Hassan R., Rizwan A., Farhan S., Sabir B., 2017. Comparative study of conventional and satellite based agriculture information system. International Journal of Computer, and Information Engineering 11(3): 304–309. DOI 10.5281/zenodo.1129113.HassanR.RizwanA.FarhanS.SabirB.2017Comparative study of conventional and satellite based agriculture information systemInternational Journal of Computer, and Information Engineering11330430910.5281/zenodo.1129113Open DOISearch in Google Scholar

Hendrickx F., Maelfait J.P., Van Wingerden W., Schweiger O., Speelmans M., Aviron S., Augenstein I., Billeter R., Bailey D., Bukacek R., 2007. How landscape structure, land-use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapes. Journal of Applied Ecology 44(2): 340–351. DOI 10.1111/j.1365-2664.2006.01270.x.HendrickxF.MaelfaitJ.P.Van WingerdenW.SchweigerO.SpeelmansM.AvironS.AugensteinI.BilleterR.BaileyD.BukacekR.2007How landscape structure, land-use intensity and habitat diversity affect components of total arthropod diversity in agricultural landscapesJournal of Applied Ecology44234035110.1111/j.1365-2664.2006.01270.xOpen DOISearch in Google Scholar

Howitt R.E., Medellin-Azuara J., MacEwan D., Lund J.R., Sumner D.A., 2014. Economic analysis of the 2014 drought for California agriculture. Center for Watershed Sciences, University of California, Davis, California: 28.HowittR.E.Medellin-AzuaraJ.MacEwanD.LundJ.R.SumnerD.A.2014Economic analysis of the 2014 drought for California agricultureCenter for Watershed Sciences, University of CaliforniaDavis, California28Search in Google Scholar

Iranian Bureau of Statistics, 2011. Statistical yearbook of Isfahan Province in 2011. Deputy of Statistics and Information of Isfahan Management and Planning Organization. First Turn 876. (In Persian).Iranian Bureau of Statistics2011Statistical yearbook of Isfahan Province in 2011Deputy of Statistics and Information of Isfahan Management and Planning OrganizationFirst Turn 876. (In Persian).Search in Google Scholar

Khan M., De Bie C., Van Keulen H., Smaling E., Real R., 2010. Disaggregating and mapping crop statistics using hypertemporal remote sensing. International Journal of Applied Earth Observation and Geoinformation 12(1): 36–46. DOI 10.1016/j.jag.2009.09.010.KhanM.De BieC.Van KeulenH.SmalingE.RealR.2010Disaggregating and mapping crop statistics using hypertemporal remote sensingInternational Journal of Applied Earth Observation and Geoinformation121364610.1016/j.jag.2009.09.010Open DOISearch in Google Scholar

Leitão A.B., Miller J., Ahern J., McGarigal K., 2012. Measuring landscapes: A planner's handbook. Island Press: 272.LeitãoA.B.MillerJ.AhernJ.McGarigalK.2012Measuring landscapes: A planner's handbookIsland Press272Search in Google Scholar

Li Q., Wang C., Zhang B., Lu L., 2015. Object-based crop classification with Landsat-MODIS enhanced time-series data. Remote Sensing 7(12): 16091–16107. DOI 10.3390/rs71215820.LiQ.WangC.ZhangB.LuL.2015Object-based crop classification with Landsat-MODIS enhanced time-series dataRemote Sensing712160911610710.3390/rs71215820Open DOISearch in Google Scholar

Lillesand T., Kiefer R.W., Chipman J., 2015. Remote sensing and image interpretation. 7th Edition, John Wiley & Sons: 736 p.LillesandT.KieferR.W.ChipmanJ.2015Remote sensing and image interpretation7th EditionJohn Wiley & Sons736 p.Search in Google Scholar

Lunetta R.S., Lyon J.G., 2004. Remote sensing and GIS accuracy assessment. CRC Press: 138. DOI 10.1201/9780203497586.LunettaR.S.LyonJ.G.2004Remote sensing and GIS accuracy assessmentCRC Press13810.1201/9780203497586Open DOISearch in Google Scholar

Ma X., Ma Y., 2017. The spatiotemporal variation analysis of virtual water for agriculture and livestock husbandry: A study for Jilin Province in China. Science of the Total Environment 586: 1150–1161. DOI 10.1016/j.scitotenv.2017.02.106.MaX.MaY.2017The spatiotemporal variation analysis of virtual water for agriculture and livestock husbandry: A study for Jilin Province in ChinaScience of the Total Environment5861150116110.1016/j.scitotenv.2017.02.10628215794Open DOISearch in Google Scholar

Markham B., Barsi J., Kvaran G., Ong L., Kaita E., Biggar S., Czapla-Myers J., Mishra N., Helder D., 2014. Landsat-8 operational land imager radiometric calibration and stability. Remote Sensing 6(12): 12275–12308. DOI 10.3390/rs61212275.MarkhamB.BarsiJ.KvaranG.OngL.KaitaE.BiggarS.Czapla-MyersJ.MishraN.HelderD.2014Landsat-8 operational land imager radiometric calibration and stabilityRemote Sensing612122751230810.3390/rs61212275Open DOISearch in Google Scholar

McGarigal K., 1995. FRAGSTATS: Spatial pattern analysis program for quantifying landscape structure. US Department of Agriculture, Forest Service, Pacific Northwest Research Station: 351, 122. DOI 10.2737/PNW-GTR-351.McGarigalK.1995FRAGSTATS: Spatial pattern analysis program for quantifying landscape structureUS Department of Agriculture, Forest Service, Pacific Northwest Research Station351, 122.10.2737/PNW-GTR-351Open DOISearch in Google Scholar

McGarigal K., 2017. Landscape metrics for categorical map patterns. Lecture Notes.McGarigalK.2017Landscape metrics for categorical map patternsLecture NotesSearch in Google Scholar

Möller M., Lymburner L., Volk M., 2007. The comparison index: A tool for assessing the accuracy of image segmentation. International Journal of Applied Earth Observation and Geoinformation 9(3): 311–321. DOI 10.1016/j.jag.2006.10.002.MöllerM.LymburnerL.VolkM.2007The comparison index: A tool for assessing the accuracy of image segmentationInternational Journal of Applied Earth Observation and Geoinformation9331132110.1016/j.jag.2006.10.002Open DOISearch in Google Scholar

Mulla D.J., 2013. Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps. Biosystems Engineering 114(4): 358–371. DOI 10.1016/j.biosystemseng.2012.08.009.MullaD.J.2013Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gapsBiosystems Engineering114435837110.1016/j.biosystemseng.2012.08.009Open DOISearch in Google Scholar

Nikolaos T., 2015. Forecasting and classifying potato yields for precision agriculture based on time series analysis of multispectral satellite imagery. 66.NikolaosT.2015Forecasting and classifying potato yields for precision agriculture based on time series analysis of multispectral satellite imagery66Search in Google Scholar

Peña J.M., Gutiérrez P.A., Hervás-Martínez C., Six J., Plant R.E., López-Granados F., 2014. Object-based image classification of summer crops with machine learning methods. Remote Sensing 6(6): 5019–5041. DOI 10.3390/rs6065019.PeñaJ.M.GutiérrezP.A.Hervás-MartínezC.SixJ.PlantR.E.López-GranadosF.2014Object-based image classification of summer crops with machine learning methodsRemote Sensing665019504110.3390/rs6065019Open DOISearch in Google Scholar

Pishgar-Komleh S.H., Ghahderijani M., Sefeedpari P., 2012. Energy consumption and CO2 emissions analysis of potato production based on different farm size levels in Iran. Journal of Cleaner Production 33: 183–191. DOI 10.1016/j.jclepro.2012.04.008.Pishgar-KomlehS.H.GhahderijaniM.SefeedpariP.2012Energy consumption and CO2 emissions analysis of potato production based on different farm size levels in IranJournal of Cleaner Production3318319110.1016/j.jclepro.2012.04.008Open DOISearch in Google Scholar

Rahman R., Saha S.K., 2008. Remote sensing, spatial multi criteria evaluation (SMCE) and analytical hierarchy process (AHP) in optimal cropping pattern planning for a flood prone area. Journal of Spatial Science 53(2): 161–177. DOI 10.1080/14498596.2008.9635156.RahmanR.SahaS.K.2008Remote sensing, spatial multi criteria evaluation (SMCE) and analytical hierarchy process (AHP) in optimal cropping pattern planning for a flood prone areaJournal of Spatial Science53216117710.1080/14498596.2008.9635156Open DOISearch in Google Scholar

Rhee J., Im J., Carbone G.J., 2010. Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing data. Remote Sensing of Environment 114(12): 2875–2887. DOI 10.1016/j.rse.2010.07.005.RheeJ.ImJ.CarboneG.J.2010Monitoring agricultural drought for arid and humid regions using multi-sensor remote sensing dataRemote Sensing of Environment114122875288710.1016/j.rse.2010.07.005Open DOISearch in Google Scholar

Roy D.P., Ju J., Kline K., Scaramuzza P.L., Kovalskyy V., Hansen M., Loveland T.R., Vermote E., Zhang C., 2010. Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States. Remote Sensing of Environment 114(1): 35–49. DOI 10.1016/j.rse.2009.08.011.RoyD.P.JuJ.KlineK.ScaramuzzaP.L.KovalskyyV.HansenM.LovelandT.R.VermoteE.ZhangC.2010Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United StatesRemote Sensing of Environment1141354910.1016/j.rse.2009.08.011Open DOISearch in Google Scholar

Roy D.P., Wulder M., Loveland T.R., Woodcock C., Allen R., Anderson M., Helder D., Irons J., Johnson D., Kennedy R., 2014. Landsat-8: Science and product vision for terrestrial global change research. Remote Sensing of Environment 145: 154–172. DOI 10.1016/j.rse.2014.02.001.RoyD.P.WulderM.LovelandT.R.WoodcockC.AllenR.AndersonM.HelderD.IronsJ.JohnsonD.KennedyR.2014Landsat-8: Science and product vision for terrestrial global change researchRemote Sensing of Environment14515417210.1016/j.rse.2014.02.001Open DOISearch in Google Scholar

Saroinsong F., Harashina K., Arifin H., Gandasasmita K., Sakamoto K., 2007. Practical application of a land resources information system for agricultural landscape planning. Landscape and Urban Planning 79(1): 38–52. DOI 10.1016/j.landurbplan.2006.03.002.SaroinsongF.HarashinaK.ArifinH.GandasasmitaK.SakamotoK.2007Practical application of a land resources information system for agricultural landscape planningLandscape and Urban Planning791385210.1016/j.landurbplan.2006.03.002Open DOISearch in Google Scholar

Soffianian A., Pourmanafi S., Soltani S., Homami M., Bashari H., Bagheri M., 2013. Isfahan land-use planning project, land use evaluation. In: Province G.G.o.I. (Ed).SoffianianA.PourmanafiS.SoltaniS.HomamiM.BashariH.BagheriM.2013Isfahan land-use planning project, land use evaluationIn: Province G.G.o.I. (Ed).Search in Google Scholar

Southworth J., Nagendra H., Tucker C., 2002. Fragmentation of a landscape: Incorporating landscape metrics into satellite analyses of land-cover change. Landscape Research 27(3): 253–269. DOI 10.1080/01426390220149511.SouthworthJ.NagendraH.TuckerC.2002Fragmentation of a landscape: Incorporating landscape metrics into satellite analyses of land-cover changeLandscape Research27325326910.1080/01426390220149511Open DOISearch in Google Scholar

Tong Yang X., Liu H., Gao X., 2015. Land cover changed object detection in remote sensing data with medium spatial resolution. International Journal of Applied Earth Observation and Geoinformation 38: 129–137. DOI 10.1016/j.jag.2014.12.015.Tong YangX.LiuH.GaoX.2015Land cover changed object detection in remote sensing data with medium spatial resolutionInternational Journal of Applied Earth Observation and Geoinformation3812913710.1016/j.jag.2014.12.015Open DOISearch in Google Scholar

Turner M., Gardner R., O’Neill R., 2015. Landscape ecology in theory and practice: Pattern and process. Springer, New York. DOI 10.1007/978-1-4939-2794-4.TurnerM.GardnerR.O’NeillR.2015Landscape ecology in theory and practice: Pattern and processSpringerNew York10.1007/978-1-4939-2794-4Open DOISearch in Google Scholar

Van Knippenberg D., Dahlander L., Haas M.R., George G., 2015. Information, attention, and decision making. Academy of Management Journal 58(3): 649–657. DOI 10.5465/amj.2015.4003.Van KnippenbergD.DahlanderL.HaasM.R.GeorgeG.2015Information, attention, and decision makingAcademy of Management Journal58364965710.5465/amj.2015.4003Open DOISearch in Google Scholar

Weidner U., 2008. Contribution to the assessment of segmentation quality for remote sensing applications. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 37(B7): 479–484.WeidnerU.2008Contribution to the assessment of segmentation quality for remote sensing applicationsInternational Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences37B7479484Search in Google Scholar

White E.V., Roy D.P., 2015. A contemporary decennial examination of changing agricultural field sizes using Landsat time series data. Geo: Geography and Environment 2(1): 33–54. DOI 10.1002/geo2.4.WhiteE.V.RoyD.P.2015A contemporary decennial examination of changing agricultural field sizes using Landsat time series dataGeo: Geography and Environment21335410.1002/geo2.4502058127669424Open DOISearch in Google Scholar

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