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Exploration of the Relationship Between Landscape Diversity and Carbon Storage Potential Using Remote Sensing and GIS

Yıl 2021, , 89 - 96, 30.06.2021
https://doi.org/10.25308/aduziraat.822263

Öz

Human-induced Land Cover / Land Use (LCLU) changes have caused land degradation in the last decade and have led to an intense reduction of carbon especially in the Mediterranean basin. Remote sensing based metrics based on experimental assumptions to predict carbon storage can be used in simplified estimates of local carbon stocks where field data is missing. The aim of this study is to examine the relationship between landscape diversity and carbon storage through remote sensing and GIS. Conducted in Manisa, this study used LCLU data dated 2018, three landscape diversity metrics –Shannon’s diversity index (SHDI), patch richness density (PRD), and Simpson’s evenness index (SIEI) were calculated for sample areas at different distances. Diversity values and aboveground carbon storage values were evaluated by correlation analysis. As a result, all landscape diversity metrics explained the relationship between landscape diversity and carbon storage at medium level for 3000 m. This study suggests that SHDI explains this relationship better than other metrics (p <0.05). Future studies can generate new metrics that will allow cost effective and practical measurement of potential carbon storage using LCLU data. Thus, changes in carbon storage can also be practically monitored.

Kaynakça

  • Botequilha Leitão A, Ahern J (2002) Applying landscape ecological concepts and metrics in sustainable landscape planning. Landscape and Urban Planning59(2): 65-93.
  • Brunori E, Salvati L, Mancinelli R, Smiraglia D, Biasi R (2017) Multi-temporal land use and cover changing analysis: The environmental impact in Mediterranean area. International Journal of Sustainable Development ve World Ecology24(3) 276-288.
  • Cardinale BJ, Gross K, Fritschie K, Flombaum P, Fox JW, Rixen C, Ruijven J, van Reich PB, Scherer-Lorenzen M, Wilsey BJ (2013) Biodiversity simultaneously enhances the production and stability of community biomass, but the effects are independent. Ecology94(8): 1697-1707.
  • Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Fölster H, Fromard F, Higuchi N, Kira T, Lescure JP, Nelson BW, Ogawa H, Puig H, Riéra B, Yamakura, T (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia145(1): 87-99.
  • Chen Y, Lu H, Li J, Xia J (2020) Effects of land use cover change on carbon emissions and ecosystem services in Chengyu urban agglomeration, China. Stochastic Environmental Research and Risk Assessment34(8): 1197-1215.
  • Chowdhury M, Hasan ME, Abdullah-Al-Mamun MM (2020) Land use/land cover change assessment of Halda watershed using remote sensing and GIS. The Egyptian Journal of Remote Sensing and Space Science23(1): 63-75.
  • Cushman SA, McGarigal K, Neel MC (2008) Parsimony in landscape metrics: Strength, universality, and consistency. Ecological Indicators8(5): 691-703.
  • Davies ZG, Edmondson JL, Heinemeyer A, Leake JR, Gaston KJ (2011) Mapping an urban ecosystem service: Quantifying above-ground carbon storage at a citywide scale. Journal of Applied Ecology48(5): 1125-1134.
  • Dewan AM, Yamaguchi Y (2009) Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography29(3): 390-401.
  • Frank S, Fürst C, Koschke L, Makeschin F (2012) A contribution towards a transfer of the ecosystem service concept to landscape planning using landscape metrics. Ecological Indicators21:30-38.
  • Golkar F, Shirvani A (2020) Spatial and temporal distribution and seasonal prediction of satellite measurement of CO2 concentration over Iran. International Journal of Remote Sensing41(23): 8891-8909.
  • Harpole WS, Sullivan LL, Lind EM, Firn J, Adler PB, Borer ET, Chase J, Fay PA, Hautier Y, Hillebrand H, MacDougall AS, Seabloom EW, Williams R, Bakker JD, Cadotte MW, Chaneton EJ, Chu C, Cleland EE, D’Antonio C, Wragg PD (2016) Addition of multiple limiting resources reduces grassland diversity. Nature:537(7618): 93-96.
  • Hesselbarth MH, Sciaini M, With KA, Wiegand K, Nowosad J (2019) landscapemetrics: an open‐source R tool to calculate landscape metrics. Ecography 42(10): 1648- 1657.
  • Hooper DU, Adair EC, Cardinale BJ, Byrnes JEK, Hungate BA, Matulich KL, Gonzalez A, Duffy JE, Gamfeldt L, O’Connor MI (2012) A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature486(7401): 105-108.
  • Houghton RA, Nassikas AA (2017) Global and regional fluxes of carbon from land use and land cover change 1850–2015. Global Biogeochemical Cycles31(3): 456-472.
  • Hu Y, BatunacunZhen L, Zhuang D (2019) Assessment of Land-Use and Land-Cover Change in Guangxi, China. Scientific Reports9(1):2189.
  • Jantz P, Goetz S, Laporte N (2014) Carbon stock corridors to mitigate climate change and promote biodiversity in the tropics. Nature Climate Change4(2): 138–142.
  • Lausch A, Herzog F (2002) Applicability of landscape metrics for the monitoring of landscape change: Issues of scale, resolution and interpretability. Ecological Indicators2(1): 3-15.
  • Lausch Angela, Blaschke T, Haase D, Herzog F, Syrbe RU, Tischendorf L, Walz U (2015) Understanding and quantifying landscape structure – A review on relevant process characteristics, data models and landscape metrics. Ecological Modelling295: 31-41.
  • Li H, Wu J (2004) Use and misuse of landscape indices. Landscape Ecology19(4): 389-399.
  • Li W, Niu Z, Liang X, Li Z, Huang N, Gao S, Wang C, Muhammad S (2015) Geostatistical modeling using LiDAR-derived prior knowledge with SPOT-6 data to estimate temperate forest canopy cover and above ground biomass via stratified random sampling. International Journal of Applied Earth Observation and Geoinformation41: 88-98.
  • Liu S, Li X, Chen D, Duan Y, Ji H, Zhang L, Chai Q, Hu X (2020) Understanding Land use/Land cover dynamics and impacts of human activities in the Mekong Delta over the last 40 years. Global Ecology and Conservation22: e00991.
  • McGarigal K (2014) Landscape Pattern Metrics. In Wiley StatsRef: Statistics Reference Online. American Cancer Society.
  • Muñoz‐Rojas M, Jordán A, Zavala LM, Rosa DD, Abd‐ Elmabod SK, Anaya‐Romero, M (2015) Impact of Land Use and Land Cover Changes on Organic Carbon Stocks in Mediterranean Soils (1956–2007). Land Degradation ve Development26(2): 168-179.
  • Myeong S, Nowak DJ, Duggin MJ (2006) A temporal analysis of urban forest carbon storage using remote sensing. Remote Sensing of Environment101(2): 277-282.
  • Ni‐Meister W, Lee S, Strahler AH, Woodcock CE, Schaaf C, Yao T, Ranson KJ, Sun G, Blair JB (2010) Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing. Journal of Geophysical Research: Biogeosciences115(G2).
  • Öztürk MZ, Çetin kaya G, Aydin S (2017) Köppen-Geiger İklim Sınıflandırmasına Göre Türkiye’nin İklim Tipleri. Coğrafya Dergisi35: 17-27.
  • Patenaude G, Hill RA, Milne R, Gaveau DLA, Briggs BBJ, Dawson TP (2004) Quantifying forest above ground carbon content using LiDAR remote sensing. Remote Sensing of Environment93(3): 368-380.
  • Perre FV, Willig MR, Presley SJ, Andemwana FB, Beeckman H, Boeckx P, Cooleman S, Haan M, Kesel AD, Dessein S, Grootaert P, Huygens D, Janssens SB, Kearsley E, Kabeya PM, Leponce M, Broeck DV, Verbeeck H, Würsten B, Verheyen E (2018) Reconciling biodiversity and carbon stock conservation in an Afrotropical forest landscape. Science Advances4(3): eaar6603.
  • Poulter B, Frank D, Ciais P, Myneni RB, Andela N, Bi J, Broquet G, Canadell JG, Chevallier F, Liu YY, Running SW, Sitch S, van der Werf GR (2014) Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature509(7502): 600-603.
  • Sabatini FM, Andrade RB, Paillet Y, Ódor P, Bouget C, Campagnaro T, Gosselin F, Janssen P, Mattioli W, Nascimbene J, Sitzia T, Kuemmerle T, Burrascano S (2019) Trade-offs between carbon stocks and biodiversity in European temperate forests. Global Change Biology25(2): 536-548.
  • Sande MT, Poorter L, Kooistra L, Balvanera P, Thonicke K, Thompson J, Arets EJM M, Alaniz NG, Jones L, Mora F, Mwampamba TH, Parr T, Peña‐Claros M (2017) Biodiversity in species, traits, and structure determines carbon stocks and uptake in tropical forests. Biotropica49(5): 593-603.
  • Singh H, Garg RD, Karnatak HC, Roy A (2018) Spatial landscape model to characterize biological diversity using R statistical computing environment. Journal of Environmental Management206: 1211-1223.
  • Sütünç HS, Çorbacı, ÖL (2020) Building Urban Green Infrastructure Systems Using Ecological Planning Principles: Siirt Sample. Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi16(2): 70-88.
  • Şık L, Gemic i Y (2009)Yunt Dağı (Manisa) Orman Vejetasyonunun Bitki Sosyolojisi Yönünden Araştırılması.Celal Bayar Üniversitesi Fen Bilimleri Dergisi5(1): 75-86.
  • Sintayehu DW, Belayneh A, Dechassa N (2020) Aboveground carbon stock is related to land cover and woody species diversity in tropical ecosystems of Eastern Ethiopia. Ecological Processes9(1): 37.
  • Strassburg BBN, Kelly A, Balmford A, Davies RG, Gibbs HK, Lovett A, Miles L, Orme CDL, Price J, Turner RK, Rodrigues ASL (2010) Global congruence of carbon storage and biodiversity in terrestrial ecosystems. Conservation Letters3(2): 98-105.
  • Sumarga E, Nurudin N, Suwandhi I (2020) Land-Cover and Elevation-Based Mapping of Aboveground Carbon in a Tropical Mixed-Shrub Forest Area in West Java, Indonesia. Forests11(6): 636.
  • Uuemaa E, Antrop M, Roosaare J, Marja R, Mander Ü (2009) Landscape metrics and indices: An overview of their use in landscape research. Living reviews in landscape research3(1): 1-28.
  • Verburg PH, Alexander P, Evans T, Magliocca NR, Malek Z, Rounsevell MD, van Vliet J (2019) Beyond land cover change: Towards a new generation of land use models. Current Opinion in Environmental Sustainability38: 77-85.
  • Wu X, Wang S, Fu B, Liu Y, Zhu Y (2018) Land use optimization based on ecosystem service assessment: A case study in the Yanhe watershed. Land Use Policy72: 303-312.
  • Yu Z, Lu C, Tian H, Canadell JG (2019) Largely underestimated carbon emission from land use and land cover change in the conterminous United States. Global Change Biology25(11): 3741-3752.
  • Yuan Z, Wang S, Ali A, Gazol A, Ruiz-Benito P, Wang X, Lin F, Ye J, Hao Z, Loreau M (2018) Aboveground carbon storage is driven by functional trait composition and stand structural attributes rather than biodiversity in temperate mixed forests recovering from disturbances. Annals of Forest Science 75(3): 67.

Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi

Yıl 2021, , 89 - 96, 30.06.2021
https://doi.org/10.25308/aduziraat.822263

Öz

Antropojenik faaliyetler kaynaklı Arazi Kullanımı/Arazi Örtüsü (AK/AO) değişimi, önemli miktarda toprak tahribatı ve arazi kaybına neden olmuştur. Bu nedenle, özellikle son on yılda Akdeniz’de karbon tutulumu azalmıştır. Arazi verisinin eksik olduğu alanlarda karbon depolanmasını tahmin etmek için deneysel varsayımlara dayanan küresel değerler, uzaktan algılama teknikleri ile yerel karbon stoklarının basitleştirilmiş tahminlerinde kullanılabilir. Bu çalışmanın amacı, peyzaj çeşitliliği ve karbon depolama potansiyeli arasındaki ilişkinin uzaktan algılama ve CBS aracılığıyla incelenmesidir. Manisa il sınırı bütününden oluşan peyzajda yürütülen bu çalışmada, güncel arazi kullanımı/arazi örtüsü verisi kullanılarak, farklı mesafelerdeki örneklik alanlar için peyzaj çeşitliliği metriklerinden Shannon çeşitlilik indeksi (SHDI), yama yoğunluğu (PRD) ve Simpson eşitlik indeksi (SIEI) hesaplanmıştır. Çeşitlilik değerleri ile yer üstü karbon tutumu değerleri korelasyon analizi ile değerlendirilmiştir. Sonuç olarak, kullanılan tüm peyzaj çeşitlilik metrikleri peyzaj çeşitliliği ve karbon depolama potansiyeli arasındaki ilişkiyi 3000 m’de en iyi düzeyde açıklamıştır. SHDI’nın bu ilişkiyi diğer metriklere göre daha iyi açıkladığı görülmüştür (p < 0,05). Ancak ilişkinin düzeyi ortadır ve yönü pozitiftir. Bundan sonraki çalışmalarda, AK/AO verisini kullanılarak karbon depolama potansiyelinin hızlı, pratik ve daha yüksek güvenilirlik seviyesinde ölçülmesini sağlayacak yeni metrikler üretilebilir. Böylece, AK/AO değişimlerine bağlı olarak arazideki karbon depolama potansiyeli değişimi de pratik olarak izlenebilir.

Kaynakça

  • Botequilha Leitão A, Ahern J (2002) Applying landscape ecological concepts and metrics in sustainable landscape planning. Landscape and Urban Planning59(2): 65-93.
  • Brunori E, Salvati L, Mancinelli R, Smiraglia D, Biasi R (2017) Multi-temporal land use and cover changing analysis: The environmental impact in Mediterranean area. International Journal of Sustainable Development ve World Ecology24(3) 276-288.
  • Cardinale BJ, Gross K, Fritschie K, Flombaum P, Fox JW, Rixen C, Ruijven J, van Reich PB, Scherer-Lorenzen M, Wilsey BJ (2013) Biodiversity simultaneously enhances the production and stability of community biomass, but the effects are independent. Ecology94(8): 1697-1707.
  • Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Fölster H, Fromard F, Higuchi N, Kira T, Lescure JP, Nelson BW, Ogawa H, Puig H, Riéra B, Yamakura, T (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia145(1): 87-99.
  • Chen Y, Lu H, Li J, Xia J (2020) Effects of land use cover change on carbon emissions and ecosystem services in Chengyu urban agglomeration, China. Stochastic Environmental Research and Risk Assessment34(8): 1197-1215.
  • Chowdhury M, Hasan ME, Abdullah-Al-Mamun MM (2020) Land use/land cover change assessment of Halda watershed using remote sensing and GIS. The Egyptian Journal of Remote Sensing and Space Science23(1): 63-75.
  • Cushman SA, McGarigal K, Neel MC (2008) Parsimony in landscape metrics: Strength, universality, and consistency. Ecological Indicators8(5): 691-703.
  • Davies ZG, Edmondson JL, Heinemeyer A, Leake JR, Gaston KJ (2011) Mapping an urban ecosystem service: Quantifying above-ground carbon storage at a citywide scale. Journal of Applied Ecology48(5): 1125-1134.
  • Dewan AM, Yamaguchi Y (2009) Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization. Applied Geography29(3): 390-401.
  • Frank S, Fürst C, Koschke L, Makeschin F (2012) A contribution towards a transfer of the ecosystem service concept to landscape planning using landscape metrics. Ecological Indicators21:30-38.
  • Golkar F, Shirvani A (2020) Spatial and temporal distribution and seasonal prediction of satellite measurement of CO2 concentration over Iran. International Journal of Remote Sensing41(23): 8891-8909.
  • Harpole WS, Sullivan LL, Lind EM, Firn J, Adler PB, Borer ET, Chase J, Fay PA, Hautier Y, Hillebrand H, MacDougall AS, Seabloom EW, Williams R, Bakker JD, Cadotte MW, Chaneton EJ, Chu C, Cleland EE, D’Antonio C, Wragg PD (2016) Addition of multiple limiting resources reduces grassland diversity. Nature:537(7618): 93-96.
  • Hesselbarth MH, Sciaini M, With KA, Wiegand K, Nowosad J (2019) landscapemetrics: an open‐source R tool to calculate landscape metrics. Ecography 42(10): 1648- 1657.
  • Hooper DU, Adair EC, Cardinale BJ, Byrnes JEK, Hungate BA, Matulich KL, Gonzalez A, Duffy JE, Gamfeldt L, O’Connor MI (2012) A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature486(7401): 105-108.
  • Houghton RA, Nassikas AA (2017) Global and regional fluxes of carbon from land use and land cover change 1850–2015. Global Biogeochemical Cycles31(3): 456-472.
  • Hu Y, BatunacunZhen L, Zhuang D (2019) Assessment of Land-Use and Land-Cover Change in Guangxi, China. Scientific Reports9(1):2189.
  • Jantz P, Goetz S, Laporte N (2014) Carbon stock corridors to mitigate climate change and promote biodiversity in the tropics. Nature Climate Change4(2): 138–142.
  • Lausch A, Herzog F (2002) Applicability of landscape metrics for the monitoring of landscape change: Issues of scale, resolution and interpretability. Ecological Indicators2(1): 3-15.
  • Lausch Angela, Blaschke T, Haase D, Herzog F, Syrbe RU, Tischendorf L, Walz U (2015) Understanding and quantifying landscape structure – A review on relevant process characteristics, data models and landscape metrics. Ecological Modelling295: 31-41.
  • Li H, Wu J (2004) Use and misuse of landscape indices. Landscape Ecology19(4): 389-399.
  • Li W, Niu Z, Liang X, Li Z, Huang N, Gao S, Wang C, Muhammad S (2015) Geostatistical modeling using LiDAR-derived prior knowledge with SPOT-6 data to estimate temperate forest canopy cover and above ground biomass via stratified random sampling. International Journal of Applied Earth Observation and Geoinformation41: 88-98.
  • Liu S, Li X, Chen D, Duan Y, Ji H, Zhang L, Chai Q, Hu X (2020) Understanding Land use/Land cover dynamics and impacts of human activities in the Mekong Delta over the last 40 years. Global Ecology and Conservation22: e00991.
  • McGarigal K (2014) Landscape Pattern Metrics. In Wiley StatsRef: Statistics Reference Online. American Cancer Society.
  • Muñoz‐Rojas M, Jordán A, Zavala LM, Rosa DD, Abd‐ Elmabod SK, Anaya‐Romero, M (2015) Impact of Land Use and Land Cover Changes on Organic Carbon Stocks in Mediterranean Soils (1956–2007). Land Degradation ve Development26(2): 168-179.
  • Myeong S, Nowak DJ, Duggin MJ (2006) A temporal analysis of urban forest carbon storage using remote sensing. Remote Sensing of Environment101(2): 277-282.
  • Ni‐Meister W, Lee S, Strahler AH, Woodcock CE, Schaaf C, Yao T, Ranson KJ, Sun G, Blair JB (2010) Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing. Journal of Geophysical Research: Biogeosciences115(G2).
  • Öztürk MZ, Çetin kaya G, Aydin S (2017) Köppen-Geiger İklim Sınıflandırmasına Göre Türkiye’nin İklim Tipleri. Coğrafya Dergisi35: 17-27.
  • Patenaude G, Hill RA, Milne R, Gaveau DLA, Briggs BBJ, Dawson TP (2004) Quantifying forest above ground carbon content using LiDAR remote sensing. Remote Sensing of Environment93(3): 368-380.
  • Perre FV, Willig MR, Presley SJ, Andemwana FB, Beeckman H, Boeckx P, Cooleman S, Haan M, Kesel AD, Dessein S, Grootaert P, Huygens D, Janssens SB, Kearsley E, Kabeya PM, Leponce M, Broeck DV, Verbeeck H, Würsten B, Verheyen E (2018) Reconciling biodiversity and carbon stock conservation in an Afrotropical forest landscape. Science Advances4(3): eaar6603.
  • Poulter B, Frank D, Ciais P, Myneni RB, Andela N, Bi J, Broquet G, Canadell JG, Chevallier F, Liu YY, Running SW, Sitch S, van der Werf GR (2014) Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature509(7502): 600-603.
  • Sabatini FM, Andrade RB, Paillet Y, Ódor P, Bouget C, Campagnaro T, Gosselin F, Janssen P, Mattioli W, Nascimbene J, Sitzia T, Kuemmerle T, Burrascano S (2019) Trade-offs between carbon stocks and biodiversity in European temperate forests. Global Change Biology25(2): 536-548.
  • Sande MT, Poorter L, Kooistra L, Balvanera P, Thonicke K, Thompson J, Arets EJM M, Alaniz NG, Jones L, Mora F, Mwampamba TH, Parr T, Peña‐Claros M (2017) Biodiversity in species, traits, and structure determines carbon stocks and uptake in tropical forests. Biotropica49(5): 593-603.
  • Singh H, Garg RD, Karnatak HC, Roy A (2018) Spatial landscape model to characterize biological diversity using R statistical computing environment. Journal of Environmental Management206: 1211-1223.
  • Sütünç HS, Çorbacı, ÖL (2020) Building Urban Green Infrastructure Systems Using Ecological Planning Principles: Siirt Sample. Düzce Üniversitesi Orman Fakültesi Ormancılık Dergisi16(2): 70-88.
  • Şık L, Gemic i Y (2009)Yunt Dağı (Manisa) Orman Vejetasyonunun Bitki Sosyolojisi Yönünden Araştırılması.Celal Bayar Üniversitesi Fen Bilimleri Dergisi5(1): 75-86.
  • Sintayehu DW, Belayneh A, Dechassa N (2020) Aboveground carbon stock is related to land cover and woody species diversity in tropical ecosystems of Eastern Ethiopia. Ecological Processes9(1): 37.
  • Strassburg BBN, Kelly A, Balmford A, Davies RG, Gibbs HK, Lovett A, Miles L, Orme CDL, Price J, Turner RK, Rodrigues ASL (2010) Global congruence of carbon storage and biodiversity in terrestrial ecosystems. Conservation Letters3(2): 98-105.
  • Sumarga E, Nurudin N, Suwandhi I (2020) Land-Cover and Elevation-Based Mapping of Aboveground Carbon in a Tropical Mixed-Shrub Forest Area in West Java, Indonesia. Forests11(6): 636.
  • Uuemaa E, Antrop M, Roosaare J, Marja R, Mander Ü (2009) Landscape metrics and indices: An overview of their use in landscape research. Living reviews in landscape research3(1): 1-28.
  • Verburg PH, Alexander P, Evans T, Magliocca NR, Malek Z, Rounsevell MD, van Vliet J (2019) Beyond land cover change: Towards a new generation of land use models. Current Opinion in Environmental Sustainability38: 77-85.
  • Wu X, Wang S, Fu B, Liu Y, Zhu Y (2018) Land use optimization based on ecosystem service assessment: A case study in the Yanhe watershed. Land Use Policy72: 303-312.
  • Yu Z, Lu C, Tian H, Canadell JG (2019) Largely underestimated carbon emission from land use and land cover change in the conterminous United States. Global Change Biology25(11): 3741-3752.
  • Yuan Z, Wang S, Ali A, Gazol A, Ruiz-Benito P, Wang X, Lin F, Ye J, Hao Z, Loreau M (2018) Aboveground carbon storage is driven by functional trait composition and stand structural attributes rather than biodiversity in temperate mixed forests recovering from disturbances. Annals of Forest Science 75(3): 67.
Toplam 43 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ziraat Mühendisliği
Bölüm Araştırma
Yazarlar

Derya Gülçin 0000-0001-7118-0174

Yayımlanma Tarihi 30 Haziran 2021
Yayımlandığı Sayı Yıl 2021

Kaynak Göster

APA Gülçin, D. (2021). Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi, 18(1), 89-96. https://doi.org/10.25308/aduziraat.822263
AMA Gülçin D. Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi. ADÜ ZİRAAT DERG. Haziran 2021;18(1):89-96. doi:10.25308/aduziraat.822263
Chicago Gülçin, Derya. “Uzaktan Algılama Ve CBS Teknikleri Ile Peyzaj Çeşitliliği Ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi”. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi 18, sy. 1 (Haziran 2021): 89-96. https://doi.org/10.25308/aduziraat.822263.
EndNote Gülçin D (01 Haziran 2021) Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi 18 1 89–96.
IEEE D. Gülçin, “Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi”, ADÜ ZİRAAT DERG, c. 18, sy. 1, ss. 89–96, 2021, doi: 10.25308/aduziraat.822263.
ISNAD Gülçin, Derya. “Uzaktan Algılama Ve CBS Teknikleri Ile Peyzaj Çeşitliliği Ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi”. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi 18/1 (Haziran 2021), 89-96. https://doi.org/10.25308/aduziraat.822263.
JAMA Gülçin D. Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi. ADÜ ZİRAAT DERG. 2021;18:89–96.
MLA Gülçin, Derya. “Uzaktan Algılama Ve CBS Teknikleri Ile Peyzaj Çeşitliliği Ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi”. Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi, c. 18, sy. 1, 2021, ss. 89-96, doi:10.25308/aduziraat.822263.
Vancouver Gülçin D. Uzaktan Algılama ve CBS Teknikleri ile Peyzaj Çeşitliliği ve Karbon Depolama Potansiyeli Arasındaki İlişkinin İncelenmesi. ADÜ ZİRAAT DERG. 2021;18(1):89-96.