Mera Vejetasyon Ölçüm Yöntemleri
Özet
Bu bölüm, mera ekosistemlerinde bitki örtüsünün niceliksel ve niteliksel analizleri için kullanılan yöntemleri detaylı bir şekilde incelemektedir. Transekt (hat), lup (halka), nokta çerçeve, tekerlekli nokta, kuadrat (çerçeve), pantograf, gözle tahmin ve hava fotoğraflama gibi geleneksel ve modern tekniklerin uygulama esasları, avantajları ve sınırlılıkları karşılaştırmalı olarak sunulmaktadır. Yöntemlerin seçimi, bitki örtüsünün yoğunluğu, arazi yapısı ve çalışmanın amacına göre değişkenlik göstermektedir. Özellikle uzaktan algılama teknolojileri (NDVI, drone görüntüleri) gibi güncel yaklaşımların mera yönetimindeki rolü vurgulanmaktadır. Bölüm, sürdürülebilir mera yönetimi için doğru ölçüm tekniklerinin önemini ortaya koyarak, ilgili alanda çalışmalar yürüten akademisyenler, öğrenciler, özel sektörde veya kamuda çalışan ziraat mühendisleri ve araştırmacılar için kapsamlı bir rehber niteliği taşımaktadır.
This chapter provides a comprehensive examination of quantitative and qualitative analysis methods used for vegetation assessment in pasture ecosystems. It presents a comparative analysis of both traditional and modern techniques, including transect (line), loop (ring), point frame, wheel point, quadrat (frame), pantograph, visual estimation, and aerial photography methods, detailing their implementation principles, advantages, and limitations. The selection of appropriate methods varies depending on vegetation density, terrain characteristics, and research objectives. Particular emphasis is placed on the role of contemporary approaches such as remote sensing technologies (NDVI, drone imagery) in pasture management. By highlighting the importance of accurate measurement techniques for sustainable pasture management, this chapter serves as an essential reference for academics, students, agricultural engineers working in both private and public sectors, and researchers active in this field.
Referanslar
Hazar Kalonya, D. İklim değişikliği azaltım ve uyum süreçlerinde mera alanlarının önemi. Çevre, Şehir ve İklim Dergisi, 2022; 1(1), 128-157.
Altın M, Gökkuş A, Koç A. Çayır ve mera yönetimi. Ankara: T.C. Tarım ve Köyişleri Bakanlığı. TÜGEM Çayır-Mera Yem Bitkileri ve Havza Geliştirme Dairesi Başkanlığı; 2011.
Tosun F, Altın A. Çayır-mera-yayla kültürü ve bunlardan faydalanma yöntemleri. Samsun; Ondokuz Mayıs Üni. Ziraat Fak., Yayını; 1981.
Canfield RH. Application of the line interception method in sampling range vegetation. Journal of Forestry, 1941; 39(4), 388-394.
Tosun F. Botanical composition of prairie vegetation in relation to certain site characteristics and management practices. Nebraska University, Doctoral Thesis, 1961.
Uluocak N. Kırklareli yöresi meraları ve floristik analizleri. İstanbul Üniversitesi Orman Fakültesi Dergisi, 1974; 13(2), 131-194.
Gökkuş A, Koç A, Çomaklı B. Çayır-Mera Uygulama Kılavuzu. Erzurum: Atatürk Üniversitesi Ziraat Fakültesi Yayınları No: 142, 2015.
Avcıoğlu R. Çayır-Mera Bitki Topluluklarının Özellikleri ve İncelenmesi. İzmir: Ege Üniversitesi Ziraat Fakültesi Yayınları No: 466, 1983.
Bakır Ö. Vejetasyon Etüd ve Ölçümlerinde Kullanılan Bazı Önemli Metodların Mukayesesi. Ankara Üniversitesi Ziraat Fakültesi Yıllığı, 1970; 19, 550-579.
Parker KW. A method for measuring trend in range condition on national forest ranges. Forest Service, 1951; US Department of Agriculture, 26p.
Driscoll RS. A Loop Method for Measuring Ground-Cover Characteristics on Permanent Plots. Journal of Range Management, 1958; 11(2), 94–94.
Parker KW, Harris RW. The 3-step method for measuring condition and trend of forest ranges: a resume of its history, development and use. In Techniques and methods of measuring understory vegetation. Proc. of a symposium at Tifton, Georgia.
Babalık A. Çayır-meralarda dip kaplama ölçüm yöntemleri. Turkish Journal of Forestry, 2004; 5(1), 50-72.
Tung T, Avcıoğlu R. Vejetasyon Ölçme Yöntemleri (Nokta Çerçeve Yöntemi). İzmir: Ormancılık Araştırma Enstitüsü Yayınları, Dergi Serisi No: 72, Sayı 2, Cilt 36, 1990.
Levy, EB, Madden EA. The Point Method for Pasture Analysis. New Zealand Journal of Agriculture, 1933; 46, 267-279.
Aydın İ, Uzun F. Çayır-Mera Amenajmanı ve Islahı. Samsun: Ondokuz Mayıs Üniversitesi Ziraat Fakültesi Yayınları, No: 9, 2002.
Tidmarsh CEM, Havenga CM. The wheel-point method of survey and measurement of semi-open grassland and Karoo vegetation in South Africa. Memoirs of the Botanical Survey of South Africa. 1955; 19, 1-49.
Griffin GF. An enhanced wheel-point method for assessing cover, structure and heterogeneity in plant communities. Journal of Range Management, 1989; 42(1), 79-81.
Anonim. Ulusal mera kullanım ve yönetim projesi sonuç raporu. 2012; TUBİTAK 1007 106G017 nolu proje.
Koç A, Çakal Ş. Comparison of some rangeland canopy coverage method. In International Soil Congress Natural Resource Management for Sustainable Development. 2004; 7(10), 41-45.
Gençkan S. Çayır-Mera Kültürü, Amenajmanı, Islahı. İzmir: Ege Üniversitesi Ziraat Fakültesi Yayınları No: 483, 1985.
Mosley JC, Bunting SC, Hironaka M. Quadrat and sample sizes for frequency sampling mountain meadow vegetation. The Great Basin Naturalist, 1989; 49(2), 241–248.
Eraç A, Ekiz H. Çayır-Mera Amenajmanı Uygulama Kılavuzu. Ankara: Ankara Üniversitesi Ziraat Fakültesi Yayınları No: 990, 1986.
Berend K. The humble quadrat. Knots and Bolts, Northern Woodlands, 2021; Photo by K. Amatangelo. https://northernwoodlands.org/knots_and_bolts/humble-quadrat
Cooper WS. An apparatus for photographic recording of quadrats. Journal of Ecology, 1924; 12(2), 317-321.
Knipling EB. Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment, 1970; 1(3), 155-159.
Booth DT, Cox SE. Image‐based monitoring to measure ecological change in rangeland. Frontiers in Ecology and the Environment, 2008; 6(4), 185-190.
Hardin PJ, Jackson MW, Anderson VJ, Johnson R. Detecting squarrose knapweed (Centaurea virgata Lam. ssp. squarrosa Gugl.) using a remotely piloted vehicle: A Utah case study. GIScience & Remote Sensing, 2007; 44(3), 203-219.
Breckenridge RP, Dakins M, Bunting S, Harbour JL, White S. Comparison of unmanned aerial vehicle platforms for assessing vegetation cover in sagebrush steppe ecosystems. Rangeland Ecology & Management, 2011 64(5), 521-532.
Laliberte AS, Rango A. Image processing and classification procedures for analysis of sub-decimeter imagery acquired with an unmanned aircraft over arid rangelands. GIScience & Remote Sensing, 2011; 48(1), 4-23.
Baena S, Moat J, Whaley O, Boyd DS. Identifying species from the air: UAVs and the very high-resolution challenge for plant conservation. PloS one, 2017; 12(11), e0188714.
Cunliffe AM, Brazier RE, Anderson K. Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry. Remote Sensing of Environment, 2016; 183, 129-143.
Jensen JL, Mathews AJ. Assessment of image-based point cloud products to generate a bare earth surface and estimate canopy heights in a woodland ecosystem. Remote Sensing, 2016; 8(1), 50.
Olsoy PJ, Shipley LA, Rachlow JL, Forbey JS, Glenn NF, Burgess MA, Thornton DH. Unmanned aerial systems measure structural habitat features for wildlife across multiple scales. Methods in Ecology and Evolution, 2018; 9(3), 594-604.
Gillan JK, Karl JW, van Leeuwen WJ. Integrating drone imagery with existing rangeland monitoring programs. Environmental Monitoring and Assessment, 2020; 192(5), 269.
Michez A, Lejeune P, Bauwens S, Herinaina AAL, Blaise Y, Castro Muñoz E, Bindelle J. Mapping and monitoring of biomass and grazing in pasture with an unmanned aerial system. Remote Sensing, 2019; 11(5), 473.
Gillan JK, McClaran MP, Swetnam TL, Heilman P. Estimating forage utilization with drone-based photogrammetric point clouds. Rangeland Ecology & Management, 2019; 72(4), 575-585.
d'Oleire-Oltmanns S, Marzolff I, Peter KD, Ries JB. Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco. Remote Sensing, 2012; 4(11), 3390-3416.
Gillan JK, Karl JW, Elaksher A, Duniway MC. Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements. Remote Sensing, 2017; 9(5), 437.
Barrachina M, Cristóbal J, Tulla AF. Estimating above-ground biomass on mountain meadows and pastures through remote sensing. International Journal of Applied Earth Observation and Geoinformation, 2015; 38, 184–192.
Fern RR, Foxley, EA, Bruno A, Morrison ML. Suitability of NDVI and OSAVI as estimators of green biomass and coverage in a semi-arid rangeland. Ecological Indicators, 2018, 94, 16–21.
Otgonbayar M, Atzberger C, Chambers J, Damdinsuren A. Mapping pasture biomass in Mongolia using partial least squares, random forest regression and Landsat 8 imagery. International Journal of Remote Sensing, 2019; 40, 3204–3226.
Li C, Zhou L, Xu W. Estimating aboveground biomass using Sentinel-2 MSI data and ensemble algorithms for grassland in the Shengjin Lake Wetland, China. Remote Sensing, 2021; 13, 1595.
Tang R, Zhao Y, Lin H. Spatio-temporal variation characteristics of aboveground biomass in the headwater of the yellow river based on machine learning. Remote Sensing, 2021; 13, 3404.
Wang J, Xiao X, Bajgain R, Starks P, Steiner J, Doughty RB, Chang Q. Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images. ISPRS Journal of Photogrammetry and Remote Sensing, 2019; 154, 189–201.
Tucker CJ, Dregne HE, Newcomb WW. Expansion and contraction of the Sahara Desert from 1980 to 1990. Science, 1991; 253(5017), 299-300.
Reed BC, Brown JF, VanderZee D, Loveland TR, Merchant JW, Ohlen DO. Measuring phenological variability from satellite imagery. Journal of Vegetation Science, 1994; 5(5), 703-714.
Fuller DO. Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987-1993. International Journal of Remote Sensing, 1998; 19(10), 2013-2018.
Thoma DP, Bailey DW, Long DS, Nielsen GA, Henry MP, Breneman MC, Montagne C. Short-term monitoring of rangeland forage conditions with AVHRR imagery. 2002; Rangeland Ecology & Management/Journal of Range Management Archives, 55(4), 383-389.
Jia GJ, Epstein HE, Walker DA. Greening of arctic Alaska, 1981–2001. Geophysical Research Letters, 2003; 30(20), 2067.
Reed BC. Trend analysis of time-series phenology of North America derived from satellite data. 2006; GIScience & Remote Sensing, 43(1), 24-38.
Karnieli A, Gilad U, Ponzet M, Svoray T, Mirzadinov R, Fedorina O. Assessing land-cover change and degradation in the Central Asian deserts using satellite image processing and geostatistical methods. Journal of Arid Environments, 2008; 72(11), 2093-2105.
Fretwell PT, Convey P, Fleming AH, Peat HJ, Hughes KA. Detecting and mapping vegetation distribution on the Antarctic Peninsula from remote sensing data. Polar Biology, 2011; 34, 273-281.
Mermer A, Yıldız H, Ünal E, Aydoğdu M, Özaydın A, Dedeoğlu F, Mutlu Z. Monitoring rangeland vegetation through time series satellite images (NDVI) in Central Anatolia Region. In 2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics) (pp. 213-216).
Li S, Potter C, Hiatt C. Monitoring of net primary production in California rangelands using Landsat and MODIS satellite remote sensing. Natural Resources, 2012; 3(2), 10.
Zhang X, Friedl MA, Schaaf CB. Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements. Journal of Geophysical Research: Biogeosciences, 2006; 111(G4).
Richardson AJ, Everitt JH. Using spectral vegetation indices to estimate rangeland productivity. Geocarto International, 1992; 7(1), 63-69.
Washington-Allen RA, West NE, Ramsey RD. Remote sensing-based dynamical systems analysis of sagebrush steppe vegetation in rangelands. In Proceedings of the 7th International Rangelands Congress, 2003; Vol. 26, pp. 416-418.
Ghazal M, Al Khalil Y, Hajjdiab H. UAV-based remote sensing for vegetation cover estimation using NDVI imagery and level sets method. In 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (pp. 332-337). IEEE.
Marcial-Pablo MDJ, Gonzalez-Sanchez A, Jimenez-Jimenez SI, Ontiveros-Capurata RE, Ojeda-Bustamante W. Estimation of vegetation fraction using RGB and multispectral images from UAV. International Journal of Remote Sensing, 2019; 40(2), 420-438.
Théau J, Lauzier-Hudon É, Aubé L, Devillers N. Estimation of forage biomass and vegetation cover in grasslands using UAV imagery. PloS One, 2021; 16(1), e0245784.
Referanslar
Hazar Kalonya, D. İklim değişikliği azaltım ve uyum süreçlerinde mera alanlarının önemi. Çevre, Şehir ve İklim Dergisi, 2022; 1(1), 128-157.
Altın M, Gökkuş A, Koç A. Çayır ve mera yönetimi. Ankara: T.C. Tarım ve Köyişleri Bakanlığı. TÜGEM Çayır-Mera Yem Bitkileri ve Havza Geliştirme Dairesi Başkanlığı; 2011.
Tosun F, Altın A. Çayır-mera-yayla kültürü ve bunlardan faydalanma yöntemleri. Samsun; Ondokuz Mayıs Üni. Ziraat Fak., Yayını; 1981.
Canfield RH. Application of the line interception method in sampling range vegetation. Journal of Forestry, 1941; 39(4), 388-394.
Tosun F. Botanical composition of prairie vegetation in relation to certain site characteristics and management practices. Nebraska University, Doctoral Thesis, 1961.
Uluocak N. Kırklareli yöresi meraları ve floristik analizleri. İstanbul Üniversitesi Orman Fakültesi Dergisi, 1974; 13(2), 131-194.
Gökkuş A, Koç A, Çomaklı B. Çayır-Mera Uygulama Kılavuzu. Erzurum: Atatürk Üniversitesi Ziraat Fakültesi Yayınları No: 142, 2015.
Avcıoğlu R. Çayır-Mera Bitki Topluluklarının Özellikleri ve İncelenmesi. İzmir: Ege Üniversitesi Ziraat Fakültesi Yayınları No: 466, 1983.
Bakır Ö. Vejetasyon Etüd ve Ölçümlerinde Kullanılan Bazı Önemli Metodların Mukayesesi. Ankara Üniversitesi Ziraat Fakültesi Yıllığı, 1970; 19, 550-579.
Parker KW. A method for measuring trend in range condition on national forest ranges. Forest Service, 1951; US Department of Agriculture, 26p.
Driscoll RS. A Loop Method for Measuring Ground-Cover Characteristics on Permanent Plots. Journal of Range Management, 1958; 11(2), 94–94.
Parker KW, Harris RW. The 3-step method for measuring condition and trend of forest ranges: a resume of its history, development and use. In Techniques and methods of measuring understory vegetation. Proc. of a symposium at Tifton, Georgia.
Babalık A. Çayır-meralarda dip kaplama ölçüm yöntemleri. Turkish Journal of Forestry, 2004; 5(1), 50-72.
Tung T, Avcıoğlu R. Vejetasyon Ölçme Yöntemleri (Nokta Çerçeve Yöntemi). İzmir: Ormancılık Araştırma Enstitüsü Yayınları, Dergi Serisi No: 72, Sayı 2, Cilt 36, 1990.
Levy, EB, Madden EA. The Point Method for Pasture Analysis. New Zealand Journal of Agriculture, 1933; 46, 267-279.
Aydın İ, Uzun F. Çayır-Mera Amenajmanı ve Islahı. Samsun: Ondokuz Mayıs Üniversitesi Ziraat Fakültesi Yayınları, No: 9, 2002.
Tidmarsh CEM, Havenga CM. The wheel-point method of survey and measurement of semi-open grassland and Karoo vegetation in South Africa. Memoirs of the Botanical Survey of South Africa. 1955; 19, 1-49.
Griffin GF. An enhanced wheel-point method for assessing cover, structure and heterogeneity in plant communities. Journal of Range Management, 1989; 42(1), 79-81.
Anonim. Ulusal mera kullanım ve yönetim projesi sonuç raporu. 2012; TUBİTAK 1007 106G017 nolu proje.
Koç A, Çakal Ş. Comparison of some rangeland canopy coverage method. In International Soil Congress Natural Resource Management for Sustainable Development. 2004; 7(10), 41-45.
Gençkan S. Çayır-Mera Kültürü, Amenajmanı, Islahı. İzmir: Ege Üniversitesi Ziraat Fakültesi Yayınları No: 483, 1985.
Mosley JC, Bunting SC, Hironaka M. Quadrat and sample sizes for frequency sampling mountain meadow vegetation. The Great Basin Naturalist, 1989; 49(2), 241–248.
Eraç A, Ekiz H. Çayır-Mera Amenajmanı Uygulama Kılavuzu. Ankara: Ankara Üniversitesi Ziraat Fakültesi Yayınları No: 990, 1986.
Berend K. The humble quadrat. Knots and Bolts, Northern Woodlands, 2021; Photo by K. Amatangelo. https://northernwoodlands.org/knots_and_bolts/humble-quadrat
Cooper WS. An apparatus for photographic recording of quadrats. Journal of Ecology, 1924; 12(2), 317-321.
Knipling EB. Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment, 1970; 1(3), 155-159.
Booth DT, Cox SE. Image‐based monitoring to measure ecological change in rangeland. Frontiers in Ecology and the Environment, 2008; 6(4), 185-190.
Hardin PJ, Jackson MW, Anderson VJ, Johnson R. Detecting squarrose knapweed (Centaurea virgata Lam. ssp. squarrosa Gugl.) using a remotely piloted vehicle: A Utah case study. GIScience & Remote Sensing, 2007; 44(3), 203-219.
Breckenridge RP, Dakins M, Bunting S, Harbour JL, White S. Comparison of unmanned aerial vehicle platforms for assessing vegetation cover in sagebrush steppe ecosystems. Rangeland Ecology & Management, 2011 64(5), 521-532.
Laliberte AS, Rango A. Image processing and classification procedures for analysis of sub-decimeter imagery acquired with an unmanned aircraft over arid rangelands. GIScience & Remote Sensing, 2011; 48(1), 4-23.
Baena S, Moat J, Whaley O, Boyd DS. Identifying species from the air: UAVs and the very high-resolution challenge for plant conservation. PloS one, 2017; 12(11), e0188714.
Cunliffe AM, Brazier RE, Anderson K. Ultra-fine grain landscape-scale quantification of dryland vegetation structure with drone-acquired structure-from-motion photogrammetry. Remote Sensing of Environment, 2016; 183, 129-143.
Jensen JL, Mathews AJ. Assessment of image-based point cloud products to generate a bare earth surface and estimate canopy heights in a woodland ecosystem. Remote Sensing, 2016; 8(1), 50.
Olsoy PJ, Shipley LA, Rachlow JL, Forbey JS, Glenn NF, Burgess MA, Thornton DH. Unmanned aerial systems measure structural habitat features for wildlife across multiple scales. Methods in Ecology and Evolution, 2018; 9(3), 594-604.
Gillan JK, Karl JW, van Leeuwen WJ. Integrating drone imagery with existing rangeland monitoring programs. Environmental Monitoring and Assessment, 2020; 192(5), 269.
Michez A, Lejeune P, Bauwens S, Herinaina AAL, Blaise Y, Castro Muñoz E, Bindelle J. Mapping and monitoring of biomass and grazing in pasture with an unmanned aerial system. Remote Sensing, 2019; 11(5), 473.
Gillan JK, McClaran MP, Swetnam TL, Heilman P. Estimating forage utilization with drone-based photogrammetric point clouds. Rangeland Ecology & Management, 2019; 72(4), 575-585.
d'Oleire-Oltmanns S, Marzolff I, Peter KD, Ries JB. Unmanned aerial vehicle (UAV) for monitoring soil erosion in Morocco. Remote Sensing, 2012; 4(11), 3390-3416.
Gillan JK, Karl JW, Elaksher A, Duniway MC. Fine-resolution repeat topographic surveying of dryland landscapes using UAS-based structure-from-motion photogrammetry: Assessing accuracy and precision against traditional ground-based erosion measurements. Remote Sensing, 2017; 9(5), 437.
Barrachina M, Cristóbal J, Tulla AF. Estimating above-ground biomass on mountain meadows and pastures through remote sensing. International Journal of Applied Earth Observation and Geoinformation, 2015; 38, 184–192.
Fern RR, Foxley, EA, Bruno A, Morrison ML. Suitability of NDVI and OSAVI as estimators of green biomass and coverage in a semi-arid rangeland. Ecological Indicators, 2018, 94, 16–21.
Otgonbayar M, Atzberger C, Chambers J, Damdinsuren A. Mapping pasture biomass in Mongolia using partial least squares, random forest regression and Landsat 8 imagery. International Journal of Remote Sensing, 2019; 40, 3204–3226.
Li C, Zhou L, Xu W. Estimating aboveground biomass using Sentinel-2 MSI data and ensemble algorithms for grassland in the Shengjin Lake Wetland, China. Remote Sensing, 2021; 13, 1595.
Tang R, Zhao Y, Lin H. Spatio-temporal variation characteristics of aboveground biomass in the headwater of the yellow river based on machine learning. Remote Sensing, 2021; 13, 3404.
Wang J, Xiao X, Bajgain R, Starks P, Steiner J, Doughty RB, Chang Q. Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images. ISPRS Journal of Photogrammetry and Remote Sensing, 2019; 154, 189–201.
Tucker CJ, Dregne HE, Newcomb WW. Expansion and contraction of the Sahara Desert from 1980 to 1990. Science, 1991; 253(5017), 299-300.
Reed BC, Brown JF, VanderZee D, Loveland TR, Merchant JW, Ohlen DO. Measuring phenological variability from satellite imagery. Journal of Vegetation Science, 1994; 5(5), 703-714.
Fuller DO. Trends in NDVI time series and their relation to rangeland and crop production in Senegal, 1987-1993. International Journal of Remote Sensing, 1998; 19(10), 2013-2018.
Thoma DP, Bailey DW, Long DS, Nielsen GA, Henry MP, Breneman MC, Montagne C. Short-term monitoring of rangeland forage conditions with AVHRR imagery. 2002; Rangeland Ecology & Management/Journal of Range Management Archives, 55(4), 383-389.
Jia GJ, Epstein HE, Walker DA. Greening of arctic Alaska, 1981–2001. Geophysical Research Letters, 2003; 30(20), 2067.
Reed BC. Trend analysis of time-series phenology of North America derived from satellite data. 2006; GIScience & Remote Sensing, 43(1), 24-38.
Karnieli A, Gilad U, Ponzet M, Svoray T, Mirzadinov R, Fedorina O. Assessing land-cover change and degradation in the Central Asian deserts using satellite image processing and geostatistical methods. Journal of Arid Environments, 2008; 72(11), 2093-2105.
Fretwell PT, Convey P, Fleming AH, Peat HJ, Hughes KA. Detecting and mapping vegetation distribution on the Antarctic Peninsula from remote sensing data. Polar Biology, 2011; 34, 273-281.
Mermer A, Yıldız H, Ünal E, Aydoğdu M, Özaydın A, Dedeoğlu F, Mutlu Z. Monitoring rangeland vegetation through time series satellite images (NDVI) in Central Anatolia Region. In 2015 Fourth International Conference on Agro-Geoinformatics (Agro-geoinformatics) (pp. 213-216).
Li S, Potter C, Hiatt C. Monitoring of net primary production in California rangelands using Landsat and MODIS satellite remote sensing. Natural Resources, 2012; 3(2), 10.
Zhang X, Friedl MA, Schaaf CB. Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements. Journal of Geophysical Research: Biogeosciences, 2006; 111(G4).
Richardson AJ, Everitt JH. Using spectral vegetation indices to estimate rangeland productivity. Geocarto International, 1992; 7(1), 63-69.
Washington-Allen RA, West NE, Ramsey RD. Remote sensing-based dynamical systems analysis of sagebrush steppe vegetation in rangelands. In Proceedings of the 7th International Rangelands Congress, 2003; Vol. 26, pp. 416-418.
Ghazal M, Al Khalil Y, Hajjdiab H. UAV-based remote sensing for vegetation cover estimation using NDVI imagery and level sets method. In 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (pp. 332-337). IEEE.
Marcial-Pablo MDJ, Gonzalez-Sanchez A, Jimenez-Jimenez SI, Ontiveros-Capurata RE, Ojeda-Bustamante W. Estimation of vegetation fraction using RGB and multispectral images from UAV. International Journal of Remote Sensing, 2019; 40(2), 420-438.
Théau J, Lauzier-Hudon É, Aubé L, Devillers N. Estimation of forage biomass and vegetation cover in grasslands using UAV imagery. PloS One, 2021; 16(1), e0245784.
