Spatial Distribution Pattern of MODIS-NDVI and Correlation between NDVI and Meteorology Factors in Shandong Province in China

Song, Dongmei; Guo, Peng; Sheng, Hui

doi:10.2529/piers070907105158

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…The MODIS/Terra MOD17A3H data products [38] provide accurate measurements of terrestrial vegetation growth, including global gross primary productivity (GPP) and annual net primary productivity (NPP). The NPP data were synthesized from 45 periods (8-day synthetic data) at a spatial resolution of 500 m in gC/m 2 , and were processed using projection change, mosaicking, and cropping to investigate the spatial and temporal variation of NPP in the two years of 2010 and 2020 in the Urat front banner, as well as to conduct the driving factor analysis for this study [39,40]. Negative values, fire point instability values, and background noise are not removed from the monthly products of NPP, but the annual data for 2010 and 2020 provide cloud-free mean lights and exclude transient lights, so the use of MOD17A3 data for these two years to validate only the NPP estimated by the CASA model is sufficient for the experiment.…”

Section: Data Source and Its Pre-processingmentioning

confidence: 99%

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Yan

Wang

Zhao

et al. 2022

Water

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Monitoring the spatio-temporal dynamics of desertification is critical for desertification control. Using the Urat front flag as the study area, Landsat remote sensing images between 2010 and 2020 were selected as data sources, along with MOD17A3H as auxiliary data. Additionally, RS and GIS theories and methods were used to establish an Albedo–NDVI feature space based on the normalized difference vegetation index (NDVI) and land surface albedo. The desertification difference index (DDI) was developed to investigate the dynamic change and factors contributing to desertification in the Urat front banner. The results show that: ① the Albedo–NDVI feature space method is effective and precise at extracting and classifying desertification information, which is beneficial for quantitative analysis and monitoring of desertification; ② from 2010 to 2020, the spatial distribution of desertification degree in the Urat front banner gradually decreased from south to north; ③ throughout the study period, the area of moderate desertification land increased the most, at an annual rate of 8.2%, while the area of extremely serious desertification land decreased significantly, at an annual rate of 9.2%, indicating that desertification degree improved during the study period; ④ the transformation of desertification types in Urat former banner is mainly from very severe to moderate, from severe to undeserted, and from mild to undeserted, with respective areas of 22.5045 km2, 44.0478 km2, and 319.2160 km2. Over a 10-year period, the desertification restoration areas in the study area ranged from extremely serious desertification to moderate desertification, from serious desertification to non-desertification, and from weak desertification to non-desertification, while the desertification aggravation areas ranged mainly from serious desertification to moderate desertification; ⑤ NPP dynamic changes in vegetation demonstrated a zonal increase in distribution from west to east, and significant progress was made in desertification control. The change in desertification has accelerated significantly over the last decade. Climate change and irresponsible human activities have exacerbated desertification in the eastern part of the study area.

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Section: Data Source and Its Pre-processingmentioning

confidence: 99%

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Yan

Wang

Zhao

et al. 2022

Water

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“…We use such a definition to define contact rates among ticks, hosts, and reservoirs based on current climate data, and the projected climate for the years 2030 and 2050 based on the land surface temperature (LSTD) and the Normalized Difference Vegetation Index (NDVI). The NDVI is an estimate of the photosynthetic activity of the vegetation, but many studies have utilized this index as a proxy of the relative humidity of an area [21,22]. In addition, these variables and their annual oscillations are the best descriptors of the environmental niche of arthropod vectors [23].…”

Section: Introductionmentioning

confidence: 99%

Could climate trends disrupt the contact rates between Ixodes ricinus (Acari, Ixodidae) and the reservoirs of Borrelia burgdorferi s.l.?

Fernández-Ruiz

Estrada-Peña

2020

PLoS ONE

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This study addresses the modifications that future climate conditions could impose on the transmission cycles of Borrelia burgdorferi s.l. by the tick Ixodes ricinus in Europe. Tracking the distribution of foci of a zoonotic agent transmitted by vectors as climate change shapes its spatial niche is necessary to issue self-protection measures for the human population. We modeled the current distribution of the tick and its predicted contact rates with 18 species of vertebrates known to act as reservoirs of the pathogen. We approached an innovative way for estimating the possibility of permanent foci of Borrelia afzelii or Borrelia garinii tracking separately the expected spatial overlap among ticks and reservoirs for these pathogens in Europe. Environmental traits were obtained from MODIS satellite images for the years 2002-2017 (baseline) and projected on scenarios for the years 2030 and 2050. The ratio between MODIS baseline/current interpolated climatologies (WorldClim), and the ratio between MODIS-projected year 2050 with five climate change scenarios for that year (WorldClim) revealed no significant differences, meaning that projections from MODIS are reliable. Models predict that contact rates between the tick and reservoirs of either B. garinii or B. afzelii are spatially different because those have different habitats overlap. This is expected to promote different distribution patterns because of the different responses of both groups of reservoirs to environmental variables. Models for 2030 predict an increase in latitude, mainly in the circulation of B. garinii, with large areas of expected permanent contact between vector and reservoirs in Nordic countries and central Europe. However, climate projections for the year 2050 predict an unexpected scenario of contact disruption. Though large areas in Europe would be suitable for circulation of the pathogens, the predicted lack of niche overlap among ticks and reservoirs could promote a decrease in permanent foci. This development represents a proof-of-concept for the power of jointly modeling both the vector and reservoirs in a common framework. A deeper understanding of the unanticipated result regarding the year 2050 is needed.

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“…Özellikle NDVI ile vejetasyon dinamikleri arasındaki ilişkilerin ortaya konmasına dayanan çalışmalar onlarca yıllık geçmişe sahiptir [19,20]. Söz konusu araştırmalara uluslararası [21] [4]. Alansal olarak yüzey koşullarının heterojenleştiği koşullar, zamansal olarak ise gün doğumu ve batımı sırasındaki özel koşullar, BREB yaklaşımının doğruluğunu sınırlayıcı durumlardır [26].…”

Section: Introductionunclassified

Bitki Yüzeyinin Enerji Dengesi Bileşenlerinin Belirli Fenolojik Aşamalarda Analizi

Çaldag¹

2019

deufmd

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Öz İklim değişiminin sıcaklık artışları, yağışların azalması, artan buharlaşma gibi etkileri; geniş alanda yetiştirilen bitki türlerinin su ihtiyacına ve üretim değerlerine yönelik çalışmalar için önemlidir. Bitki su tüketimi (evapotranspirasyon) verisi, bir bölgede yapılması planlanan tarımsal sulama projelerinin temelini oluşturmaktadır. Yüzeyler ile atmosfer arasındaki su döngüsünü idare eden yüzey enerji dengesi bileşenlerinin saptanması da bu noktada bir ihtiyaç halini almaktadır. Yüzey enerji dengesi bileşenlerinin saptanması amacıyla yaygın olarak kullanılan Bowen Oranı Enerji Dengesi (Bowen Ratio Energy Balance, BREB) Yöntemi, bu çalışmada kanola yüzeyi üzerine uygulanmıştır. Bu kapsamda Kırklareli Atatürk Toprak Su ve Tarımsal Meteoroloji Araştırma Enstitüsü Müdürlüğü deneme alanında 2016 gelişme döneminin çiçeklenme aşamasında buharlaşma gizli ısı akısı, toprak ısı akısı, net radyasyon, hissedilir ısı akısı ile bitki yüzeyinin normalleştirilmiş fark vejetasyon indeksi (Normalized Difference Vegetation Index, NDVI) belirlenerek, ölçülen bileşenler ile hesaplanan bileşenler arasındaki ilişkiler araştırılmıştır. Sonuçta ölçüm dönemi içinde net radyasyon değerinin en yüksek olduğu tarih; 27 Nisan 2016 olarak belirlenmiştir. Bu tarih, seçilen günler için hesaplanan evapotranspirasyon değerlerinin de en yüksek olduğu zaman aralığı içindedir. Aynı dönemin NDVI değerlerinin de benzer biçimde 22 Mart-14 Nisan 2016 arasında maksimum değerlere ulaştığı belirlenmiştir.

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Spatial Distribution Pattern of MODIS-NDVI and Correlation between NDVI and Meteorology Factors in Shandong Province in China

Cited by 7 publications

References 7 publications

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Monitoring of Land Desertification Changes in Urat Front Banner from 2010 to 2020 Based on Remote Sensing Data

Could climate trends disrupt the contact rates between Ixodes ricinus (Acari, Ixodidae) and the reservoirs of Borrelia burgdorferi s.l.?

Bitki Yüzeyinin Enerji Dengesi Bileşenlerinin Belirli Fenolojik Aşamalarda Analizi

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