The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Mangroves critically require conservation activity due to human encroachment and environmental unsustainability. The forests must be conserving through monitoring activities with an application of remote sensing satellites. Recent high-resolution multispectral satellite was used to produce Normalized Difference Vegetation Index (NDVI) and Tasselled Cap transformation (TC) indices mapping for the area. Satellite Pour l’Observation de la Terre (SPOT) SPOT-6 was employed for ground truthing. The area was only a part of mangrove forest area of Tanjung Piai which estimated about 106 ha. Although, the relationship between the spectral indices and dendrometry parameters was weak, we found a very significant between NDVI (mean) and stem density (y=10.529x + 12.773) with R2=0.1579. The sites with NDVI calculated varied from 0.10 to 0.26 (P1 and P2), under the environmental stress due to sand deposition found was regard as unhealthy vegetation areas. Whereas, site P5 with NDVI (mean) 0.67 is due to far distance from risk wave’s zone, therefore having young/growing trees with large lush green cover was regard as healthy vegetation area. High greenness indicated in TC means, the bands respond to a combination of high absorption of chlorophyll in the visible bands and the high reflectance of leaf structures in the near-infrared band, which is characteristic of healthy green vegetation. Overall, our study showed our tested WV-2 image combined with ground data provided valuable information of mangrove health assessment for Tanjung Piai, Johor, Malay Peninsula.

To evaluate water use and the supporting water source of a tropical rainforest, a 4‐year assessment of evapotranspiration (ET) was conducted in Pasoh Forest Reserve, a lowland dipterocarp forest in Peninsular Malaysia. The eddy covariance method and isotope signals of rain, plant, soil, and stream waters were used to determine forest water sources under different moisture conditions. Four sampling events were conducted to collect soil and plant twig samples in wet, moderate, dry, and very dry conditions for the identification of isotopic signals. Annual ET from 2012 to 2015 was quite stable with an average of 1,182 ± 26 mm, and a substantial daily ET was observed even during drought periods, although some decline was observed, corresponding with volumetric soil water content. During the wet period, water for ET was supplied from the surface soil layer between 0 and 0.5 m, whereas in the dry period, approximately 50% to 90% was supplied from the deeper soil layer below 0.5‐m depth, originating from water precipitated several months previously at this forest. Isotope signatures demonstrated that the water sources of the plants, soil, and stream were all different. Water in plants was often different from soil water, probably because plant water came from a different source than water that was strongly bound to the soil particles. Plants showed no preference for soil depth with their size, whereas the existence of storage water in the xylem was suggested. The evapotranspiration at this forest is balanced and maintained using most of the available water sources except for a proportion of rapid response run‐off.

Normalized difference vegetation index (NDVI) has been widely applied for monitoring vegetation dynamics. However, NDVI values are known to be profoundly affected by various external factors. In this study, the variation of NDVI values and trends among the several long-term NDVI datasets with resolution of 1, 4 and 8 km were assessed to understand the differences between the available datasets. The assessment items were 1) Pearson's correlation coefficient, 2) trend map and breakpoint spatial similarities and 3) comparison of NDVI from Landsat and Flux tower in 2007-2015. The comparison revealed a maximum correlation coefficient of 0.67 among NDVI datasets and average spatial similarity of 37.2% among the trend maps estimated from NDVI datasets. Furthermore, there was a possibility of having significantly opposite trends between two trend maps from different NDVI products. Comparisons with NDVI from vegetation pixel in Landsat 5 TM and 8 OLI resulted in the R 2 between 0.06 and 0.68 and RMSE of 0.07-0.2, while comparison with NDVI from flux tower data yielded the RMSE of 0.04-0.41, although the R 2 was relatively weak at 0-0.18. Our study highlights the possibility of differences among NDVI datasets, and suggests that these differences should be reconciled especially in time-series analysis.

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Early examination of the water condition of the plants utilizing remote sensing technology can be used to assess the health of the vegetation in the Eucalyptus forest plantation. To preserve a sustainable wood supply and wooded region that is necessary to human life and vital wood supplies, the forested region should be protected from disease and environmental damage. Disease and environmental impacts are two of the most critical challenges in Eucalyptus forest management. To calculate the vegetation index and identify land cover in the research region, remote sensing with Catalyst Professional software based on Object Analyst (OBIA) tools was utilized. The NDVI (Normalized Difference Vegetation Index) is a valuable index for assessing early vegetation health. For atmospheric correction and haze removal, the image was first pre-processed with ATCOR tools. Second, the image was converted to NDVI using algorithm library tools. In addition, for land cover classification in the area, an OBIA based on Support Vector Machine (SVM) was utilized, followed by an accuracy assessment. Using ArcGIS software, zonal statistics were used to calculate the NDVI value for each land cover category. According to the method, the map produced roads, plantations, buildings, low-density vegetation, oil palm, and open area classifications. Based on accuracy assessment in OBIA, plantation, oil palm, and open area were all 100% accurate, whereas low-density vegetation and oil palm were 100% accurate according to the user. Producer accuracy was lowest on roads, whereas user accuracy was lowest in open areas. Non-vegetated land is difficult to classify at this site, according to the accuracy assessment results. The map improved accuracy since the study used a lower segmentation scale factor of 50, which produced fine vectors ascribed for classification. The average NDVI for oil palm area was 0.71, and 0.69 for plantation. Because it was difficult to classify open areas and roads, the NDVI for the class was low, at 0.37 and 0.22, respectively. From land use classification, the plantation was classified (37%), low-density vegetation area (28%), and oil palm (21%). Others make up only 2 to 7% of the site’s overall area. According to the study, NDVI is a useful indicator for assessing the health of vegetation in areas where NDVI values are larger than 0.70 and presents pf mixed landscape and non-vegetated features. A higher NDVI value implies that the plant is in good enough shape to conduct photosynthetic activities thus producing biomass for sustaining vegetation health. This type of inquiry can forecast more indices to produce higher accuracy of land use maps for the Eucalyptus plantation. At the same time, this type of research can assist forest managers in detecting large areas in their plantation for vegetation health assessment such as for early disease detection.

Sap flow pattern of Tectona grandis planted at lowland forest assessed. This study aimed to determine the sap movement of two different diameter sizes T. grandis. Two sizes selected were 16 and 38 cm in diameter at breast height (dbh). Sap flow meter (SFM) used to assess the sap velocity rates at the interval of 30 min within 24 h for 15 days. Diurnal sap flow of T. grandis shows that mean velocity is high during day time compared night time. Small diameter has high sap flow compared to that of bigger diameter. A flow rates was high at the inner layer and less at outer layer for smaller tree. The variation was vice versa when the tree was getting bigger. Variations in sap flow of T. grandis characterized by several environmental factors. It was found that size contribute in the differed sap flow of T. grandis. ABSTRAKKajian telah dilakukan terhadap corak aliran sap bagi Tectona grandis yang ditanam di hutan tanah rendah. Tujuan kajian ini ialah untuk menentukan pergerakan sap bagi dua diameter dirian pokok T. grandis yang berbeza. Dua saiz yang dipilih adalah 16 dan 38 cm diameter pada paras dada (ppd). Alat pengesan aliran sap (Sap flow meter -SFM) digunakan untuk menilai kadar halaju sap pada selang 30 minit dalam tempoh 24 jam selama 15 hari. Purata aliran siang malam oleh T. grandis menunjukkan bahawa halaju purata adalah tinggi pada waktu siang berbanding waktu malam. Saiz diameter yang kecil mempunyai aliran sap yang lebih tinggi berbanding dengan diameter yang besar. Bagi saiz diameter pokok yang kecil, kadar aliran sap adalah tinggi di lapisan dalaman berbanding lapisan luar. Corak perbezaan ini akan menjadi sebaliknya apabila saiz pokok tersebut semakin besar. Variasi dalam aliran sap T. grandis dicirikan oleh beberapa faktor persekitaran. Penemuan mendapati bahawa saiz diameter pokok menyumbang kepada perbezaan aliran sap pada T. grandis. FIGURE 7. Diurnal sap velocity of the 16 cm DBH Tectona grandis FIGURE 8. Diurnal sap velocity of the 38.5 cm DBH Tectona grandis

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