Modelling the productivity of Siberian larch forests from Landsat NDVI time series in fragmented forest stands of the Mongolian forest-steppe

Study on the evolution of ecological environment and irrigation behavior since mulched drip irrigation in Yanqi basin, Xinjiang

Analyzing the ecological and behavioral effects of changes in irrigation practices in oases provides valuable insights for water resource management and the sustainable development of oasis agriculture in arid regions. Taking the Yanqi Basin as a case study, this research draws on long-term empirical data and remote sensing information to evaluate the ecological and irrigation behavior effects resulting from shifts in irrigation methods. And explores the deep societal causes behind these behavioral changes. The findings demonstrate: (1). Between 2000 and 2010, the rapid adoption of groundwater extraction and mulched drip irrigation (MDI) technology temporarily alleviated the water supply-demand contradiction. However, from 2010 to 2020, as the adoption of water-saving practices significantly expanded and agricultural irrigation areas grew substantially, the irrigation paradox emerged, where increased efficiency paradoxically led to greater water consumption. (2). From 2000 to 2020, the groundwater table depth in the irrigation district dropped by 8-16 m, total soluble salt content decreased by 2-5 g/L, and soil salinity decreased by 4-12 g/kg. The proportion of severely salinized and saline soil areas fell from 21.74% in 1999 to 9.75% in 2020. The longstanding salinization issues that had plagued the irrigation district were effectively mitigated with the widespread adoption of MDI. (3). The irrigation district's vegetation ecological quality index (VEQI) showed a slow but steady upward trend in cultivated areas over the years. In contrast, natural vegetation areas such as forests and grasslands exhibited an initial increase followed by a decline. The trends in VEQI responded well to changes in irrigation practices. (4). The economic benefits driven by water-saving technologies and the expansion of cultivated land are deep societal factors behind the changes in irrigation behavior. These benefits also fostered improvements in users' understanding and awareness of irrigation practices. The shift in irrigation methods in the Yanqi Basin has led to a decline in groundwater levels, an irrigation paradox, and moderate damage to natural vegetation. However, it has had a significant positive impact on improving regional groundwater quality and mitigating soil salinization. Furthermore, it facilitates the further exploration of regional water conservation potential, enhancing the research on the regional water and soil resource management system.

Fusion of airborne multimodal point clouds for vegetation parameter correction extraction in burned areas

Most experimental studies use unimodal data for processing, the RGB image point cloud cannot separate the shrub and tree layers according to the visible vegetation index, and the airborne laser point cloud is difficult to distinguish between the ground and grass ranges, to address the above problems, a multi-band information image fusing the LiDAR point cloud and the RGB image point cloud is constructed. In this study, data collected from UAV platforms, including RGB image point clouds and laser point clouds, were used to construct a fine canopy height model (using laser point cloud data) and high-definition digital orthophotos (using image point cloud data), and the orthophotos were fused with a canopy height model (CHM) by selecting the Difference Enhancement Vegetation Index (DEVI) and Normalised Green-Blue Discrepancy Index (NGBDI) after comparing the accuracy of different indices. Morphological reconstruction of CHM + DEVI/NGBDI fusion image, remove unreasonable values; construct training samples, using classification regression tree algorithm, segmentation of the range of the burned areas and adaptive extraction of vegetation as trees, shrubs and grasslands, tree areas as foreground markers using the local maximum algorithm to detect the tree apexes, the non-tree areas are assigned to be the background markers, and the Watershed Transform is performed to obtain the segmentation contour; the original laser point cloud is divided into chunks according to the segmented single-tree contour, and the highest point is traversed to search for the highest point, and corrected for the height of the single-tree elevations one by one. Accuracy analysis of the vegetation information extracted by the method with the measured data showed that the improved method increased the overall recall rate by 4.1%, the overall precision rate by 3.7%, the overall accuracy F1 score by 3.9%, and the tree height accuracy by 8.8%, 1.4%, 1.7%, 6.4%, 1.8%, and 0.3%, respectively, in the six sampling plots. The effectiveness of the improved method is verified, while the higher the degree of vegetation mixing in the region the better the extraction effect of the improved algorithm.

Trend analysis of MODIS NDVI time series and its relationship to temperature and precipitation in Northeastern of Iran

Vegetation plays a crucial role in providing organic matter and regulating energy exchange on the Earth's surface. This study investigates the changes in vegetation cover, temperature, and precipitation in northeastern Iran during 2001-2020. MODIS-NDVI time series data and climatic data from 11 synoptic stations were utilized. The nonparametric Mann-Kendall method was employed to detect trends in vegetation cover and climatic variables. Additionally, the correlation between climatic parameters and vegetation was examined. Trend analysis revealed significant increases/decreases in vegetation cover in 32%/26% of the region, respectively. The increasing trend in vegetation cover was predominantly observed in highlands, suggesting that a warmer climate has enhanced the living conditions for plants in these regions. The vegetation trend map indicates an expansion of vegetation cover in the northern and central parts of Iran during the past 20 years, whereas the southern and eastern portions experienced declines. The relationship between vegetation and elevation revealed that vegetation increased above 1,850 m and decreased below 850 m. Trend analysis showed no significant trend in precipitation data since the beginning of the twenty-first century, but an increasing trend in temperature was observed in 82% of the region's area, excluding the western strip. Correlation coefficients between temperature, precipitation, and vegetation indicated that declining temperatures are the limiting factors for vegetation in the highlands, while in lowland areas, the decrease in precipitation significantly diminishes vegetation growth.

Time-series analysis of satellite imagery for detecting vegetation cover changes in Indonesia

Indonesia has one of the world's largest tropical forests; thus, its deforestation and environmental degradation are a global concern. This study is the first to perform comprehensive big data analyses with coherent vegetation criteria to measure the vegetation change at a high temporal resolution (every 16-day period) for 20 years and the high administrative resolution (regency or city) all over Indonesia. The normalized difference vegetation index (NDVI) of the Moderate Resolution Imaging Spectroradiometer is analyzed through state space modeling. The findings reveal that the NDVI increases in almost all regencies, except in urban areas. A high correlation between the NDVI change and the time is observed in Sumatra, Papua, and Kalimantan. The gain of the NDVI values is obvious in the Central and Eastern Java Island. Human activities, such as the expansion of agriculture and forestry and forest conservation policies, are the key factors for the observed pattern.

No Signs of Long-term Greening Trend in Western Mongolian Grasslands

Trends for increased vegetation greenness based on satellite-derived data have been repeatedly published for the temperate grassland biome (including forest steppes) of eastern Inner Asia since 1982. Although this greening trend has been attenuated or partially reversed by drought in the early twenty-first century, linear increases in the Normalized Difference Vegetation Index (NDVI) or other parameters of vegetation greenness are nevertheless evident when the period since 1982 is regarded. However, the question arises whether these trends are part of a long-term trend driven by climate change, as simultaneously forests in the region show widespread drought-induced growth reductions and mortality outbreaks. Therefore, we hypothesized that the post-1982 greening trend was neither part of a long-term trend nor unprecedented. To test this hypothesis, we analyzed monthly maximum NDVI data from AVHRR time series and correlated these data with standardized tree-ring data of Larix sibirica from two regions of western Mongolia. We used linear regression to model the NDVI from tree-ring anomalies and to reconstruct the NDVI since 1940. These reconstructions show that the availability of satellite-based NDVI data coincidentally began during a dry period of low vegetation greenness in the early 1980s and was followed by a wet phase in the 1990s, producing the linear greening trend. No positive long-term trend in the reconstructed NDVI was observed from 1940 to 2010. This result rules out a recent climate change-driven greening trend for the grasslands and forest steppes of western Mongolia and calls into question its existence for all of eastern Inner Asia.

Satellite observations document trends consistent with a boreal forest biome shift

The boreal forest biome is a major component of Earth's biosphere and climate system that is projected to shift northward due to continued climate change over the coming century. Indicators of a biome shift will likely first be evident along the climatic margins of the boreal forest and include changes in vegetation productivity, mortality, and recruitment, as well as overall vegetation greenness. However, the extent to which a biome shift is already underway remains unclear because of the local nature of most field studies, sparsity of systematic ground-based ecological monitoring, and reliance on coarse resolution satellite observations. Here, we evaluated early indicators of a boreal forest biome shift using four decades of moderate resolution (30 m) satellite observations and biogeoclimatic spatial datasets. Specifically, we quantified interannual trends in annual maximum vegetation greenness using an ensemble of vegetation indices derived from Landsat observations at 100,000 sample sites in areas without signs of recent disturbance. We found vegetation greenness increased (greened) at 38 [29, 42] % and 22 [15, 26] % of sample sites from 1985 to 2019 and 2000 to 2019, whereas vegetation greenness decreased (browned) at 13 [9, 15] % and 15 [13, 19] % of sample sites during these respective periods [95% Monte Carlo confidence intervals]. Greening was thus 3.0 [2.6, 3.5] and 1.5 [0.8, 2.0] times more common than browning and primarily occurred in cold sparsely treed areas with high soil nitrogen and moderate summer warming. Conversely, browning primarily occurred in the climatically warmest margins of both the boreal forest biome and major forest types (e.g., evergreen conifer forests), especially in densely treed areas where summers became warmer and drier. These macroecological trends reflect underlying shifts in vegetation productivity, mortality, and recruitment that are consistent with early stages of a boreal biome shift.

Effects of Forest Fragmentation on the Volume of Wood Resources in Managed, Pine-Dominated Forests in Poland

Forest fragmentation is a widespread phenomenon that directly or indirectly affects the processes that take place both in forest ecosystems and in their immediate surroundings. So far, many studies confirm its negative effects, especially on biodiversity. On the other hand, there are few studies that address the effects of forest fragmentation on the amount of accumulated biomass or carbon, as well as on the characteristics of wood resources in managed forests. Therefore, issues related to timber production, which are important from the point of view of multifunctional forest management, are omitted. The aim of our research was to add to the knowledge in this area. In particular, we focused on assessing the impact of forest fragmentation on wood resources based on an analysis of edge effects in forest patches (units formed by combining forest fragments characterized by structural connectivity). Vector data describing the topography of forest fragments in Poland and the results of the National Forest Inventory (NFI) from 2015–2019 were used as material for solving this problem. The results of our research showed that the effects of fragmentation on managed pine stands depend on the age of the stand and the fertility of the habitat. In young stands growing on barren or strongly barren habitats, growing stock volume turned out to be significantly higher in the edge zone. In older stands, especially on moderately fertile habitats, significantly higher resources were found in the interior zone of forest patches. Habitat quality also had a significant effect on the amount of carbon accumulated. In strongly barren habitats, higher carbon mass was found in edge zones, while in moderately fertile habitats, stands had higher carbon volume in the interior zone. Our results illustrate that forest fragmentation is a very complex process that can increase or reduce wood resources, depending on the age of the stand and the quality of the habitat. From the standpoint of measurable benefits, it was concluded that protection from the negative effects of fragmentation should focus primarily on older stands and more fertile habitats.

Temporal Pattern Analysis of Cropland Phenology in Shandong Province of China Based on Two Long-Sequence Remote Sensing Data

Vegetation phenology dynamics have attracted worldwide attention due to its direct response to global climate change and the great influence on terrestrial carbon budgets and ecosystem productivity in the past several decades. However, most studies have focused on phenology investigation on natural vegetation, and only a few have explored phenology variation of cropland. In this study, taking the typical cropland in the Shandong province of China as the target, we analyzed the temporal pattern of the Normalized Difference Vegetation Index (NDVI) and phenology metrics (growing season start (SOS) and end (EOS)) derived from the Global Inventory Monitoring and Modeling System (GIMMS) 3-generation version 1 (1982–2015) and the Vegetation Index and Phenology (VIP) version 4 (1981–2016), and then investigated the influence of climate factors and Net Primary Production (NPP, only for EOS) on SOS/EOS. Results show a consistent seasonal profile and interannual variation trend of NDVI for the two products. Annual average NDVI has significantly increased since 1980s, and hugely augmentations of NDVI were detected from March to June for both NDVI products (p < 0.01), which indicates a consistent greening tendency of the study region. SOSs from both products are correlated well with the ground-observed wheat elongation and spike date and have significantly advanced since the 1980s, with almost the same changing rate (0.65/0.64 days yr-1, p < 0.01). EOS also exhibits an earlier but weak advancing trend. Due to the significant advance of SOS, the growing season duration has significantly lengthened. Spring precipitation has a relatively stronger influence on SOS than temperature and shortwave radiation, while a greater correlation coefficient was diagnosed between EOS and autumn temperature/shortwave radiation than precipitation/NDVI. Autumn NPP exhibits a nonlinear effect on EOS, which is first earlier and then later with the increase of autumn NPP. Overall, we highlight the similar capacity of the two NDVI products in characterizing the temporal patterns of cropland phenology.