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In addition, for low- and medium-resolution remote-sensing phenology products (e.g., MODIS/VIIRS), it is difficult even for UAVs or phenocams to provide validation data at the comparable pixel scale, in which case indirect "validation" can be performed using higher-spatial-resolution satellite data [[30]]. Land surface phenology (LSP) is an important research field in terrestrial remote sensing and has become an indispensable approach in global change research, as evidenced by many important scientific findings supported by LSP in recent decades. As such, we organized this Special Issue to cover the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine LSP retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. [Extracted from the article]

Water yield (WY) refers to the difference between precipitation and evapotranspiration (ET), which is vital for available terrestrial water. Climate change has led to significant changes in precipitation and evapotranspiration on a global scale, which will affect the global WY. Nevertheless, how terrestrial WY has changed during the past few decades and which factors dominated the WY changes are not fully understood. In this study, based on climate reanalysis and remote sensing data, the spatial and temporal patterns of terrestrial WY were revisited from 1981 to 2018 globally using an improved Mann-Kendall trend test method with a permutation test. The response patterns of WY to precipitation and ET are also investigated. The results show that the global multi-year mean WY is 297.4 mm/a. Based on the traditional Mann-Kendall trend test, terrestrial WY showed a significant (p < 0.05) increase of 5.72% of the total valid grid cells, while it showed a significant decrease of 7.68% of those. After correction using the calibration method, the significantly increasing and decreasing areas are reduced by 10.52% and 10.58% of them, respectively. After the correction, the confirmed increase and decrease in WY are mainly located in Africa, eastern North America and Siberia, and parts of Asia and Oceania, respectively. The dominant factor for increasing WY is precipitation, while that for decreasing WY was the combined effect of precipitation and evapotranspiration. The achievements of this study are beneficial for improving the understanding of WY in response to hydrological variables in the context of climate change. [ABSTRACT FROM AUTHOR]

Spring greening has been widely observed across the Northern Hemisphere (NH) using a remotely sensed vegetation index (e.g., the normalized difference vegetation index, NDVI). However, there is still a debate on the ecological effects of spring greening on seasonal carbon and water budgets. This study jointly investigated the concurrent and lagged effects of spring greening on carbon gain (gross primary productivity, GPP) and water loss (evapotranspiration, ET) in the summer-active ecosystems at mid and high latitudes of NH using remote sensing and multimodel ensemble data during 1982–2013. The results showed that the collective promotion of spring greening to concurrent GPP and ET is widespread despite variations in magnitude and significance. Both beneficial and adverse lagged effects of spring greening on summer GPP commonly appear with an obvious spatial heterogeneity and difference among climate-plant types. However, the expected significant suppression of spring greening to summer GPP was rarely observed even in the areas where spring ET was significantly promoted by spring greening. Nevertheless, when drought was taken into account, the response patterns of spring water use to spring greening varied to some extent, and the adverse lagged effect of spring greening to summer GPP appeared or strengthened in some regions, especially during the years with dry summer. Given the predicted warming of the climate and more frequent climatic extremes, the adverse effect of spring greening should be given more attention. [ABSTRACT FROM AUTHOR]

Abstract A clear interannual variability in annual production of grasslands (termed AEVI) has been reported over the Tibetan Plateau (TP), but the underlying mechanism has not been fully understood. Here, we explained the interannual variability of AEVI during 2001–2015 by two phenological metrics (the start and end of the growing season, termed SOS and EOS, respectively) and one physiological metric (the maximum capacity of canopy light absorbance, termed MEVI) using MODIS Enhanced Vegetation Index (EVI) data over the TP. The results showed that the interannual variability of AEVI can be well attributed to not only the trends of, but also the sensitivities of AEVI to, the selected biological metrics. On the one hand, the advancing SOS and delaying EOS dominated the study area while both increased and decreased MEVI were observed. On the other hand, the AEVI responded negatively to the SOS and positively to the EOS and MEVI, exhibiting significant variations along the temperature and precipitation gradients. Hence, the current interannual variability of SOS and EOS mainly increased the AEVI; meanwhile, both enhancement and suppression of the interannual variability of MEVI to the AEVI were widespread over the TP. Overall, the interannual variability of MEVI mostly contributed to that of the AEVI, indicating a dominant role of the physiological metric rather than phenological metrics in carbon gain of TP grasslands. The achievements of this study are helpful to understand the underlying biological causes of the interannual variability of grassland production over the TP. Graphical abstract Unlabelled Image Highlights • The advancing SOS and delaying EOS widely increase grassland production on the TP. • Consistent variability of annual max EVI and grassland production is widespread. • The physiological metric plays a dominant role in changes of grassland production. [ABSTRACT FROM AUTHOR]

Ecological geographic regions, also called eco-regions, can be used to divide a remotely sensed image, which is helpful for reducing the complexity of land cover types within eco-regions and for improving the classification accuracy of land cover. In this case study in China, we improved a method of ecological geographic regionalization that is more suitable for remote sensing mapping of regional land cover, and we obtained new eco-regions. The canonical correspondence analysis (CCA) and k-means clustering were adopted in the ecological geographic regionalization using both seasonal remotely-sensed vegetation information and environmental data including climate, elevation and soil features. Our results show that the combination of seasonal vegetation information and the CCA performed well in the selection of the dominant environmental factor of the biogeographic pattern, and it can be used as regionalization indicators of eco-regions. We found that thermal factors are the most important driving forces of the biogeographic pattern in China, which followed by moisture factors. Two global land cover products (MODIS MCD12C1 and GlobCover) were used to assess our eco-regions. The results show that our eco-regions performed better than that of a previous study regarding the complexity of land cover types, such as in the number of types and the proportional area of the major/secondary type. These results indicate that the method of ecological geographic regionalization, which is based on environmental factors associated with seasonal vegetation features, is effective for reducing the regional complexity of land cover. [ABSTRACT FROM AUTHOR]

In this study, we detected the spectrum and vegetation index responses of Masson pine to acid stress using ground-based hyperspectral radiometry and satellite-based multispectral remote sensing. From the hyperspectral detection, we found that the spectral reflectance of stressed Masson pine increased with increase in acidity in the visible region, while an opposite result was found in the near-infrared (NIR) region. The simulated normalized difference vegetation index (NDVI) derived from hyperspectral data of Masson pine presented higher values under weaker acid stress in general. Similar results were observed by satellite-derived NDVI across four acidity gradient transects in subtropical China. Both annual average NDVI and inter-annual NDVI trends of Masson pine forest increased with increase in annual average precipitation acidity (pH), indicating that acid stress would inhibit the growth of Masson pine under certain environmental conditions. However, there are limitations and uncertainties in our present work, and the integration of long-term ground-based and satellite-based observations of vegetation growth and acidity deposition is urgently needed. [ABSTRACT FROM PUBLISHER]

The Jing-Jin-Ji urban group (JJJug), the Yangtze River Delta urban group (YRDug) and the Pearl River Delta urban group (PRDug) are major urban groups of eastern China that play crucial roles in the economy and ecology. With rapid urbanization, demand for land for urban construction has significantly increased, causing direct and indirect losses of forests. At the same time, forest protection and restoration are being promoted in the construction of forested urban groups in response to the 13th Five-Year Plan for forestry development of China in the abovementioned regions. These inevitable contradictory demands for land may inhibit regional sustainable development. However, how forest coverage changed and its ecological impacts in recent decades have rarely been systematically evaluated. To address this issue, this paper quantitatively investigated the spatial and temporal variations in forest coverage and the evolution of landscape patterns using remote sensing data across the JJJug, the YRDug and the PRDug from 1992 to 2015. The results show that forest coverage in the JJJug first increased and then decreased, while that in the YRDug and the PRDug showed a sustained decline during the study period. In the case of land displacement, on the one hand, the three urban groups exhibited a transition from forest to farmland in the forest-farm ecotone at medium and high altitudes. On the other hand, grassland and shrubland were changed into forest mainly in the outer suburbs. Furthermore, in general, the landscape fragmentation in the urban groups significantly increased because of urban expansion. Besides, that of the JJJug exhibited an obvious spatial heterogeneity with a decline in the north while an increase in the south. Overall, unbalanced forest displacement, which could lead to a negative effect on both forest-coverage quantity and landscape quality, should be given more attention in the future development of forested urban groups. It is shows the conceptual illustration of unbalanced forest displacement and its impacts due to urban expansion across the coastal urban groups of eastern China. On the one hand, conversions from forest to farmland or grassland in the forest-farm ecotone were widely observed at medium and high altitudes of the study area. On the other hand, the grasslands and shrublands were converted into forest mainly in the outer suburbs. Moreover, the landscape fragmentation of the urban groups mainly increased due to the direct and indirect effects of urban expansion. Overall, unbalanced forest displacement may lead to a negative effect on both forest-coverage quantity and landscape quality, which should be given close attention. Unlabelled Image • Forest coverage generally decreased across the coastal urban groups of eastern China in recent decades. • Altitude-related forest losses due to the indirect impact of urban expansion were widely observed. • Unbalanced forest displacement led to increasing landscape fragmentation of the urban groups. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a bridge between the atmosphere, vegetation and soil, and its dynamics reflect the energy exchange and transformation between the three. Among SM at different soil profiles, root zone soil moisture (RZSM) plays a significant role in vegetation growth. Therefore, reliable estimation of RZSM at the regional scale is of great importance for drought warning, agricultural yield estimation, forest fire monitoring, etc. Many satellite products provide surface soil moisture (SSM) at the thin top layer of the soil, approximately 2 cm from the surface. However, the acquisition of RZSM at the regional scale is still a tough issue to solve, especially in the semi-arid areas with a lack of in situ observations. Linking the dynamics of SSM and RZSM is promising to solve this issue. The soil moisture analytical relationship (SMAR) model can relate RZSM to SSM based on a simplified soil water balance equation, which is suitable for the simulation of soil moisture mechanisms in semi-arid areas. In this study, the Xiliaohe River Basin is the study area. The SMAR model at the pixels where in situ sites were located is established, and parameters (a, b, sw2, sc1) at these pixels are calibrated by a genetic algorithm (GA). Then the spatial parameters are estimated by the random forest (RF) regression method with the soil, meteorological and vegetation characteristics of the study area as explanatory variables. In addition, the importance of soil, climatic and vegetation characteristics for predicting SMAR parameters is analyzed. Finally, the spatial RZSM in the Xiliaohe River Basin is estimated by the SMAR model at the regional scale with the predicted spatial parameters, and the variation of the regional SMAR model performance is discussed. A comparison of estimated RZSM and in-situ RZSM showed that the SMAR model at the point and regional scales can both meet the RMSE benchmark from NASA of 0.06 cm3·cm−3, indicating that the method this study proposed could effectively estimate RZSM in semi-arid areas based on remotely sensed SSM data. [ABSTRACT FROM AUTHOR]

Nature reserve establishment can lead to conflict with some stakeholders. Zoning management is useful to mitigate against the conflict between human development and nature reserves, and a nature reserve can be divided into three zones: the core zone, buffer zone, and experimental zone. So far, how to monitor and evaluate the effectiveness of zoning management in nature reserves is a problem faced by remote sensing scientists and ecologists. Net primary productivity (NPP) is a key indicator which can be used to monitor and evaluate the effectiveness of zoning management in nature reserves. However, to date there has been no research on the effectiveness of zoning management on NPP, and the estimation of NPP in the Tianmu Mountain Nature Reserve also has not been studied. Based on remote sensing data and in situ measurements, the Carnegie–Ames–Stanford approach (CASA) model was used to estimate NPP in the Tianmu Mountain Nature Reserve during the period 1984–2014. We used the observed NPP to verify the simulated NPP, and the results show that the simulated NPP was consistent with the observed NPP (R2 ≥ 0.85, p ≤ 0.0002, RMSE = 52.62 g C m−2 year−1, where R2 represents coefficient of determination, p represents statistical significance, and RMSE represents root mean square error). This means that the CASA model is suitable for NPP estimation in the Tianmu Mountain Nature Reserve. The results also indicate that NPP showed an increasing trend during the period 1984–2014, and the increase over the whole period was 6.66%. The total of the annual averaged NPP was 3.07 × 1010 g C year−1, while the annual averaged NPP per unit area was 708 g C m−2 year−1. The largest averaged annual NPP per unit appeared in the core zone (720 g C m−2 year−1), followed by the buffer zone (711 g C m−2 year−1), with the experimental zone having the smallest averaged annual NPP per unit (706 g C m−2 year−1). At the p < 0.1 level, there was no region where NPP had decreased significantly in the core zone and buffer zone, and the area of the regions where NPP had decreased significantly in the experimental zone was 8.04 ha. At the p < 0.05 level, there was no area where NPP had decreased significantly in the three zones of the Tianmu Mountain Nature Reserve. The results show that the zoning management on NPP was effective in the Tianmu Mountain Nature Reserve. [ABSTRACT FROM AUTHOR]

Increased nitrogen (N) deposition and land-use and land-cover change (LUCC) have influenced the terrestrial ecosystem carbon budget in China over the past few decades. However, the coupling effects of N deposition and LUCC on the carbon cycle remain unclear. This study first evaluated the effects of LUCC on N deposition based on estimated N deposition data from NO column remote sensing data and the GlobeLand30 LUCC dataset, and then assessed the coupling effects of N deposition and LUCC on carbon budgets in China based on a terrestrial ecosystem process-based model. The results showed that the average rate of increase in N deposition in China was 0.35 Tg N yr (Tg = 10 g), which caused net primary production (NPP) and net ecosystem production (NEP) to rise by 92.2 Tg C yr and 46.9 Tg C yr, respectively. The effects of LUCC reduced N deposition by 0.21 Gg N yr (Gg = 10 g). The land changed from forest to cropland had the greatest rate of increase in N deposition among all types of land-cover change. Changes from cropland to forest slowed the rate of N deposition increase the most. Generally, the change in N deposition resulting from LUCC reduced NPP and NEP by 0.7 and 0.4 Gg C yr, respectively. Compared with the total effects of N deposition on NPP and NEP, N deposition changes caused by LUCC had a limited aggregate effect on the C budget. [ABSTRACT FROM AUTHOR]