Variation In Vegetation Cover Research Articles

Spatial–Temporal Variations and the Driving Factors of Vegetation Coverage in the Loess Hilly and Gully Region of China

To determine the spatial–temporal variations and the factors leading to vegetation recovery in the loess hilly and gully region of China, this study analyzed a two-decade trend in the variation of vegetation cover based on normalized difference vegetation index (NDVI) data from 1998 to 2019 using the Sen + MK test and Hurst index and determined the driving factors using the Geodetector model. The vegetation index in the area was high in the southeast and low in the northwest, with an overall increasing rate of 0.0108/year. The areas with significant improvement in vegetation cover accounted for 95.14%, and the areas with persistent change accounted for 37.36%. Annual precipitation is the most crucial factor driving the NDVI change, and potential evapotranspiration, relative humidity, elevation, land use type, and vegetation type can also explain local variations. The effect of compound factors is significantly greater than that of a single factor. The most effective factors are annual precipitation, potential evapotranspiration, relative humidity and elevation, which varied between 559.4–698.6 mm, 530.6–744.6 mm, 59%–62%, and 2006–2717 m, respectively. The land use, vegetation, and soil types suitable for healthy vegetation growth are forest, coniferous forest, and eluvial soil.

Impacts of Climate Change and Human Activities on NDVI Change in Eastern Coastal Areas of China

Based on the datasets of normalized difference vegetation index (NDVI), temperature, precipitation, and solar radiation and the methods of trend, partial correlation, and residual analyses, this study explored the spatiotemporal variation in NDVI and its response to climate change from 1982 to 2019 in eastern coastal areas of China. Then, the effects of climate change and non-climatic factors (e.g., human activities) on NDVI trends were analyzed. The results showed that:① the NDVI trend varied greatly in different regions, stages, and seasons. On average, the growing season NDVI increased faster during 1982-2000 (stage I) than that during 2001-2019 (stage Ⅱ) in the study area. Moreover, NDVI in spring showed a more rapid increase than that in other seasons in both stages. ② For a given stage, the relationships between NDVI and each climatic factor varied in different seasons. For a given season, the major climatic factors associated with NDVI change were different between the two stages. The relationships between NDVI and each climatic factor showed great spatial differences in the study period. In general, the increase in growing season NDVI in the study area from 1982 to 2019 was closely related to the rapid warming. The increase in precipitation and solar radiation in stage Ⅱ also played a positive role. ③ In the past 38 years, climate change played a greater role in the change in growing season NDVI than non-climatic factors, including human activities. Whereas non-climatic factors dominated the increase in growing season NDVI during stage I, climate change played a major role during stage Ⅱ. We suggest that more attention should be paid to the impacts of various factors on vegetation cover variation during different periods to promote the understanding of terrestrial ecosystem changes.

Impacts of climate change and human activities on vegetation coverage variation in mountainous and hilly areas in Central South of Shandong Province based on tree-ring.

It is of great significance to understand the characteristics and influencing factors of vegetation coverage variation in the warm temperate zone. As a typical region of the warm temperate zone in eastern China, the mountainous and hilly region in central-south Shandong Province has fragile ecological environment and soil erosion problem. Studying on vegetation dynamics and its influencing factors in this region will help to better understand the relationship between climate change and vegetation cover change in the warm temperate zone of eastern China, and the influence of human activities on vegetation cover dynamics. Based on dendrochronology, a standard tree-ring width chronology was established in the mountainous and hilly region of central-south Shandong Province, and the vegetation coverage from 1905 to 2020 was reconstructed to reveal the dynamic change characteristics of vegetation cover in this region. Secondly, the influence of climate factors and human activities on the dynamic change of vegetation cover was discussed through correlation analysis and residual analysis. In the reconstructed sequence, 23 years had high vegetation coverage and 15 years had low vegetation coverage. After low-pass filtering, the vegetation coverage of 1911-1913, 1945-1951, 1958-1962, 1994-1996, and 2007-2011 was relatively high, while the vegetation coverage of 1925-1927, 1936-1942, 2001-2003, and 2019-2020 was relatively low. Although precipitation determined the variation of vegetation coverage in this study area, the impacts of human activities on the change of vegetation coverage in the past decades cannot be ignored. With the development of social economy and the acceleration of urbanization, the vegetation coverage declined. Since the beginning of the 21st century, ecological projects such as Grain-for-Green have increased the vegetation coverage.

Spatiotemporal Variations in Fractional Vegetation Cover and Their Responses to Climatic Changes on the Qinghai–Tibet Plateau

The alpine vegetation of the Qinghai–Tibet Plateau (QTP) is extremely vulnerable and sensitive to climatic fluctuations, making it an ideal area to study the potential impacts of climate on vegetation dynamics. Fractional vegetation cover (FVC) is regarded as one of the key indicators in monitoring semiarid and arid ecosystems due to its sensitive responses to vegetation behavior under climatic changes. Although many studies have analyzed the responses of vegetation on the QTP to climatic change, limited information is available on the influence of climatic variables on FVC changes in this area. In this study, we used satellite images and meteorological data to investigate the spatiotemporal variations of FVC during the growing season (FVCGS) during 1998–2018 and evaluated the responses to changes in climatic variables. Results showed that FVCGS displayed an overall fluctuating rise of 0.01/10 a (p < 0.01) over the study period. The FVCGS variation was spatially heterogeneous, with a general trend of greening in the northern and browning in the southern QTP. Obvious correlations were observed between the average FVC, average temperature, and total precipitation of the growing season, with precipitation being the primary controlling factor for vegetation growth. Some regions in the northwestern and northeastern QTP showed greening trends due to the positive influence of precipitation. Some areas in the southwestern QTP experienced browning trends due to water shortages caused, probably, by the weakening of the Indian monsoon. Browning in the southeastern parts was likely caused by drought and permafrost degradation resulting from high temperature. The inconsistent trend of vegetation change on the QTP is relatively high considering the continuous warming and changing atmospheric circulation patterns. FVC in most regions of the QTP has 0–1 month temporal responses to precipitation and temperature. Moreover, the one-month lagged effects of temperature and precipitation had a greater influence on steppe and desert vegetation than on other vegetation types. This research provides new perspectives for understanding the QTP vegetation response to climatic changes and a basis for making reasonable vegetation conservation and management policies.

Temporal and spatial characteristics of vegetation coverage and their influencing factors in the Sugan Lake wetland on the northern margin of the Qinghai–Tibet Plateau

Fractional vegetation cover (FVC) is an important indicator of the development or reversal of salt marsh due to its absence in arid desert areas. Many studies have emphasized the differences in factors that affect fractional vegetation cover (FVC) in different temporal and spatial scales. However, few studies have reported on the temporal and spatial variations in vegetation coverage and their response to climate and also on the hydrological environment in inland salt marsh wetlands. Accordingly, based on a wetland community survey, different types of data, such as meteorological data, hydrological data, and Landsat remote sensing image data, recorded during the period from 1990 to 2020 were collected. The characteristics of the spatial and temporal distribution of vegetation coverage in the Sugan Lake wetland over the past 30 years were analyzed using a binary pixel model. Furthermore, a quantitative analysis on the response of vegetation coverage to hydrological and meteorological factors was undertaken. The results of the present study showed that the dimidiate pixel model had a high simulation accuracy in retrieving the vegetation coverage in inland salt marsh wetlands. The vegetation coverage of the Sugan Lake wetland increased with each year from 1990 to 2020, and its annual average was 19.34%. The spatial distribution of vegetation coverage was patchy and decreased from the center to the edge of the wetland. Within the same period, the vegetation coverage showed an increasing trend in Quan-shui and He-hong areas and a decreasing trend in the Shan-hong area. Vegetation coverage was mainly affected by various factors, such as precipitation, lake area, surface runoff, groundwater depth, and residential density, respectively. It was significantly positively correlated with precipitation (R2 = 0.56, P < 0.01), lake area (R2 = 0.50, P < 0.01), air temperature (R2 = 0.46, P < 0.01), and river system density (R2 = 0.52, P < 0.01) and negatively correlated with groundwater depth (R2 =-0.57, P < 0.01) and residential density (R2 = −0.38, P < 0.05). Implicit in these findings are complex mechanisms of change in vegetation coverage that help prevent the degradation of vegetation in fragile ecosystems.

Accelerated Soil Erosion and Sedimentation Associated with Agricultural Activity in Crater-Lake Catchments of Western Uganda

Intensifying agricultural activity associated with rapid population growth in rural western Uganda exerts immense pressure on natural resources, threatening not only soil fertility in the uplands but also water quality of the region’s many small crater lakes. To assess the relative risk of excess sediment and nutrient loading to individual lakes due to (inter) rill erosion within the catchments, we used the revised universal soil loss equation (RUSLE) and sediment delivery distributed model (SEDD) to estimate soil loss and sedimentation in 75 crater-lake catchments with diverse types and intensities of land use, including 17 catchments situated partly or entirely in national parks. We found that variation in potential soil loss (Ap) among all studied catchments was strongly related to differences in mean slope within each catchment. We also found substantial seasonal variation in vegetation cover, and thus, estimated actual soil loss (Am), on both cultivated land and protected savanna grassland, whereas the vegetation cover of protected semi-deciduous tropical forest was seasonally stable. Lacking detailed field data to validate model output, we used the ratio between estimated actual soil loss (Am) and potential soil loss (Ap) to evaluate the relative influences of land-use intensity and type, as well as the impact of protective measures. Our results showed that due to their characteristically steep slopes (21% on average), all crater catchments were highly susceptible to soil loss, and because most of them were small (203 ha on average), a large portion of the eroded material was transported to and deposited in the lakes. Given the strong dependence of the local population on these crater lakes as source of water and fish protein, and on the surrounding land for crop production, increased effort by environmental planners and managers is required to safeguard or restore the long-term availability of these natural resources. Avoiding bare soil conditions by restoring natural vegetation or employing agricultural techniques that provide high vegetation cover throughout the year are likely to result in considerable improvements.

Comparative Study on Remote Sensing Methods for Forest Height Mapping in Complex Mountainous Environments

Forest canopy height is one of the critical parameters for carbon sink estimation. Although spaceborne lidar data can obtain relatively high precision canopy height on discrete light spots, to obtain continuous canopy height, the integration of optical remote sensing image data is required to achieve “from discrete to continuous” extrapolation based on different prediction models (parametric model and non-parametric model). This study focuses on the Shangri-La area and seeks to assess the practical applicability of two predictive models under complex mountainous conditions, using a combination of active and passive remote sensing data from ICESat-2 and Sentinel-2. The research aims to enhance our understanding of the effectiveness of these models in addressing the unique challenges presented by mountainous terrain, including rugged topography, variable vegetation cover, and extreme weather conditions. Through this work, we hope to contribute to the development of improved geospatial prediction algorithms for mountainous regions worldwide. The results show the following: (1) the fitting effect of the selected parametric model (empirical function regression) is poor in the area of Quercus acutissima and Pinus yunnanensis; (2) evaluation of the importance of each explanatory variable in the non-parametric model (random forest regression) shows that topographic and meteorological factors play a dominant role in canopy height inversion; (3) when random forest regression is applied to the inversion of canopy height, there is often a problem of error accumulation, which is of particular concern to the Quercus acutissima and Pinus yunnanensis; (4) the random forest regression with the optimal features has relatively higher precision by comparing the inversion accuracy of canopy height data of the empirical function regression, random forest regression with all features, and random forest regression with the optimal features in the study area, i.e., R2 (coefficient of determination) = 0.865 and RMSE (root mean square error) = 3.184 m. In contrast, the poor estimation results reflected by the empirical function regression, mainly resulting from the lack of consideration of topographic and meteorological factors, are not applicable to the inversion of canopy height under complex topographic conditions.

Drought Assessment across Erbil Using Satellite Products

In this article, meteorological and agricultural droughts across the Erbil province, Iraq, were assessed using remote sensing data and satellite products. To this end, the long-term (2000–2022) Standardized Precipitation Evapotranspiration index (SPEI) at 1- and 3-month accumulation periods (SPEI-1 and SPEI-3) as well as the Normalized Difference Vegetation Index (NDVI) across Erbil were utilized. While the former was retrieved from the global SPEI data repository, the latter was derived from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The spatiotemporal variations in the SPEI indices indicated that two to nine extreme drought events occurred in the province with an increasing northward pattern. An increasing trend in the long-term NDVI series was also detected, having more diversity in vegetation coverage in the northern part of the province. The relationship between the SPEI and MODIS-NDVI was found to be positive but insignificant. Thus, we concluded that short-term meteorological droughts were not the only reason for the agricultural droughts in Erbil. Furthermore, the climate characteristics related to the cumulative water balance over a previous season is not an important trigger for the spatial variation in vegetation coverage across the province.

The effect of post-wildfire management practices on vegetation recovery: Insights from the Sapadere fire, Antalya, Türkiye

Post-wildfire management actions mainly targeting the removal of salvage logs and burned trees is a common but controversial practice. Although it aims to regain some of the natural and economic value of a forest, it also requires disturbing burned areas, which may have some negative consequences affecting, for instance, the carbon cycle, soil erosion, and vegetation cover. Observations from different geographic settings contribute to this scientific debate, and yet, the spatiotemporal evolution of the post-fire road network developed as part of fire management practices and its influence on vegetation recovery has been rarely examined. Specifically, we still lack observations from Türkiye, though wildfires are a common event. This research examined the evolution of the vegetation cover in relation to post-fire road constructions and the resultant debris materials in areas affected by the 2017 Sapadere fire in Antalya, Türkiye. We used multi-sensor, multi-temporal optical satellite data and monitored the variation in both vegetation cover and road network from the pre-to post-fire periods between 2014 and 2021. Our results showed that fire management practices almost doubled the road network in the post-fire period, from 487 km to 900 km. Overall, 7% of the burned area was affected by these practices. As a result, vegetation cover in those areas shows only ∼50% recovery, whereas undisturbed areas exhibit ∼100% recovery 5 years after the event. Notably, such spatiotemporal analysis carried out for different burned areas would provide a better insight into the most suitable post-fire management practices. Our findings, in particular, show that the current practices need to be revisited as they cause a delay in vegetation recovery.

A dataset of 250m-resolution NDVI of spatio-temporal variations of vegetation in the growing season on the Mongolian Plateau (2001–2021)

The Mongolian Plateau has a great impact on the ecological security in northern China. Vegetation has an important indicator effect on climate change and ecological environment. The spatial-temporal pattern and trend of vegetation are important indicators for evaluating regional ecological conditions. Based on MOD13Q1 NDVI data, we used R language to call Google Earth Engine service for monthly maximum synthesis in this study. And we then used R language terra package to complete the annual mean synthesis of the growing season, coefficient of variation calculation, Theil-Sen median trend analysis, Mann-Kendall test and Hurst index calculation, so as to form a dataset of 250m-resolution NDVI of spatio-temporal variations of vegetation in the growing season on the Mongolian Plateau (2001–2021). The dataset contains the spatial and temporal variation patterns and trend characteristics of vegetation on the Mongolian Plateau. Through data sharing, it can provide data support for scientific understanding of temporal and spatial variation of vegetation cover on the Mongolian Plateau.

Identification of Vegetation Coverage Variation and Quantitative the Impact of Environmental Factors on Its Spatial Distribution in the Pisha Sandstone Area

Over the past few decades, global vegetation cover has obviously changed, particularly in the Loess Plateau, due to vegetation restoration projects in China. This study focuses on the Pisha Sandstone area (PSA) and uses various statistical analysis methods to study the spatiotemporal changes in vegetation coverage (VEC) at different time scales. The effects of topographical and climatic factors on VEC were also quantitatively evaluated using the GeoDetector in the spatial distribution. The results of the study confirm that, on an annual scale, the area with a significant increase in VEC has reached 63.89% (p < 0.05). Change points were diagnosed to have occurred mainly between 2002 and 2012 at different time scales, with the percentage of significant change points in VEC accounting for more than 20% from April to October (p < 0.05). Temporal and spatial changes in precipitation mainly caused VEC changes. In 45.35% of the region, precipitation was significantly and positively correlated with VEC at an annual scale (p < 0.05). Moreover, VEC was most conducive to growth and increase at 1050–1500 m above sea level and 0–21° slope, respectively. In most areas, there was an enhanced interaction relationship between various factors on VEC. Converting farmland to forests in suitable areas, selecting appropriate tree species, and improving soil is conducive to ecological restoration in the PSA in the future.

Response of soil erosion to vegetation restoration and terracing on the Loess Plateau

Soil erosion exhibited significant decrease due to the implementation of considerable soil and water conservation practices on the Loess Plateau, and further induced less sediment discharged into the Yellow River. However, the influences of these practices on soil erosion have not been comprehensively investigated over large-scale regions. This study analyzed spatiotemporal variation of vegetation cover, and identified the distribution of terraces by using Google Earth remote sensing images in the whole Loess Plateau. The USLE model (Universal Soil Loss Equation) was applied to estimate responses of soil erosion to vegetation restoration and terraces. The annual regional-averaged NDVI increased from of 0.46 in 2000 to 0.63 in 2018, suggesting significant vegetation improvement due to afforestation. We detected 4.73 × 104 km2 of terraces by 2018, which covered approximately 1.5% of the whole Loess Plateau. The terraces were mainly distributed in the upstream of the Weihe River, Fenhe, Zuli, Jinghe, and Taohe River basins. The validated soil erosion model showed that vegetation changes caused a remarkable reduction of 51.2% soil erosion from 2000 to 2018 across the Loess Plateau. A scenario modelling with terraces reduced 19.4% of soil erosion, indicating their significant effects on soil erosion controlling. This study could give a useful reference to assess soil erosion changes response to vegetation restoration and terrace at a large scale. The results can be used to optimize the spatial layout of the measures for soil erosion control in the Loess Plateau in the future.

Vegetation Cover Variation in Dry Valleys of Southwest China: The Role of Precipitation

Many ecological restoration projects have been carried out in Southwest China; however, changes in vegetation cover in the dry valleys of Southwest China have rarely been reported. With their unique characteristics of high temperatures and low humidity, these dry valleys have considerably lower vegetation cover than their neighboring areas, making them the main sediment sources of rivers in Southwest China. Thus, it is imperative to understand changes in vegetation cover in China’s dry valleys, as well as the effects of changes in precipitation, since water deficit is the dominant cause of obstructed plant growth. In this study, changes in fractional vegetation cover (FVC) in dry valleys in the period 2000 to 2020 were analyzed based on MODIS-NDVI data, and the effects of precipitation were also analyzed. Our results indicated that: (1) the long-term mean annual FVC values in the dry–hot valleys (DHVs), dry–warm valleys (DWVs), and dry–temperate valleys (DTVs) were 0.426, 0.504, and 0.446, respectively; (2) significant decreasing trends in FVC were mainly found in DHVs and DWVs that were distributed in the southwestern part of the dry valley region (DVR), which was mainly due to the decrease in precipitation; and (3) significant increasing trends were reported in DTVs of the Min River and the Baishui River, which was probably due to the increase in precipitation. By analyzing the temporal trends of FVC in dry valleys, this study highlighted the effects of precipitation on the dynamics of FVC and demonstrated that anthropogenic activities such as urbanization, land use changes, and hydro-power project construction may also have considerable effects on FVC in dry valleys. Overall, this study not only provides insights that might inform further detailed studies on the dynamics and mechanisms of vegetation cover, but could also provide valuable guidance for ecological restoration management in the dry valley region.

Spatio-Temporal Variation and Climatic Driving Factors of Vegetation Coverage in the Yellow River Basin from 2001 to 2020 Based on kNDVI

The Yellow River Basin (YRB) is a fundamental ecological barrier in China and is one of the regions where the ecological environment is relatively fragile. Studying the spatio-temporal variations in vegetation coverage in the YRB and their driving factors through a long-time-series vegetation dataset is of great significance to eco-environmental construction and sustainable development in the YRB. In this study, we sought to characterize the spatio-temporal variation in vegetation coverage and its climatic driving factors in the YRB from 2001 to 2020 by constructing a new kernel normalized difference vegetation index (kNDVI) dataset based on MOD13 A1 V6 data from the Google Earth Engine (GEE) platform. Using Theil–Sen median trend analysis, the Mann–Kendall test, and the Hurst exponent, we investigated the spatio-temporal variation characteristics and future development trends of the vegetation coverage. The climatic driving factors of vegetation coverage in the YRB were obtained via partial correlation analysis and complex correlation analysis of the associations between kNDVI and both temperature and precipitation. The results reveal the following: The spatial distribution pattern of kNDVI in the YRB showed that vegetation coverage was high in the southeast and low in the northwest. Vegetation coverage fluctuated from 2001 to 2020, with a main significant trend of increasing growth at a rate of 0.0995/5a. The response of vegetation to climatic factors was strong in the YRB, with a stronger response to precipitation than to temperature. Additionally, the main driving factors of vegetation coverage in the YRB were found to be non-climatic factors, which were mainly distributed in Henan, southern Shaanxi, Shanxi, western Inner Mongolia, Ningxia, and eastern Gansu. The areas driven by climatic factors were mainly distributed in northern Shaanxi, Shandong, Qinghai, western Gansu, northeastern Inner Mongolia, and Sichuan. Our findings have implications for ecosystem restoration and sustainable development in the YRB.

Fractional vegetation cover ratio estimated from radiative transfer modeling outperforms spectral indices to assess fire severity in several Mediterranean plant communities

The obtention of wall-to-wall fire severity estimates through reliable remote sensing-based techniques that align with management needs is a critical factor in post-fire decision-making processes. In this paper, we novelty proposed a multi-date change detection framework based on the variation in fractional vegetation cover (FCOVER), with enough ecological sense and physical basis to be generalizable across different plant communities and burned landscapes with varying environmental conditions. This framework meets the definition of fire severity operationally used in the field as a biophysical indicator when fire effects on the understory and overstory layers are linked. The FCOVER was retrieved from Sentinel-2 surface reflectance scenes by inverting PROSAIL-D radiative transfer model (RTM) simulations using the random forest regression algorithm. FCOVER retrievals were validated in the field using burned and unburned control plots. We computed the FCOVERr metric as the ratio of post-fire to pre-fire FCOVER. We tested the relationship of the FCOVERr and the most common bi-temporal spectral indices in the literature, i.e. the differenced Normalized Burn Ratio (dNBR), the Relative dNBR (RdNBR) and the Relativized Burn Ratio (RBR), with the Composite Burn Index (CBI) measured in field plots for validation purposes in two case-study wildfires in the western Mediterranean Basin. We also calculated the transferability of FCOVERr and the spectral indices between different plant communities within each site, as well as between sites. The predictive errors of pre and post-fire FCOVER retrievals were found to be low (RMSE ≈ 10%) for the two study sites. Overall, the FCOVERr metric provided more accurate CBI estimations (R2 = 0.87 ± 0.04) than spectral indices (R2 = 0.71 ± 0.13). The CBI was linearly related with the FCOVERr metric for both sites, whereas the type of relationship with spectral indices was not consistent, which translated into better transferability performance of the FCOVERr metric (nRMSE = 14.27% ± 3.75%) than that of the spectral indices (nRMSE = 21.97% ± 8.09%), not only between different Mediterranean plant communities within sites, but also between the two sites. Spectral indices underestimated moderate to high fire severity to a greater extent than FCOVERr in the CBI field plots, and misclassified fire severity in several areas with patchiness fire effects identified in the field. The FCOVERr product proposed in this study may be a sound choice for the operational identification of priority areas for post-fire management.

Effects of climate change and anthropogenic activity on the vegetation greening in the Liaohe River Basin of northeastern China

Elucidating the response mechanism of variation in vegetation trend to determinant is of great value to environmental resource management, particularly significant in the ecologically fragile area. The Liaohe River Basin (LRB) is a key part of eco-security in China, which has experienced apparent climatic variations and intensified human activities in recent decades. Yet, it still remains not clear about drivers in shaping the spatio-temporal patterns of vegetation growth. Here, the normalized difference vegetation index (NDVI) was utilized to investigate the spatio-temporal variation of vegetation coverage from 2000 to 2019. Then, we incorporated partial derivatives analysis to conduct attribution analyses of vegetation greening in light of the meteorological data. The prime findings are as follows: (1) The vegetation coverage in the LRB presented a growing state in the recent 20 years at a rate of 0.0031/a, with significant spatial and temporal heterogeneity due to its slope; (2) The attribution results showed that the average contribution of precipitation, temperature, and solar radiation to the NDVI changes in the LRB was 0.00205/a, 0.00008/a, and −0.00028/a, respectively. (3) The climatic change played the most dominant role in influencing vegetation activities as a result of the relative contributions of 59.68% of NDVI changes (40.32% contributed by anthropogenic activities); (4) LULC dynamics were characterized by an increase in forest land and large-scale ecological afforestation projects, which increase vegetation coverage. Conversely, urbanization adversely affected vegetation variations. Understanding the findings of this study is expected to offer further scientific support and practical implications for monitoring the local vegetation status.

Spatiotemporal variation of vegetation cover in mining areas of Dexing City, China

Dexing City is an important mining city in China, abounding in copper ore, lead ore, zinc ore, and other metal resources, and there are two large open-pit mines in its territory, Dexing Copper Mine and Yinshan Mine. The two open-pit mines have been expanding their mining production scale since 2005, with frequent mining activities; and the expansion of the pits and the discharge of solid waste will undoubtedly increase the land use and cause the destruction of vegetation. Therefore, we plan to visualize the change in vegetation cover in Dexing City from 2005 to 2020 and the expansion of the two open-pit mines by calculating changes of the Fractional Vegetation Cover (FVC) in the mining area using remote sensing technology. In this study, we calculated the FVC of Dexing City in 2005, 2010, 2015 and 2020 using data from NASA Landsat Database via ENVI image analysis software, plotted the FVC reclassified maps via ArcGIS, and conducted field investigations in the mining areas of Dexing City. In this way, we can visualize the spatial and temporal changes of vegetation cover in Dexing City from 2005 to 2020, and appreciate the situation of mining expansion and its solid waste discharge in Dexing City. The results of this study showed that the vegetation cover of Dexing City remained stable from 2005 to 2020, as the expansion of mining scale and mine pits was accompanied by active environmental management and land reclamation, setting a positive example for other mining cities.

Mapping groundwater dependent ecosystem potential in a semi-arid environment using a remote sensing-based multiple-lines-of-evidence approach

ABSTRACT Groundwater dependent ecosystems (GDEs) are vulnerable to groundwater regime changes. However, their protection is often hampered by challenges in their identification. Within is presented a remote sensing-based GDE potential mapping approach based on the persistency of relevant vegetation parameters during prolonged dry periods as an indicator of potential ‘consistency’ of water supply (e.g. groundwater). The study uses a novel approach to characterising persistency for selected vegetation parameters based on a normalised difference measure and an adaptation of the coefficient of variation statistic. Aggregation of parameters was facilitated through the analytic hierarchy process providing a structured weighting approach to minimise parameter bias. The approach is demonstrated in the semi-arid Flinders Ranges of South Australia where new groundwater resources are being sought to support local domestic and industry needs. Variations in GDE potential were mapped to better target areas where exploration of groundwater should be avoided. Mapping results indicated a high-level of agreement of 77% with an independent springs dataset, along with an 87% agreement with areas coinciding with known phreatophyte species and depths to groundwater. The index-based mapping approach has potential applicability across landscapes, as it normalises for variations in vegetation cover, minimises technical overheads, and employs continental-wide remote sensing data-products.

The comprehensive evaluation of how water level fluctuation and temperature change affect vegetation cover variations at a lake of ecological importance (Poyang Lake), China

Wetland vegetation is crucial to ecosystem services provided by lake wetlands worldwide. While environmental elements like hydrological factors and temperature have a wide impact on vegetation cover changes in lake wetlands, their effects on vegetation cover changes haven’t been well separated and evaluated in the context of local temperature change worldwide. Here, we developed a novel indicator (Rtaw) to decouple and evaluate the effects of temperature change and the change of a typical hydrological factor, namely water level, on vegetation cover changes in the Poyang Lake wetland (PLW) from 2003 to 2014. Rtaw compares the vegetation cover changes in the PLW caused by water level fluctuation to those caused by temperature change. The impact of each environmental factor on wetland vegetation changes was measured by the change in area of vegetation-covered PLW (Ap). Our results demonstrate that the PLW experiences the most significant vegetation cover decrease and increase in June and September, respectively. Annual Ap generally increases from 2003 to 2014. The vegetation cover-changed PLW generally extends from the Poyang Lake's center to its coast. Furthermore, while the water level fluctuation-induced vegetation cover variations in the PLW are typically 0.6 times stronger than that caused by temperature change, the latter is 0.17 ∼ 2.99 times stronger than the former around every three years and when seasons change. This is caused by the extreme water level, temperature, and their changes with particular values. Meanwhile, the anomalous impact of temperature change occurs in the PLW’s vast region. Overall, the applied Rtaw in the PLW revealed the periodic control of temperature change on vegetation cover changes which are widely thought to be dominated by hydrological variations. Therefore, our work could contribute to a more comprehensive assessment of the vegetation cover changes in lake wetlands. This also implies that the effects of extreme temperature events on vegetation cover changes in lake wetlands should be paid enough attention.

Long-Term Variability of Vegetation Cover and Its Driving Factors and Effects over the Zuli River Basin in Northwest China

Vegetation information is a critical factor in regional environment management under climate change. In this study, a typical arid and semi-arid watershed on the Loess Plateau, the Zu Li River Basin (ZRB), was selected to study the long-term changes in vegetation cover and its drivers and impacts. Unlike existing normalized vegetation index (NDVI) products, which have coarse spatial resolution and short time horizons, this study used the 30 m Landsat dataset analyzed in the Google Earth Engine (GEE) to generate high-resolution and long-term NDVI data, which are the most ideal for monitoring vegetation dynamics using long-time-series data products. The results showed that the annual mean maximum NDVI (normalized vegetation index) in the ZRB increased during 1987–2021, with a significant (p < 0.05) increasing trend in most areas. Upstream vegetation cover increased more than midstream and downstream, but the increase was smaller. Precipitation in the ZRB area was significantly (p < 0.05) correlated with the NDVI series, except for the upstream pass area, where human activities played an important role. NDVI was significantly (p < 0.05) negatively correlated with runoff coefficient and sand content, indicating that vegetation cover was an important reason for the decrease in runoff coefficient and sand content.