Trends In Vegetation Cover Research Articles

Spatiotemporal Variation and Influence Factors of Vegetation Cover in the Yellow River Basin (1982–2021) Based on GIMMS NDVI and MOD13A1

Depicting the spatiotemporal dynamics of vegetation cover in the Yellow River Basin (YRB) and delineating the influences of climate change and human activities on the dynamics have been of significant importance for understanding the surface earth systems in general and also for formulating ecological protection plans of the YRB in particular. This study uses the GIMMS NDVI dataset from 1982 to 2015 and the MOD13A1 NDVI dataset from 2000 to 2021 to explore the spatial and temporal characteristics of vegetation cover in the YRB for the period from 1982 to 2021 with an attempt to reveal the influencing factors. The spatial distribution and temporal variation characteristics of vegetation cover are analyzed by maximum value composite, Theil-Sen median trend analysis, and Mann–Kendall test. Combined with the mean annual temperature and annual precipitation in the same period, influencing factors of vegetation cover in the YRB are discussed by using binary linear regression analysis and residual analysis. Results show that: (1) the multi-year average NDVI values increase from the northwest to the southeast and that the annual mean values of the vegetation covers fluctuate relatively greatly along an increasing trend with a growth rate of 0.019/(10a). Understandably, the monthly mean NDVI values show a single-peak distribution pattern, with August being the peak time (0.4936). (2) 77.35% of the studied areas are characterized by exhibiting an increasing trend of vegetation cover during the study period (i.e., 1982–2021). (3) Vegetation cover of the YRB is affected by the combined effects of climate change and human activities, with human activities being more significant in the observed amelioration of vegetation cover.

Spatio-temporal vegetation cover analysis to determine climate change in Papua New Guinea

PurposeThe climate change and related impacts are experienced around the world. There arise different triggering factors to climate change and impact. The purpose of this study is to figure out how changes in vegetation cover may or may not have an impact to climate change. The research will produce ideas for vegetation preservation and replant.Design/methodology/approachThe investigation was probed for 34 years’ time period starting from the year 1981 to 2015. After testing and checking for serial autocorrelation in the vegetation data series, Mann–Kendal nonparametric statistical evaluation was carried out to investigate vegetation cover trends. Sen’s method was deployed to investigate the magnitude of vegetation cover change in natural differential vegetation index (NDVI) unit per year. Furthermore, the ArcGIS spatial analysis tools were used for the calculation of mean NDVI distribution and also for carrying out the spatial investigation of trends at each specific location within the study region.FindingsThe yearly mean NDVI during the study period was observed to have a decreasing trend. The mean NDVI value ranges between 0.32 and 0.98 NDVI unit, and hence, this means from less or poor vegetated zones to higher or healthier vegetated zones. The mean NDVI value was seen decreasing toward the highlands regions. The NDVI-rainfall correlation was observed to be stronger than the NDVI-temperature correlation. The % area coverage of NDVI-rainfall positive correlation was higher than the negative correlation. The % area coverage of NDVI-temperature negative correlation was higher than the positive correlation within the study region. Rainfall is seen as a highly influencing climatic factor for vegetation growth than the temperature within the study region.Originality/valueThis study in this country is a new approach for climate change monitoring and planning for the survival of the people of Papua New Guinea, especially for the farmer and those who is living in the coastal area.

Green balance in urban areas as an indicator for policy support: a multi-level application

Green spaces are increasingly recognised as key elements in enhancing urban resilience as they provide several ecosystem services. Therefore, their implementation and monitoring in cities are crucial to meet sustainability targets. In this paper, we provide a methodology to compute an indicator that assesses changes in vegetation cover within Urban Green Infrastructure (UGI). Such an indicator is adopted as one of the indicators for reporting on the key area “nature and biodiversity” in the Green City Accord (GCA). In the first section, the key steps to derive the indicator are described and a script, which computes the trends in vegetation cover using Google Earth Engine (GEE), is provided. The second section describes the application of the indicator in a multi-scale, policy-orientated perspective. The analysis has been carried out in 696 European Functional Urban Areas (FUAs), considering changes in vegetation cover inside UGI between 1996 and 2018. Results were analysed for the EU and the United Kingdom. The Municipality of Padua (Italy) is used as a case study to illustrate the results at the local level. Over the last 22 years, a slight upward trend characterised the vegetation growth within UGI in European FUAs. Within core cities and densily built-upcommuting zones, the trend was stable; in non-densely built-up areas, an upward trend was recorded. Vegetation cover in UGI has been relatively stable in European cities. However, a negative balance between abrupt changes in greening and browning has been recorded, affecting most parts of European cities (75% of core cities and 77% of commuting zones in densely built-up areas). This still indicates ongoing land take with no compensation of green spaces that are lost to artificial areas. Focusing on the FUA of Padua, a downward trend was observed in 33.3% and 12.9% of UGI in densely built-up and not-densely built-up areas, respectively. Within the FUA of Padua, most municipalities are characterised by a negative balance between abrupt greening and browning, both in non-densely built-up and densely built-up areas. This approach complements traditional metrics, such as the extent of UGI or tree canopy cover, by providing a valuable measure of condition of urban ecosystems and an instrument to monitor the impact of land take.

Long-Term Monitoring of Vegetation Dynamics in the Rhodopi Mountain Range National Park-Greece

While deforestation is a major environmental issue in the tropics, with thousands of hectares converted to agricultural land every year, in Europe the opposite trend is observed, with land abandonment in mountainous and semi-mountainous areas allowing the afforestation of former agricultural and pastoral land. This trend allows semi-natural ecosystems to recover after a prolonged period of exploitation and often over-exploitation, but it may also lead to significant loss of landscape heterogeneity with potentially detrimental effects on biodiversity. The current study aims to monitor changes in the vegetation coverage across a period of 35 years (between 1984 and 2019) in the Rhodopi Mountains range National Park in northern Greece. A time series of LANDSAT TM (16 images), LANDSAT ETM + (1 image) and LANDSAT 8 OLI/TIRS (4 images) were employed. One data transformation method was applied (TCT), and five vegetation indices (NDVI, NDWI, SAVI, EVI2 and BSI) were calculated to capture the land cover transition during the study period. The obtained results and all used indices suggest that over the study period there was a continuous trend of vegetation cover increasing, with open areas decreasing. The observed trend was further confirmed using Object Oriented Image Analysis on two pairs of images sensed in 1984 and 2019, respectively. The results suggest that almost 22.000 ha of open habitats have been lost to broadleaved and conifer woodlands, while the former also appear to be advancing into conifer-covered areas. This trend has led to significant loss of landscape heterogeneity and to a broadleaf-dominated landscape. The results are discussed in relation to their driving forces, the potential implications on biodiversity and the risk of wildfires in the near future.

Recovery of plains rough fescue grasslands on reclaimed well sites

Plains rough fescue (Festuca hallii), once dominant in grasslands of the Northern Great Plains, has been reduced to remnants mainly through agricultural and energy sector development. This study assessed the impacts of oil and gas well site disturbances on plains rough fescue grassland to predict successional trends following disturbance. We examined trends in vegetation cover, richness, diversity, and community composition for two construction techniques (topsoil stripping, minimum disturbance), three revegetation methods (agronomic seed mix, native seed mix, natural recovery), and two reclamation scenarios (reclaimed within < 10 yrs; reclaimed within > 10 yrs) relative to adjacent undisturbed prairie (reference sites) over 28 years in 33 grassland sites. Reclamation success was more closely related to methods of construction and revegetation than years since reclamation. Species richness, diversity, both native and non-native species cover, and species composition were similar between undisturbed prairie and areas subject to minimum disturbance and natural recovery. In contrast, undisturbed prairie differed from areas with topsoil stripping and seeding to either agronomic or native species. Plant community composition on minimum disturbance sites with natural recovery was returning to a predisturbed plains rough fescue community within 10 years after reclamation. Impacts of construction method that involved intensive soil handling and seeding with native or non-native seed mixes were disruptive to recovery of fescue grassland. We therefore recommend retaining grassland sod intact through minimum disturbance and utilizing natural recovery as the best option for successful reclamation of native rough fescue grassland after well site disturbance.

Spatiotemporal variation and influencing factors of vegetation dynamics based on Geodetector: A case study of the northwestern Yunnan Plateau, China

Exploring vegetation dynamics and their responses to different natural and anthropogenic factors is crucial for understanding ecosystem processes in the context of global change. As an important ecological security barrier in Southwest China, the northwestern Yunnan Plateau (NYP) provides a variety of ecosystem services. In this study, we investigated the spatiotemporal variation in vegetation cover and quantitatively analysed the relative contributions of potential influencing factors and their interactions to vegetation change on the NYP from 2005 to 2015 using a novel spatial analysis method, the Geodetector model (GDM). Additionally, the most suitable types or ranges of the main influencing factors that were conducive to vegetation growth were identified. Our results showed that the trend of vegetation cover on the NYP was generally negative, with a rate of − 0.0031 yr−1 during the 11-year study period, and was spatially heterogeneous. Areas with obviously decreasing trends were almost twice as large as those with increasing trends (27.49% and 14.37%, respectively) and were mainly concentrated in southeastern and northern Dali as well as the central part of Diqing. Vegetation dynamics were primarily driven by soil type (24.8%), elevation (18.6%), geomorphic type (16.1%), and vegetation type (13.2%), and anthropogenic factors played a weak role in vegetation change, with a contribution of less than 10%, demonstrating that the influences of natural factors on vegetation change were greater than those of anthropogenic factors. Moreover, the interaction of pairwise factors played a more important role in affecting vegetation dynamics than did each factor individually. These findings are helpful for better understanding the complex mechanisms of vegetation change and providing scientific suggestions for the prevention of vegetation degradation in fragile ecosystems.

Dynamic Trends of 100-year Anthropogenic Vegetation Cover under the Influence of the White Sea – Baltic Canal

The process of economic use of the White Sea region landscapes has historically impacted the vegetation cover trends. The reason lies in the intensity of development adjusted for time factor. We have provided a variety of events related with nature resource management of the Karelian Pomorye landscapes involved in iron production, salt making, sawmills construction, shipbuilding, building of railway and the White Sea – Baltic Canal (WBC), marshland reclamation, housing development and wood logging. These are the types of forest resources which did impact tree layer depletion. We have pre-conditioned to use a geobotanical map of the Shueretsko-Sorokskaya Forest Dacha, Kem Uyezd, the Karelian Autonomous Soviet Socialist Republic, which was compiled under the direction of K. F. Malyarevsky in 1925. An idea leaped into our mind to trace long-term influence made by the anthropogenic factor on differentiation, dynamics and stability processes experienced by swamp and forest geosystems. The research problem is the study of the duration and limitation of development, chronological researching role in landscape transformations. The original features of the study conducted to develop historical and geoecological line of geography.

Interannual variation in riparian vegetation cover and its relationship with river flow under a high level of human intervention: an example from the Yongding River Basin.

Riparian vegetation cover is significantly affected by a river's hydrological conditions. Especially in arid and semiarid areas, low flow will degrade riparian vegetation, and recent, intensive human activities in the Yongding River Basin have caused a sharp decrease in river flow. We analyzed interannual change in riparian vegetation, river flow effects, and land use on vegetation coverage using the 40years (1977-2016) of remote sensing images and river flow, combined with 38years (1980-2018) of land use data. The normalized difference vegetation index (NDVI) was used to determine vegetation cover in five different categories: extremely low, low, medium, high, and extremely high based on the pixel dichotomy model. The weighted average was calculated to obtain vegetation cover trends. We show that riparian vegetation cover from four rivers increased. Compared with 1977, in 2016, combined high and extremely high vegetation covers at the Dongyang, Yang, Sanggan, and Yongding Rivers increased by 20.3%, 26.7%, 50.0%, and 39.2%, respectively. High (R = -0.976, P < 0.01) and extremely high (R = -0.762, P < 0.05) vegetation covers are negatively correlated with flow in the Yongding River. The high vegetation cover of the Sanggan River riparian zone is negatively correlated with river flow (R = -0.683, P < 0.05). In the Dongyang and Sanggan Rivers, land use analysis in the riparian zone showed that change in cultivated land, grassland, and forest were significantly correlated with high and extremely high vegetation cover. The abundant cultivated land and restoration activities are likely responsible for the increase of riparian vegetation cover as river flows decline.

Spatial and temporal variations of vegetation coverage in the middle section of Yellow River Basin based on terrain gradient:Taking Yan'an City as an example.

Vegetation restoration is an important requirement for ecological protection and high-quality development in the Yellow River Basin. In-depth understanding the temporal and spatial differentiation of vegetation has important practical significance. With the four Landsat TM/OLI remote sensing images as the data source, the pixel binary model was used to estimate vegetation coverage. The transfer matrix, geological information map, and the center of gravity migration model were used to analyze the temporal and spatial variations of vegetation coverage in Yan'an City in the middle of the Yellow River Basin from 1988 to 2018. The spatial variation of vegetation cover to elevation and slope was explored using terrain distribution index combined with terrain data. The results showed that vegetation coverage in Yan'an was low in the north region and high in the south region. The vegetation coverage increased significantly due to policy changes. From 1988 to 2018, the vegetation change pattern in Yan'an was dominated by continuous improvement and stability. Vegetation coverage increased in about 50% of the area. 83% of the study area with high vegetation coverage remained stable. At each elevation and slope level, the advantage of high vegetation cove-rage increased with time. At each slope level, vegetation cover increased with slope. The transition direction of vegetation cover of different levels in Yan'an was basically consistent with the overall spatial change trend of vegetation cover, with the overall shift being from north to west. The vegetation construction in Yan'an has achieved remarkable results, though the vegetation coverage in the north still needs to be improved. Optimizing vegetation types and structures is an important direction for future vegetation construction.

An NDVI-based Analysis of the Temporal and Spatial Characteristics of Vegetation Coverage in Guizhou Province

The MOD13A1 data with 500 m resolution from 2001 to 2018 was used to calculate the NDVI change trend of each pixel. Linear trend analysis and correlation analysis were used to analyze the spatiotemporal variation characteristics of vegetation coverage in Guizhou Province. Combining the precipitation use efficiency of vegetation from 2001 to 2018 with the land cover data of 2010 and 2017, the NDVI characteristics of different land cover types were studied. The results are as follows. First, from 2001 to 2018, the vegetation cover area in Guizhou Province has shown an overall increasing trend, and the ecological environment has been significantly improved, especially in Bijie and Liupanshui areas. Second, overall, the change trend of vegetation cover area shows that the improvement area in Guizhou Province is larger than the degradation area, and degradation concentrates in the urban expansion area. Third, the overall efficiency of precipitation utilization by vegetation in Guizhou Province is not consistent with the change trend of vegetation cover. Fourth, the NDVI of Guizhou Province showed a good correlation with rainfall and air temperature in the same period. However, vegetation growth did not lag behind the change of air temperature, and the lag period of rainfall was 1 month. In other words, the sensitivity of vegetation growth to air temperature was higher than that of rainfall. Finally, the NDVI values of different land cover types in the vegetation growing season have different characteristics: NDVI(woodland)>NDVI(arable land)>NDVI(grassland)>NDVI(construction land)>NDVI (water body).

Dynamic Response of Phragmites australis and Suaeda salsa to Climate Change in the Liaohe Delta Wetland

Because of its unique geographical location and ecological function, the Liaohe Delta Wetland is important in maintaining regional ecological balance and security. Monitoring and evaluating changes in the wetland are therefore of great importance. We used medium- and high-resolution satellite data, meteorological station data, and site measurement data to analyze changes in the area and spatial distribution of Phragmites australis and Suaeda salsa in the Liaohe Delta Wetland from 1998 to 2017, as well as their growth response to the climate change. The results showed that during 1998–2017, the areas of both P. australis and S. salsa wetlands alternated through periods of decreasing, increasing, and then decreasing trends. The annual change in the area and spatial distribution range of S. salsa fluctuated more than that of P. australis. The annual variation of normalized difference vegetation index (NDVI) in P. australis wetland showed an upward trend from 1998 to 2017. The area of P. australis cover that was improved, unchanged, and decreased accounted for 81.8%, 12.3%, and 5.9%, respectively, of the total area; evaporation and wind speed were the main meteorological factors affecting the NDVI; and contribution rates of the climate change and human activities to the NDVI were 73.2% and 26.8%, respectively. The area with vegetation cover being mainly S. salsa that was improved, unchanged, and decreased accounted for 63.3%, 18.3%, and 18.4%, respectively, of the total area; and no meteorological factors significantly affected the NDVI of S. salsa in the region. The interaction between vegetation growth and meteorological factors may help to explain the increasing trend in vegetation cover. The improvement in wetland vegetation also led to carbon sequestration and an increase in sequestration capacity.

Assessing vegetation restoration potential under different land uses and climatic classes in northeast Iran

This study examines the trends in vegetation cover using the Growing Season NDVI (GSN) time series in moderate spatial resolution (250 m) over Khorasan Razavi province, in northeast Iran, during the period 2004–2015. The province is largely desert, with extra-arid, arid, and semi-arid de Martonne climate zones dominating, while rangelands, shrublands and deserts cover most areas, making it an ideal territory for monitoring vegetation trends and implement future restoration projects. Most parts of the province and land-cover classes show no trends in vegetation cover, but large decreasing trends occur in areas covered by sand dunes, previously reforested lands and clay pit areas. Trends in various land-cover types are also examined as functions of the climatic class and the Terrain Niche index (TNI), which is characteristic of the topography, revealing large decreasing trends in the extra-arid climatic zone. In addition, most of the areas exhibit Hurst exponent values around 0.5, implying stochastic time series without any consistency and a likelihood of random vegetation and land cover changes in the future. This study also aims to determine likely future vegetation status and the most favourable areas for restoration projects through analysis of two indexes (Future Restoration Dispersal Index, FRDI and Future Uncertainty Dispersal Index, FUDI). The results show that reforestation, sand dunes and clay pits areas are the most favourable for implementing restoration projects, while the spatial distribution of the potential restoration classes reveals that the southern and northeastern parts of Khorasan Razavi province are the most favourable areas for establishing environmental restoration activities in order to avoid further degradation of ecosystems.

Spatial and temporal variation Trend Analysis of vegetation cover in Urban agglomeration of Pearl River Delta from 2000 to 2015

Based on MODIS NDVI remote sensing data, the methods of regression analysis, CV stability analysis, Hurst exponent analysis are used to invert the spatio-temporal variation trend of vegetation cover in the Pearl River Delta region from 2000 to 2015. On this basis, the future change trend of vegetation cover was predicted. The results indicate that (1) the vegetation coverage in the Pearl River Delta was on a rising trend in general from 2000 to 2015 (0.029/10 years). (2). The vegetation change in The Pearl River Delta region was mainly significantly improved (39.73%), and significantly degraded and slightly degraded areas accounted for only 13.22%, which were staggered with significantly improved regions. (3) Degree of vegetation cover fluctuation in cities and surrounding areas has significant spatial consistency with degraded areas of vegetation cover, which indicates that there is a certain correlation between the change of vegetation cover around the city and human activities. (4) Combined with the analysis of future and past trends, the condition that vegetation cover firstly degrades and then improves will occur. While vegetation degradation may occur in non-urban concentrated areas without good ecological planning. The research results will be helpful to understand the trend and spatial distribution of vegetation in the Pearl River Delta region.

Spatiotemporal analysis of trends in vegetation change across an artificial desert oasis, Northwest China, 1975–2010

Vegetation change has become a worldwide environmental concern. Artificial desert oases in the Northwest China are among the most ecologically sensitive environments and are also a repository of ecosystem services by relying on vegetation system. Over the last four decades, land transformation related to anthropogenic activities and climate change is among the main drivers of changing vegetation cover in Northwest China. In an oasis where field-based research is challenging due to diverse landscape and heterogenous relief, quantifying changes in vegetation system using remote sensing can provide available information regarding trends in vegetation cover and its linkages with driving forces. This study aimed to explore spatiotemporal dynamics of vegetation change through examining time series normalized difference vegetation index (NDVI) over the period 1975–2010 in an artificial desert oasis in Northwest China. A time series imagery derived from Landsat product was analyzed for the presence of trends in vegetation change. Using the nonparametric Sen’s and Mann-Kendall methods, over 13.56% of oasis land surfaces were found to exhibit significant increasing trends, and almost 6.07% of oasis land surfaces were found to exhibit significant decreasing trends. The 80.38% spatial distribution of vegetation showed no change trends significantly. The relationships between the detected NDVI trends and land cover also were evaluated by using spatial mapping method. Results showed that the spatiotemporal pattern of vegetation change was consistent with the climate-related change of vegetation growing conditions and implementation of ecosystem management during the study period.

Quantifying the impacts of lithology on vegetation restoration using a random forest model in a karst trough valley, China

Karst regions in southwest China are characterized by vulnerable ecological environment. Knowledge on the driving factors of vegetation cover change could provide valuable information for ecological restoration management. However, quantitative identification of the key drivers for the vegetation restoration remains challenging in karst trough valleys. In this study, we used normalized difference vegetation index (NDVI) time series (2000–2016), Theil-Sen median analysis, Mann-Kendall trend test, and Hurst exponent to analyze the vegetation cover trends in a karst trough valley. The performance of multiple linear regression (MLR), generalized additive models (GAM), support vector machine (SVM), and random forest (RF) in accounting for vegetation cover change were compared. The results showed that vegetation cover trends for increasing, stable and decreasing accounted for 71.44%, 28.16% and 0.40% of the study area, respectively. Lithology had a significant effect on spatial patterns of temporal change and future sustainability in NDVI (p < .01). RF performed much better than MLR, GAM and SVM in accounting for vegetation cover change. The RF model had much lower fitting error indices (MAE = 1.46*10−3, RMSE = 1.92*10−3) and higher R2 (0.65) than MLR, GAM and SVM models. Thus, RF model was applied to identify impacts of driving factors on vegetation cover change quantitatively. Precipitation change, lithology and elevation were key factors for vegetation cover change. The vegetation restoration and reconstruction projects should pay more attention to the region where limestone and above-900 m elevation dominate, due to relatively slow vegetation growth in these regions. The new understandings obtained in this study enrich our knowledge of the effects of lithology and topography on the vegetation cover change and are necessary to guide sustainable projects of ecological recovery in karst trough valleys.

Long-term NDVI and recent vegetation cover profiles of major offshore island nesting sites of sea turtles in Saudi waters of the northern Arabian Gulf

Abstract Vegetation is an important ecological component of offshore islands in the Arabian Gulf (AG), which maintains long-term resilience of these islands. This is achieved by influencing sediment retention and moisture acquisition via condensation during periods of high humidity and by providing a variety of microhabitats for island fauna. The resilience of offshore islands’ ecosystems in the Saudi waters is important because they host the largest number of nesting hawksbill and green turtles in the AG. This study defines the characteristics and the long-term trends in vegetation cover of the offshore islands used by sea turtles as nesting grounds in the northern AG. To establish a ground-validated baseline for vegetation profiles, a 50 m × 50 m grid system is developed on Karan and Jana islands (Is.) with photo-quadrats taken at each grid intersection. The 1,317 and 444 photo-quadrats, for Karan and Jana Is., respectively, were analyzed for maximum plant height and percent cover of living (green) plants, dead plants, and bare sand. Landsat 7 and 8 satellite top-of-atmosphere reflectance images were used to calculate the Normalized Difference Vegetation Index (NDVI) from 1999 through 2018 to analyze the long-term vegetation profiles of the islands. Monthly rainfall data from five meteorological stations along the Eastern Province of Saudi Arabia and Oceanic Nino Index (ONI) are presented to provide a context of the long-term NDVI time series variability. The ground-validated vegetation profiles provided baseline data during the onset of summer in 2017 and revealed differences in maximum plant height and the extent of living, dead vegetation and sand cover on Jana Is. (28.3 cm, 19.9%, 63.3%, and 16.8%) and Karan Is. (21.7 cm, 20.6%, 48.7%, and 30.7%), respectively. The NDVI data for both islands are grouped into three periods, namely: 2001–2007 - high winter, low summer; 2008–2013 – low winter, low summer; 2014–2018 – irregular high/low winter, low summer. The long-term trend showed a slightly decreasing NDVI when compared in the context of the high NDVI measured for the two islands during the early 2000 s, particularly during the winter time. An extended reduction in winter NDVI was recorded for six years from 2008 to 2013, which coincided with reduced rainfall in the region and prolonged La Nina. Five extreme dips in winter NDVI values coincided with strong (2000, 2008, and 2011) and moderate (2012 and 2018) La Nina events. Long-term vegetation profiles of the offshore islands seemed to be tightly coupled with long-term rainfall patterns.

Effects of Climatic Variability and Non-Climatic Factors on Mopane Worms’ (Gonimbrasia Belina) Distribution and Livelihood Options in North Central Namibia

Mopane worms (Gonimbrasia belina) are an important source of food and income for households in Northern Namibia. However, their access and availability in many areas have declined, mainly due to climate change and human activities. This has affected many households&amp;rsquo; livelihoods, making them vulnerable to poverty and food insecurity. With these factors in mind, this study sought to identify the extent to which the availability and distribution of mopane worms are influenced in the Tsandi and Okahao constituencies. The study used structured questionnaires to collect information from households in the study area, to interview key informants, and to carry out group discussions. A total of 70 households and 6 key informants were interviewed, along with 4 focus group discussions that were carried out to elicit perceptions, and to obtain views on the availability of mopane worms, and possible causes of the decline in the study area. Data were analysed using descriptive statistics, while GIS was used to determine trends in vegetation cover, temperature and rainfall in the area. The rainfall trend indicates variability, with a generally declining trend. A slight increase in temperature has been observed too. Vegetation showed a browning trend in the study area, indicating declining habitats of mopane worms. The results have indicated that more women depend on mopane worms for survival, mainly as a source of income. Thus the decline in their availability greatly affects their food sources and their income diversification opportunities. Trading was found to be an important form of employment for the unemployed rural people, but with the potential to generate higher income levels that can improve their livelihoods. Moreover, despite the climatic factors, human activities seemed to indicate a greater influence on the availability of mopane worms, due to activities such as overharvesting, land clearing for agriculture and household use/fencing. Thus, there is a greater need to control the harvesting of mopane worms and to control tree cutting activities in order to reduce the impacts of climatic and non-climatic factors on their availability.

A Statistical Approach to Detect Land Cover Changes in Mediterranean Ecosystems Using Multi-Temporal Landsat Data: The Case Study of Pianosa Island, Italy

The normalized difference vegetation index (NDVI) is commonly used to detect spatiotemporal changes of vegetation cover. This study modeled the spatiotemporal changes of land cover on Pianosa Island, Italy, in the period 1999–2015, using the multi-temporal Landsat images. Since the end of the 1990s, the natural vegetation has been re-colonizing an area of abandoned agricultural land and the island is undergoing a process of re-naturalization in harsh (drought and hot) environmental conditions. Hence, it is an ideal test site to monitor the effects of anthropogenic and climatic stressors on vegetation dynamics under Mediterranean climate. In this work, we proposed a new statistical approach based on a pixel-by-pixel analysis of multi-temporal Landsat images. Mean (µ) and standard deviation (σ) values of the NDVI images taken in 2015 were used for the determination of the pixel thresholds (µ ± 3σ). The evaluation of land cover change was carried out by comparing the µ value of a single NDVI pixel for 2015 with the same pixel of different years of the study period. The results indicate that surface reflectance (SR) Landsat images are more suitable in detecting the vegetation dynamics on the island than the top of atmosphere (TOA) ones and highlight an increasing trend of vegetation cover on Pianosa Island, mainly during the early seven years following the land abandonment in all the main land cover classes: abandoned crops and pastures, Mediterranean macchia, and woodland. However, the abandoned agricultural and pasture areas showed a higher increase in the vegetation cover and a shift in the shape of the normalized frequency distribution of the SR NDVI data during the study period, suggesting that a colonization process from other vegetation classes is occurring (i.e., Mediterranean macchia and trees are colonizing the abandoned land, partly replacing herbaceous species). Our data highlight that the statistical approach applied in this study is suitable for detecting vegetation cover changes associated with anthropogenic and climatic drivers in a typical Mediterranean environment and could be proposed as a new methodological approach in several other land monitoring studies.

Dynamic Response to Climate Change by Phragmites australis and Suaeda salsa in Liaohe Delta Wetland

Because of its unique geographical location and its ecological function, the Liaohe Delta wetland is important in maintaining regional ecological balance and security. Monitoring and evaluating change in the wetland are therefore of great importance. We used medium- and high-resolution satellite data, meteorological station data and site measurement data to analyze changes in the area and spatial distribution of Phragmites australis and Suaeda salsa in the Liaohe Delta wetland from 1998 to 2017, as well as their growth response to climate change. The results showed that during the period 1998–2017, the area of both P. australis and S. salsa wetlands alternated through periods of decreasing, then increasing and then decreasing trends. The annual change in area and spatial distribution range of S. salsa fluctuated more than that of P. australis. The annual variation of normalized difference vegetation index (NDVI) in P. australis wetland showed an upward trend from 1998 to 2017. The area of P. australis cover that was improved, unchanged or decreased accounted for 81.8%, 12.3%, and 5.9%, respectively, of the total area. Evaporation and wind speed were the main meteorological factors affecting NDVI. The contribution rates of climate change and human activities to NDVI were 73.2% and 26.8%, respectively. The area where vegetation cover was mainly S. salsa and that was improved, unchanged or decreased accounted for 63.3%, 18.3%, and 18.4%, respectively, of the total area. No meteorological factors significantly affected NDVI in the region. The interaction between vegetation growth and meteorological factors may help to explain the increasing trend in vegetation cover. The improvement in wetland vegetation also led to carbon sequestration and an increase in sequestration capacity.

Determination of vegetation cover trends based on the calculation of the normalized vegetation index on the example of Petrykivskyi district of Dnipropetrovsk region

The technique of analyzing using Spatial Analyst ArcGIS Desktop tools was developed to determine the nature of vegetation changes based on a normalized vegetation index. Geoinformation analysis was carried out on the example of Petrykivskyi district of Dnipropetrovsk region for the period 2016-2018. The applied technique allowed to correctly interpret the water surface, artificial materials, as well as land with and without vegetation. Ranking by such categories made it possible to identify areas with sparse vegetation (farmland, pastures) and dense vegetation (tree plantations, forest areas), and to estimate their area. Spatial Analyst tools constructed vegetation maps according to the normalized vegetation index and calculated changes in vegetation density during 2016-2018.