Positive Normalized Difference Vegetation Index Trends Research Articles

Анализ восстановления растительного покрова в пределах Шуруповских карьеров на основе данных дистанционного зондирования

The article presents an analysis of restoration processes within two quarries located in the northwest of the Shurupovsky Khutor in the Frolovsky district of the Volgograd region. The described methods of revegetation analysis within the quarry-dump complexes included images from the USGS Earth Explorer portal (US Geological Survey). The Landsat-5 TM satellite images were used in July 2007, Landsat 8 OLI_TIRS was used in July 2015, and Landsat 9 OLI_TIRS described the status in July 2022. Using the ArcGIS geoinformation system 10.3.1, we considered multispectral images of different times and calculated the Normalized Difference Vegetation Index (NDVI) for 2007, 2015, and 2022. As a second index, we calculated the NDVI trend for 2007–2015 and 2015–2022. Based on the results of interpretation, the assessment of changes in the vegetation cover of quarry-dump complexes was carried out. As a result, it was revealed that the vegetation cover of quarries demonstrated different restoration pathways despite their close territorial location. By 2022, the NDVI of the eastern quarry did not exceed 0.2, and the NDVI of the western quarry increased to 0.5. However, in general, there is a positive NDVI trend in the territories of both quarries. Resulting from the data obtained, NDVI maps and NDVI trend maps for the studied quarries were prepared. Tables for calculating changes in the areas of flooding and vegetation cover of the Shurupov quarries for 2007, 2015, and 2022 were created in MS Excel.

The imprint of urbanization on vegetation in the ecologically fragile area: A case study from China’s Loess Plateau

Rapid urbanization significantly affects vegetation growth in urban environments. Responses of vegetation to urbanization at high spatial resolutions and long temporal ranges are still unclear, especially in ecologically fragile areas. Here, we explored urbanization impacts on vegetation across China’s Loess Plateau (CLP) from 2000 to 2020 at a spatial resolution of 30 m. Urbanization and annual maximum Normalized Difference Vegetation Index (NDVI) in urban agglomerations, provincial capital cities, also the whole CLP experienced a rapid increase over this period; the annual maximum NDVI (NDVImax) in urban areas decreased before 2011 but increased afterward to reach its maximum value in 2018, and in non-urban areas, a significant increase was found between 2000 and 2020. NDVImax with significant reduction areas were mostly distributed in the urbanization area. A total of 97.56%, 53.66%, 80.49%, and 100% of all cities’ urban core, urbanization, urban, and non-urban areas, respectively, indicated an increase in NDVImax during 2000–2020. For 97.56% (40/41) of the cities in the CLP, the increases in NDVImax in the non-urban areas were stronger than the NDVImax increases detected in the urban areas of these cities. In general, the urban areas of most cities (29/41) in the CLP had positive NDVI trends of greater than 50%. The NDVImax generally decreased with increasing urbanization development intensity (UDI) in 2000 and 2020 in the CLP along with five urban agglomerations. These findings have important implications for understanding urbanization impacts on vegetation, urbanization management, and development in ecologically fragile areas.

Prevalence and drivers of abrupt vegetation shifts in global drylands

The constant provision of plant productivity is integral to supporting the liability of ecosystems and human wellbeing in global drylands. Drylands are paradigmatic examples of systems prone to experiencing abrupt changes in their functioning. Indeed, space-for-time substitution approaches suggest that abrupt changes in plant productivity are widespread, but this evidence is less clear using observational time series or experimental data at a large scale. Studying the prevalence and, most importantly, the unknown drivers of abrupt (rather than gradual) dynamical patterns in drylands may help to unveil hotspots of current and future dynamical instabilities in drylands. Using a 20-y global satellite-derived temporal assessment of dryland Normalized Difference Vegetation Index (NDVI), we show that 50% of all dryland ecosystems exhibiting gains or losses of NDVI are characterized by abrupt positive/negative temporal dynamics. We further show that abrupt changes are more common among negative than positive NDVI trends and can be found in global regions suffering recent droughts, particularly around critical aridity thresholds. Positive abrupt dynamics are found most in ecosystems with low seasonal variability or high aridity. Our work unveils the high importance of climate variability on triggering abrupt shifts in vegetation and it provides missing evidence of increasing abruptness in systems intensively managed by humans, with low soil organic carbon contents, or around specific aridity thresholds. These results highlight that abrupt changes in dryland dynamics are very common, especially for productivity losses, pinpoint global hotspots of dryland vulnerability, and identify drivers that could be targeted for effective dryland management.

Expanding vegetated areas by human activities and strengthening vegetation growth concurrently explain the greening of Seoul

Many studies have reported that urbanization leads to a decrease in the normalized difference vegetation index (NDVI) due to the expansion of impervious cover. Some studies, however, have reported positive NDVI trends in urban areas due to warming and CO2 fertilization effects, as well as the creation of green space. Thus, we examined spatial and temporal variations of the growing season maximum NDVI in a megacity, Seoul, which has rapidly urbanized over the past decades, by analyzing a 32-year time series (1987 – 2018) of Landsat satellite images in Google Earth Engine. Continuous change detection and classification and random forest algorithms were integrated to classify Seoul land cover types annually. We found an overall increasing NDVI trend at the city scale (0.002 yr−1). Significant NDVI trends were found for approximately 46 % of Seoul, with greening and browning trends accounting for 39 % and 7 %, respectively. Greening pixels appeared mainly on impervious (23 % with a significant NDVI trend), deciduous (10 %), and evergreen (3 %) land cover as of 2018. Stable impervious, deciduous, and evergreen land cover pixels showed a greening trend over the 32 years (0.002 yr−1), which stemmed from the planting of trees in areas with impervious cover, such as streets and residential areas, and vegetation growth in forest areas. Disturbed area pixels showed fluctuating NDVI values, but there were more greening pixels (20 %) than browning pixels (5 %). Our findings indicate that a detailed knowledge of land use and land cover changes is required to understand NDVI trends in urban areas.

NDVI-based ecological dynamics of forest vegetation and its relationship to climate change in Romania during 1987–2018

Forests have become increasingly stressed by climate change, including in Romania over recent decades, but their response to climate dynamics has not yet been analysed in this country. This study aims to investigate, for the first time, recent ecological changes in forests across Romania, in relation to climate dynamics that affected the country from 1987 to 2018. To this end, countrywide remote sensing (Landsat) data were processed for forest boundaries over the 32 years, in order to compute annual (summer season data) Normalized Difference Vegetation Index (NDVI) datasets, which were subsequently investigated as trends using the Mann-Kendall test and Sen's slope estimator. Simultaneously, various climatic data (temperature, precipitation and reference evapotranspiration) were processed through interpolation techniques and via the same two statistical tools, and were subsequently used for exploring the impact of climate change on Romanian forestlands after 1987. The results highlighted general greening (increasing NDVI) trends of forests nationally (65% of all NDVI changes, which total over 30.000 km2 across Romania), which were dominated by widespread positive NDVI trends detected in the Carpathians region of Romania. This general ecological dynamic suggests a possible enhancement in vegetation productivity in the country’s high-altitude areas. Contrasting browning (decreasing NDVI) trends were found for 35% of Romanian forestlands marked by NDVI changes, especially apparent in the Extra-Carpathians (lowland) region, which indicates that in these cases forests were degraded or devitalized. However, the statistical significance of both greening and browning trends is limited across the country. The analysis of climatic trends and of correlations between annual NDVI and climate data indicated that recent warming throughout Carpathians may be an important driving force of forest greening in temperature-limited mountain regions. This finding is supported by an at least moderate intensity of air temperature – NDVI relationships (r correlation coefficient values of ∼50%, the highest of all eco-climatic relationships analysed), generally detected throughout mountain environments. At the same time, it seems that evapotranspiration increase accounted at least in part for forest browning in lowland areas, while the impact of precipitation in forest ecological dynamics remains unclear. All these findings can be useful for a better forest management under the future climate change conditions in Romania.

Article Title Variations in Growing Season NDVI and Its Sensitivity to Climate Change Responses to Green Development in Mountainous Areas

The Normalized Difference Vegetation Index (NDVI) is sensitive to changes in surface vegetation cover. Research into how climate change impacts surface vegetation cover is essential to manage ecological systems and promote green development. The Western Henan Mountains, located in the transitional zone between the northern subtropical and warm temperate zones of China, is an ideal location to study the impacts of climate change on surface vegetation cover. Combining a digital elevation model (DEM) with temperature and precipitation data; and MODIS-NDVI imagery (2000∼2017) for the Western Henan Mountains, this study explores variations in the growing season NDVI and its response to climate change. Results show that there are significant changes with fluctuations in NDVI values from 2000 to 2017. NDVI increased at a growth rate of 0.027 per decade (p < 0.05) overall, indicating vegetation conditions have gradually improved. Although the NDVI value showed an overall increasing trend, 19.12% of the areas showed a decreasing trend, interspersing and intersecting spatially, showing significant spatial differences. NDVI increased initially, but then decreased as a function of elevation, which was shown to be proportional to slope and independent of aspect. Variables including elevation and slope gradient are shown to provide high explanation of NDVI variability, whilst temperature is shown to have a more significant impact on NDVI than precipitation. However, vegetation responses to temperature and precipitation covaried with both slope and aspect. Positive NDVI trends were strongest at low elevations (i.e., <1,100 masl), which we attribute to vegetation restoration activities. Lower NDVI values characterized gentle slopes (<5°), whilst higher values were, in contrast, associated with steeper slopes (5∼10°). This study highlights the complex mechanisms and their relations governing vegetation response to climate change and should form an instructive basis for both future modeling studies investigating the response of vegetation to future global warming.

Evaluating the Relationships of Inter-Annual Farmland Vegetation Dynamics with Biodiversity Using Multi-Spatial and Multi-Temporal Remote Sensing Data

Agricultural landscapes are highly dynamic ecosystems, but the effects of temporal farmland vegetation dynamics on species diversity have not been widely studied. In 93 sample farm landscapes in eastern Ontario, Canada, biodiversity data for seven taxa were collected in 2011 and 2012, prior to the initiation of this study. The goal of this study was to determine if trends and variability in vegetation productivity detected in these sample landscapes using long-term archived moderate and coarse resolution remote sensing time series data are related to the measured biodiversity. Mid-summer Moderate Resolution Imaging Spectroradiometer (MODIS) (2000–2011) and Landsat 5 (1985–2011) Normalized Difference Vegetation Index (NDVI) data were used with the Thiel–Sen slope and Contextual Mann–Kendall trend analysis to identify pixels showing significant trends. NDVI temporal metrics included 1) the percentage of pixels in each landscape with a significant negative or positive trend, and 2) the temporal coefficient of variation (CV) of both the mean and spatial CV of landscape NDVI. Larger areas of significant positive NDVI trends were found in the sample landscapes than negative trends, the former being associated with agricultural intensification or crop changes and the latter with smaller areas of natural vegetation removal. Landsat better-detected changes in individual fields or small areas of natural vegetation due to its much smaller pixel size. In addition, the longer Landsat time series showed a change in the NDVI trend from positive (1985–2000) to negative or a leveling off (2000–2011) for many pixels. In biodiversity modeling, the Landsat temporal CV of NDVI was negatively correlated with 2011–2012 plant and beetle diversity, while plant biodiversity was positively correlated with the percentage of pixels in a sample landscape showing a significantly positive NDVI trend. No significant relationships were found using the MODIS data. This study shows that temporal trends and variability in farmland vegetation density derived from Landsat data are related to biodiversity for certain taxa and that such relationships should be considered along with the more commonly studied spatial landscape attributes in evaluating landscape-level impacts of farming on biodiversity.

Assessment of the Spatial and Temporal Variability of Arid Ecosystems in the Republic of Buryatia

Climate change and anthropogenic activity in the Republic of Buryatia aggravate the processes of desertification and land degradation. The territory of Buryatia was zoned according to the aridity index based on ENVIREM climate data with a high spatial resolution. Long-term changes in the vegetation cover in arid and humid zones are quantitatively assessed based on a combined study of the time series of the normalized-difference vegetation index (NDVI) with the Advanced Very High Radiation Radiometer (AVHRR), meteorological series of the NCEP/NCAR Reanalysis data set, and field studies. Maps of the spatial distribution of NDVI linear trends and precipitation for 1982–2015 (with the differentiation of the wet (1982–1999) and dry periods (2000–2015)) have been constructed. During the wet period, positive NDVI trends are observed for almost the entire republic, while the dry period is characterized by a significant increase in negative trends of the vegetation index. A positive correlation between the Selyaninov hydrothermal coefficient and NDVI is observed for intermountain steppe basins, while it is negative for forest landscapes. The dynamics of the NDVI for steppe vegetation is more dependent on precipitation, while the dynamics of the NDVI for forests is more significantly correlated with temperature. Reforestation, postpyrogenic succession, the bushing of fallow lands, and other factors determine the growth in the NDVI. Negative NDVI trends are characteristic of steppe ecosystems with low precipitation and forest ecosystems exposed to felling and fires.

Recent NDVI Trends in Mainland Spain: Land-Cover and Phytoclimatic-Type Implications

The temporal evolution of vegetation is one of the best indicators of climate change, and many earth system models are dependent on an accurate understanding of this process. However, the effect of climate change is expected to vary from one land-cover type to another, due to the change in vegetation and environmental conditions. Therefore, it is pertinent to understand the effect of climate change by land-cover type to understand the regions that are most vulnerable to climate change. Hence, in this study we analyzed the temporal statistical trends (2001–2016) of the MODIS13Q1 normalized difference vegetation index (NDVI) to explore whether there are differences, by land-cover class and phytoclimatic type, in mainland Spain and the Balearic Islands. We found 7.6% significant negative NDVI trends and 11.8% significant positive NDVI trends. Spatial patterns showed a non-random distribution. The Atlantic biogeographical region showed an unexpected 21% significant negative NDVI trends, and the Alpine region showed only 3.1% significant negative NDVI trends. We also found statistical differences between NDVI trends by land cover and phytoclimatic type. Variance explained by these variables was up to 35%. Positive trends were explained, above all, by land occupations, and negative trends were explained by phytoclimates. Warmer phytoclimatic classes of every general type and forest, as well as some agriculture land covers, showed negative trends.

Monitoring NDVI Inter-Annual Behavior in Mountain Areas of Mainland Spain (2001–2016)

Currently, there exists growing evidence that warming is amplified with elevation resulting in rapid changes in temperature, humidity and water in mountainous areas. The latter might result in considerable damage to forest and agricultural land cover, affecting all the ecosystem services and the socio-economic development that these mountain areas provide. The Mediterranean mountains, moreover, which host a high diversity of natural species, are more vulnerable to global change than other European ecosystems. The protected areas of the mountain ranges of peninsular Spain could help preserve natural resources and landscapes, as well as promote scientific research and the sustainable development of local populations. The temporal statistical trends (2001–2016) of the MODIS13Q1 Normalized Difference Vegetation Index (NDVI) interannual dynamics are analyzed to explore whether the NDVI trends are found uniformly within the mountain ranges of mainland Spain (altitude > 1000 m), as well as in the protected or non-protected mountain areas. Second, to determine if there exists a statistical association between finding an NDVI trend and the specific mountain ranges, protected or unprotected areas are studied. Third, a possible association between cover types in pure pixels using CORINE (Co-ordination of Information on the Environment) land cover cartography is studied and land cover changes between 2000 and 2006 and between 2006 and 2012 are calculated for each mountainous area. Higher areas are observed to have more positive NDVI trends than negative in mountain areas located in mainland Spain during the 2001–2016 period. The growing of vegetation, therefore, was greater than its decrease in the study area. Moreover, differences in the size of the area between growth and depletion of vegetation patterns along the different mountains are found. Notably, more negatives than expected are found, and fewer positives are found than anticipated in the mountains, such as the Cordillera Cantábrica (C.Cant.) or Montes de Murcia y Alicante (M.M.A). Quite the reverse happened in Pirineos (Pir.) and Montes de Cádiz y Málaga (M.C.M.), among others. The statistical association between the trends found and the land cover types is also observed. The differences observed can be explained since the mountain ranges in this study are defined by climate, land cover, human usage and, to a small degree, by land cover changes, but further detailed research is needed to get in-depth detailed conclusions. Conversely, it is found that, in protected mountain areas, a lower NDVI pixels trend than expected (>20%) occurs, whereas it is less than anticipated in unprotected mountain areas. This could be caused by management and the land cover type.

Does grazing cause land degradation? Evidence from the sandy Ferlo in Northern Senegal

AbstractIt has been widely asserted that a high grazing pressure has led to a reduction in vegetation production at decadal time scales, implying land degradation, in African drylands, and in the Sahel in particular. We test this hypothesis by analyzing spatiotemporal patterns of vegetation production in the northwestern Ferlo in Senegal. Normalized difference vegetation index (NDVI) patterns, here used to represent vegetation production, were determined on the basis of Earth observation MODIS and PROBA‐V data. Furthermore, woody cover was assessed by very high spatial resolution (VHR) imagery. Because livestock is concentrated around deep wells in the dry season for watering, while for management they concentrate daily around pastoral family settlements or camps all year round, we studied the dependence of NDVI on distance from deep wells and camps. Locations of wells and camps were determined by visual inspection of VHR images. We found that ‘inverse grazing gradients,’ defined as decreasing NDVI/production with increasing distance, dominated both around wells and camps. Further, we found neither decrease nor increase in woody cover with distance to wells. Both positive and negative trends in wet season NDVI over the period 2000–2016 were identified within the study area, yet temporal trends were predominantly positive in proximity to deep wells. Around pastoral camps, positive NDVI trends were generally elevated relative to the regional average. The results question the validity of claims that high grazing pressure causes land degradation at the landscape scale, yet they show that grazing does lead to substantial spatial redistribution of vegetation production.

Vegetation Indices Do Not Capture Forest Cover Variation in Upland Siberian Larch Forests

Boreal forests are changing in response to climate, with potentially important feedbacks to regional and global climate through altered carbon cycle and albedo dynamics. These feedback processes will be affected by vegetation changes, and feedback strengths will largely rely on the spatial extent and timing of vegetation change. Satellite remote sensing is widely used to monitor vegetation dynamics, and vegetation indices (VIs) are frequently used to characterize spatial and temporal trends in vegetation productivity. In this study we combine field observations of larch forest cover across a 25 km2 upland landscape in northeastern Siberia with high-resolution satellite observations to determine how the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) are related to forest cover. Across 46 forest stands ranging from 0% to 90% larch canopy cover, we find either no change, or declines in NDVI and EVI derived from PlanetScope CubeSat and Landsat data with increasing forest cover. In conjunction with field observations of NDVI, these results indicate that understory vegetation likely exerts a strong influence on vegetation indices in these ecosystems. This suggests that positive decadal trends in NDVI in Siberian larch forests may correspond primarily to increases in understory productivity, or even to declines in forest cover. Consequently, positive NDVI trends may be associated with declines in terrestrial carbon storage and increases in albedo, rather than increases in carbon storage and decreases in albedo that are commonly assumed. Moreover, it is also likely that important ecological changes such as large changes in forest density or variable forest regrowth after fire are not captured by long-term NDVI trends.

Assessing Land Degradation Dynamics and Distinguishing Human-Induced Changes from Climate Factors in the Three-North Shelter Forest Region of China

Land degradation is a major threat to the sustainability of human habitation, and it is essential to assess it quantitatively. Assessment of the human-induced aspect is especially important for planning appropriate prevention measures. This paper used the Three-North Shelter Forest Program region as the study area, and assessed the land degradation dynamic using a time series of summed normalized difference vegetation index (NDVI) based on a trend analysis of the Theil-Sen slope and Mann-Kendall test. The human-induced land degradation was separated from degradation driven by climate using the meteorological dataset through the residual trend (RESTREND) method for the period 1982–2006. The results showed that (1) the NDVI in the study area mainly exhibited an increasing trend, approximately 13.00% of the study area experienced significantly positive NDVI trends and 6.20% showed decline. Furthermore, (2) the correlation between the summed NDVI and precipitation was higher than the correlation between NDVI and temperature, suggesting that precipitation was the most essential factor that impacted NDVI dynamic in the study area; (3) The significant trends of vegetation by anthropogenic disturbances were detected, which were significant positive and negative trends of 11.93% and 6.19%, respectively. All of these findings enrich our knowledge of human activities that impact land degradation in arid or semi-arid regions and provide a scientific basis for the management of ecological restoration programs.

Regional and landscape-scale variability of Landsat-observed vegetation dynamics in northwest Siberian tundra

Widespread increases in Arctic tundra productivity have been documented for decades using coarse-scale satellite observations, but finer-scale observations indicate that changes have been very uneven, with a high degree of landscape- and regional-scale heterogeneity. Here we analyze time-series of the Normalized Difference Vegetation Index (NDVI) observed by Landsat (1984–2012), to assess landscape- and regional-scale variability of tundra vegetation dynamics in the northwest Siberian Low Arctic, a little-studied region with varied soils, landscape histories, and permafrost attributes. We also estimate spatio-temporal rates of land-cover change associated with expansion of tall alder (Alnus) shrublands, by integrating Landsat time-series with very-high-resolution imagery dating to the mid-1960s. We compiled Landsat time-series for eleven widely-distributed landscapes, and performed linear regression of NDVI values on a per-pixel basis. We found positive net NDVI trends (‘greening’) in nine of eleven landscapes. Net greening occurred in alder shrublands in all landscapes, and strong greening tended to correspond to shrublands that developed since the 1960s. Much of the spatial variability of greening within landscapes was linked to landscape physiography and permafrost attributes, while between-landscape variability largely corresponded to differences in surficial geology. We conclude that continued increases in tundra productivity in the region are likely in upland tundra landscapes with fine-textured, cryoturbated soils; these areas currently tend to support discontinuous vegetation cover, but are highly susceptible to rapid increases in vegetation cover, as well as land-cover changes associated with the development of tall shrublands.

Combined analysis of land cover change and NDVI trends in the Northern Eurasian grain belt

We present an approach to regional environmental monitoring in the Northern Eurasian grain belt combining time series analysis of MODIS normalized difference vegetation index (NDVI) data over the period 2001-2008 and land cover change (LCC) analysis of the 2001 and 2008 MODIS Global Land Cover product (MCD12Q1). NDVI trends were overwhelmingly negative across the grain belt with statistically significant (p⩽0.05) positive trends covering only 1% of the land surface. LCC was dominated by transitions between three classes; cropland, grassland, and a mixed cropland/natural vegetation mosaic. Combining our analyses of NDVI trends and LCC, we found a pattern of agricultural abandonment (cropland to grassland) in the southern range of the grain belt coinciding with statistically significant (p⩽0.05) negative NDVI trends and likely driven by regional drought. In the northern range of the grain belt we found an opposite tendency toward agricultural intensification; in this case, represented by LCC from cropland mosaic to pure cropland, and also associated with statistically significant (p⩽0.05) negative NDVI trends. Relatively small clusters of statistically significant (p⩽0.05) positive NDVI trends corresponding with both localized land abandonment and localized agricultural intensification show that land use decision making is not uniform across the region. Land surface change in the Northern Eurasian grain belt is part of a larger pattern of land cover land use change (LCLUC) in Eastern Europe, Russia, and former territories of the Soviet Union following realignment of socialist land tenure and agricultural markets. Here, we show that a combined analysis of LCC and NDVI trends provides a more complete picture of the complexities of LCLUC in the Northern Eurasian grain belt, involving both broader climatic forcing, and narrower anthropogenic impacts, than might be obtained from either analysis alone.

Migration and environment in Ghana: a cross-district analysis of human mobility and vegetation dynamics

Migration—environment linkages are at the centre of media attention because of public concern about climate change and a perceived “flooding” of migrants from less developed countries into more affluent parts of the world. In the past few years, a substantial body of conceptual literature about environmentally induced migration has evolved, but there is still a paucity of empirical work in this area. Moreover, the environmental causes of migration have been studied largely in isolation of the environmental consequences. In this paper we present an analysis of migration and vegetation dynamics for one country (Ghana) to assess four migration—environment linkages. On the one hand, we look at two environmental drivers of migration: environmental push and pull. On the other hand, we look at the environmental impact of migration on source and destination areas. Census data at the district level (N=110) are used to map domestic migration flows in Ghana, which are then related to vegetation dynamics retrieved from a remotely sensed Normalized Difference Vegetation Index (NDVI) dataset (1981— 2006). The analysis shows that at the national level, there are significant but weak correlations between migration and vegetation cover and trends therein. Districts with a migration deficit (more out-migration than in-migration) tend to be more sparsely vegetated and have experienced a more positive NDVI trend over the past quarter century than districts with a migration surplus. A disaggregation of data in three principle migration systems shows stronger correlations. Namely that north—south migration and cocoa frontier settlement have important environmental dimensions, but environmental factors do not seem to play a major role in migration to the capital, Accra. An important insight from this paper is that migration flows in Ghana can be explained partly by vegetation dynamics but are also strongly related to rural population densities. This is because access to natural resources is often more important than the scarcity or abundance of natural resources per se. This study further shows that satellite remote sensing can provide valuable input to analyses of migration—environment linkages.

Evaluating the Consistency of the 1982–1999 NDVI Trends in the Iberian Peninsula across Four Time-series Derived from the AVHRR Sensor: LTDR, GIMMS, FASIR, and PAL-II

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast.

Trends in vegetation NDVI from 1 km AVHRR data over Canada for the period 1985–2006

Long‐term changes in the Normalized Difference Vegetation Index (NDVI) have been evaluated in several studies but results have not been conclusive due to differences in data processing as well as the length and time of the analysed period. In this research a newly developed 1 km Advanced Very High Resolution Radiometer (AVHRR) satellite data record for the period 1985–2006 was used to rigorously evaluate NDVI trends over Canada. Furthermore, climate and land cover change as potential causes of observed trends were evaluated in eight sample regions. The AVHRR record was generated using improved geolocation, cloud screening, correction for sun‐sensor viewing geometry, atmospheric correction, and compositing. Results from both AVHRR and Landsat revealed an increasing NDVI trend over northern regions where comparison was possible. Overall, 22% of the vegetated area in Canada was found to have a positive NDVI trend based on the Mann–Kendal test at the 95% confidence level. Of these, 40% were in northern ecozones. The mean absolute difference of NDVI measurements between AVHRR and Landsat data was <7%. When compared with results from other studies, similar trends were found over northern areas, while in southern regions the results were less consistent. Local assessment of potential causes of trends in each region revealed a stronger influence of climate in the north compared to the south. Southern regions with strong positive trends appeared to be most influenced by land cover change.

The greening and browning of Alaska based on 1982–2003 satellite data

AbstractAim To examine the trends of 1982–2003 satellite‐derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska.Location Arctic and subarctic Alaska.Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982–2003 data set with 64‐km2 pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100‐km climate station buffers. The 1982–2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers.Results At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west‐to‐east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate.Main conclusions There was a contrast in trends of 1982–2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers.

Trends in the surface vegetation dynamics of the national parks of Spain as observed by satellite sensors

AbstractQuestions: What are the current dynamics, as observed by synoptic sensors, of surface vegetation in Spanish protected areas? Are these areas and their vegetation types uniformly affected by the increase in vegetation greenness detected throughout Europe?Location: Iberian National Parks of Spain.Methods: We used the normalized difference vegetation index (NDVI) from global inventory modeling and mapping studies (GIMMS) advanced very high resolution radiometer (AVHRR) dataset to monitor surface vegetation. NDVI is a surrogate for the photosynthetically active radiation absorbed by vegetation (fAPAR). This functional attribute has a short‐time response to disturbances, is connected to ecosystem services and can be monitored through remote sensing. First, we provide a baseline description of the NDVI dynamics in the parks and analysed its temporal trends (1981–2003). Then, we evaluated the relationships of the seasonal dynamics and interannual trends with the climate conditions, vegetation types and conservation histories of the parks.Results: The parks showed two patterns of NDVI dynamics corresponding to Mediterranean and Eurosiberian regions. Most parks showed areas with positive NDVI trends that tended to have higher proportions of Mediterranean coniferous and mixed forests, oro‐Mediterranean scrublands, heathlands, maquis and garrigues. Negative trends were scarce and associated with marshes and Alpine coniferous forests. The lack of a common response in all parks was related to their different environmental conditions, management, and conservation histories. Conclusions: National parks are changing in the short term but not uniformly. This study represents a basis for the incorporation of functional attributes of ecosystems in the management and monitoring of protected areas in the face of global change.