Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran)

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.     

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p?<?0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p?<?0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.     

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km²) and 11.8% (6374 km²) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological–socioeconomic systems.     

Geospatial assessment and monitoring of historical forest cover changes (1920–2012) in Nilgiri Biosphere Reserve,Western Ghats,India

Deforestation in the biosphere reserves, which are key Protected Areas has negative impacts on biodiversity, climate, carbon fluxes and livelihoods. Comprehensive study of deforestation in biosphere reserves is required to assess the impact of the management effectiveness. This article assesses the changes in forest cover in various zones and protected areas of Nilgiri Biosphere Reserve, the first declared biosphere reserve in India which forms part of Western Ghats-a global biodiversity hotspot. In this study, we have mapped the forests from earliest available topographical maps and multi-temporal satellite data spanning from 1920’s to 2012 period. Mapping of spatial extent of forest cover, vegetation types and land cover was carried out using visual interpretation technique. A grid cell of 1 km?×?1 km was generated for time series change analysis to understand the patterns in spatial distribution of forest cover (1920–1973–1989–1999–2006–2012). The total forest area of biosphere reserve was found to be 5,806.5 km² (93.8 % of total geographical area) in 1920. Overall loss of forest cover was estimated as 1,423.6 km² (24.5 % of the total forest) with reference to 1920. Among the six Protected Areas, annual deforestation rate of >0.5 was found in Wayanad wildlife sanctuary during 1920–1973. The deforestation in Nilgiri Biosphere Reserve is mainly attributed to conversion of forests to plantations and agriculture along with submergence due to construction of dams during 1920 to 1989. Grid wise analysis indicates that 851 grids have undergone large-scale negative changes of >75 ha of forest loss during 1920–1973 while, only 15 grids have shown >75 ha loss during 1973–1989. Annual net rate of deforestation for the period of 1920 to 1973 was calculated as 0.5 followed by 0.1 for 1973 to 1989. Our analysis shows that there was large-scale deforestation before the declaration of area as biosphere reserve in 1986; however, the deforestation has drastically reduced after the declaration due to high degree of protection, thus indicating the secure future of reserve in the long term under the current forest management practices. The present work will stand as the most up-to-date assessment on the forest cover of the Nilgiri Biosphere Reserve with immediate applications in monitoring and management of forest biodiversity.     

Impacts of climate warming on vegetation in Qaidam Area from 1990 to 2003

The observed warming trend in the Qaidam area, an arid basin surrounded by high mountains, has caused land surface dynamics that are detectable using remotely sensed data. In this paper, we detected land-cover changes in the Qaidam Area between 1990 and 2003 in attempt to depict its spatial variability. The land-cover changes were categorized into two trends: degradation and amelioration, and their spatial patterns were examined. Then we estimated the correlation coefficients between growing-season NDVI and several climatic factors with the consideration of duration and lagging effects. The results show that the inter-annual NDVI variations are positively correlated with May to July precipitations, but not significantly correlated with sunshine duration. We observed no obvious trend in precipitation or sunshine duration from 1990 to 2003. Thus, the authors suggest that their slight fluctuations may not be responsible to the decade-scaled land-cover changes. However, our results indicate a good positive relationship between the NDVI trend and climate warming in the ameliorated areas, but a negative one in the degraded areas. By statistical analyses, we found that degradations mainly occurred at the oasis boundaries and at lower elevations in the non-oasis regions where effective soil moisture might have been reduced by the warming-caused increase in evapotranspiration. At higher elevations where thermal condition acts as a major limiting factor, ameliorations were unequivocally detected, which is attributable to the direct facilitation by temperature increases. We suggest that the impacts of the observed climate warming on vegetation are spatially heterogeneous, depending on the combinations of thermal condition and moisture availability.     

Climate change impacts detection in dry forested ecosystem as indicated by vegetation cover change in —Laikipia,of Kenya

The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.     

The spatiotemporal dynamics of urbanisation and local climate: A case study of Islamabad,Pakistan

Rapid and unplanned urbanisation, together with climate change, are increasingly affecting the local climatic conditions of urban settlements. Spatiotemporal analysis using land use/land cover (LULC), land surface temperature (LST), and local climatic zone (LCZ) assessments have been helpful in understanding the urbanisation characteristics and morphology. Islamabad, the capital and the only planned city of Pakistan, has witnessed a consistent rise in local temperatures, increased built-up areas, and reduced vegetation cover during the past decades. This study explores the spatiotemporal dynamics of LULC, LST, and LCZ in Islamabad using satellite remote sensing data and spectral indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results indicate a whopping increase in a built-up area in the city (113% during 2013 and 2019). A positive correlation between LST and NDBI, whereas a negative correlation between LST and NDVI clearly indicates how urbanisation (and reduction in vegetation cover) are impacting the local temperatures. Assessment and analysis of LCZs helped to understand the variations and deviations of current LULC from the master plan. It was observed that compact low-rise urban development is the most prevalent. The outcomes of this study are expected to inform the urban planners, climatologists, and policymakers with the knowledge helpful for devising climate-resilient development policies that could reduce thermal stresses in the capital cities.     

Quantifying the effect of trend,fluctuation, and extreme event of climate change on ecosystem productivity

Climate change comprises three fractions of trend, fluctuation, and extreme event. Assessing the effect of climate change on terrestrial ecosystem requires an understanding of the action mechanism of these fractions, respectively. This study examined 11 years of remotely sensed-derived net primary productivity (NPP) to identify the impacts of the trend and fluctuation of climate change as well as extremely low temperatures caused by a freezing disaster on ecosystem productivity in Hunan province, China. The partial least squares regression model was used to evaluate the contributions of temperature, precipitation, and photosynthetically active radiation (PAR) to NPP variation. A climatic signal decomposition and contribution assessment model was proposed to decompose climate factors into trend and fluctuation components. Then, we quantitatively evaluated the contributions of each component of climatic factors to NPP variation. The results indicated that the total contribution of the temperature, precipitation, and PAR to NPP variation from 2001 to 2011 in Hunan province is 85 %, and individual contributions of the temperature, precipitation, and PAR to NPP variation are 44 % (including 34 % trend contribution and 10 % fluctuation contribution), 5 % (including 4 % trend contribution and 1 % fluctuation contribution), and 36 % (including 30 % trend contribution and 6 % fluctuation contribution), respectively. The contributions of temperature fluctuation-driven NPP were higher in the north and lower in the south, and the contributions of precipitation trend-driven NPP and PAR fluctuation-driven NPP are higher in the west and lower in the east. As an instance of occasionally triggered disturbance in 2008, extremely low temperatures and a freezing disaster produced an abrupt decrease of NPP in forest and grass ecosystems. These results prove that the climatic trend change brought about great impacts on ecosystem productivity and that climatic fluctuations and extreme events can also alter the ecosystem succession process, even resulting in an alternative trajectory. All of these findings could improve our understanding of the impacts of climate change on the provision of ecosystem functions and services and can also provide a basis for policy makers to apply adaptive measures to overcome the unfavorable influence of climate change.     

Spatial distribution pattern of degree–day factors of glaciers on the Qinghai–Tibetan Plateau

Glaciers have a very obvious feedback effect on the global water cycle and environmental change. The Qinghai–Tibetan Plateau, also known as the “Water Towers of Asia,” provides an important source of freshwater resources derived from glacial meltwater. Changes in glaciers on the Qinghai–Tibetan Plateau are the most important aspect of the research related to global climate change. Because only a few input parameters are available, the degree–day factor model of glacier mass balance has been widely used on the Qinghai–Tibetan Plateau. Study of the spatial distribution pattern of degree–day factors for glaciers on the Qinghai–Tibetan Plateau and the factors that influence glaciers is important scientifically. The study of degree–day factors is important to the calculation of the glacial grid mass balance on the Qinghai–Tibetan Plateau, and this data can be used in the analysis of the response of glaciers experiencing climate change and for predicting future glacial trends. Through an analysis of the degree–day factors related to 24 glaciers on the Qinghai–Tibetan Plateau, one can conclude that the mean value of glacial degree–day factors on the Qinghai–Tibetan Plateau is 8.14 mm day^?1 °C^?1. The glacial degree–day factor shows a longitudinal zonality with values ranging from high to low from east to west, a latitudinal zonality with values ranging from high to low from south to north, and a vertical zonal regularity along with the change of elevation. The spatial distribution pattern of glacial degree–day factors in the Tibetan Plateau is related to the fact that the climate environment across the Qinghai–Tibetan Plateau is mainly affected by the Indian monsoon, the eastern monsoon, and the westerly winds. The climate gradually changes from cold-humid to warm-humid from northwest to southeast. The single-unit glacier of Qinghai–Tibetan Plateau—the Renlongba Glacier—is located in the southeastern portion of the Qinghai–Tibetan Plateau in a warm and humid climate; its degree–day factor is slightly large, averaging at 6.12 mm day^?1 °C^?1. Mountainous barriers exist in the eastern and western parts of the Renlongba Glacier. On the east side, the degree–day factor is small (5.63 mm day^?1 °C^?1) because of large mountains block weather systems. The glacial tongue is affected by valley wind, contributing to glacial ablation, so the degree–day factor is large on the tongue, averaging at 6.56 mm day^?1 °C^?1. The degree–day factor on the west side of the Renlongba Glacier increases gradually increasing radiation and elevation, presenting a vertical zonal feature. In general, the climate of the Qinghai–Tibetan Plateau is mainly affected by the Indian and eastern monsoons and by westerly winds. In dry and cold climatic conditions, the glacial degree–day factor in the Tibetan Plateau is small, while at warm and humid climate conditions, it is large, with latitudinal, longitudinal, and vertical zonality. In addition, the degree–day factor is also affected by blocking, topography, and other local microclimatic conditions.     

Decadal time-scale monitoring of forest fires in Similipal Biosphere Reserve,India using remote sensing and GIS

Analyzing the spatial extent and distribution of forest fires is essential for sustainable forest resource management. There is no comprehensive data existing on forest fires on a regular basis in Biosphere Reserves of India. The present work have been carried out to locate and estimate the spatial extent of forest burnt areas using Resourcesat-1 data and fire frequency covering decadal fire events (2004–2013) in Similipal Biosphere Reserve. The anomalous quantity of forest burnt area was recorded during 2009 as 1,014.7 km². There was inconsistency in the fire susceptibility across the different vegetation types. The spatial analysis of burnt area shows that an area of 34.2 % of dry deciduous forests, followed by tree savannah, shrub savannah, and grasslands affected by fires in 2013. The analysis based on decadal time scale satellite data reveals that an area of 2,175.9 km² (59.6 % of total vegetation cover) has been affected by varied rate of frequency of forest fires. Fire density pattern indicates low count of burnt area patches in 2013 estimated at 1,017 and high count at 1,916 in 2004. An estimate of fire risk area over a decade identifies 12.2 km² is experiencing an annual fire damage. Summing the fire frequency data across the grids (each 1 km²) indicates 1,211 (26 %) grids are having very high disturbance regimes due to repeated fires in all the 10 years, followed by 711 grids in 9 years and 418 in 8 years and 382 in 7 years. The spatial database offers excellent opportunities to understand the ecological impact of fires on biodiversity and is helpful in formulating conservation action plans.     

Monitoring and validating the temporal dynamics of interday streamflow from two upland head micro-watersheds with different vegetative conditions during dry periods of the growing season in the Bohemian Massif,Czech Republic

At present, dynamic land use, climate change, and growing needs for fresh water are increasing the demand on the ecosystem effects of forest vegetation. Mountainous areas are at the forefront of scientific interest in European forest ecology and forest hydrology. Although uplands cover a significant area of the Czech Republic and other countries and are often covered with forest formations, they do not receive an appropriate amount of attention. Therefore, two experimental upland head micro-watersheds in the Bohemian Massif were selected for study because they display similar natural conditions, but different vegetative conditions (forest versus meadow). During the 2011 growing season, short-term streamflow measurements were carried out at the discharge profiles of both catchments and were evaluated in relation to climatic data (rainfall and temperature). The basic premise was that the streamflow in a forested catchment must exhibit different temporal dynamics compared to that in treeless areas and that these differences can be attributed to the effects of woody vegetation. These conclusions were drawn from measurements performed during dry periods lasting several days. A decreasing streamflow trend during the day part of the day (0900–1900 hours) was observed in both localities. The decrease reached approx. 44 % of the initial morning streamflow (0.24 dm³ s^?1 day^?1) in the treeless catchment and approx. 20 % (0.19 dm³ s^?1 day^?1) in the forested catchment. At night (1900–0900 hours), the streamflow in the forested catchment increased back to its initial level, whereas the streamflow in the treeless catchment stagnated or slowly decreased. We attribute these differences to the ecosystem effects of woody vegetation and its capacity to control water loss during the day. This type of vegetation can also function as a water source for the hydrographic network during the night.     

Atmospheric Change and Biodiversity

Strategies to conserve biodiversity need to include the monitoring, modelling, adaptation and regulation of the composition of the atmosphere. Atmospheric issues include climate variability and extremes; climate change; stratospheric ozone depletion; acid deposition; photochemical pollution; suspended particulate matter; and hazardous air pollutants. Coarse filter and fine filter approaches have been used to understand the complexity of the interactions between the atmosphere and biodiversity. In the first approach, climate-based models, using GIS technology, helped create future biodiversity scenarios under a 2 × CO₂ atmosphere. In the second approach, the SI/MAB forest biodiversity monitoring protocols helped calibrate the climate-forest biodiversity baseline and, as global diagnostics, helped identify where the biodiversity was in equilibrium with the present climate. Forest climate monitoring, an enhancing protocol, was used in a co-location approach to define the thermal buffering capacity of forest ecosystems and their ability to reduce and ameliorate global climate variability, extremes and change.     

The effect of river damming on vegetation: is it always unfavourable? A case study from the River Tiber (Italy)

River damming leads to strong hydromorphological alterations of the watercourse, consequently affecting river vegetation pattern. A multitemporal and spatial analysis of the dam effect on composition, structure and dynamic of the upstream vegetation was performed on Tiber River at Nazzano-dam (Rome). The main research questions were as follows: How does plant landscape vary over time and along the river? Where does the dam effect on vegetation end? How does naturalistic importance of the vegetation affected by damming change over time? Data collection was performed mapping the vegetation in aerial photos related to the period before (1944), during (1954) and after dam construction (1984, 2000). The plant landscape has significantly changed over time and along the river, particularly as a result of the dam construction (1953). The major vegetation changes have involved riparian forests and macrophytes. Dam effect on vegetation is evident up to 3 km, and gradually decreases along an attenuation zone for about another 3 km. Despite the fact that the damming has caused strong local hydromorphological modification of the river ecosystem transforming it into a sub-lacustrine habitat, it has also led to the formation of wetlands of considerable naturalistic importance. Indeed, in these man-made wetlands, optimal hydrological conditions have been created by favouring both the expansion of pre-existing riparian communities and the rooting of new aquatic communities, albeit typical of lacustrine ecosystems. Some of these plant communities have become an important food resource, refuge or nesting habitats for aquatic fauna, while others fall into category of Natura 2000 habitats. Therefore, river damming seems to have indirectly had a “favourable” effect for habitat conservation and local biodiversity.     

Analyzing deforestation rates, spatial forest cover changes and identifying critical areas of forest cover changes in North-East India during 1972–1999

Deforestation is recognized as one of the most significant component in LULC and global changes scenario. It is imperative to assess its trend and the rates at which it is occurring. The changes will have long-lasting impact on regional climate and in turn on biodiversity. In North-East India, one of the recognized global biodiversity hotspots, approximately 30% of total forest cover is under pressure of rapid land use changes. This region harbors variety of rare and endemic species of flora and fauna. It also has a strong bearing on regional climatic conditions. Extensive shifting cultivation, compounded by increasing population pressure and demands for agriculture land are the prime drivers in addition to other proximate drivers of deforestation. It is therefore of prime concern to analyse forest cover changes in the region, assess rate of change and extent and to identify the areas, which show repetitive changes. We analyzed forest cover maps from six temporal datasets based on satellite data interpretation, converted to geospatial database since 1972 till 1999. The states of Meghalaya, Nagaland and Tripura show highest changes in forest cover. Arunachal Pradesh shows least dynamic areas and maintains a good forest cover owing to its topographical inaccessibility in some areas. The present study reports the forest cover changes in the region using geospatial analysis and analyse them to devise proper management strategies.     

Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986–1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.     

A glimpse at short-term controls of evapotranspiration along the southern slopes of Kilimanjaro

Future climate characteristics of the southern Kilimanjaro region, Tanzania, are mainly determined by local land-use and global climate change. Reinforcing increasing dryness throughout the twentieth century, ongoing land transformation processes emphasize the need for a proper understanding of the regional-scale water budget and possible implications on related ecosystem functioning and services. Here, we present an analysis of scintillometer-based evapotranspiration (ET) covering seven distinct habitat types across a massive climate gradient from the colline savanna woodlands to the upper-mountain Helichrysum zone (940 to 3960 m.a.s.l.). Random forest-based mean variable importance indicates an outstanding significance of net radiation (R _net) on the observed ET across all elevation levels. Accordingly, topography and frequent cloud/fog events have a dampening effect at high elevations, whereas no such constraints affect the energy and moisture-rich submontane coffee/grassland level. By contrast, long-term moisture availability is likely to impose restrictions upon evapotranspirative net water loss in savanna, which particularly applies to the pronounced dry season. At plot scale, ET can thereby be approximated reasonably using R _net, soil heat flux, and to a lesser degree, vapor pressure deficit and rainfall as predictor variables (R ² 0.59 to 1.00). While multivariate regression based on pooled meteorological data from all plots proves itself useful for predicting hourly ET rates across a broader range of ecosystems (R ² = 0.71), additional gains in explained variance can be achieved when vegetation characteristics as seen from the NDVI are considered (R ² = 0.87). To sum up, our results indicate that valuable insights into land cover-specific ET dynamics, including underlying drivers, may be derived even from explicitly short-term measurements in an ecologically highly diverse landscape.     

Assessment of some remote sensing techniques used to detect land use/land cover changes in South-East Transilvania,Romania

This paper assesses the image differencing technique for the Normalized Difference Vegetation Index (NDVI), the second principal component (PC2), and the TM 4 band (TM 4), as well as the post-classification comparison (PCC) in order to analyze the land use/land cover changes in the South-East Transilvania, Romania. The analysis was performed using two frames from Landsat 5 TM satellite images acquired on August 5, 1993 and July 24, 2009. After applying the NDVI, PC2, and TM 4 image differencing techniques, the images obtained were transformed into change/no change maps. The thresholds identified to highlight the changes were set at 0.6 s for NDVI and 0.7 s for PC2 and TM 4. Before applying the PCC technique, the satellite images were classified through the supervised classification method. The overall accuracy obtained was 85.91 % and the kappa statistics 0.8249 for 1993, 88.18 % and 0.8497 for 2009, respectively. The assessment of the changes detection methods in the studied area shows that the first place is occupied by NDVI image differencing with an overall accuracy of 83.80 %, followed by PCC method with 83.20 %, PC2 difference with an overall accuracy of 81.60 %, and TM 4 difference with an overall accuracy of 79.40 %.     

River pollution remediation monitored by optical and infrared high-resolution satellite images

The Bormida River Basin, located in the northwestern region of Italy, has been strongly contaminated by the ACNA chemical factory. This factory was in operation from 1892 to 1998, and contamination from the factory has had deleterious consequences on the water quality, agriculture, natural ecosystems and human health. Attempts have been made to remediate the site. The aims of this study were to use high-resolution satellite images combined with a classical remote sensing methodology to monitor vegetation conditions along the Bormida River, both upstream and downstream of the ACNA chemical factory site, and to compare the results obtained at different times before and after the remediation process. The trends of the Normalised Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) along the riverbanks are used to assess the effect of water pollution on vegetation. NDVI and EVI values show that the contamination produced by the ACNA factory had less severe effects in the year 2007, when most of the remediation activities were concluded, than in 2006 and 2003. In 2007, the contamination effects were noticeable up to 6 km downstream of the factory, whereas in 2003 and 2006 the influence range was up to about 12 km downstream of the factory. The results of this study show the effectiveness of remediation activities that have been taking place in this area. In addition, the comparison between NDVI and EVI shows that the EVI is more suitable to characterise the vegetation health and can be considered an additional tool to assess vegetation health and to monitor restoration activities.     

Research on the relationship between the fractional coverage of the submerged plant Vallisneria spiralis and observed spectral parameters

The present paper discusses the relationship between the coverage fraction of submerged plants and the observed spectral characteristics. The purpose of this paper is to validate a remote sensing technology to monitor the change in the plant composition of a water body. In the current study, the reflectance spectra of the submerged plant Vallisneria spiralis at different fraction coverages of the wetland in Hangzhou Bay were measured. The relationships between the fraction coverage of V. spiralis and simulated Quickbird normalized difference vegetation index (NDVI), red edge, and other spectral characteristic parameters were established. The results showed that the spectral reflectance characteristics of submerged plant V. spiralis were mainly in the visible light (490–650 nm) and near infrared (700–900 nm). The rate of change of the blue band curve and simulated Quickbird NDVI showed a higher correlation with the V. spiralis coverage, so estimation models of the fraction coverage were constructed using these parameters. The estimated fraction coverage of V. spiralis with different models were validated with ground data, and the accuracy of estimation models was assessed. The most suitable estimated fraction coverage of V. spiralis was obtained using the rate of change of the blue band curve and simulated Quickbird NDVI. The present work demonstrated a method to monitor the distribution and dynamical variation of submerged plants at the large scale.     

Statistical Modeling of Health Effects on Climate-Sensitive Variables and Assessment of Environmental Burden of Diseases Attributable to Climate Change in Nepal

An ecological time-series study is conducted to quantify health-effect coefficients associated with climate-sensitive variables namely temperature, rainfall, relative humidity, and wind speed and estimate environmental burden of diseases attributed to temperature as the main climatic variable together with climate change in Nepal. The study is based upon daily data of climate-sensitive variables and hospitalizations collected for 5 years between 2009 and 2014. Generalized linear model is used to estimate health-effect coefficients accounting distributed lag effects. Results show 3.08%, 10.14%, and 3.27% rise in water-borne, vector-borne, and renal disease hospitalizations, respectively, and 3.67% rise in water- and vector-borne disease deaths per 1 °C rise in average temperature. Similarly, 2.45% and 1.44% rise in heart disease hospitalization and all-cause mortality, respectively per 1 °C rise in absolute difference of average temperature with its overall average (20 °C). The computed attributable fractions are 0.3759, 0.6696, 0.2909, and 0.1024 for water-borne, vector-borne, renal, and heart disease hospitalizations, respectively, and 0.0607 and 0.4335 for all-cause mortality and disease-specific mortality of water- and vector-borne diseases, respectively. The percent change in attributable burdens due to climate change are found to be 4.32%, 4.64%, 7.20%, and ?2.29% for water-borne, vector-borne, renal, and heart disease hospitalizations, respectively, and ?1.39% and 6.55% for all-cause deaths and water-borne and vector-borne disease deaths, respectively. In conclusion, climate-sensitive variables have significant effects on many major health burdens in Nepal. In the context of changing climatic scenarios around the world including that of Nepal, such changes are bound to affect the health burden of Nepalese people.