Search results for: vegetation encroachment

Authors: Ahmed Ali Samejo, Riffat Sultana

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Pakistan has the sandy Thar Desert in the eastern area, which share border line with India and has exotic fauna and flora, the livelihood of native people rely on livestock and rain fed cultivated fields. The climate of Thar Desert is very harsh and stressful due to frequent drought and very little rainfall, which may occur during monsoon season in the months of July to October and temperature is high, and wind speed also increases in April to June. Schistocerca gregaria is a destructive pest of vegetation from Mauritania to the border line of Pakistan and India. Sometimes they produce swarms which consume all plant where ever they land down and cause the loss in agro-economy of the world. During the recent study, we observed that vegetation was not unique throughout the Thar Desert in the year 2015, because the first spell of rainfall showered over all areas of the Thar Desert in July. However, the second and third spell of rain was confined to village Mahandre jo par and surroundings from August to October. Consequently, vegetation and cultivated crops grew up specially bajra crop (Pennistum glaucum). The climate of Mahandre jo par and surroundings became favorable for S.gregaria, and remaining areas of Thar Desert went hostile. Therefore desert locust attracted to the pleasant area (Mahandre jo par and surroundings) and gradually concentrated, increased reproductive activities, but did not gregarize due to the harvest of bajra crop and the onset of the winter season with an immediate decrease in temperature. An outbreak was near to come into existence, and thereupon conditions become stressful for hoppers to continue further development. Afore mentioned was one reason behind hurdle to the outbreak, another reason might be that migration and concentration of desert locust took place at the end of the season, so climate becomes unfavorable for hoppers, due to dryness of vegetation. Soils also become dry, because rainfall was not showered in end of the season, that’s why eggs that were deposited in late summer were desiccated. This data might be proved fruitful to forecast any outbreak update in future.

Keywords: agro-economy, destructive pest, climate, outbreak, vegetation

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Authors: M. E. Razipoor, T. Masunaga, K. Sato, M. S. Saboory

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Estimation of soil erosion is economically and environmentally important in Herat, Afghanistan. Degradation of soil has negative impact (decreased soil fertility, destroyed soil structure, and consequently soil sealing and crusting) on life of Herat residents. Water and wind are the main erosive factors causing soil erosion in Herat. Furthermore, scarce vegetation cover, exacerbated by socioeconomic constraint, and steep slopes accelerate soil erosion. To sustain soil productivity and reduce soil erosion impact on human life, due to sustaining agricultural production and auditing the environment, it is needed to quantify the magnitude and extent of soil erosion in a spatial domain. Thus, this study aims to estimate soil loss potential and its spatial distribution in Herat, Afghanistan by applying RUSLE in GIS environment. The rainfall erosivity factor ranged between values of 125 and 612 (MJ mm ha-1 h-1 year-1). Soil erodibility factor varied from 0.036 to 0.073 (Mg h MJ-1 mm-1). Slope length and steepness factor (LS) values were between 0.03 and 31.4. The vegetation cover factor (C), derived from NDVI analysis of Landsat-8 OLI scenes, resulting in range of 0.03 to 1. Support practice factor (P) were assigned to a value of 1, since there is not significant mitigation practices in the study area. Soil erosion potential map was the product of these factors. Mean soil erosion rate of Herat Province was 29 Mg ha-1 year-1 that ranged from 0.024 Mg ha-1 year-1 in flat areas with dense vegetation cover to 778 Mg ha-1 year-1 in sharp slopes with high rainfall but least vegetation cover. Based on land cover map of Afghanistan, areas with soil loss rate higher than soil loss tolerance (8 Mg ha-1 year-1) occupies 98% of Forests, 81% rangelands, 64% barren lands, 60% rainfed lands, 28% urban area and 18% irrigated Lands.

Keywords: Afghanistan, erosion, GIS, Herat, RUSLE

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Authors: H. Arzani, Z. Arzani

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Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

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Authors: Alisa Salimova, Jiane Zuo, Christopher Homer

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The objective of this study is to analyse the North Canal riparian zone land use with the help of remote sensing analysis in ArcGis using 30 cloudless Landsat8 open-source satellite images from May to August of 2013 and 2017. Land cover, urban construction, heat island effect, vegetation cover, and water system change were chosen as the main parameters and further analysed to evaluate its impact on the North Canal water quality. The methodology involved the following steps: firstly, 30 cloudless satellite images were collected from the Landsat TM image open-source database. The visual interpretation method was used to determine different land types in a catchment area. After primary and secondary classification, 28 land cover types in total were classified. Visual interpretation method was used with the help ArcGIS for the grassland monitoring, US Landsat TM remote sensing image processing with a resolution of 30 meters was used to analyse the vegetation cover. The water system was analysed using the visual interpretation method on the GIS software platform to decode the target area, water use and coverage. Monthly measurements of water temperature, pH, BOD, COD, ammonia nitrogen, total nitrogen and total phosphorus in 2013 and 2017 were taken from three locations of the North Canal in Tongzhou district. These parameters were used for water quality index calculation and compared to land-use changes. The results of this research were promising. The vegetation coverage of North Canal riparian zone in 2017 was higher than the vegetation coverage in 2013. The surface brightness temperature value was positively correlated with the vegetation coverage density and the distance from the surface of the water bodies. This indicates that the vegetation coverage and water system have a great effect on temperature regulation and urban heat island effect. Surface temperature in 2017 was higher than in 2013, indicating a global warming effect. The water volume in the river area has been partially reduced, indicating the potential water scarcity risk in North Canal watershed. Between 2013 and 2017, urban residential, industrial and mining storage land areas significantly increased compared to other land use types; however, water quality has significantly improved in 2017 compared to 2013. This observation indicates that the Tongzhou Water Restoration Plan showed positive results and water management of Tongzhou district had been improved.

Keywords: North Canal, land use, riparian vegetation, river ecology, remote sensing

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Authors: Damian Czubak

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The Białowieża Forest is a very valuable natural area, included in the World Natural Heritage at UNESCO, where, due to infestation by the bark beetle (Ips typographus), norway spruce (Picea abies) have deteriorated. This catastrophic scenario led to an increase in fire danger. This was due to the occurrence of large amounts of dead wood and grass cover, as light penetrated to the bottom of the stands. These factors in a dry state are materials that favour the possibility of fire and the rapid spread of fire. One of the objectives of the study was to monitor the quantitative and qualitative changes of combustible material on the permanent decay plots of spruce stands from 2012-2022. In addition, the size of the area with highly flammable vegetation was monitored and a classification of the stands of the Białowieża Forest by flammability classes was made. The key factor that determines the potential fire hazard of a forest is combustible material. Primarily its type, quantity, moisture content, size and spatial structure. Based on the inventory data on the areas of forest districts in the Białowieża Forest, the average fire load and its changes over the years were calculated. The analysis was carried out taking into account the changes in the health status of the stands and sanitary operations. The quantitative and qualitative assessment of fallen timber and fire load of ground cover used the results of the 2019 and 2021 inventories. Approximately 9,000 circular plots were used for the study. An assessment was made of the amount of potential fuel, understood as ground cover vegetation and dead wood debris. In addition, monitoring of areas with vegetation that poses a high fire risk was conducted using data from 2019 and 2021. All sub-areas were inventoried where vegetation posing a specific fire hazard represented at least 10% of the area with species characteristic of that cover. In addition to the size of the area with fire-prone vegetation, a very important element is the size of the fire load on the indicated plots. On representative plots, the biomass of the land cover was measured on an area of 10 m2 and then the amount of biomass of each component was determined. The resulting element of variability of ground covers in stands was their flammability classification. The classification developed made it possible to track changes in the flammability classes of stands over the period covered by the measurements.

Keywords: classification, combustible material, flammable vegetation, Norway spruce

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Authors: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

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Rangelands in semi-arid areas provide a good source for feeding huge numbers of animals and serving environmental, economic and social importance; therefore, these areas are considered economically very important for the pastoral sector in Sudan. This paper investigates the means of differentiating between different rangelands sites according to soil types using principal component analysis to assist in monitoring and assessment purposes. Three rangeland sites were identified in the study area as flat sandy sites, sand dune site, and hard clay site. Principal component analysis (PCA) was used to reduce the number of factors needed to distinguish between rangeland sites and produce a new set of data including the most useful spectral information to run satellite image processing. It was performed using selected types of data (two vegetation indices, topographic data and vegetation surface reflectance within the three bands of MODIS data). Analysis with PCA indicated that there is a relatively high correspondence between vegetation and soil of the total variance in the data set. The results showed that the use of the principal component analysis (PCA) with the selected variables showed a high difference, reflected in the variance and eigenvalues and it can be used for differentiation between different range sites.

Keywords: principal component analysis, PCA, rangeland sites, semi-arid areas, soil types

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Authors: Nadeem Munawar, Tariq Mahmood

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Habitat manipulation is an important technique that can be used for controlling rodent damage in agricultural ecosystems. It involves intentionally manipulation of vegetation cover in adjacent habitats around the active burrows of rodents to reduce shelter, food availability and to increase predation pressure. The current study was conducted in the Pothwar Plateau during the respective non-crop period of wheat-groundnut (post-harvested and un-ploughed/non-crop fallow lands) with the aim to assess the impact of the reduction in vegetation height of adjacent habitats (field borders) on rodent’s richness and abundance. The study area was divided into two sites viz. treated and non-treated. At the treated sites, habitat manipulation was carried out by removing crop cache, and non-crop vegetation’s over 10 cm in height to a distance of approximately 20 m from the fields. The trapping sessions carried out at both treated and non-treated sites adjacent to wheat-groundnut fields were significantly different (F 2, 6 = 13.2, P = 0.001) from each other, which revealed that a maximum number of rodents were captured from non-treated sites. There was a significant difference in the overall abundance of rodents (P < 0.05) between crop stages and between treatments in both crops. The manipulation effect was significantly observed on damage to crops, and yield production resulted in the reduction of damage within the associated croplands (P < 0.05). The outcomes of this study indicated a significant reduction of rodent population at treated sites due to changes in vegetation height and cover which affect important components, i.e., food, shelter, movements and increased risk sensitivity in their feeding behavior; therefore, they were unable to reach levels where they cause significant crop damage. This method is recommended for being a cost-effective and easy application.

Keywords: agricultural ecosystems, crop damage, habitat manipulation, rodents, trapping

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Authors: Hosia T. Pule, Julius T. Tjelele, Michelle J. Tedder, Dawood Hattas

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Acceptability of plant material to herbivores is influenced by, among other factors; nutrients, plant secondary metabolites and growth stage of the plants. However, the effect of these factors on Seriphium plumosum L. acceptability to livestock is still not clearly understood, despite its importance in managing its encroachment in grassland communities. The study used 2 x 2 x 2 factorial analysis of variance to investigate the effect of season (wet and dry), fire, slope position (top and bottom) and their interaction on Seriphium plumosum chemistry. We tested the hypothesis that S. plumosum chemistry varies temporally, spatially and pre- and post-fire treatment. Seriphium plumosum edible material was collected during the wet and dry season from burned and unburned areas on both top and bottom slopes before being analysed for protein (CP) content, neutral detergent fibre (NDF), total phenolics (TP) and condensed tannins (CT). Season had a significant effect on S. plumosum protein content, neutral detergent fibre, total phenolics and condensed tannins. Fire had a significant effect on CP. Interaction of season x fire had a significant effect on NDF and CP (p < 0.05). Seriphium plumosum in the wet season (6.69% ± 0.20 (SE)) had significantly higher CP than in the dry season (5.22% ± 0.13). NDF was significantly higher (58.01% ± 0.41) in the dry season than in the wet season (53.17% ± 0.34), while TP were significantly higher in the dry season (14.44 mg/gDw ± 1.03) than in the wet season (11.08 mg/gDw ± 1.07). CT in the wet season were significantly higher (1.56 mg/gDw ± 0.13) than in the dry season (1 mg/gDw ± 0.03). CP was significantly higher in burned (6. 31 % ± 0.22) than in unburned S. plumosum edible material (5.60 % ± 0.15). Seriphium plumosum CP was significantly higher in wet season x burned (7.34 % ± 0.31) than wet season x unburned (6.08 % ± 0.20) material and dry season x burned (5.34 % ± 0.18) and unburned (5.09 % ± 0.18) material were similar. NDF was similar in dry season x burned (58.31% ± 0.54) and dry season x unburned (57.69 % ± 0.62) material and significantly higher than similar wet season x burned (52.43% ± 0.45) and wet season x post-unburned (53.88% ± 0.47) material. This study suggests integrating fire, browsers, and supplements as encroacher S. plumosum control agents, especially in the wet season, following fire due to high S. plumosum CP content.

Keywords: acceptability, chemistry, edible material, encroachment, phenolics, tannins

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Authors: Bagher Bayat, Wouter Verhoef, Behnaz Arabi, Christiaan Van der Tol

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The aim of this study was to follow the canopy reflectance patterns in response to soil water deficit and to detect trends of changes in biophysical and biochemical parameters of grass (Poa pratensis species). We used visual interpretation, imaging spectroscopy and radiative transfer model inversion to monitor the gradual manifestation of water stress effects in a laboratory setting. Plots of 21 cm x 14.5 cm surface area with Poa pratensis plants that formed a closed canopy were subjected to water stress for 50 days. In a regular weekly schedule, canopy reflectance was measured. In addition, Leaf Area Index (LAI), Chlorophyll (a+b) content (Cab) and Leaf Water Content (Cw) were measured at regular time intervals. The 1-D bidirectional canopy reflectance model SAIL, coupled with the leaf optical properties model PROSPECT, was inverted using hyperspectral measurements by means of an iterative optimization method to retrieve vegetation biophysical and biochemical parameters. The relationships between retrieved LAI, Cab, Cw, and Cs (Senescent material) with soil moisture content were established in two separated groups; stress and non-stressed. To differentiate the water stress condition from the non-stressed condition, a threshold was defined that was based on the laboratory produced Soil Water Characteristic (SWC) curve. All parameters retrieved by model inversion using canopy spectral data showed good correlation with soil water content in the water stress condition. These parameters co-varied with soil moisture content under the stress condition (Chl: R2= 0.91, Cw: R2= 0.97, Cs: R2= 0.88 and LAI: R2=0.48) at the canopy level. To validate the results, the relationship between vegetation parameters that were measured in the laboratory and soil moisture content was established. The results were totally in agreement with the modeling outputs and confirmed the results produced by radiative transfer model inversion and spectroscopy. Since water stress changes all parts of the spectrum, we concluded that analysis of the reflectance spectrum in the VIS-NIR-MIR region is a promising tool for monitoring water stress impacts on vegetation.

Keywords: hyperspectral remote sensing, model inversion, vegetation responses, water stress

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Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

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Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, Worldview-2, land parcels

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

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Authors: Yogita Mishra, Arijit Roy, Dhruval Bhavsar

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The study estimates the nitrogen concentration in selected vegetation community’s i.e. chir pine (pinusroxburghii) by using hyperspectral satellite data and also identified the appropriate spectral bands and nitrogen indices. The Short Wave InfraRed reflectance spectrum at 1790 nm and 1680 nm shows the maximum possible absorption by nitrogen in selected species. Among the nitrogen indices, log normalized nitrogen index performed positively and negatively too. The strong positive correlation is taken out from 1510 nm and 760 nm for the pinusroxburghii for leaf nitrogen concentration and leaf nitrogen mass while using NDNI. The regression value of R² developed by using linear equation achieved maximum at 0.7525 for the analysis of satellite image data and R² is maximum at 0.547 for ground truth data for pinusroxburghii respectively.

Keywords: hyperspectral, NDNI, nitrogen concentration, regression value

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Authors: Dionisios Panagiotaras, Ioannis P. Kokkoris, Dionysios Koulougliotis, Dimitra Lekka, Alexandra Skalioti

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In the summer of 2021, Greece was affected by devastating forest fires in various regions of the country, resulting in human losses, destruction or degradation of the natural environment, infrastructure, livestock and cultivations. The present study concerns a pilot assessment of natural vegetation regeneration in the second, in terms of area, fire-affected region for 2021, at Ancient Olympia area, located in West Peloponnisos (Ilia Prefecture), Greece. A standardised field sampling protocol for assessing natural regeneration was implemented at selected sites where the forest fire had occurred previously (in 2007), and the vegetation (Pinus halepensis forest) had regenerated naturally. The results of the study indicate the loss of the established natural regeneration of Pinus halepensis forest, as well as of the tree-layer in total. Post-fire succession species are recorded to the shrub and the herb layer, with a varying cover. Present findings correspond to the results of field work and analysis one year after the fire, which will form the basis for further research and conclusions on taking action for restoration schemes in areas that have been affected by fire more than once within a 20-year period.

Keywords: forest, pinus halepensis, ancient olympia, post fire vegetation

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Authors: Alemayehu Hailemicael Mezgebe, A. J. Solomon Raju

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Context: Lake Chamo is a significant lake in the Ethiopian Rift Valley, known for its diversity of wildlife and vegetation. However, the lake is facing various threats due to human activities and global effects. The poor management of resources could lead to food insecurity, ecological degradation, and loss of biodiversity. Research Aim: The aim of this study is to analyze the environmental implications of lake level changes using GIS and remote sensing. The research also aims to examine the floristic composition of the lakeside vegetation and propose spatially oriented environmental planning for the sustainable utilization of the biodiversity resources. Methodology: The study utilizes multi-temporal satellite images and aerial photographs to analyze the changes in the lake area over the past 45 years. Geospatial analysis techniques are employed to assess land use and land cover changes and change detection matrix. The composition and role of the lakeside vegetation in the ecological and hydrological functions are also examined. Findings: The analysis reveals that the lake has shrunk by 14.42% over the years, with significant modifications to its upstream segment. The study identifies various threats to the lake-wetland ecosystem, including changes in water chemistry, overfishing, and poor waste management. The study also highlights the impact of human activities on the lake's limnology, with an increase in conductivity, salinity, and alkalinity. Floristic composition analysis of the lake-wetland ecosystem showed definite pattern of the vegetation distribution. The vegetation composition can be generally categorized into three belts namely, the herbaceous belt, the legume belt and the bush-shrub-small trees belt. The vegetation belts collectively act as different-sized sieve screen system and calm down the pace of incoming foreign matter. This stratified vegetation provides vital information to decide the management interventions for the sustainability of lake-wetland ecosystem.Theoretical Importance: The study contributes to the understanding of the environmental changes and threats faced by Lake Chamo. It provides insights into the impact of human activities on the lake-wetland ecosystem and emphasizes the need for sustainable resource management. Data Collection and Analysis Procedures: The study utilizes aerial photographs, satellite imagery, and field observations to collect data. Geospatial analysis techniques are employed to process and analyze the data, including land use/land cover changes and change detection matrices. Floristic composition analysis is conducted to assess the vegetation patterns Question Addressed: The study addresses the question of how lake level changes and human activities impact the environmental health and biodiversity of Lake Chamo. It also explores the potential opportunities and threats related to water utilization and waste management. Conclusion: The study recommends the implementation of spatially oriented environmental planning to ensure the sustainable utilization and maintenance of Lake Chamo's biodiversity resources. It emphasizes the need for proper waste management, improved irrigation facilities, and a buffer zone with specific vegetation patterns to restore and protect the lake outskirt.

Keywords: buffer zone, geo-spatial, lake chamo, lake level changes, sustainable utilization

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: Zegrar Ahmed, Ghabi Mohamed

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The degradation of arid and semi-arid ecosystems in Algeria has become a palpable fact that only hinders progress and rural development. In these exceptionally fragile environments, the decline of vegetation is done according to an alarming increase and wind erosion dominates. The ecosystem is subjected to a long hot dry season and low annual average rainfall. The urgency of the fight against desertification is imposed by the very nature of the process that tends to self-accelerate, resulting when human intervention is not forthcoming the irreversibility situations, preventing any possibility of restoration state of these zones. These phenomena have led to different degradation processes, such as the destruction of vegetation, soil erosion, and deterioration of the physical environment. In this study, the work is mainly based on the criteria for classification and identification of physical parameters for spatial analysis and multi-sources to determine the vulnerability of major steppe formations and their impact on desertification. we used Landsat data with two different dates March 2010 and November 2014 in order to determine the changes in land cover, sand moving and land degradation for the diagnosis of the desertification Phenomenon. The application, through specific processes, including the supervised classification was used to characterize the main steppe formations. An analysis of the vulnerability of plant communities was conducted to assign weights and identify areas most susceptible to desertification. Vegetation indices are used to characterize the steppe formations to determine changes in land use.

Keywords: remote sensing, SIG, ecosystem, degradation, desertification

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Authors: Endalkachew Abebe Kebede, Bojin Bojinov, Andon Vasilev Andonov, Orhan Dengiz

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Remote sensing has a potential application in assessing and monitoring the plants' biophysical properties using the spectral responses of plants and soils within the electromagnetic spectrum. However, only a few reports compare the performance of different remote sensing sensors against in-situ field spectral measurement. The current study assessed the potential applications of open data source satellite images (Sentinel 2 and Landsat 9) in estimating the biophysical properties of the wheat crop on a study farm found in the village of OvchaMogila. A Landsat 9 (30 m resolution) and Sentinel-2 (10 m resolution) satellite images with less than 10% cloud cover have been extracted from the open data sources for the period of December 2021 to April 2022. An Unmanned Aerial Vehicle (UAV) has been used to capture the spectral response of plant leaves. In addition, SpectraVue 710s Leaf Spectrometer was used to measure the spectral response of the crop in April at five different locations within the same field. The ten most common vegetation indices have been selected and calculated based on the reflectance wavelength range of remote sensing tools used. The soil samples have been collected in eight different locations within the farm plot. The different physicochemical properties of the soil (pH, texture, N, P₂O₅, and K₂O) have been analyzed in the laboratory. The finer resolution images from the UAV and the Leaf Spectrometer have been used to validate the satellite images. The performance of different sensors has been compared based on the measured leaf spectral response and the extracted vegetation indices using the five sampling points. A scatter plot with the coefficient of determination (R2) and Root Mean Square Error (RMSE) and the correlation (r) matrix prepared using the corr and heatmap python libraries have been used for comparing the performance of Sentinel 2 and Landsat 9 VIs compared to the drone and SpectraVue 710s spectrophotometer. The soil analysis revealed the study farm plot is slightly alkaline (8.4 to 8.52). The soil texture of the study farm is dominantly Clay and Clay Loam.The vegetation indices (VIs) increased linearly with the growth of the plant. Both the scatter plot and the correlation matrix showed that Sentinel 2 vegetation indices have a relatively better correlation with the vegetation indices of the Buteo dronecompared to the Landsat 9. The Landsat 9 vegetation indices somewhat align better with the leaf spectrometer. Generally, the Sentinel 2 showed a better performance than the Landsat 9. Further study with enough field spectral sampling and repeated UAV imaging is required to improve the quality of the current study.

Keywords: landsat 9, leaf spectrometer, sentinel 2, UAV

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Authors: Neha Devi, P. K. Joshi

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Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. One of the most significant forms of global disturbance, impacting community dynamics, biogeochemical cycles and local and regional climate across a wide range of ecosystems ranging from boreal forests to tropical rainforest is wildfire Assessment of fire danger is a function of forest type, fuelwood stock volume, moisture content, degree of senescence and fire management strategy adopted in the ground. Remote sensing has potential of reduction the uncertainty in mapping fuels. Hyperspectral remote sensing is emerging to be a very promising technology for wildfire fuels characterization. Fine spectral information also facilitates mapping of biophysical and chemical information that is directly related to the quality of forest fire fuels including above ground live biomass, canopy moisture, etc. We used Hyperion imagery acquired in February, 2016 and analysed four fuel characteristics using Hyperion sensor data on-board EO-1 satellite, acquired over the Shiwalik Himalayas covering the area of Champawat, Uttarakhand state. The main objective of this study was to present an overview of methodologies for mapping fuel properties using hyperspectral remote sensing data. Fuel characteristics analysed include fuel biomass, fuel moisture, and fuel condition and fuel type. Fuel moisture and fuel biomass were assessed through the expression of the liquid water bands. Fuel condition and type was assessed using green vegetation, non-photosynthetic vegetation and soil as Endmember for spectral mixture analysis. Linear Spectral Unmixing, a partial spectral unmixing algorithm, was used to identify the spectral abundance of green vegetation, non-photosynthetic vegetation and soil.

Keywords: forest fire fuel, Hyperion, hyperspectral, linear spectral unmixing, spectral mixture analysis

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Authors: Khadija Bouzaachane, El Mahdi El Guarmah

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The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

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Authors: A. Cittadino, P. Gantes, C. Coviella, M. Casset, A. Sanchez Caro

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Three currently active landfills receive the waste from Buenos Aires city and the Great Buenos Aires suburbs. One of the first landfills to receive solid waste from this area was located in Villa Dominico, some 7 km south from Buenos Aires City. With an area of some 750 ha, including riparian habitats, divided into 14 cells, it received solid wastes from June 1979 through February 2004. In December 2010, a biological monitoring program was set up by CEAMSE and Universidad Nacional de Lujan, still operational to date. The aim of the monitoring program is to assess the state of several biological groups within the landfill and to follow their dynamics overtime in order to identify if any, early signs of damage the landfill activities might have over the biota present. Bird and rodent populations, aquatic and terrestrial invertebrates’ populations, cells vegetation coverage, and surrounding areas vegetation coverage and main composition are followed by quarterly samplings. Bird species richness and abundance were estimated by observation over walk transects on each environment. A total of 74 different species of birds were identified. Species richness and diversity were high for both riparian surrounding areas and within the landfill. Several grassland -typical of the 'Pampa'- bird species were found within the landfill, as well as some migratory and endangered bird species. Sherman and Tomahawk traps are set overnight for small mammal sampling. Rodent populations are just above detection limits, and the few specimens captured belong mainly to species common to rural areas, instead of city-dwelling species. The two marsupial species present in the region were captured on occasions. Aquatic macroinvertebrates were sampled on a watercourse upstream and downstream the outlet of the landfill’s wastewater treatment plant and are used to follow water quality using biological indices. Water quality ranged between weak and severe pollution; benthic invertebrates sampled before and after the landfill, show no significant differences in water quality using the IBMWP index. Insect biota from yellow sticky cards and pitfall traps showed over 90 different morphospecies, with Shannon diversity index running from 1.9 to 3.9, strongly affected by the season. An easy-to-perform non-expert demandant method was used to assess vegetation coverage. Two scales of determination are utilized: field observation (1 m resolution), and Google Earth images (that allow for a better than 5 m resolution). Over the eight year period of the study, vegetation coverage over the landfill cells run from a low 83% to 100% on different cells, with an average between 95 to 99% for the entire landfill depending on seasonality. Surrounding area vegetation showed almost 100% coverage during the entire period, with an average density from 2 to 6 species per sq meter and no signs of leachate damaged vegetation.

Keywords: biological indicators, biota monitoring, landfill species diversity, waste management

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Authors: Abubakar Aminu

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Sand dunes, as a major product of desertification, is well known to affect soil resources, water resources and vegetation, especially in arid and semi-arid region; this scenario disrupt the livelihood security of people in the affected areas. The research assessed the episode of sand dune accumulation on water resources, soil and vegetation in Gada local government of Sokoto State, Nigeria. In this paper, both qualitative and quantitative methods were used to generate data which was analyzed and discussed. The finding of the paper shows that livelihood was affected by accumulations of sand dunes as water resources and soils were affected negatively thereby reducing crop yields and making livestock domestication a very difficult and expensive task; the finding also shows that 60% of the respondents agreed to planting of trees as the major solution to combat sand dunes accumulation. However, the soil parameters tested indicated low Organic carbon, low Nitrogen, low Potassium, Calcium and Phosphorus but higher values were recorded in Sodium and Cation exchange capacity which served as evidence of the high or strong aridity nature of the soil in the area. In line with the above, the researcher recommended a massive tree planting campaign to curtail desertification as well as using organic manures for higher agricultural yield and as such, improvement in livelihood security.

Keywords: soils, vegetatio, water, desertification

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Authors: Amina Beldjazia, Djamel Alatou, Khaled Missaoui

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The forest of Mahouna is a part of the mountain range of the Tell Atlas in the northeast of Algeria. It is characterized by a significant biodiversity. The management of this resource requires thorough the understanding of the current state of the vegetation (inventories), degradation factors and ongoing monitoring of the various long-term ecological changes. Digital mapping is a very effective way to in-depth knowledge of natural resources. The realization of a vegetation map based on satellite images, aerial photographs and the use of geographic information system (GIS), shows large values results of the vegetation of the massif in the scientific view point (the development of a database of the different formations that exist on the site, ecological conditions) and economic (GIS facilitate our task of managing the various resources and diversity of the forest). The methodology is divided into three stages: the first involves an analysis of climate data (1988 to 2013); the second is to conduct field surveys (soil and phytoecological) during the months of June and July 2013 (10 readings), the third is based on the development of different themes and synthetic cards by software of GIS (ENVI 4.6 and 10 ARCMAP). The results show: cork oak covers an area of 1147 ha. Depending on the environmental conditions, it rests on sandstone and individualizes between 3 layers of vegetation from thermo-mediterranean (the North East part with 40ha), meso-Mediterranean (1061 ha) and finally the supra-Mediterranean (46ha ). The map shows the current actual state of the cork oak forest massif of Mahouna, it is an older forest (>150 years) where regeneration is absent because of several factors (fires, overgrazing, leaching, erosion, etc.). The cork oak is in the form of dense forest with Laburnum and heather as the dominant species. It may also present in open forest dominated by scrub species: Daphne gniduim, Erica arborea, Calycotome spinosa, Phillyrea angustifolia, Lavandula stoechas, Cistus salvifolius.

Keywords: biodiversity, environmental, Mahouna, Cork oak

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Authors: Saveena Bogtapa, Jagbir Singh Kirti

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Himalaya is one of the most fascinating ranges in the world. In India, it comprises 18 percent of the land area. Lahoul valley which is a part of Trans-Himalaya region is well known for its unique, diverse flora and fauna. It lies in the North-Eastern corner of the state Himachal Pradesh where its altitude ranges between 2500m to 5000m. Vegetation of this region is dry-temperate to alpine type. The diversity of the area is very less, rare, unique and highly endemic. But today, as a lot of environmental degradation has taken place in this hot spot of biodiversity because of frequent developmental and commercial activities which lead to the diversity of this area comes under a real threat. Therefore, as part of the research, butterflies which are known for their attractiveness as well as usefulness to the ecosystem, are used for the study. The diversity of butterflies of a particular area not only provides a healthy environment but also serves as the first step of conservation to the biodiversity. Their distribution in different habitats and altitude type helps us to understand the species richness and abundance in an area. Moreover, different environmental parameters which affect the butterfly community has also recorded. Hence, the present study documents the butterfly diversity in an unexplored habitat and altitude types at Lahoul valley. The valley has been surveyed along with altitudinal gradients (from 2500m to 4500m) and in various habitats like agriculture land, grassland, scrubland, riverine and in different types of forests. Very rare species of butterflies have been explored, and these will be discussed along with different parameters during the presentation.

Keywords: butterflies, diversity, Lahoul valley, altitude, vegetation

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Authors: Khalid Al Mutairi, Mashhor Mansor, Magdy El-Bana, Asyraf Mansor, Saud AL-Rowaily

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Urban expansion and the associated increase in anthropogenic pressures have led to a great loss of the Red Sea’s biodiversity. Floristic composition, diversity, and environmental controls were investigated for 210 relive's on twenty coral islands of Farasan in the Red Sea, Saudi Arabia. Multivariate statistical analyses for classification (Cluster Analysis), ordination (Detrended Correspondence Analysis (DCA), and Redundancy Analysis (RDA) were employed to identify vegetation types and their relevance to the underlying environmental gradients. A total of 191 flowering plants belonging to 53 families and 129 genera were recorded. Geophytes and chamaephytes were the main life forms in the saline habitats, whereas therophytes and hemicryptophytes dominated the sandy formations and coral rocks. The cluster analysis and DCA ordination identified twelve vegetation groups that linked to five main habitats with definite floristic composition and environmental characteristics. The constrained RDA with Monte Carlo permutation tests revealed that elevation and soil salinity were the main environmental factors explaining the vegetation distributions. These results indicate that the flora of the study archipelago represents a phytogeographical linkage between Africa and Saharo-Arabian landscape functional elements. These findings should guide conservation and management efforts to maintain species diversity, which is threatened by anthropogenic activities and invasion by the exotic invasive tree Prosopis juliflora (Sw.) DC.

Keywords: biodiversity, classification, conservation, ordination, Red Sea

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Authors: Meenal Surawar, Rajashree Kotharkar

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Urban Heat Island (UHI) is found more pronounced as a prominent urban environmental concern in developing cities. To study the UHI effect in the Indian context, the Nagpur urban area has been explored in this paper using Landsat 7 ETM+ satellite images through Remote Sensing and GIS techniques. This paper intends to study the effect of LU/LC pattern on daytime Land Surface Temperature (LST) variation, contributing UHI formation within the Nagpur Urban area. Supervised LU/LC area classification was carried to study urban Change detection using ENVI 5. Change detection has been studied by carrying Normalized Difference Vegetation Index (NDVI) to understand the proportion of vegetative cover with respect to built-up ratio. Detection of spectral radiance from the thermal band of satellite images was processed to calibrate LST. Specific representative areas on the basis of urban built-up and vegetation classification were selected for observation of point LST. The entire Nagpur urban area shows that, as building density increases with decrease in vegetation cover, LST increases, thereby causing the UHI effect. UHI intensity has gradually increased by 0.7°C from 2000 to 2006; however, a drastic increase has been observed with difference of 1.8°C during the period 2006 to 2013. Within the Nagpur urban area, the UHI effect was formed due to increase in building density and decrease in vegetative cover.

Keywords: land use/land cover, land surface temperature, remote sensing, urban heat island

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Authors: Suraj Jena, Rabindra Kumar Panda

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The study region of the reported study was in Eastern India, having a sub-humid sub-tropical climate and sandy loam soil. The rainfall in this region has wide temporal and spatial variation. Due to lack of adequate surface water to meet the irrigation and household demands, groundwater is being over exploited in that region leading to continuous depletion of groundwater level. Therefore, there is an obvious urgency in reversing the depleting groundwater level through induced recharge, which becomes more critical under the climate change scenarios. The major goal of the reported study was to investigate the effects of climate change on groundwater recharge and subsequent adaptation strategies. Groundwater recharge was modelled using HELP3, a quasi-two-dimensional, deterministic, water-routing model along with global climate models (GCMs) and three global warming scenarios, to examine the changes in groundwater recharge rates for a 2030 climate under a variety of soil and vegetation covers. The relationship between the changing mean annual recharge and mean annual rainfall was evaluated for every combination of soil and vegetation using sensitivity analysis. The relationship was found to be statistically significant (p<0.05) with a coefficient of determination of 0.81. Vegetation dynamics and water-use affected by the increase in potential evapotranspiration for large climate variability scenario led to significant decrease in recharge from 49–658 mm to 18–179 mm respectively. Therefore, appropriate conjunctive use, irrigation schedule and enhanced recharge practices under the climate variability and land use/land cover change scenarios impacting the groundwater recharge needs to be understood properly for groundwater sustainability.

Keywords: Groundwater recharge, climate variability, Land use/cover, GCM

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Authors: Jessica Vasil'chuk, Elena Ivanova, Pavel Krechetov, Vladimir Litvinsky, Nadine Budantseva, Julia Chizhova, Yurij Vasil'chuk

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Carbonate minerals’ isotopic composition is widely used as a proxy for environmental parameters of the past. Pedogenic carbonate coatings on lower surfaces of coarse rock fragments are studied in order to indicate the climatic conditions and predominant vegetation under which they were formed. The purpose of the research is to characterize the isotopic composition of carbonate pedofeatures in soils of Minusink Hollow and estimate its correlation with isotopic composition of soil pore water, precipitation, vegetation and parent material. The samples of pedogenic carbonates, vegetation, carbonate parent material, soil water and precipitation water were analyzed using the Delta-V mass spectrometer with options of a gas bench and element analyser. The soils we studied are mainly Kastanozems that are poorly moisturized, therefore soil pore water was extracted by ethanol. Oxygen and carbon isotopic composition of pedogenic carbonates was analyzed in 3 key sites. Kazanovka Khakass state national reserve, Hankul salt lake, region of Sayanogorsk aluminum smelter. Vegetation photosynthetic pathway in the region is mainly C3. δ18O values of carbonate coatings in soils of Kazanovka vary in a range from −7.49 to −10.5‰ (vs V-PDB), and the smallest value −13.9‰ corresponds the coatings found between two buried soil horizons which 14C dates are 4.6 and 5.2 kyr BP. That may indicate cooler conditions of late Holocene than nowadays. In Sayanogorsk carbonates’ δ18O range is from −8.3 to −11.1‰ and near the Hankul Lake is from −9.0 to −10.2‰ all ranges are quite similar and may indicate coatings’ uniform formation conditions. δ13C values of carbonate coatings in Kazanovka vary from −2.5 to −6.7‰, the highest values correspond to the soils of Askiz and Syglygkug rivers former floodplains. For Sayanogorsk the range is from −4.9 to −6.8‰ and for Hankul from −2.3 to −5.7‰, where the highest value is for the modern salt crust. δ13C values of coatings strongly decrease from inner (older) to outer (younger) layers of coatings, that can indicate differences connected with the diffusion of organic material. Carbonate parent material δ18O value in the region vary from −11.1 to −12.0‰ and δ13C values vary from −4.9 to −5.7‰. Soil pore water δ18O values that determine the oxygen isotope composition of carbonates vary due to the processes of transpiration and mixing in the studied sites in a wide range of −2.0 to −13.5‰ (vs V-SMOW). Precipitation waters show δ18O values from -6.6‰ in May and -19.0‰ in January (snow) due to the temperature difference. The main conclusions are as follows: pedogenic carbonates δ13C values (−7…−2,5‰) show no correlation with modern C3 vegetation δ13C values (−30…−26‰), expected values under such vegetation are (−19…−15‰) but are closer to C4 vegetation. Late Holocene climate for the Minusinsk Hollow according to obtained data on isotope composition of carbonates and soil pore water chemical composition was dryer and cooler than present, that does not contradict with paleocarpology data obtained for the region. The research was supported by Russian Science Foundation (grant №14-27-00083).

Keywords: carbon, oxygen, pedogenic carbonates, South Siberia, stable isotopes

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Authors: H. Tavakoli, S. S. Mohtasebi, R. Alimardani, R. Gebbers

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Nitrogen (N) is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. N demand of crops varies spatially across fields due to spatial differences in soil conditions. In addition, the response of a crop to the fertilizer applications is heavily reliant on plant available water. Matching N supply to water availability is thus essential to achieve an optimal crop response. The objective of this study was to determine effect of drought stress on estimation of nitrogen status of winter wheat by some vegetation indices. During the 2012 growing season, a field experiment was conducted at the Bundessortenamt (German Plant Variety Office) Marquardt experimental station which is located in the village of Marquardt about 5 km northwest of Potsdam, Germany (52°27' N, 12°57' E). The experiment was designed as a randomized split block design with two replications. Treatments consisted of four N fertilization rates (0, 60, 120 and 240 kg N ha-1, in total) and two water regimes (irrigated (Irr) and non-irrigated (NIrr)) in total of 16 plots with dimension of 4.5 × 9.0 m. The indices were calculated using readings of a spectroradiometer made of tec5 components. The main parts were two “Zeiss MMS1 nir enh” diode-array sensors with a nominal rage of 300 to 1150 nm with less than 10 nm resolutions and an effective range of 400 to 1000 nm. The following vegetation indices were calculated: NDVI, GNDVI, SR, MSR, NDRE, RDVI, REIP, SAVI, OSAVI, MSAVI, and PRI. All the experiments were conducted during the growing season in different plant growth stages including: stem elongation (BBCH=32-41), booting stage (BBCH=43), inflorescence emergence, heading (BBCH=56-58), flowering (BBCH=65-69), and development of fruit (BBCH=71). According to the results obtained, among the indices, NDRE and REIP were less affected by drought stress and can provide reliable wheat nitrogen status information, regardless of water status of the plant. They also showed strong relations with nitrogen status of winter wheat.

Keywords: nitrogen status, drought stress, vegetation indices, precision agriculture

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Authors: Abdulkadir I.

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Scientists have come to terms with the fact that climate change has been and is expected to cause a significant increase in the severity and frequency of drought events. The northeast region of Nigeria is one of the most, if not the most, affected regions by drought in the country. Therefore, it is on this note that the present study applied ArcGIS and XLSTAT Software and explored drought and its trend in the northeast region of the country using the vegetation health index (VHI), Mann-Kendal, and Sen’s slope between 2001 and 2020. The study also explored the areas that remained under drought and no-drought conditions at intervals of five years for the period under review. The result of Mann-Kendal (-0.07) and Sen’s slope (-0.19) revealed that there was a decreasing trend in VHI over the period under review. The result further showed that the period between 2010 and 2015 had a minimum area of no-drought conditions of about 24%, with Gombe State accounting for the lowest percentage among the six States, about 0.9% of the total area of no-drought conditions. The result further showed the areas that were under drought conditions between 2010 and 2015 represented about 9.1%, with Borno State accounting for the highest percentage among the six States, about 2.5% of the total area under drought conditions. The masked-out areas stood at 66.8%, with Borno State accounting for the highest percentage among the six States, about 20.2% of the total area under drought conditions. Therefore, collective efforts are needed to put in place sustainable land management in the affected areas so as to mitigate the sprawl of desertification in the region.

Keywords: climate change, drought, Mann Kendal, sustainable land management, vegetation health index

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