NDVI and vegetation cover

This session discusses various methods which acquire, store, analyze and visualize geospatial data, and presents the outcomes of empirical studies using GIS or mapping methods. The session also deals with applications of digital data, and GIS, and mapping to various fields of earth and planetary science and human society. All presentations and discussion of this session are made in English.

One of the major impacts associated with unplanned rapid urban growth is the decrease of urban vegetation, which is often replaced with impervious surfaces such as buildings, parking lots, roads, and pavements. Consequently, as the percentage of impervious surfaces continues to increase at the expense of vegetation cover, surface urban heat island (SUHI) forms and becomes more intense. The Colombo Metropolitan Area (CMA), Sri Lanka, is one of the rapidly urbanizing metropolitan regions in South Asia. In this study, we examined the spatiotemporal variations of land surface temperature (LST) in the CMA in the context of the SUHI phenomenon using Landsat data. More specifically, we examined the relationship of LST with the normalized difference vegetation index (NDVI) and the normalized difference built-up index (NDBI) at three time points (1997, 2007 and 2017). In addition, we also identified environmentally critical areas based on LST and NDVI. We found significant correlations of LST with NDVI (negative) and NDBI (positive) (p < 0.001) across all three time points. Most of the environmentally critical areas are located in the central business district (CBD), near the harbor, across the coastal belt, and along the main transportation network. We recommend that those identified environmentally critical areas be considered in the future urban planning and landscape development of the city. Green spaces can help improve the environmental sustainability of the CMA.

Eucalyptus merupakan salah satu jenis tanaman kehutanan yang banyak dibudidayakan di berbagai negara karena memiliki nilai ekonomi dan lingkungan yang tinggi. Namun, tanaman eucalyptus juga rentan terhadap serangan hama dan penyakit yang dapat menurunkan produktivitas dan kualitasnya. Pemantauan atau monitoring yang akurat dan tepat waktu diperlukan untuk mengendalikan hama dan penyakit tanaman eucalyptus. Monitoring hama dan penyakit tanaman eucalyptus secara konvensional dilakukan dengan cara observasi langsung oleh manusia, namun metode ini memiliki beberapa kelemahan. Oleh karena itu, perlu adanya upaya untuk meningkatkan efektivitas dan efisiensi monitoring hama dan penyakit tanaman eucalyptus dengan memanfaatkan teknologi kecerdasan buatan atau Artificial Intelligence (AI). AI dapat digunakan untuk melakukan deteksi dan klasifikasi hama dan penyakit tanaman eucalyptus secara otomatis dengan menggunakan algoritma pembelajaran mesin atau pembelajaran mendalam dan pengolahan citra. Tujuan dari penelitian ini adalah untuk menyajikan tinjauan komprehensif tentang penggunaan AI dalam mendeteksi hama dan penyakit tanaman eucalyptus dengan menggunakan metode Systematic Literature Review (SLR). Penelitian ini mengidentifikasi, mengevaluasi, dan menganalisis literatur yang relevan dengan topik penelitian dari berbagai sumber digital. Penelitian ini juga memberikan gambaran menyeluruh tentang perkembangan terkini, metode-metode yang digunakan, hasil-hasil yang dicapai, serta tantangan dan peluang yang ada dalam bidang penelitian AI untuk deteksi hama dan penyakit tanaman eucalyptus.

Land transformation is caused by natural as well as anthropogenic driving forces and its impact on the regional environment is a key issue in understanding the relationship between society and the environment. Here, we investigate Land Use Land Cover (LULC) change over four decades, based on Landsat satellite imagery for 1987, 1997, 2007, and 2017, for the Barddhaman district of West Bengal, India. In total, six land use and land cover types have been identified. Over the period in question, there are notable increases in the area under built-up land, plantations and water bodies, whereas there has been a marked decrease in forest cover, agricultural land, and in bare land. The diverse effects of land transformation on the natural environment have been assessed using Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Leaf Area Index (LAI), Effective Roughness Length (ERL), and Surface Albedo (SA). Overall, mean annual LST increased by 2.91C during the study period, while there were reduced values for vegetation indices and an increase in the water index over the period 1987–2017. LAI and ERL both exhibit notable decreases, although the pattern was not uniform across the study area. For example, LAI values increased over time in the Kalna, Memari, Jamalpur, Ausgram, and Kanksa regions. In Faridpur-Durgapur, Raniganj, Asansol, and Raina, increases in surface albedo and ERL were more marked than in other regions. Negative correlations
are found between LST-NDVI and NDVI-NDWI, while there is no correlation between LST and NDWI. During the period 1987–2017, NDVI values have declined, although the NDWI shows no clear trend. LULC change is shown to have had a series of negative impacts on the environment of the Barddhaman district. In response, technological, economic, policy, or legislation measures are needed to restore degraded ecosystem services in the district as well as other areas where similar impacts are experienced.

The preservation of biodiversity hotspots in rapidly urbanizing regions is an increasing global concern. In this context, the present study employs remote sensing techniques to evaluate the effectiveness of public policies in the Serra do Japi Reserve, a rare Atlantic Forest remnant in São Paulo State, renowned for its ecological richness and high species endemism. Using multitemporal satellite imagery, the study assessed changes in vegetation cover between 2013 and 2023 to determine the impact of implemented policies, particularly following the area's designation as a natural heritage site in 1983. The results revealed consistently high Normalized Difference Vegetation Index (NDVI) values within the Serra do Japi Preservation, Restoration, and Recovery Zone and the surrounding Jundiaí region over the ten-year period, indicating stable preserved vegetation cover. Histogram analysis of reclassified ΔNDVI values showed that 94.5% of pixels within the Serra do Japi Zone exhibited no significant change, while Rev. 2 77.5% of pixels in the urban area of Jundiaí remained stable, indicating greater vegetation variability in urbanized regions compared to the protected area. Additionally, only 2% of pixels within Serra do Japi indicated possible vegetation loss, a proportion notably lower than that observed in the municipality's urban area. Localized vegetation loss was detected in the southern areas adjacent to the reserve, underscoring the importance of continuous monitoring and restoration efforts. The use of remote sensing proved to be a reliable and cost-effective tool for detecting subtle spatial and temporal changes in vegetation. Therefore, reinforcing conservation frameworks and ensuring the continuation of long-term monitoring programs are essential to prevent future degradation and maintain the ecological resilience of the Serra do Japi Reserve.

For the purposes of environmental monitoring of the assessment of the impact of urbanisation processes on the environment, the normalized difference vegetation index (NDVI) can be used, the determination of which makes it possible to assess the degree of favourability of the city's green areas.

Kecamatan Muaragembong sebagai muara dari Sungai Citarum, mengalami dinamika ekosistem yang signifikan akibat peningkatan intensitas abrasi dan sedimentasi di area pesisir yang berpotensi mempengaruhi kondisi ekosistem sekitarnya, khususnya ekosistem mangrove. Penelitian ini bertujuan untuk mengevaluasi dan memperkirakan tingkat kesehatan, kerusakan, dan luas total ekosistem mangrove di Kecamatan Muaragembong melalui analisis kerapatan tajuk. Data kerapatan tajuk dikumpulkan di lapangan menggunakan metode purposive stratified sampling dengan pendekatan fotografi hemisferik. Hasil klasifikasi menunjukkan luas total mangrove yang berhasil dipetakan seluas 1.073,65 ha, dengan koefisien Kappa sebesar 0,87, menandakan tingkat akurasi yang sangat baik. Evaluasi kesehatan komunitas mangrove mengungkapkan, bahwa 49,66% dari area mangrove berada dalam kondisi baik, 19,80% dalam kondisi normal, dan 30,54% dalam kondisi buruk. Data kerapatan tajuk menunjukkan hubungan sedang dengan koefisien determinasi sebesar 0,4219 (42,19%), yang dipengaruhi oleh faktor eksternal dan resolusi spasial citra yang digunakan.

Drought is one of the most complex natural disasters that causes economic, social and environmental damage and is often described as a creeping phenomenon. Drought monitoring using satellite images can represent the severity of drought in areas with a lack of meteorological precipitation data and compensate for its spatial and temporal deficiency. In this research, the drought of Golestan province has been investigated using SPI, TCI, VCI and VHI indices and with the help of MODIS sensor satellite images. Therefore, first, VHI, VCI and TCI drought index maps were extracted. The findings in the TCI index study showed that in 2000, more than 80% of the studied area experienced severe drought. Similarly, in 2010, 2017 and 2018, a significant part of the studied area was in a severe drought situation. By examining the VCI index, 2008, and 2011. The maps also show that a very severe meteorological drought occurred in 2008. In the study of the VHI index during a period of 21 years in the studied area, it showed that the years

Various natural and anthropogenic activities such as climate change, urbanization and industrialization play a vital role in changing the land characteristics. These changes does not only affect the human lives and activities, but also results in tremendous decrease in agricultural productivity and arable land. Thus, the purpose of this study is to analyze the land degradation and desertification in Pakistan using satellite imageries data acquired from the Landsat 8 and 9. For the empirical analysis, various indices such as Normalized Difference Vegetation Index, Normalized Difference Bare Soil Index, Supervised classification and Land Surface Temperature are examined using Google earth engine cloud computing platform. The results showed that desertified and built-up-land are increasing, while degraded land, arable land, and vegetative land are decreasing in the study area. Also, results of land surface temperature analysis showed a rise in the temperature up to 3.06 0 C as compared to previous two years. Moreover, estimated findings from regression analysis showed that Normalized Difference Vegetation Index, and Normalized Difference Bare Soil Index positively affects the Land Surface Temperature. The findings of study are important for government and concern stakeholders to take necessary measures to stop the conversion of productive green land into unproductive degraded and desertified land.

Geographic Information System (GIS) software was used to create a watershed vulnerability model for Bernalillo County, New Mexico. Watershed vulnerability was investigated as a function of soil erosion and infiltration criteria: precipitation, land slope, soil erodibility (K-factor), vegetation cover (NDVI), land use, drainage density, saturated hydraulic conductivity, and hydrologic soil group. Respective criteria weights were derived using a Fuzzy Analytic Hierarchy Process (FAHP) supported by expert opinion. A survey of 10 experts, representing New Mexico Institute of Mining and Technology (NMT), the New Mexico Bureau of Geology and Mineral Resources (NMBGMR), and the United States Geologic Survey (USGS), provided model input data for an integrated pair-wise comparison matrix for soil erosion and for infiltration. Individual criteria weights were determined by decomposing the respective fuzzy synthetic extent matrix using the centroid method. GIS layers were then combined based on criteria weights to produce maps of soil erosion potential and infiltration potential. A composite watershed vulnerability map was generated by equal weighting of each input map. Model results were categorized into five vulnerability categories: not vulnerable (N), slightly vulnerable (SV), moderately vulnerable (MV), highly vulnerable (HV), and extremely vulnerable (EV). The resulting FAHP/GIS model was used to generate a watershed vulnerability map of discrete areas in Bernalillo County, which may be vulnerable to stormwater run-off events and soil erosion. Such high volume run-off events can cause erosion damage to property and infrastructure.

Urbanization often results in a rise in urban development and a decrease in green cover, which are primary catalysts in increasing urban temperature. The elevated temperature of the microclimate of metropolitan areas, compared to their vicinities, is referred to as Urban Heat Island (UHI). Heat islands cause human discomfort, and life-threatening health issues along with increased energy consumption and aggravated pollution. This paper attempts to comprehend the impact and influence of green cover on the intensity of UHI in the microclimate of Aligarh city areas using the mobile traverse method. Two research objectives formulated to accomplish the study include the evaluation of the impact of green cover on the UHI effect in microclimatic conditions and a proposal of a mitigation strategy to alleviate the UHI impact in the affected area. This study dealt with only ambient D.B.T. and relative humidity-R.H. (%) observations and was confined to only two specific identified locations in Aligarh city. This research determined the presence and extent of UHI's microclimate variation concerning green cover within urban communities of distinct environmental layouts and functionalities. Spatial analysis of the data showed that with the 10% reduction in green cover, there was a rise in temperature by 0.082°C in short distances. These findings are beneficial for reducing the impact in UHI-affected areas and for developing a thermally comfortable environment along with improved urban planning.

This study focuses on evaluating the potential of ALOS/PALSAR time-series data to analyze the activation of deep-seated landslides in the foothill zone of the high mountain Alai range in the southern Tien Shan (Kyrgyzstan). Most previous field-based landslide investigations have revealed that many landslides have indicators for ongoing slow movements in the form of migrating and newly developing cracks. L-band ALOS/PALSAR data for the period between 2007 and 2010 are available for the 484 km 2 area in this study. We analyzed these data using the Small Baseline Subset (SBAS) time-series technique to assess the surface deformation related to the activation of landslides. We observed up to ±17 mm/year of LOS velocity deformation rates, which were projected along the local steepest slope and resulted in velocity rates of up to -63 mm/year. The obtained rates indicate very slow movement of the deep-seated landslides during the observation time. We also compared these movements with precipitation and earthquake records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with an earthquake event. Overall, the results of this study indicated the great potential of L-band InSAR time series analysis for

This study focuses on evaluating the potential of ALOS/PALSAR time-series data to analyze the activation of deep-seated landslides in the foothill zone of the high mountain Alai range in the southern Tien Shan (Kyrgyzstan). Most previous field-based landslide investigations have revealed that many landslides have indicators for ongoing slow movements in the form of migrating and newly developing cracks. L-band ALOS/PALSAR data for the period between 2007 and 2010 are available for the 484 km 2 area in this study. We analyzed these data using the Small Baseline Subset (SBAS) time-series technique to assess the surface deformation related to the activation of landslides. We observed up to ±17 mm/year of LOS velocity deformation rates, which were projected along the local steepest slope and resulted in velocity rates of up to -63 mm/year. The obtained rates indicate very slow movement of the deep-seated landslides during the observation time. We also compared these movements with precipitation and earthquake records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with an earthquake event. Overall, the results of this study indicated the great potential of L-band InSAR time series analysis for

Hyperspectral Imaging has become an important method in monitoring vegetation and crops and producing information regarding onset of diseases. The availability of spectrometers in the market is not only costly but also requires standard-operating-procedures in using them. The use of Specim IQ, a handheld spectrometer with a wavelength-captivating-range of 400-1000 nm has been found to be optimistic in field-application with least complexity. In this paper, an early possible detection of downy mildew has been analysed through the difference in spectral distribution patterns through the reflectance-wavelength graph so that the well-advanced result may avert any significant damage over the visual eyes.

Damien Closson 1, Yvers Cornet 1, André Ozer 1, Herbert Hansen 2, Dominique Derauw 2, Christian Barbier 2 ... 1 Laboratoire de Géomorphologie et Télédétection, Université de Liège, Belgium 2 Centre Spatial de Liège, Université de Liège, Avenue du Pré-Aily, B-4031 Angleur, ...

Due to the excessive use of natural resources in the contemporary world, the importance of ecological and environmental condition modeling has increased. Wetlands and cities represent the natural and artificial strategic areas that affect ecosystem conditions. Changes in the ecological conditions of these areas have a great impact on the conditions of the global ecosystem. Therefore, modeling spatiotemporal variations of the ecological conditions in these areas is critical. This study was aimed at comparing degrees of variation among surface ecological conditions due to natural and unnatural factors. Consequently, the surface ecological conditions of Gomishan city and Gomishan wetland in Iran were modeled for a period of 30 years, and the spatiotemporal variations were evaluated and compared with each other. To this end, 20 Landsat 5, 7, and 8, and 432 Moderate Resolution Imaging Spectroradiometer (MODIS), monthly land surface temperature (LST) (MOD11C3) and normalized difference ve...

Hyperspectral Imaging has become an important method in monitoring vegetation and crops and producing information regarding onset of diseases. The availability of spectrometers in the market is not only costly but also requires standard-operating-procedures in using them. The use of Specim IQ, a handheld spectrometer with a wavelength-captivating-range of 400-1000 nm has been found to be optimistic in field-application with least complexity. In this paper, an early possible detection of downy mildew has been analysed through the difference in spectral distribution patterns through the reflectance-wavelength graph so that the well-advanced result may avert any significant damage over the visual eyes.

The widespread oil extraction in the Niger Delta and the impacts on different types of vegetation are poorly understood due to lack of ground access. This study aims to determine the impact of oil spills on vegetation in the Niger Delta using a Landsat satellite-derived normalised difference vegetation index (NDVI). The impact of oil spill volume and time after an oil spill on the health of different types of vegetation were evaluated, and the time series of the changes in NDVI were analysed to determine the medium- and long-term responses of vegetation to oil spill exposure, using a combination of linear regression and paired t-tests. With regards to the relationship between spill volume and NDVI, a moderate correlation (R
2 = 0.5018) was observed for spill volumes in the range of 401–1000 barrels for sparse vegetation, for volumes greater than 1000 barrels for dense vegetation (R 2 = 0.4356),
whilst no correlation was found for mangrove vegetation at any range of spill volume. Similarly, the results of the paired t-test confirmed a significant difference (p-value < 0.05) between the change in NDVI values for spill sites and non-spill sites for all vegetation types, with the sparse vegetation being the most affected of the three types. However, the impact of the oil spill on vegetation over a period is not statistically significant. The outcomes of this study provide insights into how different types of vegetation in the Niger Delta respond to oil spills, which could ultimately help in designing an oil spill clean-up program to reduce the impact on the environment.

Urban areas are quickly expanding around the world, promoting deep changes in biodiversity. However, certain biogeographic realms, like the Afrotropics, are clearly understudied despite urbanization overlapping with their biodiversity hotspots. A commonly highlighted reason for the lack of information from the Afrotropics has been the logistical problem associated with data collection in the field. Recent advances in satellite remote sensing imagery offer an excellent opportunity to revert this situation, enhancing the understanding of urban impacts on biodiversity. The Normalized Difference Vegetation Index (NDVI) is the most commonly used remotely sensed spectral index (hereafter: indicator) despite several studies showing its limitations and advocating for the use of alternative indicators. Thus, this study identifies the best indicators of bird taxonomic, functional, and phylogenetic diversity in Afrotropical urban and non-urban areas. To do so, we sampled birds at 400 points equally distributed across eight Nigerian areas, two vegetation zones (rainforest vs savannah), and two habitats (urban vs non-urban), and extracted 29 indicators (mean and SD) at 50-m radius of each point (exact area of bird censuses). Random Forest Regressions and Generalized Linear Mixed Effect Models were used to identify the topmost ranked indicator of each avian diversity component, and its variation between urban and non-urban areas. The Modified Chlorophyll Absorption Ratio Index (MCARI) was the best indicator of taxonomic and phylogenetic diversity, while the Normalized Difference Water Index II (NDWI2) and Soil Adjusted Total Vegetation Index (SATVI) got the most support for functional diversity and phylogenetic divergence, respectively. In most cases, NDVI ranks very low (occupying the 25th percentile), not supporting its use for monitoring avian diversity in the Afrotropics. MCARI and NDWI2 showed different associations with taxonomic and functional diversity depending on the habitat, highlighting the need for considering urban areas differently while using these indicators. Our study provides useful tools to remotely monitor Afrotropical avian diversity, particularly in expansive, inaccessible or insecure areas, which could also be more cost-effective.

The purpose of this research is to estimate above ground biomass and above ground carbon stock from the living trees without below ground carbon stock, necromass, litters and the soil carbon in the urban forest in Ketapang district and to see the spreading of carbon in the map view. The method that utilized is non destructive method, which using a combination between Landsat 7 ETM+ satellite imaginary and allometrics method to estimate the carbon stock. The urban forest in Ketapang district is fresh water swamp forests which have a big biodiversity of its flora and the fauna. The result of this research show that the urban forest have an enough big carbon stock especially carbon stock from the stem, the branch, and the leaf, and its total value is 6.216,26 ton C from the total 87,91 hectare of the vegetation areal in the urban forest have, it's have a potential to sequestration of carbon as much as 18.202,91 ton CO 2 equivalent, and from the total of carbon stock, we have known that the average of the carbon stock is 70,71 ton C/ha or its equal with it's potension to absorb the carbon dioxide on the atmospheric as equal as 207,76 ton CO 2 ha-1 equivalent.

Horticultural crops unlike field crops are perennial in nature, not having distinct phenology. It is difficult to discriminate horticultural crops using temporal multispectral data. Major limitation of multispectral data is lesser number of bands and mixed pixels which may not be able to discriminate fruit crops but the hyperspectral data has the advantage of having relatively large number of narrow, contiguous bands which lead to continuous spectral reflectance curve, making intricate details visible in the spectrum. For comparison of multispectral data with hyperspectral data, the hyperspectral data which have 2151 numbers of bands has been brought to multispectral level as because multispectral data has very less number of bands. Therefore, in the hyperspectral data, average at 50 nm, 100 nm and 250 nm interval was taken to reduces the data set into 42, 22 and 9 bands. The 4 tier statistical procedure which includes one way Analysis of variance (ANOVA), Classification and regression tree (CART), Jeffries-Matusita (J-M) distance and Linear discriminant analysis (LDA) technique was applied in the reduced band data set. The result of J-M distance and LDA were used to observe whether the reduced band data set can be able to discriminate the fruit crops. The study reveals the limitation of multispectral data in fruit crop discrimination. As the number of bands gets reduced the discriminative power of the data set also gets down.

Spatial and temporal variation of land surface temperature
(LST) in the Kandy District of Sri Lanka
Rashmika Nawarathna B N, Rekha Nianthi, Subasinghe S I S
Department of Geography, University of Peradeniya, Peradeniya, Sri Lanka

In Sri Lanka, there is a considerable increase in the average annual LST in the city of Colombo, and it might have occurred in the city of Kandy as well. Increases in LST can affect to many issues. Research on LST is useful for green city planning and policymaking for development in urban areas. This study examined the spatial and temporal variation of LST in the Kandy District in 1996 and 2017. Geospatial tools such as remote sensing and GIS were used to analyse data. Landsat satellite data has been collected by the United States Geological Survey. The NDVI, NDBI, and NDWI were used to classify the different land uses and to find out the relationships between LST. The mean LST was increased by 2.36°C in 2017 compared to 1996. The LST was higher in the City of Kandy in 2017 than in 1996. The Eastern part of the Kandy was slightly higher in 2017 than in 1996. There is a significant negative correlation (α=0.01) between LST and NDVI. The NDBI increased by 0.11 in 2017, compared to 1996 and spread into suburb areas. The significant strong relationship between NDBI and LST was identified. The lack of satellite images is one of the serious barriers to analysing the LST. Land-use changes, increased build-up areas and decreases in vegetation and water bodies have affected to rise in land surface temperature in the Kandy. The future land use planning should be considered to mitigate the effects of LST in Kandy City.

In recent years, a critical understanding of the sustainable urban environment has become central to many urban studies, leading numerous scholars to employ geospatial tools and techniques to examine the sustainability of growing cities in the developing world. In this study, the Colombo district where the capital city of Sri Lanka is located, was selected with the prospect of monitoring the impacts of urbanization on environmental sustainability. The study uses the spectral indices of remote sensing, including the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-Up Index (NDBI), Land Surface Temperature (LST), and Environmental Criticality Index (ECI) to detect the aspects of urbanization and environmental sustainability of the study area. The results show that there has been a dramatic increase in environment criticality from 1997 to 2008, and a slight decrease indicated from 2008 to 2017, coinciding with the government urban planning initiatives. However, the decline of environmental sustainability of the city center and along the transport corridors could be identified in the context of this study. Finally, by drawing attention of the landscape and land use planners, the study emphasizes the aspects that should be considered in future urban planning.

In this paper, nonlinear vibration of the functionally graded rectangular plates made of piezoelectric BaTiO3 and magnetostrictive CoFe2O4, whit simply supported boundary condition has been investigated. It is assumed that the composition is varied from the bottom surfaces to top surface, i.e., the top surface of the plate is piezoelectric-rich, whereas the bottom surface is magnetostrictive-rich. In addition, material properties are graded along the thickness according to volume fraction power-law distribution. Based on the Reddy’s third-order share deformation plate theory, the governing equations of motion, whereas Maxwell equations for electrostatics and magnetostatics are used to model the electric and magnetic behavior. Then, the nonlinear partial differential equations of motion are transformed into five coupled nonlinear ordinary differential equations by using the Galerkin method. Afterward, the obtained coupled ordinary differential equations are reduced to a single nonlinear differential equation which include nonlinear inertia and stiffness terms with quadratic and cubic nonlinear terms. A perturbation method is used to solve the equation of motion analytically. The results for natural frequency are compared with the available results for isotropic, laminated and piezo-laminated plates and good agreement is found between the results of present study with the results of previously published papers. In the forced vibration, primary, super-harmonic resonances are studied and the frequency response equation has been obtained. Because of the importance of the primary resonance, the stability of the steady-state motion is investigated for the primary resonance, The applied external force is assumed to be harmonic in time with a constant amplitude.

While the world population continues to grow, increasing the need to produce more and better-quality food, climate change, urban growth and unsustainable agricultural practices accelerate the loss of available arable land, compromising the sustainability of agricultural lands both in terms of productivity and environmental resilience, and causing serious problems for the production-consumption balance. This scenario highlights the urgent need for agricultural modernization as a crucial step to face forthcoming difficulties. Precision agriculture techniques appear as a feasible option to help solve these problems. However, their use needs to be reinvented and tested according to different parameters, in order to define both the environmental and the economic impact of these new technologies not only on agricultural production, but also on agricultural sustainability. This paper intends, therefore, to contribute to a better understanding of the impact of precision agriculture through the use of unmanned aerial vehicles (UAV)/remotely piloted aircraft systems (RPAS) and normalized difference vegetation index (NDVI) techniques in small Mediterranean farms. We present specific data obtained through the application of the aforementioned techniques in three farms located along the Portuguese-Spanish border, considering three parameters (seeding failure, differentiated irrigation and differentiated fertilization) in order to determine not only the ecological benefits of these methods, but also their economic and productivity aspects. The obtained results, based on these methods, highlight the fact that an efficient combination of UAV/RPAS and NDVI techniques allows for important economic savings in productivity factors, thus promoting a sustainable agriculture both in ecological and economic terms. Additionally, contrary to what is generally defended, even in small farms, as the ones assessed in this study (less than 50 ha), the costs associated with the application of the aforementioned precision agriculture processes are largely surpassed by the economic gains achieved with their application, regardless of the notorious environmental benefits introduced by the reduction of crucial production inputs as water and fertilizers.

This study utilized a remotely sensed dataset with a high spatial resolution of 3 m to predict species diversity in the Bobiri Forest Reserve (BFR), a moist semi-deciduous tropical forest in Ghana. We conducted a field campaign of tree species measurements to achieve this objective for species diversity estimation. Thirty-five field plots of 50 m × 20 m were established, and the most dominant tree species within the forest were identified. Other measurements, such as diameter at breast height (DBH ≥ 5 cm), tree height, and each plot's GPS coordinates, were recorded. The following species diversity indices were estimated from the field measurements: Shannon-Wiener (H ′ ), Simpson diversity index (D 2 ), species richness (S), and species evenness (J ′ ). The PlanetScope surface reflectance data at 3 m spatial resolution was acquired and preprocessed for species diversity prediction. The spectral/pixel information of all bands, except the coastal band, was extracted for further processing. Vegetation indices (VIs) (NDVI-normalized difference vegetation index, EVI-enhanced vegetation index, SRI-simple ratio index, SAVI-soil adjusted vegetation index, and NDRE-normalized difference red edge index) were also calculated from the spectral bands and their pixel value extracted. A correlation analysis was then performed between the spectral bands and VIs with the species diversity index. The results showed that spectral bands 6 (red) and 2 (blue) significantly correlated with the two main species diversity indices (S and H ′ ) due to their influence on vegetation properties, such as canopy biomass and leaf chlorophyll content. Furthermore, we conducted a stepwise regression analysis to investigate the most important spectral bands to consider when estimating species diversity from the PlanetScope satellite data. Like the correlation results, bands 6 (red) and 2 (blue) were the most important bands to be considered for predicting species diversity. The model equations from the stepwise regression were used to predict tree species diversity. Overall, the study's findings emphasize the relevance of remotely sensed data in assessing the ecological condition of protected areas, a tool for decision-making in biodiversity conservation.

Pests and diseases cause major harm during crop development. Also plant stress affects crop quality and quantity. Recent developments in high resolution remotely sensed data has seen a great potential in mapping cropland areas infected by pests and diseases, as well as potential vulnerable areas over expansive areas. Crop health monitoring in this study was carried out using remote sensing techniques. The present study was carried out in MPKV, Rahuri, Ahmednagar District, Maharashtra. Vegetation indices like Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were used to classify the crops into healthy and dead or unhealthy one. Sentinel-2 image data from October 2019 to January 2020 processed in Arc GIS 10.1 were used for this study. Vegetation is a key component of the ecosystem and plays an important role in stabilizing the global environment. The result showed that the average vegetation Original Research Article Kamble et al.; CJAST, 40(4): ...

There is a relationship between spectral indices, urban morphology, and spatial patterns with land surface temperature (LST). In this paper, LST and spectral indices in Tehran have been calculated using Landsat satellite images from 2000 to 2019. LST was improved and the results were evaluated using synoptic stations in Tehran. Pearson correlation coefficient and mean root error are used to evaluate the accuracy of temperature difference. The spatial variables affecting LST are examined including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Digital Elevation Model (DEM), Building Density (BD), and Road Density (RD). The rise in the temperature of the land surface temperature, which causes the formation of heat islands, is continuously increasing over time and can be seen in some parts of the city. The findings indicate that LST relative accuracy was 0.98 and the root-mean-square error is 2.65 °C. The distance pattern based on the Pearson correlation test showed an effective relationship between LST and the examined indicators. Spots prone to heat islands were identified. Each of the heat island areas of Tehran was studied according to population centers (dense areas using residential, commercial, and industrial lands). The built-up and barren areas index had the highest correlation with surface temperature in most areas. The results showed that regions 9, 13, 18, 21, and especially region 22, which has the most barren land, have the highest surface temperature compared to the surrounding areas. The findings of this study can be used in future urban planning and policy-making.

Hutan bakau often reffered to as 'mangrove', is the ecosystem transition between the land and sea or with waters around the estuary of the river. This ecosystem is affected by the tide. The mangrove ecosystem is one of the objects that can be identified by using remote sensing technology. The main goal of this research provide information on mangrove distribution based on the level of its density. Interpretation of mangrove by utilizing the technology of remote sensing using Landsat satellite imagery data 8 OLI (the Operational Land Imager)/TIRS (Thermal Infrared Sensor) by using the method of classification is Supervised Classification. The results of the classification can be used as data sources or references for research related to the density of vegetation in natural resources. Based on the results of interpretation and classification, mangrove are divided into 3 classes of density that is rare, medium and high. the results of a Ground Check from 12 locations obtained the results of the calculation accuracy of interpretation is

Hutan bakau often reffered to as 'mangrove', is the ecosystem transition between the land and sea or with waters around the estuary of the river. This ecosystem is affected by the tide. The mangrove ecosystem is one of the objects that can be identified by using remote sensing technology. The main goal of this research provide information on mangrove distribution based on the level of its density. Interpretation of mangrove by utilizing the technology of remote sensing using Landsat satellite imagery data 8 OLI (the Operational Land Imager)/TIRS (Thermal Infrared Sensor) by using the method of classification is Supervised Classification. The results of the classification can be used as data sources or references for research related to the density of vegetation in natural resources. Based on the results of interpretation and classification, mangrove are divided into 3 classes of density that is rare, medium and high. the results of a Ground Check from 12 locations obtained the results of the calculation accuracy of interpretation is

Modern agriculture faces the challenge of producing more food to meet the demands of a growing global population while minimizing its impact on the environment. To achieve this, precision agriculture has emerged as a transformative approach, harnessing cutting-edge technologies to optimize farming practices. Among these technologies, modern optical sensing has garnered significant attention due to its versatility, non-destructive nature, and high-resolution capabilities. This review explores the latest developments in optical sensing technologies and their wide-ranging applications in agriculture. We delve into the principles behind these sensors, their advantages, and their potential to revolutionize various aspects of farming, including crop monitoring, disease detection, soil analysis, and nutrient management. Additionally, we discuss challenges and opportunities for the widespread adoption of optical sensing in agriculture, highlighting the need for data integration, technological standardization, and farmer awareness. Through a
comprehensive examination of the current state-of-the-art and future prospects, this review aims to demonstrate how modern optical sensing technologies have the potential to drive sustainable and efficient agriculture.

Connectivity and road network is an integral and inseparable. There are many influences arising from the existence of the road network as well as the accompanying elements to a region. The aim of this study was to determine the correlation between road network connectivity and alteration of land cover that occurred in the nine districts of Bantul regency during 2006 to 2015, using Pearson correlation analysis and Kendall's Tau. Knowing the accuracy of Landsat 8 OLI in extracting land cover and determine the pattern of change in land cover for nine years. Road network connectivity is obtained by calculating the number of links and nodes obtained from the map of the road network. While changes in land cover obtained from ALOS AVNIR-2 satellite image extraction for 2006 and Landsat 8 OLI satellite image for 2015.

Background and Objective: The discharge of industrial effluents containing hexavalent Chromium into the environment can be very harmful to living things. Therefore, prior to this discharge into the environment, hexavalent Chromium should be removed from contaminated water and especially from wastewaters. This study aimed to analyze the effects of removal of hexavalent Chromium using derived carbon from almond green hulls. Method: In the present study, derived carbon from almond green hulls of zonal district of South Khorasan (Birjand) were used to remove hexavalent Chromium from Synthetic wastewater while contact time, density, PH, absorbent dosage and temperature were changed. Batch tests were discontinuously performed on Shaker. At the end, to assess hexavalent Chromium, Spectrophotometer UV / VIS Spectrometer T80 at 540 nm wavelength was used.

Apps available for Smartphone, as well as software for GNSS/GIS devices, permit to easily mapping the localization and shape of an area by acquiring the vertices coordinates of its contour. This option is useful for remote sensing classification, supporting the detection of representative sample sites of a known cover type to use for algorithm training or to test classification results. This article aims to analyse the possibility to produce smart maps from remotely sensed image classification in rapid way: the attention is focalized on different methods that are compared to identify fast and accurate procedure for producing up-to-date and reliable maps. Landsat 8 OLI multispectral images of northern Sicily (Italy) are submitted to various classification algorithms to distinguish water, bare soil and vegetation. The resulting map is useful for many purposes: appropriately inserted in a larger database aimed at representing the situation in a space-time evolutionary scenario, it is suitable whenever you want to capture the variation induced in a scene, e.g. burnt areas identification, vegetated areas definition for tourist-recreational purposes, etc. Particularly, pixel-based classification approaches are preferred, and experiments are carried out using unsupervised (k-means), vegetation index (NDVI, Normalized Difference Vegetation Index), supervised (minimum distance, maximum likelihood) methods. Using test sites, confusion matrix is built for each method, and quality indices are calculated to compare the results. Experiments demonstrate that NDVI submitted to k-means algorithm allows the best performance for distinguishing not only vegetation areas but also water bodies and bare soils. The resulting thematic map is converted for web publishing.

Mangroves are a multifunctional coastal ecosystem in coastal areas. Mangrove ecosystems can adapt to extreme coastal conditions, but are highly vulnerable to hazards such as regional degradation, species degradation, conflicts of interest, exploitation, and excessive mangrove use. Remote identification can help obtain the latest data related to the area of mangrove areas with time criteria and coverage of certain areas. The remote sensing used is Google Earth Engine (GEE). This study aims to be able to determine changes in the area of mangrove distribution and the level of density of mangrove ecosystems on Panjang Island, Serang Regency for the last 5 years from 2017 to 2021. The results of the distribution of mangrove areas in the span of 5 years from 2017 to 2021 the mangrove area on Panjang Island experienced a decrease in mangrove area by 5.47 ha. The level of mangrove density on Panjang island in the 5-year period from 2017 to 2021 is classified as a very rare mangrove density ...

Mangroves are a multifunctional coastal ecosystem in coastal areas. Mangrove ecosystems can adapt to extreme coastal conditions, but are highly vulnerable to hazards such as regional degradation, species degradation, conflicts of interest, exploitation, and excessive mangrove use. Remote identification can help obtain the latest data related to the area of mangrove areas with time criteria and coverage of certain areas. The remote sensing used is Google Earth Engine (GEE). This study aims to be able to determine changes in the area of mangrove distribution and the level of density of mangrove ecosystems on Panjang Island, Serang Regency for the last 5 years from 2017 to 2021. The results of the distribution of mangrove areas in the span of 5 years from 2017 to 2021 the mangrove area on Panjang Island experienced a decrease in mangrove area by 5.47 ha. The level of mangrove density on Panjang island in the 5-year period from 2017 to 2021 is classified as a very rare mangrove density ...

In recent years, the accelerated development of the remote sensing domain and the improvement of the resolution and frequency of satellite images allowed the increase in the accuracy of the evaluation of morphometric characteristics and the spatiotemporal distribution of pit lakes, including the small ones. Our study quantitatively analyzes small-scale pit lakes in the piedmont and subsidence plains from contact with the Getic and Curvature Subcarpathians from Romania using the normalized difference water index (NDWI) and data series, with different resolutions, from Landsat 8, Google Earth, and Sentinel 2A. The problems encountered in extracting the contours of the gravel pit lakes were determined by the different resolution of the images, the uneven quality of the images exported from Google Earth, and an additional challenge was given by the diversity of the analyzed land surfaces, the land use, and the optical properties of the lakes. A comparison of the obtained NDWI values usi...

With growing urbanization in mountainous landscapes, the built-up areas dominate other land use classes resulting in increased land surface temperature (LST). Gilgit city in northern Pakistan has witnessed tremendous urban growth in the recent past decades. It is anticipated that this growth will exponentially increase in the near future because of the China-Pakistan Economic Corridor (CPEC) initiatives, as this city happens to be the commercial hub of the northern region of Pakistan. The objective of present study is to explore the influence of land use and land cover variations on LST and to evaluate the relationship between LST with normalized difference vegetation index (NDVI), normalized difference water index (NDWI), and normalized difference builtup index (NDBI) values. This study is carried out on data from Google earth and thr ee Landsat images (Landsat 5-TM, Landsat 7-ETM, and Landsat OLI_TIRS-8) during the period from 1992, 2004 and 2016. Land use/cover classes are determined through supervised classification and LST maps are created using the Mono-window algorithm. The accuracy assessment of land use/cover classes is carried out comparing Google Earth digitized vector for the periods of 2004 and 2016 with Landsat classified images. Further, NDVI, NDBI, and NDWI maps are computed from images for years 1992, 2004, and 2016. The relationships of LST with NDVI, NDBI, and NDWI are computed using Linear Regression analysis. The results reveal that the variations in land use and land cover play a substantial role in LST variability. The maximum temperatures are connected with built-up areas and

The assessment of vegetation dynamics using the Normalized Difference Vegetation Index (NDVI) is crucial for the development of effective strategies for biodiversity conservation and management. Using Landsat images, this article investigates the vegetation dynamics in the Bhutan highlands of Lingzhi between 2010 and 2021. The NDVI measurements were classified into five categories, and NDVI differencing was used to determine vegetation changes over time. The main objective of the study was to assess vegetation fluctuation, which assists in the investigation of anthropogenic pressure, deforestation, urban development, natural disasters, and regular landscape changes over time. The article discovered a decline in the moderate vegetation class, which was ascribed to grassland nationalization, the legality and regularization of cordyceps collection, and a decrease in illicit cordyceps harvesting. The results highlight the need to adopt image recognition methods and the NDVI index to understand forest changes. These findings can help planners and decision-makers steer sustainable land development in similar places.

This research aims at highlighting the economic role and technical specifications, as well as the sustainable impact of using the Post-Tensioned Slab technology in the construction work, especially in the implementation of high buildings due to the urgent need to find a quick and economical construction alternatives, as well as decreasing the negative environmental impact as a result of horizontal urban expansion to agricultural areas, by supporting the vertical methods of sustainable construction, which lead to a professional execution level of high buildings in accordance with the latest technological and economic methods, and finding a practical solutions to the vertical expansion of cities. This study includes the technical characterization of the post-tensioned slab technology according to the latest international norms (State of Arts), and studying a high building with three alternatives of slabs construction (Flat Slab, Pt Slab, Drop Panel Slab), which gave exact operational indicators for the post-tensioned slabs through comparison with other alternatives. The results of the study showed a significant decrease in the usage of construction resources (Steel and concrete at 53.22% and 39.62%, respectively), as well as a decrease in the thickness of the slab with 25.93%. This study was based on the Ram Concept program for the design of post-tensioned slab, and (Revit & AutoCAD) programs in the architectural design and rise building quantities calculation for each of the three alternatives.

The rapid urban growth of the cities is a result of the population growth and the negative effects on human health and quality life are obvious which makes the monitoring of the urban growth very important. In this study monitoring over the city Tetovo in the northwestern part of Republic of Macedonia was made using remote sensed satellite images from Landsat archive that is widely used for monitoring the Earth's surface. An attempt of mapping the urban area on an annual basis from the period of 1984 to 2015 was made. Change detection in rapidly growing areas was made using the NDVI (Normalized Difference Vegetation Index) values that were classified for distinguishing the differences between urban and vegetated areas. The study area covers nine cadaster municipalities with 14.6 km 2. The results showed significant urban growth of 21.3% and 17.7% vegetation loss in the study area from 1984 to 2015.

The productivity of mangrove litterfall is the most important part of the transfer of organic materials from mangrove vegetation into the waters and soils. This research was conducted in July-August 2021 in three stations on mangrove ecosystem at Wasti Lake, Manokwari Regency. The purpose of this study was to determine the mangrove vegetation, litterfall production of Sonneratia alba, relation of Diameter at Breast High with litterfall production, and physical chemistry of the environment. The quadrant transect was used to sample mangrove vegetation and the litter trap to measure litter production. The results showed 5 types of mangroves, namely Sonneratia alba, Rhizophora stylosa, Rhizophora apiculata, Bruguiera gymnorrhiza, and Bruguiera sexangua. The highest density values ​​at each station was Sonneratia alba, namely 360 ind/ha, 540 ind/ha and 520 ind/ha with important value indexes are 268.08%, 255.59%, and 247.96%. The total litterfall production of Sonneratia alba during a pe...

Increasing population and urbanization are affecting human health and comfort. In order to get rid of these affects, mankind is changing its enviroment and looking for new life areas. This study investigates the influence of Land Cover Change (LCC) and Normalisied Densly Vegetation Index (NDVI) on Land Surface Temperature (LST) of Fethiye-Göcek Specially Protected Area (SEPA) in easterm mediterranean basin. In the study LCC, NDVI and LST were drived from landsat 5, 7 and 8 satellite image of resolation at 30x30 m acquired between 1995-2019. LST were computed based on Land Use/Land Cover (LULC) types. The Corine Index were used for determination of land uses. The results indicated that water, forest and maquia lands decreasing while urban fabric and bare lands are increasing depend upon the urbanization and forest fires in the basin. These changes in LULC widened the temperature differences between the urban and rural areas. The change in LST is associated with changes in constructional materials in urban land and in vegetation abundance both in the urban and rural areas. Vegetation has an important factor in the temperature of different land covers. That produces warming trend in temperetaure in built-up areas it causes to keep other lands warmer in cold weather. Another important result is affective Urban Heat Island (UHI) on climate change based on the impact of urbanization and land cover changes. Significantly possitive correlation were found between the urbanization rate, population and built-up area and warming rate of average air temperature and so the LST.