Lake Iriqui’s Remarkable Revival: Field Observations and a Google Earth Engine Analysis of Its Recovery After over Half a Century of Desiccation by Adil Moumane, Tarik Bahouq, Ahmed Karmaoui, Dahmane Laghfiri, Mohamed Yassine, Jamal Al Karkouri, Mouhcine Batchi, Mustapha Faouzi, Mohamed Boulakhbar, Ali Ait Youssef

“…The revival was monitored using satellite imagery from Landsat 8 and 9 and Sentinel-2A, processed through Google Earth Engine (GEE), with the Normalized Difference Water Index (NDWI) applied to detect water presence. …”
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A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species by Fabio Recanatesi, Antonietta De Santis, Lorenzo Gatti, Alessio Patriarca, Eros Caputi, Giulia Mancini, Chiara Iavarone, Carlo Maria Rossi, Gabriele Delogu, Miriam Perretta, Lorenzo Boccia, Maria Nicolina Ripa

“…This study evaluates and compares the efficacy of Sentinel-2 and Pléiades satellite imagery in classifying tree species within historic urban parks in Rome—Villa Borghese, Villa Ada Savoia, and Villa Doria Pamphilj. …”
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Quantification of Soil–Water Erosion Using the RUSLE Method in the Mékrou Watershed (Middle Niger River) by Rachid Abdourahamane Attoubounou, Hamidou Diawara, Ralf Ludwig, Julien Adounkpe

“…Land use and land cover data were extracted from satellite imagery, enabling the analysis of vegetation cover and anthropogenic impacts over four decades. …”
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Temperature Is a Key Factor Affecting Total Phosphorus and Total Nitrogen Concentrations in Northeastern Lakes Based on Sentinel-2 Images and Machine Learning Methods by Haoming Qin, Chong Fang, Ge Liu, Kaishan Song, Zhuoshi Li, Sijia Li, Hui Tao, Zhaojiang Yan

“…This study utilized machine learning algorithms based on Sentinel-2 satellite imagery for remote estimation of TP and TN concentrations in Lake Xingkai, Chagan and Songhua. …”
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Phosphorus transitions driven by cyclone biparjoy linked middle east North Africa (MENA) and Indian Thar Desert dust storm pathways in Asia’s largest grassland by Rupak Dey, Seema B. Sharma, Mahesh G. Thakkar, Ranjit Kumar Sarangi, Abhiroop Chowdhury, Aliya Naz

“…To examine the long-range transport of dust-borne phosphorus and its subsequent deposition in the target grassland, we employed an interdisciplinary approach that integrated satellite imagery and ground-based measurements. Spatial and temporal variations in dust emissions were assessed using satellite remote sensing data, while ground truthing was performed for phosphorus content analysis using standard protocols. …”
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Using OCO-2 Observations to Constrain Regional CO₂ Fluxes Estimated with the Vegetation, Photosynthesis and Respiration Model by Igor B. Konovalov, Nikolai A. Golovushkin, Evgeny A. Mareev

“…In this study, we investigate the feasibility of inferring reliable regional estimates of the net ecosystem exchange (NEE) using column-averaged dry-air mole fractions of CO₂ (XCO₂) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations as constraints on parameters of the widely used Vegetation Photosynthesis and Respiration model (VPRM), which predicts ecosystem fluxes based on vegetation indices derived from multispectral satellite imagery. We developed a regional-scale inverse modeling system that applies a Bayesian variational optimization algorithm to optimize parameters of VPRM coupled to the CHIMERE chemistry transport model and which involves a preliminary transformation of the input XCO₂ data that reduces the impact of the CHIMERE boundary conditions on inversion results. …”
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Modeling the tropical fish community related to land uses and environmental determinants by N. Takarina, O. Chuan, M. Afifudin, L. Tristan, I. Arif, A. Adiwibowo

“…Land uses at the sites were interpreted using satellite imagery. Fish diversity was determined using the Shannon–Wiener index, rarefaction curve, and Lorenz graph. …”
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Use of supervised and unsupervised approaches to make zonal application maps for variable-rate application of crop growth regulators in commercial cotton fields by Maria C. da S. Andrea, Cristiano F. de Oliveira, Fabrícia C. M. Mota, Rafael C. dos Santos, Edilson F. Rodrigues Junior, Lucas M. Bianchi, Rodrigo S. de Oliveira, Caio M. de Gouveia, Victor G. S. Barbosa, Marco A. Bispo E Silva

“…During 2022–2023 agricultural seasons, an UF was employed to generate zonal maps based on locally collected field data on plant height of cotton, satellite imagery, soil texture, and phenology data. Subsequently, a SUF (based on historical data between 2020–2021 to 2022–2023 agricultural seasons) was developed to predict plant height using remote sensing and phenology data, aiming to replicate same zonal maps but without relying on direct field measurements of plant height. …”
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Spatiotemporal analysis of oil palm land clearing by M.K. Rosyidy, E. Frimawaty

“…This study utilizes the change of oil Palm in spatial-temporal (spatial and temporal) in Jambi province related to land change and environmental impacts.METHODS: This research uses data from Landsat 8 satellite imagery. The land cover classification was done using the Maximum Likelihood approach, while the overlay method was used for land change analysis. …”
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Artificial-Intelligence-Based Investigation on Land Use and Land Cover (LULC) Changes in Response to Population Growth in South Punjab, Pakistan by Tanweer Abbas, Muhammad Shoaib, Raffaele Albano, Muhammad Azhar Inam Baig, Irfan Ali, Hafiz Umar Farid, Muhammad Usman Ali

“…Landsat 7, Landsat 8, and Sentinel-2 satellite imagery within the Google Earth Engine (GEE) cloud platform was utilized to create 2003, 2013, and 2023 LULC maps via supervised classification with a random forest (RF) classifier, which is a subset of artificial intelligence (AI). …”
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Spatiotemporal variation in biomass abundance of different algal species in Lake Hulun using machine learning and Sentinel-3 images by Zhaojiang Yan, Chong Fang, Kaishan Song, Xiangyu Wang, Zhidan Wen, Yingxin Shang, Hui Tao, Yunfeng Lyu

“…Therefore, this study proposes a machine learning method based on OLCI/Sentinel-3 satellite imagery to retrieve algal biomass abundance. …”
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Modeling regional aboveground carbon stock dynamics affected by land use and land cover changes by A.D. Malik, M.C.W. Arief, S. Withaningsih, P. Parikesit

“…Vegetation biomass was assessed using an allometric equation, and aboveground carbon stock data were extrapolated to the landscape scale using a linear regression model of measured carbon stocks and the Normalized Difference Vegetation Index derived from recent satellite imagery.FINDINGS: Vegetated areas were predominant in 2009 and 2021. …”
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Comparison of Field and Virtual Vegetation Surveys Conducted Using Uncrewed Aircraft System (UAS) Imagery at Two Coastal Marsh Restoration Projects by Aaron N. Schad, Molly K. Reif, Joseph H. Harwood, Christopher L. Macon, Lynde L. Dodd, Katie L. Vasquez, Kevin D. Philley, Glenn E. Dobson, Katie M. Steinmetz

“…Uncrewed aircraft system (UAS) technology can help fill data gaps between high-to-moderate spatial resolution (e.g., 1–30 m) satellite imagery, manned airborne data, and traditional field surveys, yet it has not been thoroughly evaluated in a virtual capacity as an alternative to traditional field vegetation plot surveys. …”
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Agricultural Drought Assessment using Remote Sensing Data (Case study: Tuyserkan County) by Maedeh Malmir, Kamran Shayesteh, Iman Pazhouhan

“…The use of remote sensing and satellite imagery as effective tools for monitoring agricultural drought has gained significant attention from researchers. …”
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The responses of vegetation water use efficiency to biomass density and CO2 balance in dryland of Central Asia during 21st century by Alphonse Kayiranga, Xi Chen, Xuexi Ma, Dative Ingabire, Tie Liu, Yaoming Li, Emeka Edwin Igboeli, Eldiiar Duulatov, Hubert Hirwa, Clement Nzabanita, Ping Hu

“…In this study, we examined the patterns and magnitude of WUE effects on desert vegetation aboveground biomass (AGB) and carbon stocks (C. stocks) and related fluxes by utilizing multiple streams of state-of-the-art multispectral satellite imagery and polynomial model across the temperate drylands of Central Asia (CA) from 2000 to 2023. …”
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Measuring spatial - temporal of Yazd urban form using spatial metrics by saeed zanganeh

“…To achieve the main objective of the paper, measuring Yazd growth and expansion by spatial metrics, it has used remote sensing data and satellite imageries and ArcGIS software. The conclusion revealed that in four periods of study, complexity or irregularity of the urban patch shapes has increased, centrality or average distance of the dispersed parts to the city center has decreased, compactness or the number and area of patches their distance from each other has decreased, porosity or ratio of open space has increased and finally population density of city has decreased in a large amount. …”
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Impacts of Land Cover and Greenness Change on Soil Loss and Erosion Risk in Damota Area Districts, Southern Ethiopia by Mamush Masha, Teshome Yirgu, Mulugeta Debele

“…The RUSLE modeling was applied using satellite imageries, ASTER GDEM, rainfall, and soil data to estimate total annual soil loss for a 100 km2 hilly and highly populated area in Ethiopia. …”
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Assessment of groundwater potential zones using geospatial techniques in Mangalore Taluk, Dakshina Kannada District, Karnataka, India by Eka Putri Elsa, Hamidi Masyhuri, M Shet Suraj, S A Swapna

“…Groundwater availability in Mangalore taluk was divided based on its hydro geomorphologic conditions. Satellite imageries are used for preparing various thematic maps, viz. slope, drainage density, lineament, land use/cover, soil, rainfall, geology and geomorphology map, which were transformed to raster class data using the feature to raster converter tool in ArcGIS. …”
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Assesment of Vegetation Cover Status in Dry Lands of The Sudan Using Social and Terrestrial Data by Mohammed Hamed Mohammed, Suzan Abdelrahman Hamad, Hassan Elnour Adam

“…Quantitative data was collected using terrestrial inventory and satellite imageries. In terrestrial inventory, 22 ground control points (GCPs) were randomly registered using GPS in order to get general overview of the land cover of the study area. …”
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Predicting of Temporal-Spatial Sand Dunes Transition Caused by Marine Storms (Case Study: The Coast of Makran, Iran) by Soleiman PirouzZadeh, Mahmood Khosravi, Samad Fotohi

“…Then to determine the changes in the movement of sand dunes in the study area ranged from twenty-three years (1991-2014), satellite imageries from Landsat 7 and 8(ETM+ sensor) with 15 and 30 meters spatial resolution , was used. …”
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