Pub Date : 2024-01-18DOI: 10.1007/s41976-024-00101-7
Sreekala S, P. Geetha, Dhanya Madhu
{"title":"Flood Susceptibility Map of Periyar River Basin Using Geo-spatial Technology and Machine Learning Approach","authors":"Sreekala S, P. Geetha, Dhanya Madhu","doi":"10.1007/s41976-024-00101-7","DOIUrl":"https://doi.org/10.1007/s41976-024-00101-7","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"106 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139614617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-29DOI: 10.1007/s41976-023-00100-0
B. Parida, Bishal Kanu, Chandra Shekhar Dwivedi
{"title":"Deciphering Forest Cover Losses and Recovery (1990–2022) Using Satellite Data in Behali Reserve Forest of Northeastern Himalaya","authors":"B. Parida, Bishal Kanu, Chandra Shekhar Dwivedi","doi":"10.1007/s41976-023-00100-0","DOIUrl":"https://doi.org/10.1007/s41976-023-00100-0","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":" 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139142540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-01DOI: 10.1007/s41976-023-00099-4
Edward Kim, Albert Wu, H. Izadkhah, Saji Abraham
{"title":"High-Resolution Soil Moisture—a European Airborne Campaign Using NASA Goddard’s Scanning L-Band Active Passive (SLAP)","authors":"Edward Kim, Albert Wu, H. Izadkhah, Saji Abraham","doi":"10.1007/s41976-023-00099-4","DOIUrl":"https://doi.org/10.1007/s41976-023-00099-4","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":" 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138617555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-24DOI: 10.1007/s41976-023-00097-6
V. Nithya, M. Josephine, V. Jeyabalaraja
{"title":"IoT-Based Crop Yield Prediction System in Indian Sub-continent Using Machine Learning Techniques","authors":"V. Nithya, M. Josephine, V. Jeyabalaraja","doi":"10.1007/s41976-023-00097-6","DOIUrl":"https://doi.org/10.1007/s41976-023-00097-6","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139241041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-18DOI: 10.1007/s41976-023-00098-5
J. V. N. Ramesh, Pavithra Roy Patibandla, Manjula Shanbhog, Srinivas Ambala, Mohd Ashraf, A. Kiran
{"title":"Ensemble Deep Learning Approach for Turbidity Prediction of Dooskal Lake Using Remote Sensing Data","authors":"J. V. N. Ramesh, Pavithra Roy Patibandla, Manjula Shanbhog, Srinivas Ambala, Mohd Ashraf, A. Kiran","doi":"10.1007/s41976-023-00098-5","DOIUrl":"https://doi.org/10.1007/s41976-023-00098-5","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"59 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139262422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-06DOI: 10.1007/s41976-023-00096-7
Sudip Kumar Kundu, Charu Singh
{"title":"Comparative Analysis of CMIP5-Based Monsoon Season Rainfall Against Satellite-Based Estimations over India","authors":"Sudip Kumar Kundu, Charu Singh","doi":"10.1007/s41976-023-00096-7","DOIUrl":"https://doi.org/10.1007/s41976-023-00096-7","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135589725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-23DOI: 10.1007/s41976-023-00094-9
Stuart Krause, Tanja GM Sanders
Abstract The mapping of forest stands and individual trees affected by drought stress is a crucial step in targeted forest management, aimed at fostering resilient and diverse forests. Unoccupied aerial vehicle (UAV)-based thermal sensing is a promising method for obtaining high-resolution thermal data. However, the reliability of typical low-cost sensors adapted for UAVs is compromised due to various factors, such as internal sensor dynamics and environmental variables, including solar radiation intensity, relative humidity, object emissivity and wind. Additionally, accurately assessing drought stress in trees is a complex task that usually requires laborious and cost-intensive methods, particularly in field settings. In this study, we investigated the feasibility of using the thermal band of the Micasense Altum multispectral sensor, while also assessing the potential for modelling tree water deficit (TWD) through point dendrometers and UAV-derived canopy temperature. Our indoor tests indicated that using a limited number of pixels (< 3) could result in temperature errors exceeding 1 K. However, enlarging the spot-size substantially reduced the mean difference to 0.02 K, validated against leaf temperature sensors. Interestingly, drought-treated (unwatered) leaves exhibited a higher root mean squared error (RMSE) (RMSE = 0.66 K and 0.73 K) than watered leaves (RMSE = 0.55 K and 0.53 K), likely due to lower emissivity of the dry leaves. Comparing field acquisition methods, the mean standard deviation (SD) for tree crown temperature obtained from typical gridded flights was 0.25 K with a maximum SD of 0.59 K ( n = 12). In contrast, a close-range hovering method produced a mean SD of 0.09 K and a maximum SD of 0.1 K ( n = 8). Modelling the TWD from meteorological and point dendrometer data for the 2021 growth season ( n = 2928) yielded an R 2 = 0.667 using a generalised additive model (GAM) with vapor pressure deficit (VPD), wind speed, and solar radiation as input features. A point dendrometer lag of one hour was also implemented. When predicting individual tree TWD with UAV-derived tree canopy temperature, relative humidity, and air temperature, an RMSE of 4.92 (μm) and R 2 of 0.87 were achieved using a GAM. Implementing leaf-to-air pressure deficit (LVPD) as an input feature resulted in an RMSE of 6.87 (μm) and an R 2 of 0.71. This novel single-shot approach demonstrates a promising method to acquire thermal data for the purpose of mapping TWD of beech trees on an individual basis. Further testing and development are imperative, and additional data from drought periods, point dendrometers, and high-resolution meteorological sources are required.
{"title":"Mapping Tree Water Deficit with UAV Thermal Imaging and Meteorological Data","authors":"Stuart Krause, Tanja GM Sanders","doi":"10.1007/s41976-023-00094-9","DOIUrl":"https://doi.org/10.1007/s41976-023-00094-9","url":null,"abstract":"Abstract The mapping of forest stands and individual trees affected by drought stress is a crucial step in targeted forest management, aimed at fostering resilient and diverse forests. Unoccupied aerial vehicle (UAV)-based thermal sensing is a promising method for obtaining high-resolution thermal data. However, the reliability of typical low-cost sensors adapted for UAVs is compromised due to various factors, such as internal sensor dynamics and environmental variables, including solar radiation intensity, relative humidity, object emissivity and wind. Additionally, accurately assessing drought stress in trees is a complex task that usually requires laborious and cost-intensive methods, particularly in field settings. In this study, we investigated the feasibility of using the thermal band of the Micasense Altum multispectral sensor, while also assessing the potential for modelling tree water deficit (TWD) through point dendrometers and UAV-derived canopy temperature. Our indoor tests indicated that using a limited number of pixels (< 3) could result in temperature errors exceeding 1 K. However, enlarging the spot-size substantially reduced the mean difference to 0.02 K, validated against leaf temperature sensors. Interestingly, drought-treated (unwatered) leaves exhibited a higher root mean squared error (RMSE) (RMSE = 0.66 K and 0.73 K) than watered leaves (RMSE = 0.55 K and 0.53 K), likely due to lower emissivity of the dry leaves. Comparing field acquisition methods, the mean standard deviation (SD) for tree crown temperature obtained from typical gridded flights was 0.25 K with a maximum SD of 0.59 K ( n = 12). In contrast, a close-range hovering method produced a mean SD of 0.09 K and a maximum SD of 0.1 K ( n = 8). Modelling the TWD from meteorological and point dendrometer data for the 2021 growth season ( n = 2928) yielded an R 2 = 0.667 using a generalised additive model (GAM) with vapor pressure deficit (VPD), wind speed, and solar radiation as input features. A point dendrometer lag of one hour was also implemented. When predicting individual tree TWD with UAV-derived tree canopy temperature, relative humidity, and air temperature, an RMSE of 4.92 (μm) and R 2 of 0.87 were achieved using a GAM. Implementing leaf-to-air pressure deficit (LVPD) as an input feature resulted in an RMSE of 6.87 (μm) and an R 2 of 0.71. This novel single-shot approach demonstrates a promising method to acquire thermal data for the purpose of mapping TWD of beech trees on an individual basis. Further testing and development are imperative, and additional data from drought periods, point dendrometers, and high-resolution meteorological sources are required.","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"51 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135365521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-21DOI: 10.1007/s41976-023-00095-8
Salahuddin M. Jaber
{"title":"Insights About the Spatial and Temporal Characteristics of the Relationships Between Land Surface Temperature and Vegetation Abundance and Topographic Elements in Arid to Semiarid Environments","authors":"Salahuddin M. Jaber","doi":"10.1007/s41976-023-00095-8","DOIUrl":"https://doi.org/10.1007/s41976-023-00095-8","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"10 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135511916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-11DOI: 10.1007/s41976-023-00093-w
S. A. Alimi, E. O. Oriola, S. S. Senbore, V. C. Alepa, F. J. Ologbonyo, F. S. Idris, H. O. Ibrahim, L. O. Olawale, O. J. Akinlabi, O. Ogungbade
Abstract The incessant reoccurrence of flooding disasters across Nigeria has mandated an urgent outlook on flood-risk management techniques. Ilorin and its environs have suffered immensely from annual flood reoccurrence. This study aims to assess flood risk within Ilorin and its environs and proffer adequate flood mitigation strategies that governments and policymakers can adopt to placate future flooding events within the state. Satellite imagery data were acquired and analyzed for flood-risk assessment of the area. Ten highly influential flood causative factors were synergized using Multi-Criteria Decision-Making techniques in this research; they are Land Surface Temperature, Elevation, Soil Moisture Index, and Distance to Stream, Drainage Density, Stream Power Index, Normalized Difference Vegetation Index, Land Use Land Cover, Slope, and Topographic Wetness Index. Findings showed that approximately 47.2% of the study area had low flood risk, while moderate and high flood-risk zones occupied 33.5% and 19.29%, respectively. Most parts of Ilorin and its environs are safe from flood disasters; only about one-quarter of the total area under investigation lies in the high flood-risk zones; these areas mostly fall within the shores of major streams, rivers, and dams within the state. A plot of previous flood cases in the state placed the affected areas in the high and moderate zones of flood risk, confirming the efficacy of geospatial techniques in flood-risk assessment. It is hoped that this study's findings and recommendations can be implemented to prevent future devastating flooding occurrences within the state.
{"title":"GIS-assisted Flood-risk Potential Mapping of Ilorin and its Environs, Kwara State, Nigeria","authors":"S. A. Alimi, E. O. Oriola, S. S. Senbore, V. C. Alepa, F. J. Ologbonyo, F. S. Idris, H. O. Ibrahim, L. O. Olawale, O. J. Akinlabi, O. Ogungbade","doi":"10.1007/s41976-023-00093-w","DOIUrl":"https://doi.org/10.1007/s41976-023-00093-w","url":null,"abstract":"Abstract The incessant reoccurrence of flooding disasters across Nigeria has mandated an urgent outlook on flood-risk management techniques. Ilorin and its environs have suffered immensely from annual flood reoccurrence. This study aims to assess flood risk within Ilorin and its environs and proffer adequate flood mitigation strategies that governments and policymakers can adopt to placate future flooding events within the state. Satellite imagery data were acquired and analyzed for flood-risk assessment of the area. Ten highly influential flood causative factors were synergized using Multi-Criteria Decision-Making techniques in this research; they are Land Surface Temperature, Elevation, Soil Moisture Index, and Distance to Stream, Drainage Density, Stream Power Index, Normalized Difference Vegetation Index, Land Use Land Cover, Slope, and Topographic Wetness Index. Findings showed that approximately 47.2% of the study area had low flood risk, while moderate and high flood-risk zones occupied 33.5% and 19.29%, respectively. Most parts of Ilorin and its environs are safe from flood disasters; only about one-quarter of the total area under investigation lies in the high flood-risk zones; these areas mostly fall within the shores of major streams, rivers, and dams within the state. A plot of previous flood cases in the state placed the affected areas in the high and moderate zones of flood risk, confirming the efficacy of geospatial techniques in flood-risk assessment. It is hoped that this study's findings and recommendations can be implemented to prevent future devastating flooding occurrences within the state.","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136210747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-15DOI: 10.1007/s41976-023-00090-z
Eunice W. King’ori, Elfatih M. Abdel-Rahman, Paul Obade, Bester Tawona Mudereri, Marian Adan, Tobias Landmann, Henri E. Z. Tonnang, Thomas Dubois
{"title":"Integrating Sentinel-2 Derivatives to Map Land Use/Land Cover in an Avocado Agro-Ecological System in Kenya","authors":"Eunice W. King’ori, Elfatih M. Abdel-Rahman, Paul Obade, Bester Tawona Mudereri, Marian Adan, Tobias Landmann, Henri E. Z. Tonnang, Thomas Dubois","doi":"10.1007/s41976-023-00090-z","DOIUrl":"https://doi.org/10.1007/s41976-023-00090-z","url":null,"abstract":"","PeriodicalId":91040,"journal":{"name":"Remote sensing in earth systems sciences","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135395198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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