Pub Date : 2023-09-22DOI: 10.1080/14498596.2023.2259857
Arvindd Kshetrimayum, Akash Goyal, Ramesh H, B. K Bhadra
ABSTRACTPearl millet (Pennisetum glaucum L.R.Br.), is the most widely cultivated food crop after rice, wheat, and maize. The aim of the project is to determine the crop acreage of Pearl millet (Bajra) using Sentinel-1A SAR data and Machine Learning Algorithm to determine the yield estimation of the Pearl millet crop at the tehsil level using the Monteith approach. The classification overall accuracy is found to be 86.48% for Agra district and 80.15% for Firozabad district. The Relative Deviation of yield estimation for the Agra and Firozabad districts is found to be 10.14 and 6, respectively.KEYWORDS: Crop acreageSentinel-1Amachine learning algorithm (random forest)yield estimationMonteith approachHI AcknowledgmentsThe authors are thankful to the Directorate of Economics and Statistics (DES) for providing the statistics report. The authors would also like to thank ESA for providing the Sentinel datasets. The authors also sincerely thank the anonymous reviewers and members of the editorial team for their comments.Disclosure statementThe authors of this paper declare that there are no conflicts of interest or financial disclosures to report in relation to the research presented in this manuscript.
{"title":"Semi physical and machine learning approach for yield estimation of pearl millet crop using SAR and optical data products","authors":"Arvindd Kshetrimayum, Akash Goyal, Ramesh H, B. K Bhadra","doi":"10.1080/14498596.2023.2259857","DOIUrl":"https://doi.org/10.1080/14498596.2023.2259857","url":null,"abstract":"ABSTRACTPearl millet (Pennisetum glaucum L.R.Br.), is the most widely cultivated food crop after rice, wheat, and maize. The aim of the project is to determine the crop acreage of Pearl millet (Bajra) using Sentinel-1A SAR data and Machine Learning Algorithm to determine the yield estimation of the Pearl millet crop at the tehsil level using the Monteith approach. The classification overall accuracy is found to be 86.48% for Agra district and 80.15% for Firozabad district. The Relative Deviation of yield estimation for the Agra and Firozabad districts is found to be 10.14 and 6, respectively.KEYWORDS: Crop acreageSentinel-1Amachine learning algorithm (random forest)yield estimationMonteith approachHI AcknowledgmentsThe authors are thankful to the Directorate of Economics and Statistics (DES) for providing the statistics report. The authors would also like to thank ESA for providing the Sentinel datasets. The authors also sincerely thank the anonymous reviewers and members of the editorial team for their comments.Disclosure statementThe authors of this paper declare that there are no conflicts of interest or financial disclosures to report in relation to the research presented in this manuscript.","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136059151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.1080/14498596.2023.2257619
Sara Sameh, Fawzi H. Zarzoura, Mahmoud El-Mewafi
ABSTRACTThis study explores the relationship between Land Use Land Cover (LULC), Land Surface Temperature (LST), and Urban Heat Island (UHI) in Dakahlia Government using Landsat 8 images from 2014 to 2020. Support Vector Machine (SVM) and Mono-Window Algorithm were used to generate LULC and estimate LST. Results reveal an increase in built-up areas, rising LST, and variable UHI thresholds. The study highlights the impact of COVID-19 on LST in 2020. Positive correlations between LST and Normalized difference build-up index (NDBI) and negative correlations with Normalized difference vegetation index (NDVI) were observed. Projections for 2030 suggest an increase in high-temperature areas.KEYWORDS: Land Surface TemperatureUrban Heat Islandland use land coverLULC indicesCA-ANN algorithm Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"Spatiotemporal analysis of Urban Heat Island and land use land cover changes using Landsat images and CA-ANN machine learning techniques: a case study of Dakahlia government, Egypt","authors":"Sara Sameh, Fawzi H. Zarzoura, Mahmoud El-Mewafi","doi":"10.1080/14498596.2023.2257619","DOIUrl":"https://doi.org/10.1080/14498596.2023.2257619","url":null,"abstract":"ABSTRACTThis study explores the relationship between Land Use Land Cover (LULC), Land Surface Temperature (LST), and Urban Heat Island (UHI) in Dakahlia Government using Landsat 8 images from 2014 to 2020. Support Vector Machine (SVM) and Mono-Window Algorithm were used to generate LULC and estimate LST. Results reveal an increase in built-up areas, rising LST, and variable UHI thresholds. The study highlights the impact of COVID-19 on LST in 2020. Positive correlations between LST and Normalized difference build-up index (NDBI) and negative correlations with Normalized difference vegetation index (NDVI) were observed. Projections for 2030 suggest an increase in high-temperature areas.KEYWORDS: Land Surface TemperatureUrban Heat Islandland use land coverLULC indicesCA-ANN algorithm Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135060265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.1080/14498596.2023.2246425
Maan Habib, Ahmed Thneibat, Ali Farghal
ABSTRACTThree-dimensional coordinate transformations are required to harmonise different types of geospatial data accurately. Developing a mathematical model for data fusion relies on ground control points that produce discrepancies between the physical reality and depicted elements. The disparities between the two coordinate systems are known as the grid-to-ground issue that can be minimised by grid-to-grid or map-to-map transformation. This study develops simplified and rapid models for map-matching with global coordinates using regularised regression approaches to improve the accuracy and reliability of geospatial data. The results indicated that the proposed approach provides superior performance and employs any area with high accuracy.KEYWORDS: 2D similarity transformationconformal polynomialGNSSdatum shiftsregularised regression approaches Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"Maximizing grid-on-grid transformation performance with regularized regression techniques for integrating multi-source geospatial data","authors":"Maan Habib, Ahmed Thneibat, Ali Farghal","doi":"10.1080/14498596.2023.2246425","DOIUrl":"https://doi.org/10.1080/14498596.2023.2246425","url":null,"abstract":"ABSTRACTThree-dimensional coordinate transformations are required to harmonise different types of geospatial data accurately. Developing a mathematical model for data fusion relies on ground control points that produce discrepancies between the physical reality and depicted elements. The disparities between the two coordinate systems are known as the grid-to-ground issue that can be minimised by grid-to-grid or map-to-map transformation. This study develops simplified and rapid models for map-matching with global coordinates using regularised regression approaches to improve the accuracy and reliability of geospatial data. The results indicated that the proposed approach provides superior performance and employs any area with high accuracy.KEYWORDS: 2D similarity transformationconformal polynomialGNSSdatum shiftsregularised regression approaches Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135059369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-19DOI: 10.1080/14498596.2023.2250749
Chunhua Jiang, Xiang Gao, Shuaimin Wang, Qianfang An, Meizhen Zhu
ABSTRACTPressure, temperature and specific humidity profiles from COSMIC-2 are compared with those from ERA5 and radiosonde data from October 2019 to September 2020. The results demonstrate that COSMIC-2 pressure and specific humidity profiles show relatively poor accuracy and stability in the lower troposphere. The 1D-Var solution effectively improves the accuracy of temperature parameters in the troposphere. Three parameters show high accuracy over one climatological year, but show slight seasonal fluctuations, especially for the specific humidity profiles in summer. Furthermore, COSMIC-2 specific humidity data show low consistency with radiosonde and ERA5 in the equatorial region.KEYWORDS: COSMIC-2ERA5radiosonde1D-Var AcknowledgementsThe authors would like to thank the UCAR (University Corporation for Atmospheric Research) for providing COSMIC-2 profiles data and University of Wyoming for providing radiosonde data. The ECMWF (European Centre for Medium-Range Meteorological Weather Forecasts) is appreciated for providing ERA5 reanalysis products. The numerical calculatione in this study have been done on the supercomputing system in the Supercomputing Center, Shandong University, Weihai.Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe COSMIC-2 profiles data can be downloaded from https://data.cosmic.ucar.edu/gnss-ro/cosmic2/nrt/level2/. The radiosonde data can be downloaded from http://weather.uwyo.edu/upperair/sounding.html. The ERA5 reanalysis products can be downloaded from https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5/.Additional informationFundingThis research is founded by the Startup Foundation for Doctors of Liaoning Province. [2021-BS-275], the Scientific Study Project for lnstitutes of Higher Learning, Ministry of Education, Liaoning Province [LJKMZ20220673], the Project supported by the State Key Laboratory of Geodesy and Earths’ Dynamics, Innovation Academy for Precision Measurement Science and Technology [SKLGED2023-3-2]; Project supported by the State Key Laboratory of Geodesy and Earths’Dynamics, Innovation Academy for Precision Measurement Science and Technology.
{"title":"Comparison of pressure, temperature and specific humidity from COSMIC-2 with radiosonde and ERA5","authors":"Chunhua Jiang, Xiang Gao, Shuaimin Wang, Qianfang An, Meizhen Zhu","doi":"10.1080/14498596.2023.2250749","DOIUrl":"https://doi.org/10.1080/14498596.2023.2250749","url":null,"abstract":"ABSTRACTPressure, temperature and specific humidity profiles from COSMIC-2 are compared with those from ERA5 and radiosonde data from October 2019 to September 2020. The results demonstrate that COSMIC-2 pressure and specific humidity profiles show relatively poor accuracy and stability in the lower troposphere. The 1D-Var solution effectively improves the accuracy of temperature parameters in the troposphere. Three parameters show high accuracy over one climatological year, but show slight seasonal fluctuations, especially for the specific humidity profiles in summer. Furthermore, COSMIC-2 specific humidity data show low consistency with radiosonde and ERA5 in the equatorial region.KEYWORDS: COSMIC-2ERA5radiosonde1D-Var AcknowledgementsThe authors would like to thank the UCAR (University Corporation for Atmospheric Research) for providing COSMIC-2 profiles data and University of Wyoming for providing radiosonde data. The ECMWF (European Centre for Medium-Range Meteorological Weather Forecasts) is appreciated for providing ERA5 reanalysis products. The numerical calculatione in this study have been done on the supercomputing system in the Supercomputing Center, Shandong University, Weihai.Disclosure statementNo potential conflict of interest was reported by the authors.Data availability statementThe COSMIC-2 profiles data can be downloaded from https://data.cosmic.ucar.edu/gnss-ro/cosmic2/nrt/level2/. The radiosonde data can be downloaded from http://weather.uwyo.edu/upperair/sounding.html. The ERA5 reanalysis products can be downloaded from https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5/.Additional informationFundingThis research is founded by the Startup Foundation for Doctors of Liaoning Province. [2021-BS-275], the Scientific Study Project for lnstitutes of Higher Learning, Ministry of Education, Liaoning Province [LJKMZ20220673], the Project supported by the State Key Laboratory of Geodesy and Earths’ Dynamics, Innovation Academy for Precision Measurement Science and Technology [SKLGED2023-3-2]; Project supported by the State Key Laboratory of Geodesy and Earths’Dynamics, Innovation Academy for Precision Measurement Science and Technology.","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135060741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-12DOI: 10.1080/14498596.2023.2251932
Yuqing Liu, Hu Wang, Yamin Dang, Yangfei Hou, Yingying Ren, Yafeng Wang
{"title":"BDS-3 phase bias products of new frequency B1C&B2a: ambiguity resolution and positioning accuracy evaluation","authors":"Yuqing Liu, Hu Wang, Yamin Dang, Yangfei Hou, Yingying Ren, Yafeng Wang","doi":"10.1080/14498596.2023.2251932","DOIUrl":"https://doi.org/10.1080/14498596.2023.2251932","url":null,"abstract":"","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135878809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-04DOI: 10.1080/14498596.2023.2247689
Xiaobin Wang, Dekang Zhu, Ye Yan, Haohui Sun
{"title":"Improved TPH for object detection in aerial images","authors":"Xiaobin Wang, Dekang Zhu, Ye Yan, Haohui Sun","doi":"10.1080/14498596.2023.2247689","DOIUrl":"https://doi.org/10.1080/14498596.2023.2247689","url":null,"abstract":"","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44057148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1080/14498596.2023.2241290
{"title":"Correction","authors":"","doi":"10.1080/14498596.2023.2241290","DOIUrl":"https://doi.org/10.1080/14498596.2023.2241290","url":null,"abstract":"","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45822167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.1080/14498596.2023.2236051
Zohaib Khan, Bharat Jhamnani
{"title":"Development of flood susceptibility map using a GIS-based AHP approach: a novel case study on Idukki district, India","authors":"Zohaib Khan, Bharat Jhamnani","doi":"10.1080/14498596.2023.2236051","DOIUrl":"https://doi.org/10.1080/14498596.2023.2236051","url":null,"abstract":"","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42073465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-24DOI: 10.1080/14498596.2023.2226672
Riyajun Jannat, M. Al-Amin
{"title":"Spatial statistics for legal process","authors":"Riyajun Jannat, M. Al-Amin","doi":"10.1080/14498596.2023.2226672","DOIUrl":"https://doi.org/10.1080/14498596.2023.2226672","url":null,"abstract":"","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49495438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-21DOI: 10.1080/14498596.2023.2236996
Álvaro Barros-Sobrín, J. Balado, M. Soilán, Enrique Mingueza-Bauzá
{"title":"Gamification for road asset inspection from Mobile Mapping System data","authors":"Álvaro Barros-Sobrín, J. Balado, M. Soilán, Enrique Mingueza-Bauzá","doi":"10.1080/14498596.2023.2236996","DOIUrl":"https://doi.org/10.1080/14498596.2023.2236996","url":null,"abstract":"","PeriodicalId":50045,"journal":{"name":"Journal of Spatial Science","volume":null,"pages":null},"PeriodicalIF":1.9,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48554006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：