测绘地理信息 Pub Date : 2023-04-28 DOI: 10.58825/jog.2023.18.1.9

PRADNYA GOVEKAR, J. T. Gudagur, AJAYKUMAR N. ASODE

引用次数: 0

Monitoring of monthly scale chlorophyll concentration variability in the Bay of Bengal and Arabian Sea using MODIS Aqua Satellite Data 利用MODIS Aqua卫星数据监测孟加拉湾和阿拉伯海的月尺度叶绿素浓度变化

测绘地理信息 Pub Date : 2023-04-28 DOI: 10.58825/jog.2023.17.1.77

K. N. Devi, R. Sarangi

引用次数: 0

Static-PPP Performance using Multi-GNSS (Single, Dual and Triple) Frequency Observations 使用多gnss(单、双、三)频率观测的静态ppp性能

测绘地理信息 Pub Date : 2023-04-28 DOI: 10.58825/jog.2023.17.1.80

A. Farah

{"title":"Static-PPP Performance using Multi-GNSS (Single, Dual and Triple) Frequency Observations","authors":"A. Farah","doi":"10.58825/jog.2023.17.1.80","DOIUrl":"https://doi.org/10.58825/jog.2023.17.1.80","url":null,"abstract":"Precise Point Positioning (PPP) is relatively modern GNSS positioning technique that proved its efficiency comparing with traditional Differential positioning technique for more than three decades. PPP requires only one receiver collecting observations at unknown station, while Differential technique requires two receivers collecting observations simultaneously one at known-position station and the other at unknown station. Extensive mitigation of different GNSS errors is essential for PPP-collected observations. Static-PPP accuracy depends on different factors such as; used GNSS system; single (GPS(G) or GLONASS(R) or BeiDou(C) or Galileo(E)) or mixed-GNSS systems (GPS/GLONASS or GPS/GLONASS/BeiDou or GPS/GLONASS/BeiDou/Galileo), observations type (single or dual or triple frequency), satellites geometry and observations duration. This research investigates static-PPP accuracy variation on three different-latitude IGS stations based on different factors; used GNSS system (single or mixed), observations type (single or dual or triple frequency) and satellites geometry. It can be concluded that GRCE combination provides 3D-accuracy of (8 cm) using single frequency observations, (1.5 mm) using dual frequency observations and (1 mm) using triple frequency observations. GRCE combination provides a convergence time of only four minutes (8 epochs) for dual frequency observations. ","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45903531","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}

引用次数: 1

Area Estimation of Mango and Coconut Crops using Machine Learning in Hesaraghatta Hobli of Bengaluru Urban District, Karnataka 在卡纳塔克邦班加罗尔市区Hesaraghatta Hobli使用机器学习估算芒果和椰子作物面积

测绘地理信息 Pub Date : 2023-04-28 DOI: 10.58825/jog.2023.17.1.75

Zubair Ahmed, P.P. Nageswara Rao, P. Srikanth

{"title":"Area Estimation of Mango and Coconut Crops using Machine Learning in Hesaraghatta Hobli of Bengaluru Urban District, Karnataka","authors":"Zubair Ahmed, P.P. Nageswara Rao, P. Srikanth","doi":"10.58825/jog.2023.17.1.75","DOIUrl":"https://doi.org/10.58825/jog.2023.17.1.75","url":null,"abstract":"Timely and accurate estimation of acreage and production of horticulture crops is necessary for deciding how much, where and when to export these commodities in the national and global markets. Remote sensing has been one of the methods adopted, in addition to conventional sampling methods, for improving the estimates. Parametric image classification algorithms have been used by many researchers for identification and area estimation of horticulture crops. But these algorithms result in several unclassified pixels leading to over/underestimates. This study has been undertaken to estimate the area of two horticulture crops (i.e., mango and coconut) of Hesaraghatta hobli of Bengaluru urban district using Convolutional Neural Network (CNN) on Google Colaband Random Forest (RF) algorithms on Google Earth Engine (GEE). Remotely sensed data acquired by the Multi-Spectral Instrument (MSI) onboard Sentiel-2A satellite was used. Spectral signatures of horticulture crops and other associated cover types have been generated to identify the cover types and for selecting appropriate band combinations. Two different band combinations were used for area estimation of selected horticulture crops: i) Near-InfraRed (NIR), Red, and Green all three having a spatial resolution of 10 m, ii) Red edge-3, Short-Wave InfraRed1 (SWIR1) and Short-Wave InfraRed2 (SWIR2) having 20 m spatial resolution. Area estimates of horticulture crops and associated cover types were validated with respect to ground truth and statistical reports from Karnataka State Directorate of Horticulture (KSDH). It was found that the CNN model performed better than RF using NIR, Red, and Green band combination with an overall accuracy of 84%, but it failed to give similar accuracies with Red edge 3, SWIR1, and SWIR2 band combination. We attempted transfer learning using the trained CNN model at two different study areas far away from the study area and found encouraging results.","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44815881","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}

引用次数: 0

Study of CNN deep learning model for temporal remote sensing data processing to map rabi crops CNN深度学习模型在时序遥感数据处理中的应用研究

测绘地理信息 Pub Date : 2022-10-31 DOI: 10.58825/jog.2022.16.2.46

Mragank Snighal, A. Payal, Ashok Kumar

{"title":"Study of CNN deep learning model for temporal remote sensing data processing to map rabi crops","authors":"Mragank Snighal, A. Payal, Ashok Kumar","doi":"10.58825/jog.2022.16.2.46","DOIUrl":"https://doi.org/10.58825/jog.2022.16.2.46","url":null,"abstract":"Convolution Neural Network (CNN) is a deep learning approach that has become an area of interest to the researchers for solving complex problems. With the evaluation of CNN, extraction of deep features for accurate classification of remotely sensed images has gained lot of momentum. This research work uses CNN deep learning model for mapping rabi crops (mustard and wheat) using temporal remote sensing data. The mappings of mustard and wheat crops have been conducted using multispectral temporal images obtained from Sentinel 2A/2B between the dates 1st Nov 2019 and 24th Feb 2020 of Banasthali, Rajasthan region. The CNN model created in this research work uses several layers along with 5 activation functions (relu, sigmoid, tanh, elu and selu) for finding out which activation function gave the best result for the proposed study. Batch size has been examined from 1 to 50 in the multiple of 5 and epochs have been tested from 1 to 10 for a training data of 200 samples for each class. The optimal value with a batch size of 5 and epochs of 30 has been calculated as best suited in this study as the accuracy was getting constant. The implementation of CNN model for classification shows better results as compared to the traditional approach as the CNN algorithms are learning algorithms. This also helps in handling the heterogeneity within a class. A comparison has been conducted using Modified Possibilistic c-Means (MPCM) fuzzy algorithm for the classification of the same set of classes. F-Score, Kappa and Overall Accuracy have been calculated to show how the proposed approach has been outperformed and the level of classification accuracy achieved.","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47225102","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}

引用次数: 0

Web-GIS based Dashboard for Real-Time Data Visualization & Analysis using Open Source Technologies 基于Web-GIS的仪表板，用于使用开源技术的实时数据可视化和分析

测绘地理信息 Pub Date : 2022-10-31 DOI: 10.58825/jog.2022.16.2.42

K. Lata, Anil Sood, K. Kaur, Amanpreet Kaur Benipal, B. Pateriya

引用次数: 0

Determination of radii of curvature for high resolution geoid models using the harmonic synthesis algorithm 用调和合成算法确定高分辨率大地水准面模型的曲率半径

测绘地理信息 Pub Date : 2022-10-31 DOI: 10.58825/jog.2022.16.2.40

Raaed Mohamed Kamel Hassouna

{"title":"Determination of radii of curvature for high resolution geoid models using the harmonic synthesis algorithm","authors":"Raaed Mohamed Kamel Hassouna","doi":"10.58825/jog.2022.16.2.40","DOIUrl":"https://doi.org/10.58825/jog.2022.16.2.40","url":null,"abstract":"Different types of radii of curvature were assessed for the geoid based on the GECO geopotential model, up to degree and order 2190. The route values of gravity and the three horizontal gravity gradients were computed based on such geopotential model and the angular velocity of the Earth. The investigation was performed on coarse global grids and finer grids covering the Egyptian territory. Respective latitudinal and longitudinal profiles for the geoidal radii were extracted. Comparisons were held with the radii of curvature on the WGS-84 ellipsoid, and with the geoidal radii derived from other models of lower resolutions. Unlike the ellipsoid, the values of the geoidal radii exhibited a rather irregular behaviour that is far from any geographical symmetry. The principal radii of the geoid do not generally occur along the meridian and prime-vertical directions. Such irregularities were found to be more exaggerated with higher degrees. At all investigated resolution levels, the signs of the principal radii assured the convexity of the geoid surface. This enabled to define, compute and compare the Gaussian mean radii for the geoid. The local residual geoidal radii showed a decaying spectral tendency. Also, the results implied that the utilized algorithm proved to be convergent. ","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49194737","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}

引用次数: 0

Geospatial Analysis of Spatial Variability of Groundwater Quality Using Ordinary Kriging: A Case Study of Dungarpur Tehsil, Rajasthan, India 基于普通克里格法的地下水水质空间变异性地理空间分析——以印度拉贾斯坦邦邓格普尔特希尔为例

测绘地理信息 Pub Date : 2022-10-31 DOI: 10.58825/jog.2022.16.2.47

Seema Jalan, D. Chouhan, Shailesh Chaure

{"title":"Geospatial Analysis of Spatial Variability of Groundwater Quality Using Ordinary Kriging: A Case Study of Dungarpur Tehsil, Rajasthan, India","authors":"Seema Jalan, D. Chouhan, Shailesh Chaure","doi":"10.58825/jog.2022.16.2.47","DOIUrl":"https://doi.org/10.58825/jog.2022.16.2.47","url":null,"abstract":"Groundwater is one the major sources of natural water being exploited excessively for various uses in India. \u0000Thus, it is very essential to monitor the spatial and temporal variability of groundwater quality. Geo-Statistical Interpolation using GIS has been considered as the best and most advanced method for the interpolation and prediction studies of groundwater pollution and quality, and is adopted universally. In this paper, ordinary Kriging with logarithmic data transformation has been used to interpolate and predict the spatial variation of groundwater quality parameters - EC, TDS, pH, Na+, Ca2+, Bi-Carbonate, Fluoride, Chloride, Sulphate and Nitrate using data pertaining to 48 well locations in the Dungarpur tehsil. Data was transformed and normalized using Logarithmic Transformation Method and Semivariograms were drawn and analyzed for selecting the suitable model. The best Semivariogram model was obtained based upon cross validation and on the lesser RMSE criterion and Coefficient of Determination. The results show that the best semivariogram model based on RMSE varied for each water quality parameter. For log transformed data Exponential model was found suitable for EC, TDS, Na+, TH etc.; Spherical model for Ca2+ ; Chloride Gaussian Model for Chloride. For original or raw for non-transformed data Exponential Model was found suitable for Fluoride, Sulphate and Nitrate; and Gaussian Model for pH and Bi-Carbonates.","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48185847","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}

引用次数: 0

Paleo-topographic Reconstruction of Cultural Landscapes using Remote Sensing and GIS: A case study of the ancient port of Tamralipti 基于遥感和GIS的文化景观古地形重建——以Tamralipti古港口为例

测绘地理信息 Pub Date : 2022-10-31 DOI: 10.58825/jog.2022.16.2.50

Pradeep S Arya, Rajani M B

{"title":"Paleo-topographic Reconstruction of Cultural Landscapes using Remote Sensing and GIS: A case study of the ancient port of Tamralipti","authors":"Pradeep S Arya, Rajani M B","doi":"10.58825/jog.2022.16.2.50","DOIUrl":"https://doi.org/10.58825/jog.2022.16.2.50","url":null,"abstract":"Human interaction with the landscape they inhabit leaves imprints that are largely inconspicuous on the ground. Yet, these remain the most thought provoking among the sets of clues available to us in fuelling the quest to understand our past. Spatial view provided by satellite imagery plays a pivotal part in enabling us to identify these imprints in the form of patterns. In this study, a paleo-environmental reconstruction of a particular cultural landscape using geo-spatial tools has been attempted. A range of historical documents (textual records such as traveller’s accounts dating to 5th and 7th centuries CE, maps of the Indian sub-continent published in the 18th and 19th centuries) and satellite imagery of the last 50 years (CORONA, Google Earth Digital Globe ) are used to identify and analyse the distribution of cultural sites that are hitherto unexplored to understand the impact of past changes to the landscape of these ancient sites located along one of the most dynamic regions of the Indian subcontinent: the Gangetic Delta. The identification of numerous sites of a distinct pattern and their distribution, analysed along with the morphological signature of the landscape on which they remain almost undetected has led to certain inferences on the possible location and extents of the ancient port of Tamralipti. The study also reveals the coastal and deltaic changes in the vicinity of the ancient port.","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46199258","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}

引用次数: 0

Monitoring Road maintenance using video-geotagging in geographical information system: an innovative approach 在地理信息系统中使用视频地理标记监控道路维护:一种创新方法

测绘地理信息 Pub Date : 2022-10-31 DOI: 10.58825/jog.2022.16.2.49

A. Mathur, Nishant Tiwari, Vipan Kumar, B. Pateriya

引用次数: 0

测绘地理信息最新文献