scholarly journals MONITORING PHENOLOGY OF FLOODPLAIN GRASSLAND AND HERBACEOUS VEGETATION WITH UAV IMAGERY

2016 ◽  
Vol XLI-B7 ◽  
pp. 569-571 ◽  
Author(s):  
W. K. van Iersel ◽  
M. W. Straatsma ◽  
E. A. Addink ◽  
H. Middelkoop
Keyword(s):  
Remote Sensing Data ◽  
Water Levels ◽  
Ecological Value ◽  
Herbaceous Vegetation ◽  
Vegetation Development ◽  
Hydraulic Roughness ◽  
Vegetation Height ◽  
Multi Temporal ◽  
One Year ◽  
Single Epoch

River restoration projects, which aim at improved flood safety and increased ecological value, have resulted in more heterogeneous vegetation. However, they also resulted in increasing hydraulic roughness, which leads to higher flood water levels during peak discharges. Due to allowance of vegetation development and succession, both ecological and hydraulic characteristics of the floodplain change more rapidly over time. Monitoring of floodplain vegetation has become essential to document and evaluate the changing floodplain characteristics and associated functioning. Extraction of characteristics of low vegetation using single-epoch remote sensing data, however, remains challenging. The aim of this study was to (1) evaluate the performance of multi-temporal, high-spatial-resolution UAV imagery for extracting temporal vegetation height profiles of grassland and herbaceous vegetation in floodplains and (2) to assess the relation between height development and NDVI changes. Vegetation height was measured six times during one year in 28 field plots within a single floodplain. UAV true-colour and false-colour imagery of the floodplain were recorded coincidently with each field survey. We found that: (1) the vertical accuracy of UAV normalized digital surface models (nDSMs) is sufficiently high to obtain temporal height profiles of low vegetation over a growing season, (2) vegetation height can be estimated from the time series of nDSMs, with the highest accuracy found for combined imagery from February and November (RMSE = 29-42 cm), (3) temporal relations between NDVI and observed vegetation height show different hysteresis behaviour for grassland and herbaceous vegetation. These results show the high potential of using UAV imagery for increasing grassland and herbaceous vegetation classification accuracy.

scholarly journals MONITORING PHENOLOGY OF FLOODPLAIN GRASSLAND AND HERBACEOUS VEGETATION WITH UAV IMAGERY

2016 ◽  
Vol XLI-B7 ◽  
pp. 569-571 ◽  
Author(s):  
W. K. van Iersel ◽  
M. W. Straatsma ◽  
E. A. Addink ◽  
H. Middelkoop
Keyword(s):  
Remote Sensing Data ◽  
Water Levels ◽  
Ecological Value ◽  
Herbaceous Vegetation ◽  
Vegetation Development ◽  
Hydraulic Roughness ◽  
Vegetation Height ◽  
Multi Temporal ◽  
One Year ◽  
Single Epoch

River restoration projects, which aim at improved flood safety and increased ecological value, have resulted in more heterogeneous vegetation. However, they also resulted in increasing hydraulic roughness, which leads to higher flood water levels during peak discharges. Due to allowance of vegetation development and succession, both ecological and hydraulic characteristics of the floodplain change more rapidly over time. Monitoring of floodplain vegetation has become essential to document and evaluate the changing floodplain characteristics and associated functioning. Extraction of characteristics of low vegetation using single-epoch remote sensing data, however, remains challenging. The aim of this study was to (1) evaluate the performance of multi-temporal, high-spatial-resolution UAV imagery for extracting temporal vegetation height profiles of grassland and herbaceous vegetation in floodplains and (2) to assess the relation between height development and NDVI changes. Vegetation height was measured six times during one year in 28 field plots within a single floodplain. UAV true-colour and false-colour imagery of the floodplain were recorded coincidently with each field survey. We found that: (1) the vertical accuracy of UAV normalized digital surface models (nDSMs) is sufficiently high to obtain temporal height profiles of low vegetation over a growing season, (2) vegetation height can be estimated from the time series of nDSMs, with the highest accuracy found for combined imagery from February and November (RMSE = 29-42 cm), (3) temporal relations between NDVI and observed vegetation height show different hysteresis behaviour for grassland and herbaceous vegetation. These results show the high potential of using UAV imagery for increasing grassland and herbaceous vegetation classification accuracy.

scholarly journals Assessing the Effect of Training Sampling Design on the Performance of Machine Learning Classifiers for Land Cover Mapping Using Multi-Temporal Remote Sensing Data and Google Earth Engine

2021 ◽  
Vol 13 (8) ◽  
pp. 1433
Author(s):  
Shobitha Shetty ◽  
Prasun Kumar Gupta ◽  
Mariana Belgiu ◽  
S. K. Srivastav
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Random Sampling ◽  
Sampling Design ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Machine Learning Classifiers ◽  
Learning Classifiers ◽  
Multi Temporal ◽  
Google Earth Engine

Machine learning classifiers are being increasingly used nowadays for Land Use and Land Cover (LULC) mapping from remote sensing images. However, arriving at the right choice of classifier requires understanding the main factors influencing their performance. The present study investigated firstly the effect of training sampling design on the classification results obtained by Random Forest (RF) classifier and, secondly, it compared its performance with other machine learning classifiers for LULC mapping using multi-temporal satellite remote sensing data and the Google Earth Engine (GEE) platform. We evaluated the impact of three sampling methods, namely Stratified Equal Random Sampling (SRS(Eq)), Stratified Proportional Random Sampling (SRS(Prop)), and Stratified Systematic Sampling (SSS) upon the classification results obtained by the RF trained LULC model. Our results showed that the SRS(Prop) method favors major classes while achieving good overall accuracy. The SRS(Eq) method provides good class-level accuracies, even for minority classes, whereas the SSS method performs well for areas with large intra-class variability. Toward evaluating the performance of machine learning classifiers, RF outperformed Classification and Regression Trees (CART), Support Vector Machine (SVM), and Relevance Vector Machine (RVM) with a >95% confidence level. The performance of CART and SVM classifiers were found to be similar. RVM achieved good classification results with a limited number of training samples.

scholarly journals A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations

2016 ◽  
Vol 100 (1) ◽  
pp. 27-38 ◽  
Author(s):  
Grazia Caradonna ◽  
Antonio Novelli ◽  
Eufemia Tarantino ◽  
Raffaela Cefalo ◽  
Umberto Fratino
Keyword(s):  
Land Cover ◽  
Satellite Data ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Geospatial Data ◽  
Usage Patterns ◽  
Mediterranean Regions ◽  
Multi Temporal ◽  
Using Data ◽  
Set Up

Abstract Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.

scholarly journals Mollusc fisheries and length–weight relationship in Tonle Sap flood pulse system, Cambodia

2018 ◽  
Vol 54 ◽  
pp. 34 ◽  
Author(s):  
Peng Bun Ngor ◽  
Ratha Sor ◽  
Leang Hour Prak ◽  
Nam So ◽  
Zeb S. Hogan ◽  
...  
Keyword(s):  
Annual Variation ◽  
Flood Pulse ◽  
Growth Patterns ◽  
Water Levels ◽  
Relationship Analysis ◽  
Weight Relationship ◽  
Daily Data ◽  
Tonle Sap ◽  
Mollusc Species ◽  
One Year

Molluscs are important for ecological function, livelihoods and fisheries, but are often forgotten in research and management. Here, we investigated intra-annual variation in the landing and growth patterns of three mollusc species, i.e., Corbicula moreletiana, Pila virescens and Pila ampullacea, using one-year daily data on landing catches and values, recorded in Kampong Chhnang province of Tonle Sap (TS) Lake. Overall, 8330 tonnes with a first sale landing value of US$ 1.4 million for the three species were reported. Also, we found that C. moreletiana was abundant during the dry season with high temperature and less precipitation. By contrast, the two Pila species were abundant from the early rainy to early dry seasons when precipitation and water levels increase. The length–weight relationship analysis indicated that a faster growth in weight of Pila species occurred in the rainy season, and a general negative allometric growth was observed for the three species. This implies that their populations were intensively fished. Our preliminary results suggest that molluscs in the TS Lake (i) are important resources in support of people's livelihoods, (ii) respond differently to intra-annual variation in temperature, precipitation and hydrology and (iii) are being intensively exploited with significant reduction in growth rate. Therefore, it is necessary to conduct further comprehensive research describing status of mollusc stocks and their ecology to support long-term management and conservation of this important aquatic fauna. Our study contributes to establishing the first important baseline data and information on key mollusc species for the TS.

scholarly journals Simulation and Assessment of Groundwater for Domestic and Irrigation Uses

2019 ◽  
Vol 5 (9) ◽  
pp. 1877-1892 ◽  
Author(s):  
Majed Rodhan Hussain ◽  
Basim Sh. Abed
Keyword(s):  
Cross Sections ◽  
Three Dimensional ◽  
Water Quality Assessment ◽  
Alluvial Fan ◽  
Water Levels ◽  
Specific Yield ◽  
Annual Rainfall ◽  
Steady State Condition ◽  
Groundwater Samples ◽  
One Year

The alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have been determined from one year field observations that were collected by General Authority of Groundwater, Diyala Governorate. Also, the observations were used for calibration of unsteady state model. Then wells were hypothetically redistributed and increased to 103 wells, assuming a distance of 1500 m between the wells, a well productivity rate of were 7 l/s, annual rainfall rate was used for recharging. Three different wells operating times were suggested and these 6, 12, and 18 hr/day with total discharge of 150, 300, 450 m3/day and maximum drawdown of 7, 11, and 20 m respectively. For water quality assessment, the collected groundwater samples were analysed at the laboratory.  Results showed that the TDS in all wells was ranged from 1000-3000 mg/l but TDS in well number 18 was exceeded 3000 mg/l which indicate that the groundwater in this well is not recommended to be used for irrigation. According to Iraqi standard for drink (IQS 2009), it can be used for drinking if saline treatment units were provided.

scholarly journals The problems of overexploitation of aquifers in semi-arid areas: the Murcia Region and the Segura Basin (South-east Spain) case

2012 ◽  
Vol 9 (5) ◽  
pp. 5729-5756 ◽  
Author(s):  
T. Rodríguez-Estrella
Keyword(s):  
Water Quality ◽  
Water Levels ◽  
Arid Areas ◽  
Karstic Aquifer ◽  
Autonomous Region ◽  
Groundwater Reserves ◽  
One Year ◽  
Semi Arid ◽  
Overexploited Aquifer ◽  
Poor Management

Abstract. A general analysis of the problems arising from aquifer exploitation in semi-arid areas such as the Autonomous Region of Murcia, which belongs to the Segura Basin is presented, with particular reference to the Ascoy-Sopalmo aquifer, which is the most overexploited aquifer in Spain. It has suffered intense overabstraction over the last forty years, given renewable water resources of 2 Mm3 yr−1 and abstractions amounting to as much as 55 Mm3 yr−1. This has resulted in the drying of springs, continuous drawdown of water levels (5 m yr−1); piezometric drops (over 30 m in one year, as a consequence of it being a karstic aquifer); increase in pumping costs (elevating water from more than 320 m depth); abandoning of wells (45 reduced to 20), diminishing groundwater reserves, and deteriorating water quality (progressing from a mixed sodium bicarbonate-chloride facies to a sodium chloride one). This is a prime example of poor management with disastrous consequences. In this sense, a series of internal measures is proposed to alleviate the overexploitation of this aquifer and of the Segura Basin, with the aim of contributing to a sustainable future.

scholarly journals CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 317-323
Author(s):  
J. Schachtschneider ◽  
C. Brenner
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Point Clouds ◽  
Urban Environments ◽  
Seasonal Effects ◽  
Data Set ◽  
Multi Temporal ◽  
One Year

Abstract. The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossible and there will always be a first time visit of an unknown or changed area, a map of an urban environment needs to model such dynamics.In this work, we use LiDAR point clouds from a large long term measurement campaign to investigate temporal changes. The data set was recorded along a 20 km route in Hannover, Germany with a Mobile Mapping System over a period of one year in bi-weekly measurements. The data set covers a variety of different urban objects and areas, weather conditions and seasons. Based on this data set, we show how scene and seasonal effects influence the measurement likelihood, and that multi-temporal maps lead to the best positioning results.

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