Showing papers in "Geocarto International in 2019"
TL;DR: An adaptive neuro-fuzzy inference system (ANFIS), with two heuristic-based computation methods namely biogeography-based optimization (BBO) and BAT algorithm (BA) with GIS to map flood susceptibility in a region of Iran shows its great potential by considering higher accuracy and lower computational time, in mapping and assessment of flood susceptibility.
Abstract: This paper couples an adaptive neuro-fuzzy inference system (ANFIS), with two heuristic-based computation methods namely biogeography-based optimization (BBO) and BAT algorithm (BA) with GIS to map...
179 citations
TL;DR: Results showed that the hybrid ensemble models could significantly improve the performance of the base classifier of BLR, and RS model had the highest performance in comparison to other landslide ensemble models.
Abstract: A novel artificial intelligence approach of Bayesian Logistic Regression (BLR) and its ensembles [Random Subspace (RS), Adaboost (AB), Multiboost (MB) and Bagging] was introduced for landslide susc...
105 citations
TL;DR: In this article, a hybrid of evidence belief function (EBF) with logistic regression and logistic model tree was used for landslide susceptibility modeling. And the performance of three models was evaluated using the area under the curve (AUC).
Abstract: In this study, we introduced novel hybrid of evidence believe function (EBF) with logistic regression (EBF-LR) and logistic model tree (EBF-LMT) for landslide susceptibility modelling. Fourteen conditioning factors were selected, including slope aspect, elevation, slope angle, profile curvature, plan curvature, topographic wetness index (TWI), stream sediment transport index (STI), stream power index (SPI), distance to rivers, distance to faults, distance to roads, lithology, normalized difference vegetation index (NDVI), and land use. The importance of factors was assessed using correlation attribute evaluation method. Finally, the performance of three models was evaluated using the area under the curve (AUC). The validation process indicated that the EBF-LMT model acquired the highest AUC for the training (84.7%) and validation (76.5%) datasets, followed by EBF-LR and EBF models. Our result also confirmed that combination of a decision tree-logistic regression-based algorithm with a bivariate statistical model lead to enhance the prediction power of individual landslide models.
99 citations
TL;DR: Land use/land cover (LULC) is a fundamental concept of the Earth's system intimately connected to many phases of the human and physical environment as mentioned in this paper, and Earth observation (EO) technology provides an in...
Abstract: Land use/land cover (LULC) is a fundamental concept of the Earth's system intimately connected to many phases of the human and physical environment. Earth observation (EO) technology provides an in...
92 citations
TL;DR: Analysis results show that the SVM has the highest prediction capability, followed by the NBT, DTNBT, BN and NB, respectively, which confirms thatThe SVM is one of the benchmark models for the assessment of susceptibility of landslides.
Abstract: In this study, the main goal is to compare the predictive capability of Support Vector Machines (SVM) with four Bayesian algorithms namely Naive Bayes Tree (NBT), Bayes network (BN), Naive Bayes (N...
81 citations
TL;DR: In this paper, the authors investigate and compare the capabilities of four machine learning methods namely LogitBoost Ensemble (LBE), Fisher's Linear Discriminate Analysis (FLDA), Logistic R...
Abstract: The purpose of this study was to investigate and compare the capabilities of four machine learning methods namely LogitBoost Ensemble (LBE), Fisher’s Linear Discriminate Analysis (FLDA), Logistic R...
60 citations
TL;DR: Many regions remain poorly studied in terms of geological mapping and mineral exploration in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistic diffic... as mentioned in this paper,.
Abstract: Many regions remain poorly studied in terms of geological mapping and mineral exploration in inaccessible regions especially in the Arctic and Antarctica due to harsh conditions and logistic diffic...
60 citations
TL;DR: In this paper, a study was applied to estimate the soil organic carbon (SOC) in soil quality and plays an imperative role in soil productivity in the agriculture ecosystems, which is an important aspect of soil quality.
Abstract: Soil organic carbon (SOC) is an important aspect of soil quality and plays an imperative role in soil productivity in the agriculture ecosystems. The present study was applied to estimate the SOC s...
57 citations
TL;DR: In this paper, the authors used multi-date Landsat images to quantify mangrove cover changes in the whole of Bangladesh from 1976 to 2015, indicating the areal extent of mangroves increased by 3.1% between 1976 and 2015.
Abstract: This study used multi-date Landsat images to quantify mangrove cover changes in the whole of Bangladesh from 1976 to 2015. Images were pre-processed with an atmospheric correction using Dark Object Subtraction (DOS) and Relative Radiometric Normalization (RRN) using Pseudo-Invariant Features (PIFs). Land Use/Land Cover (LU/LC) classification map was generated using Maximum Likelihood (MaxLike) algorithm, indicating the areal extent of mangroves increased by 3.1% between 1976 and 2015, where 1.79% of this increase occurred between 2000 and 2015. Though mangrove areas remained almost constant in the Sundarbans, Chakaria Sundarbans has almost disappeared between 1976 and 1989. The overall accuracy of Landsat MSS, TM, ETM+, and L8 OLI classified images were 80%, 80%, 87%, and 97% respectively. The study also found deforestation, shrimp & salt farm, coastal erosion and sedimentation, and mangrove plantation could be responsible for mangrove changes in Bangladesh. (Less)
43 citations
TL;DR: In this article, random forest regression (RFR), support vector regression (SVR) and artificial neural network regression (ANNR) models were evaluated for the retrieval of soil moisture covere.
Abstract: In the present study, random forest regression (RFR), support vector regression (SVR) and artificial neural network regression (ANNR) models were evaluated for the retrieval of soil moisture covere...
43 citations
TL;DR: In this article, a new index referred as Built-up Land Features Extraction Index (BLF index) was proposed to extract built-up areas from remote sensing data like Landsat 8 satellite.
Abstract: Extracting built-up areas from remote sensing data like Landsat 8 satellite is a challenge. We have investigated it by proposing a new index referred as Built-up Land Features Extraction Index (BLF ...
TL;DR: Wang et al. as discussed by the authors evaluated and compared landslide susceptibility maps of the Baxie River basin, Gansu Province, China, using three models: evidential belief function (EBF), certainty factor (CF) and frequency ratio (FR).
Abstract: This study evaluates and compares landslide susceptibility maps of the Baxie River basin, Gansu Province, China, using three models: evidential belief function (EBF), certainty factor (CF) and frequency ratio (FR). First, a landslide inventory map is constructed from satellite image interpretation and extensive field data. Second, the study area is partitioned into 17,142 slope units, and modelled using nine landslide influence parameters: elevation, slope angle, slope aspect, relief amplitude, cutting depth, gully density, lithology, normalized difference vegetation index and distance to roads. Finally, landslide susceptibility maps are presented based on EBF, CF and FR models and validated using area under curve (AUC) analysis. The success rates of the EBF, CF and FR models are 0.8038, 0.7924 and 0.8088, respectively, while the prediction rates of the three models are 0.8056, 0.7922 and 0.7989, respectively. The result of this study can be reliably used in land use management and planning.
TL;DR: Punarbhaba river of Indo-Bangladesh has experienced hydro-ecological alteration after installation of Komardanga dam in 1992 and consequently wetland and inundation areas have undergone int...
Abstract: Punarbhaba river of Indo-Bangladesh has experienced hydro-ecological alteration after installation of Komardanga dam in 1992 and consequently wetland and inundation areas have undergone int...
TL;DR: In this article, the authors quantified LULC changes and the effect of urban expropriation on land use and land cover in the city of New Orleans, USA. But they focused on urban areas.
Abstract: Understanding rates, patterns and types of land use and land cover (LULC) changes are essential for various decision-making processes. This study quantified LULC changes and the effect of urban exp...
TL;DR: In this paper, the authors used deep learning and machine learning models to understand the spatial distribution of vegetation species in order to gain knowledge on the recovery process of an ecosystem. But few studies have used DNNs and ML models to predict vegetation species distribution.
Abstract: Understanding the spatial distribution of vegetation species is essential to gain knowledge on the recovery process of an ecosystem. Few studies have used deep learning and machine learning models ...
TL;DR: In this paper, the authors investigated the effects of urbanization growth on river morphology in the downstream part of Talar River, east of Mazandaran Province, Iran and found that residential lands were increased in area by about 1631%, while forest land and riparian vegetation decreased in by approximately 99.9 and 96.2%, respectively.
Abstract: In the present study, we investigate the effects of urbanization growth on river morphology in the downstream part of Talar River, east of Mazandaran Province, Iran. Morphological and morphometric parameters in 10 equal sub-reaches were defined along a 11.5 km reach of the Talar River after land cover maps were produced for 1955, 1968, 1994, 2005 and 2013. Land cover types changed extremely during the study period. Residential lands were found to have increased in area by about 1631%, while forest land and riparian vegetation decreased in by approximately 99.9 and 96.2%, respectively. The results of morphometric and morphological factors showed that average channel width (W) for all 11.5 km of the study river decreased by 84% during the study period, while the flow length increased by about 2.14%.
TL;DR: In this paper, the authors examined the status of snow cover area (SCA) using moderate resolution images of the Kashmir Himalayas and found that snow cover makes an essential component of the hydrological system of the Himalayan region.
Abstract: Snowmelt makes an essential component of the hydrological system of Kashmir Himalayas. The present study was carried out to examine the status of Snow Cover Area (SCA) using Moderate Resolution Ima...
TL;DR: In this paper, the authors deal with the use of specific vegetation indices for extracting mangrove forests from remote sensing data, where the identification accuracy of mangroves is greatly influenced by terrestrial vegetation.
Abstract: In remote sensing the identification accuracy of mangroves is greatly influenced by terrestrial vegetation. This paper deals with the use of specific vegetation indices for extracting mangrove fore...
TL;DR: In this article, feature-oriented principal component selection, spectral angle mapper, linear spectral unmixing were applied to ASTER data based on spectral characteristics of hydrothermal alteration key minerals for a systematic selective extraction of the information of interest.
Abstract: Concealed and fossilized geothermal systems are not characterized by obvious surface manifestations like hotsprings and fumaroles, therefore, could not be easily identifiable using conventional techniques. In this investigation, the applicability of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion data-sets were evaluated in discriminating hydrothermal alteration minerals associated with geothermal systems as a proxy in identifying subtle Geothermal systems at Yankari Park, Nigeria. Feature-oriented principal component selection, spectral angle mapper, linear spectral unmixing were applied to ASTER data based on spectral characteristics of hydrothermal alteration key minerals for a systematic selective extraction of the information of interest. Analytical imaging and geophysics-developed processing methods were applied to Hyperion data for mapping iron oxide/hydroxide minerals and clay mineral assemblages in hydrothermal alteration zones. The results indicate that ASTER and Hyperion could be complemented for reconnaissance stage of targeting subtle alteration mineral assemblages associated with geothermal systems.
TL;DR: In this paper, the authors identified two standards applied to reclassify landslide-conditioning factors differ among studies and may change the accuracy of identifying landslide-prone areas, and they proposed two standards per
Abstract: The standards applied to reclassify landslide-conditioning factors differ among studies and may change the accuracy of identifying landslide-prone areas Therefore, we identified two standards per
TL;DR: It is concluded that the machine learning classifiers combined with remotely sensed data and GIS is promising for malaria vulnerability mapping, and the derived maps can be used as a fundamental basis for programmes on spatial disease control.
Abstract: This study examines the potentials of remotely sensed data, GIS and some machine learning classifiers and ensemble techniques in the investigation of the non-linear relationship between malaria occ...
TL;DR: Inland waters, characterized by small scale but a large number, play an important role in the carbon budget and global carbon cycle as discussed by the authors, and colored dissolved organic matter (CDOM) is a significant indicat...
Abstract: Inland waters, characterized by small scale but a large number, play an important role in the carbon budget and global carbon cycle. Colored dissolved organic matter (CDOM) is a significant indicat...
TL;DR: Using high-resolution Google EarthTM images in conjunction with Landsat images, the glaciers and lakes in the Baspa basin were classified to explore the recent changes as discussed by the authors, and a total number of 109 glacier...
Abstract: Using high-resolution Google EarthTM images in conjunction with Landsat images, the glaciers and lakes in the Baspa basin are classified to explore the recent changes. A total number of 109 glacier...
TL;DR: Object-based image analysis (OBIA) has been a new area of research in satellite image processing applications, since it improves the quality of information acquisition about geospatial objects as mentioned in this paper.
Abstract: Object-based image analysis (OBIA) has been a new area of research in satellite image processing applications, since it improves the quality of information acquisition about geospatial objects and ...
TL;DR: In this paper, growth in small and medium sized towns and cities have been unnoticed and growing without apriori planning in developing countries like India are an urbanization hotspot with many upcoming towns and Cities.
Abstract: Developing countries like India are an urbanization hotspot with many upcoming towns and cities. Growth in small and medium sized towns and cities have been unnoticed and growing without ap...
TL;DR: The quality of the city model obtained with the SfM/MVS approach was evaluated on a dataset of aerial images involving the Old Town of Bordeux, taking into account the possibility to acquire aerial nadir and oblique images according to multi-view.
Abstract: The use of Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) approaches to build 3D models of structures belonging to the Cultural Heritage environment is becoming more widespread. Du...
TL;DR: In this article, the authors integrated the Red Edge channel in satellite sensors for plant species discrimination and found that it was useful for plant detection in the field of plant species classification. Sentinel-2 MSI and Rapid Eye are some of the new generation satellite sensors.
Abstract: Integrating the Red Edge channel in satellite sensors is valuable for plant species discrimination. Sentinel-2 MSI and Rapid Eye are some of the new generation satellite sensors that are ch...
TL;DR: In this paper, a non-destructive, cost-effective tool for coral reef monitoring, able to integrate traditional remote sensing techniques and support researchers' work, is presented and evaluated.
Abstract: Photogrammetry represents a non-destructive, cost-effective tool for coral reef monitoring, able to integrate traditional remote sensing techniques and support researchers’ work. However, its appli...
TL;DR: In this paper, sustainable development is a vital and challenging factor for managing urban growth smartly, which contains three main components, namely economic growth, ecological protection and social jus...
Abstract: Sustainable development is a vital and challenging factor for managing urban growth smartly. This factor contains three main components, namely economic growth, ecological protection and social jus...
TL;DR: In this article, the utility of Vegetation Temperature Conditions (VTC) is demonstrated for controlling the water and energy budgets at the soil-plant-atmosphere continuum.
Abstract: Soil moisture is one of the key state variable to regulate the water and energy budgets at the soil-plant-atmosphere continuum. This study demonstrates the utility of Vegetation Temperature Conditi...