scholarly journals Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya

2019 ◽  
Vol 11 (10) ◽  
pp. 1217 ◽  
Author(s):  
Purity Rima Mbaabu ◽  
Wai-Tim Ng ◽  
Urs Schaffner ◽  
Maina Gichaba ◽  
Daniel Olago ◽  
...  
Keyword(s):  
Integrated Approach ◽  
Well Being ◽  
Time Interval ◽  
Wet Season ◽  
Alien Plant ◽  
Random Forest Classification ◽  
Lulc Changes ◽  
Forest Classification ◽  
Landsat Satellite ◽  
Gains And Losses

Woody alien plant species have been deliberately introduced globally in many arid and semi-arid regions, as they can provide services and goods to the rural poor. However, some of these alien trees and shrubs have become invasive over time, with important impacts on biodiversity, ecosystem services, and human well-being. Prosopis was introduced in Baringo County, Kenya, in the 1980s, but since then, it has spread rapidly from the original plantations to new areas. To assess land-use and land-cover (LULC) changes and dynamics in Baringo, we used a combination of dry and wet season Landsat satellite data acquired over a seven-year time interval between 1988–2016, and performed a supervised Random Forest classification. For each time interval, we calculated the extent of Prosopis invasion, rates of spread, gains and losses of specific LULC classes, and the relative importance of Prosopis invasion on LULC changes. The overall accuracy and kappa coefficients of the LULC classifications ranged between 98.1–98.5% and 0.93–0.96, respectively. We found that Prosopis coverage increased from 882 ha in 1988 to 18,792 ha in 2016. The highest negative changes in LULC classes were found for grasslands (−6252 ha; −86%), irrigated cropland (−849 ha; −57%), Vachellia tortilis-dominated vegetation (−3602 ha; −42%), and rainfed cropland (−1432 ha; −37%). Prosopis invasion alone directly accounted for over 30% of these negative changes, suggesting that Prosopis invasion is a key driver of the observed LULC changes in Baringo County. Although the management of Prosopis by utilization has been promoted in Baringo for 10–15 years, the spread of Prosopis has not stopped or slowed down. This suggests that Prosopis management in Baringo and other invaded areas in East Africa needs to be based on a more integrated approach.

scholarly journals Spatial Evolution of Prosopis Invasion and its Effects on LULC and Livelihoods in Baringo, Kenya

2019 ◽  
Author(s):  
Purity Rima ◽  
Wai-Tim Ng ◽  
Urs Schaffner ◽  
Maina Gichaba ◽  
Dan Olago ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Well Being ◽  
Time Interval ◽  
Wet Season ◽  
Alien Plant ◽  
Rural People ◽  
Random Forest Classification ◽  
Lulc Changes ◽  
Forest Classification ◽  
Landsat Satellite

Woody alien plant species have been deliberately introduced globally in many arid and semi-arid regions as they can provide services and goods to the rural poor. However, some of these alien trees and shrubs have become invasive over time, with important impacts on biodiversity, ecosystem services and human well-being. Prosopis was introduced in Baringo County, Kenya, in the 1980s, but since then it has spread rapidly from the original plantations to new areas. To assess land use and land cover (LULC) changes and dynamics in Baringo, we used a combination of dry and wet season Landsat satellite data acquired in a 7-year time interval between 1988 and 2016 and performed a supervised Random Forest classification. For each time interval we calculated extent of the invasion, rates of spread and gains and losses of specific LULC classes. We further assessed the relative importance of Prosopis invasion on LULC changes and ultimately on the provision of ecosystem services rural people depend on. Overall accuracy and kappa coefficients of the LULC classifications ranged between 98.1 % and 98.5 %, and 0.93 and 0.96, respectively. We found that Prosopis coverage increased from 882 ha in 1988 to 18,792 ha in 2016. Highest negative change in LULC classes was found for grasslands (-6252 ha; -86 %), irrigated cropland (-849 ha; -57 %), Vachellia tortilis dominated vegetation (-3602 ha; -42 %), and rainfed cropland (-1432 ha; -37 %) – all of them important categories with regard to rural people’s livelihoods. Prosopis invasion alone directly accounted for over 30% of these negative changes, suggesting that Prosopis invasion is a key driver of the observed LULC changes in Baringo County. The observed rates of invasion are alarming and ask for urgent implementation of coordinated and sustainable Prosopis management in Baringo and other invaded areas in East Africa.

scholarly journals Análise de acurácia para o mapeamento de áreas queimadas utilizando uma cena VIIRS 1Km e classificação por Random Forest

2021 ◽  
Vol 14 (6) ◽  
pp. 3225
Author(s):  
Juarez Antonio da Silva Júnior ◽  
Ubiratan Joaquim da Silva Júnior ◽  
Admilson Da Penha Pacheco
Keyword(s):  
Random Forest ◽  
Spatial Resolution ◽  
Forest Fires ◽  
Remote Sensing Data ◽  
Fire Detection ◽  
Time Interval ◽  
Validation Data ◽  
Random Forest Classification ◽  
Burned Areas ◽  
Forest Classification

A disponibilidade gratuita de dados de sensoriamento remoto em áreas atingidas por incêndios florestais em escala global oferece a oportunidade de geração sistemática de produtos terrestres de média resolução espacial, porém as conhecidas limitações de precisão é objeto de estudo em todo o mundo. Este artigo tem como objetivo analisar a acurácia da detecção de áreas queimadas utilizando o classificador Random Forest (RF) por meio de uma cena do sensor Radiômetro de Imagem Infravermelho Visível (VIIRS) (1Km) em quatro pontos da savana brasileira. Os resultados foram validados através dos produtos de referência espacial de áreas queimadas: Aq30m, Fire_cci e MCD64A1 por meio de uma abordagem estratificada possibilitando a amostragem dos dados no espaço e tempo. Os modelos de RF avaliados com seus parâmetros de entrada, em que, incluiu-se 400 árvores e um atributo, fornecendo uma taxa de erro abaixo de 4%. Os resultados mostraram que o mapeamento validado com o produto Aq30m apresentou importantes estimativas de Coeficiente de Sorensen-Dice enquanto a validação realizada entre os modelos globais, o MCD64A1 mostrou-se com maior exatidão (>50%) principalmente em feições de áreas queimadas de grandes proporções (> 200Km²). Em particular, a análise sugere que a validação de produtos de área queimada sempre deve estar ligada ao tempo mínimo da data dos dados de validação e o tamanho da área atingida pelo fogo. Os resultados mostram que esta abordagem é muito útil para ser usado para determinar áreas de floresta queimada.      Accuracy analysis for mapping burnt areas using a 1Km VIIRS scene and Random Forest classification A B S T R A C TThe availability of remote sensing data with medium spatial resolution has offered several mapping possibilities for areas affected by forest fires on the Earth's surface. In this context, the analysis of sensor spatial accuracy limitations has been the subject of global research. The objective of this study was to analyze the mapping accuracy of the VIIRS sensor on board the NOAA satellite, using the Random Forest (RF) classifier for the detection of burned areas, in four points of the Chapada dos Veadeiros National Park - Goiás, inserted in the Brazilian savanna. The methodology consisted in validating the classification using the Sorensen-Dice coefficient (SD) in a stratified approach, using as reference the products: Aq30m, Fire_cci and MCD64A1. As a result, the RF models, included 400 trees and one attribute, with an error of less than 4%. Among the global models, the MCD64A1 presented a significant accuracy, greater than 50%, especially in features of burned areas greater than 200Km². Thus, the data suggest that the quality of accuracy of the validation process of mapping products for burned areas is associated with the minimum time interval of availability of validation data and the size of the area affected by fire. Based on this, the results show effectiveness in using the RF algorithm on medium spatial resolution images for fire detection in seasonally dry forests, such as the Cerrado.Keywords: Cerrado, fires, Random Forest.

scholarly journals INVASION OF SAVANNAS BY PROSOPIS TREES IN EASTERN AFRICA: EXPLORING THEIR IMPACTS ON LULC DYNAMICS, LIVELIHOODS AND IMPLICATIONS ON SOIL ORGANIC CARBON STOCKS

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 335-340
Author(s):  
P. R. Mbaabu ◽  
U. Schaffner ◽  
S. Eckert
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Land Cover ◽  
Management Strategies ◽  
Integrated Approach ◽  
Eastern Africa ◽  
Lulc Changes ◽  
Management Interventions ◽  
Trade Offs ◽  
Landsat Satellite

Abstract. Trees of the genus Prosopis from the Americas, were introduced in Eastern Africa in the 1970s to mitigate land degradation and its associated disservices. However, over time these trees have spread and invaded valuable grasslands and croplands and consequently led to significant land use and land cover (LULC) changes and livelihood stress. Early detection of invasive species is essential for formulating effective management strategies to prevent further spread into non-invaded lands and for monitoring the outcome of management interventions. We mapped the spatio-temporal evolution and dynamics of Prosopis invasion, its impacts on LULC and livelihoods in Baringo, Kenya by applying a Random Forest classifier on Landsat satellite data over seven-year intervals from 1988 – 2016. We then linked the LULC changes to soil organic carbon (SOC) stocks that we had measured for the different LULCs and also to socio-economic data on annual costs of clearing Prosopis from farmlands. By 2016, Prosopis had invaded 18,792 ha of land, spreading at a rate of 640 ha/yr, while all other land uses and land cover declined, each by over 40% of its original coverage in 1988. Through LULC specific SOC measurements, and relating the changes to annual costs of clearing Prosopis, we found that Prosopis removal and restoration to grassland is more effective for climate change mitigation compared to Prosopis “cultivation” while also avoiding trade-offs with other ecosystem services and livelihoods. Therefore, future management of this species in Kenya and Eastern Africa should be based on a more collaborative and integrated approach.

scholarly journals Integrative Analysis with Monte Carlo Cross-Validation Reveals miRNAs Regulating Pathways Cross-Talk in Aggressive Breast Cancer

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Antonio Colaprico ◽  
Claudia Cava ◽  
Gloria Bertoli ◽  
Gianluca Bontempi ◽  
Isabella Castiglioni
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cross Talk ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrated Approach ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Stem Cell Pluripotency

In this work an integrated approach was used to identify functional miRNAs regulating gene pathway cross-talk in breast cancer (BC). We first integrated gene expression profiles and biological pathway information to explore the underlying associations between genes differently expressed among normal and BC samples and pathways enriched from these genes. For each pair of pathways, a score was derived from the distribution of gene expression levels by quantifying their pathway cross-talk. Random forest classification allowed the identification of pairs of pathways with high cross-talk. We assessed miRNAs regulating the identified gene pathways by a mutual information analysis. A Fisher test was applied to demonstrate their significance in the regulated pathways. Our results suggest interesting networks of pathways that could be key regulatory of target genes in BC, including stem cell pluripotency, coagulation, and hypoxia pathways and miRNAs that control these networks could be potential biomarkers for diagnostic, prognostic, and therapeutic development in BC. This work shows that standard methods of predicting normal and tumor classes such as differentially expressed miRNAs or transcription factors could lose intrinsic features; instead our approach revealed the responsible molecules of the disease.

scholarly journals Application of Monte Carlo cross-validation to identify pathway cross-talk in neonatal sepsis

2018 ◽  
Vol 243 (5) ◽  
pp. 444-450 ◽  
Author(s):  
Yuxia Zhang ◽  
Cui Liu ◽  
Jingna Wang ◽  
Xingxia Li
Keyword(s):  
Monte Carlo ◽  
Cross Talk ◽  
Cross Validation ◽  
Integrated Approach ◽  
Dendritic Cell Maturation ◽  
Extensive Literature ◽  
Genetic Profiling ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Monte Carlo Cross Validation

To explore genetic pathway cross-talk in neonates with sepsis, an integrated approach was used in this paper. To explore the potential relationships between differently expressed genes between normal uninfected neonates and neonates with sepsis and pathways, genetic profiling and biologic signaling pathway were first integrated. For different pathways, the score was obtained based upon the genetic expression by quantitatively analyzing the pathway cross-talk. The paired pathways with high cross-talk were identified by random forest classification. The purpose of the work was to find the best pairs of pathways able to discriminate sepsis samples versus normal samples. The results found 10 pairs of pathways, which were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways were identified according to analysis of extensive literature. Impact statement To find the best pairs of pathways able to discriminate sepsis samples versus normal samples, an RF classifier, the DS obtained by DEGs of paired pathways significantly associated, and Monte Carlo cross-validation were applied in this paper. Ten pairs of pathways were probably able to discriminate neonates with sepsis versus normal uninfected neonates. Among them, the best two paired pathways ((7) IL-6 Signaling and Phospholipase C Signaling (PLC); (8) Glucocorticoid Receptor (GR) Signaling and Dendritic Cell Maturation) were identified according to analysis of extensive literature.

scholarly journals Sensitivity Analysis of Sentinel-1 Backscatter to Oil Palm Plantations at Pluriannual Scale: A Case Study in Gabon, Africa

2021 ◽  
Vol 13 (11) ◽  
pp. 2075
Author(s):  
J. David Ballester-Berman ◽  
Maria Rastoll-Gimenez
Keyword(s):  
Time Series ◽  
Sensitivity Analysis ◽  
Oil Palm ◽  
Time Interval ◽  
Potential Candidate ◽  
Initial Growth ◽  
Natural Forests ◽  
Wet Season ◽  
Radar Signatures ◽  
The Times

The present paper focuses on a sensitivity analysis of Sentinel-1 backscattering signatures from oil palm canopies cultivated in Gabon, Africa. We employed one Sentinel-1 image per year during the 2015–2021 period creating two separated time series for both the wet and dry seasons. The first images were almost simultaneously acquired to the initial growth stage of oil palm plants. The VH and VV backscattering signatures were analysed in terms of their corresponding statistics for each date and compared to the ones corresponding to tropical forests. The times series for the wet season showed that, in a time interval of 2–3 years after oil palm plantation, the VV/VH ratio in oil palm parcels increases above the one for forests. Backscattering and VV/VH ratio time series for the dry season exhibit similar patterns as for the wet season but with a more stable behaviour. The separability of oil palm and forest classes was also quantitatively addressed by means of the Jeffries–Matusita distance, which seems to point to the C-band VV/VH ratio as a potential candidate for discrimination between oil palms and natural forests, although further analysis must still be carried out. In addition, issues related to the effect of the number of samples in this particular scenario were also analysed. Overall, the outcomes presented here can contribute to the understanding of the radar signatures from this scenario and to potentially improve the accuracy of mapping techniques for this type of ecosystems by using remote sensing. Nevertheless, further research is still to be done as no classification method was performed due to the lack of the required geocoded reference map. In particular, a statistical assessment of the radar signatures should be carried out to statistically characterise the observed trends.

scholarly journals MRI-based radiomic feature analysis of end-stage liver disease for severity stratification

2021 ◽  
Author(s):  
Jennifer Nitsch ◽  
Jordan Sack ◽  
Michael W. Halle ◽  
Jan H. Moltz ◽  
April Wall ◽  
...  
Keyword(s):  
Disease Severity ◽  
Prediction Models ◽  
Blood Parameters ◽  
Meld Score ◽  
Poor Correlation ◽  
Discrimination Ability ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Academic Center ◽  
End Stage

Abstract Purpose We aimed to develop a predictive model of disease severity for cirrhosis using MRI-derived radiomic features of the liver and spleen and compared it to the existing disease severity metrics of MELD score and clinical decompensation. The MELD score is compiled solely by blood parameters, and so far, it was not investigated if extracted image-based features have the potential to reflect severity to potentially complement the calculated score. Methods This was a retrospective study of eligible patients with cirrhosis ($$n=90$$ n = 90 ) who underwent a contrast-enhanced MR screening protocol for hepatocellular carcinoma (HCC) screening at a tertiary academic center from 2015 to 2018. Radiomic feature analyses were used to train four prediction models for assessing the patient’s condition at time of scan: MELD score, MELD score $$\ge $$ ≥ 9 (median score of the cohort), MELD score $$\ge $$ ≥ 15 (the inflection between the risk and benefit of transplant), and clinical decompensation. Liver and spleen segmentations were used for feature extraction, followed by cross-validated random forest classification. Results Radiomic features of the liver and spleen were most predictive of clinical decompensation (AUC 0.84), which the MELD score could predict with an AUC of 0.78. Using liver or spleen features alone had slightly lower discrimination ability (AUC of 0.82 for liver and AUC of 0.78 for spleen features only), although this was not statistically significant on our cohort. When radiomic prediction models were trained to predict continuous MELD scores, there was poor correlation. When stratifying risk by splitting our cohort at the median MELD 9 or at MELD 15, our models achieved AUCs of 0.78 or 0.66, respectively. Conclusions We demonstrated that MRI-based radiomic features of the liver and spleen have the potential to predict the severity of liver cirrhosis, using decompensation or MELD status as imperfect surrogate measures for disease severity.

scholarly journals Evaluation of Groundwater Using an Integrated Approach of Entropy Weight and Stochastic Simulation: A Case Study in East Region of Beijing

2021 ◽  
Vol 18 (14) ◽  
pp. 7703
Author(s):  
Yongxiang Zhang ◽  
Ruitao Jia ◽  
Jin Wu ◽  
Huaqing Wang ◽  
Zhuoran Luo
Keyword(s):  
Water Quality ◽  
Stochastic Simulation ◽  
Water Quality Index ◽  
Quality Index ◽  
Integrated Approach ◽  
Total Hardness ◽  
Chemical Components ◽  
Wet Season ◽  
Entropy Weight ◽  
Weakly Alkaline

Groundwater is an important source of water in Beijing. Hydrochemical composition and water quality are the key factors to determine the availability of groundwater. Therefore, an improved integrated weight water quality index approach (IWQI) combining the entropy weight method and the stochastic simulation method is proposed. Through systematic investigation of groundwater chemical composition in different periods, using a hydrogeochemical diagram, multivariate statistics and spatial interpolation analysis, the spatial evolution characteristics and genetic mechanism of groundwater chemistry are discussed. The results show that the groundwater in the study area is weakly alkaline and low mineralized water. The south part of the study area showed higher concentrations of total dissolved solids, total hardness and NO3−-N in the dry season and wet season, and the main hydrochemical types are HCO3−-Ca and HCO3−-Ca-Mg. The natural source mechanism of the groundwater chemical components in Chaoyang District includes rock weathering, dissolution and cation exchange, while the human-made sources are mainly residents and industrial activities. Improved IWQI evaluation results indicate that water quality decreases from southwest to northeast along groundwater flow path. The water quality index (WQI) method cannot reflect the trend of groundwater. Sensitivity analysis indicated that the improved IWQI method could describe the overall water quality reliably, accurately and stably.

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