Area Monitoring Research Articles

CORRELATION ANALYSIS OF ECONOMIC FACTORS AND HUSBAND SUPPORT TO PREGNANT WOMEN'S COMPLIANCE IN ANTENATAL CARE (ANC)

Midwifery care services in pregnancy are carried out to prepare optimal health for pregnant women and their babies, both physical, social and mental health. Antenatal care plays an important role in providing quality midwifery services, including several important service components such as health promotion, early detection of complications, diagnosis and prevention of disease. There was an increase in K4 coverage in Indonesia from 84.6% in 2020 to 88.8% in 2021. Based on the results of reporting data from Local Area Monitoring (PWS) Maternal and Child Health (KIA) in South Sumatra in 2021, the number of first visits K4 pregnancies reached 90.1%, decreasing from the K4 achievement in 2020, which was 90.9%, while for K6 coverage in South Sumatra in 2021 it reached 72.9% above the Indonesian K6 average of 63%. The purpose of this study was to find out whether economic factors, and husband's support factors correlated with obedience of pregnant women in carrying out Antenatal Care (ANC) at Lismarini Palembang's Independent Midwife Practice (PMB). This type of research is a quantitative research using an analytic survey method with a cross sectional approach. The population of this study was all 3rd trimester pregnant women who had ANC visits at BPM Lismarini Palembang, while the sample was a portion of 3rd trimester pregnant women who had ANC visits at BPM Lismarini Palembang. The sampling technique in this study was carried out by accidental sampling technique. The data analysis used was univariate analysis followed by bivariate analysis. The results of statistical tests showed that there was a relationship between economic factors and husband's support with p values of 0.029 and 0.035. From the results of the study it can be concluded that economic variables and husband's support are related to respondents' adherence to antenatal care visits at BPM Lismarini Palembang.

Monitoring urban biological invasions using citizen science: the polyphagous shot hole borer (Euwallacea fornicatus).

The online version contains supplementary material available at 10.1007/s10340-024-01744-7.

Retracted: Mine Geological Environment Monitoring and Risk Assessment in Arid and Semiarid Areas

Retracted: Mine Geological Environment Monitoring and Risk Assessment in Arid and Semiarid Areas

Testing temporal transferability of remote sensing models for large area monitoring

Applying remote sensing models outside the temporal range of their training data, referred to as temporal model transfer, has become common practice for large area monitoring projects that extrapolate models for hindcasting or forecasting to time periods lacking reference data. However, the development of appropriate validation methods for temporal transfer has lagged behind its rapid adoption. Breaking temporal transfer's assumption of temporal consistency in both remote sensing and reference data and their relationship to each other could lead to biased pixel-level predictions and small area estimators, compromising the operational validity of large area monitoring products. Few studies using temporal transfer have evaluated its effects on model accuracy at the pixel/plot level, and the propensity for biased small area estimators and trends resulting from temporal transfer remains unexplored. We present a framework for evaluating temporal transferability by combining temporal cross-validation with a multiscale map assessment to aid in identifying where and when biased model predictions could scale to small area estimates and affect predicted trends.This validation framework is demonstrated in a case study of annual percent tree canopy cover mapping in Michigan. We tested and compared temporal transferability of random forest models of canopy cover derived from 2010 to 2016 systematic dot-grid photo-interpretations at Forest Inventory and Analysis plots with Landsat spectral indices fit with the LandTrendr temporal segmentation algorithm serving as the primary predictor variables. The temporal cross-validation error (mean RMSE = 13.9% cover) was higher than the common validation approach of considering all time periods of testing data together (RMSE = 13.6% cover) and lower than models trained and tested within the same year (mean RMSE = 14.2% cover). However, the bias of model predictions and small area estimators for individual years was higher with temporal transfer models than when applying models within the same year as their training data. We also evaluated how training models using different temporal subsets and with and without LandTrendr fitting affected predictions of Michigan's 1984–2020 predicted annual mean cover. The mean cover from LandTrendr-based models followed expected and consistent trends and had less difference between models trained with different temporal subsets (max difference = 5.8% cover). While those from Landsat had high interannual variations and greater difference between temporal models (max difference = 11.2% cover). The results of this case study demonstrate that evaluation of temporal transferability is necessary for establishing the operational validity of large area monitoring products, even when using time series algorithms that improve temporal consistency.

Detection of Benggang in Remote Sensing Imagery through Integration of Segmentation Anything Model with Object-Based Classification

Benggang is a type of erosion landform that commonly occurs in the southern regions of China, posing significant threats to local farmland and human safety. Object-based classification (OBC) can be applied with high-resolution (HR) remote sensing images for detecting Benggang areas on a large spatial scale, offering essential data for aiding in the remediation efforts for these areas. Nevertheless, traditional image segmentation methods may face challenges in accurately delineating Benggang areas. Consequently, the extraction of spatial and textural features from these areas can be susceptible to inaccuracies, potentially compromising the detection accuracy of Benggang areas. To address this issue, this study proposed a novel approach that integrates Segment Anything Model (SAM) and OBC for Benggang detection. The SAM was used to segment HR remote sensing imagery to delineate the boundaries of Benggang areas. After that, the OBC was employed to identify Benggang areas based on spectral, geometrical, and textural features. In comparison to traditional pixel-based classification using the random forest classifier (RFC-PBC) and OBC based on the multi-resolution segmentation (MRS-OBC), the proposed SAM-OBC exhibited superior performance, achieving a detection accuracy of 85.46%, a false alarm rate of 2.19%, and an overall accuracy of 96.48%. The feature importance analysis conducted with random forests highlighted the GLDV Entropy, GLDV Angular Second Moment (ASM), and GLCM ASM as the most pivotal features for the identification of Benggang areas. Due to its inability to extract and utilize these textural features, the PBC yielded suboptimal results compared to both the SAM-OBC and MRS-OBC. In contrast to the MRS, the SAM demonstrated superior capabilities in the precise delineation of Benggang areas, ensuring the extraction of accurate textural and spatial features. As a result, the SAM-OBC significantly enhanced detection accuracy by 34.12% and reduced the false alarm rate by 2.06% compared to the MRS-OBC. The results indicate that the SAM-OBC performs well in Benggang detection, holding significant implications for the monitoring and remediation of Benggang areas.

Leveraging limited data from wildlife monitoring in a conflict affected region in Venezuela

Efficient monitoring of biodiversity-rich areas in conflict-affected areas with poor rule of law requires a combination of different analytical approaches to account for data biases and incompleteness. In the upland Amazon region of Venezuela, in Canaima National Park, we initiated biodiversity monitoring in 2015, but it was interrupted by the establishment of a large-scale mining development plan in 2016, compromising the temporal and geographical extent of monitoring and the security of researchers. We used a resource selection function model framework that considers imperfect detectability and supplemented detections from camera trap surveys with opportunistic off-camera records (including animal tracks and direct sighting) to (1) gain insight into the value of additional occurrence records to accurately predict wildlife resource use in the perturbated area (deforestation, fire, swidden agriculture, and human settlements vicinity), (2) when faced with security and budget constraints. Our approach maximized the use of available data and accounted for biases and data gaps. Adding data from poorly sampled areas had mixed results on estimates of resource use for restricted species, but improved predictions for widespread species. If budget or resources are limited, we recommend focusing on one location with both on-camera and off-camera records over two with cameras. Combining camera trap records with other field observations (28 mammals and 16 birds) allowed us to understand responses of 17 species to deforestation, 15 to fire, and 13 to swidden agriculture. Our study encourages the use of combinations of methods to support conservation in high-biodiversity sites, where access is restricted, researchers are vulnerable, and unequal sampling efforts exist.

Analysis of deformation law of an airport foundation pit monitoring in loess area

This paper takes an airport foundation pit project in northwest loess area as the research object, and introduces the key method technology of support, construction and monitoring of this foundation pit project. The scope of this foundation pit project is widely distributed, there are no buildings in the surrounding area, and there is less restriction on the construction space, so the GRF01 green assembled support method of Slope release with soil nail wall is adopted, which controls the deformation of the foundation pit well and at the same time, plays the role of green environmental protection and reduces the cost. The analysis of the pit monitoring data shows that the pit engineering support design scheme effectively controls the deformation of the pit, and all monitoring data did not reach the alarm value, which ensures the safety of pit excavation and in-pit operation, and achieves the dual goals of economy and environmental protection. It can provide reference for the design and construction of similar large-scale foundation pit excavation and support in loess area.

Problems and current directions of further medium-term strategic planning for the development of the health care system of the Moscow Region: expert survey results

BACKGROUND: Modern strategic planning for the development of the health care system in the region involves regular monitoring of problem areas for the timely identification of emerging problems, as well as monitoring the effectiveness of measures designed to eliminate the identified problems. Based on this, within the framework of the 5th level of medical and sociological monitoring of the results of strategic planning for the development of regional health care, which involves studying the opinions of regional experts, a study was conducted focused on studying the main problems and prospects for the development of the health care system in the Moscow Region on the most important ones from the standpoint of its strategic planning directions.
 AIM: To determine the degree of relevance of problems for the health care system of the Moscow Region and for the next medium-term strategic planning of measures for its development, as well as to evaluate the indicators from the standpoint of their significance, which will serve as the basis for compiling the archetype of the health care system in the territory of the municipal formation of the Moscow Region in order to adopt further management decisions, including taking into account municipal features.
 MATERIALS AND METHODS: A survey was conducted of experts from among the heads of regional medical organizations of the Moscow Region, their deputies for the medical profile of activity, as well as the main freelance specialists of the Ministry of Health of the Moscow Region. A total of 126 people were interviewed using formalized structured interviews and questionnaires.
 RESULTS: In the course of the study, a range of the most pressing problems of the health care system of the Moscow Region was determined today. In addition, activities were identified, the strategic planning of which is most relevant for the formation of the next medium-term program “Health of the Moscow Region”. The study also made it possible to streamline the list of indicators characterizing the archetype of the health care system in the territory of the municipality of the Moscow Region, according to the degree of their importance in making and implementing management decisions in the framework of medium-term strategic planning for health care development.
 CONCLUSION: The study demonstrated the sustainability of some problems in the health care system of the Moscow Region that currently need to be addressed.

Correlation between total deceleration area in CTG records and cord blood pH in pregnancies with IUGR.

Fetal cardiotocography is the most common method to assess fetal well-being during labor. Nevertheless, its predictive ability for acidemia is limited, both in low-risk and high-risk pregnancies (Nelson et al. in N Engl J Med 334: 613-9, 1996; Rinciples P et al. in Health and Human Development Workshop Report on Electronic Fetal Monitoring : Update on Definitions. no. 2007, 510-515, 2008), especially in high-risk pregnancies, such as those complicated by growth restriction. In this study we aim examine the association between deceleration and acceleration areas and other measure of fetal heart rate in intrapartum fetal monitoring and neonatal arterial cord blood pH in pregnancies complicated by growth restriction. A retrospective cohort study of 100 deliveries complicated by growth restriction, delivered during 2018, was conducted. Known major fetal anomalies, non-vertex presentation and elective cesarean deliveries were excluded. Total deceleration and acceleration areas were calculated as the sum of the areas within the deceleration and acceleration, respectively. In deliveries complicated by growth restriction, cord blood pH is significantly associated with total deceleration area (p = 0.05) and correlates with cumulative duration of the decelerations (Spearman's rank -0.363, p < 0.05), and total acceleration area (-0.358, p < 0.05). By comparing the cord blood pH in deliveries with a total deceleration area that was above and below the median total deceleration area, we demonstrated a significant difference between the categories. Cord blood pH significantly correlates with total deceleration area and other fetal monitoring characteristics in neonates with growth restriction. Future studies using real-time, machine-learning based techniques of fetal heart rate monitoring, may provide population specific threshold values that will support bedside clinical decision making and perhaps achieve better outcomes.

Flexible Strain Sensors Based on Bionic Parallel Vein-like Structures for Human Motion Monitoring.

In recent years, strain sensors have penetrated various fields. The capability of sensors to convert physical signals into electrical signals is of great importance in healthcare. However, it is still challenging to obtain sensors with high sensitivity, large operating range and low cost. In this paper, a stretchable strain sensor made of a double-layer conductive network, including a biomimetic multilayer graphene-Ecoflex (MLG-Ecoflex) substrate and a multilayer graphene-carbon nanotube (MLG-CNT) composite up-layer was developed. The combined action of the two layers led to an excellent performance with an operating range of up to 580% as well as a high sensitivity (gauge factor (GFmax) of 1517.94). In addition, a pressure sensor was further designed using the bionic vein-like structure with a multi-layer stacking of MLG-Ecoflex/MLG-CNT/MLG-Ecoflex to obtain a relatively high deformation along the direction of thickness. The device presented a high sensing performance (up to a sensitivity of 0.344 kPa-1) capable of monitoring small movements of the human body such as vocalizations and gestures. The good performance of the sensors together with a simple fabrication procedure (flip-molding) make it of potential use for some applications, for example human health monitoring and other areas of human interaction.

Weed detection in soybean fields using improved YOLOv7 and evaluating herbicide reduction efficacy.

With the increasing environmental awareness and the demand for sustainable agriculture, herbicide reduction has become an important goal. Accurate and efficient weed detection in soybean fields is the key to test the effectiveness of herbicide application, but current technologies and methods still have some problems in terms of accuracy and efficiency, such as relying on manual detection and poor adaptability to some complex environments. Therefore, in this study, weeding experiments in soybean fields with reduced herbicide application, including four levels, were carried out, and an unmanned aerial vehicle (UAV) was utilized to obtain field images. We proposed a weed detection model-YOLOv7-FWeed-based on improved YOLOv7, adopted F-ReLU as the activation function of the convolution module, and added the MaxPool multihead self-attention (M-MHSA) module to enhance the recognition accuracy of weeds. We continuously monitored changes in soybean leaf area and dry matter weight after herbicide reduction as a reflection of soybean growth at optimal herbicide application levels. The results showed that the herbicide application level of electrostatic spraying + 10% reduction could be used for weeding in soybean fields, and YOLOv7-FWeed was higher than YOLOv7 and YOLOv7-enhanced in all the evaluation indexes. The precision of the model was 0.9496, the recall was 0.9125, the F1 was 0.9307, and the mAP was 0.9662. The results of continuous monitoring of soybean leaf area and dry matter weight showed that herbicide reduction could effectively control weed growth and would not hinder soybean growth. This study can provide a more accurate, efficient, and intelligent solution for weed detection in soybean fields, thus promoting herbicide reduction and providing guidance for exploring efficient herbicide application techniques.

Longitudinal dissolved oxygen patterns in Atlantic salmon aquaculture sites in British Columbia, Canada

Dissolved oxygen (DO), an important water-quality parameter required to support aquatic life, is a critical factor for determining the general biological health of the aquatic ecosystem, and the concentration of DO is a critical factor in determining salmon growth and welfare. This study used longitudinal DO concentration, recorded hourly from 21 aquaculture sites, each with loggers in three separate cages, in four areas in British Columbia, Canada, between 2015 and 2017. The measurements were evaluated based on the recommended DO concentrations for protection of salmonids from hypoxia. Using a two-stage time-series analysis, we described variations in DO concentrations measured over the study period and their associations with environmental factors. Based on the water quality criteria for DO concentration, 42.3, 56.5, and 1.2% of the hourly DO data from the overall 21 aquaculture sites were classified as ‘optimal’, ‘sub-optimal’, and ‘stressed’, respectively. The frequency of hypoxic episodes differed substantially among seasons, aquaculture sites and even among cages within sites. The effects of environmental variables on DO concentration had markedly different patterns depending on the season. Significant associations with DO concentrations were observed for temperatures in the summer and winter months, and both wind direction and remotely-sensed estimated absorption from phytoplankton [aph(443)] in the winter months. The time-series regression model results showed overall (year-round) associations of temperature, wind speed, and aph(443) with DO concentrations. Describing DO measurements at these aquaculture sites provided an understanding of how much they deviated from the recommended DO concentrations, as well as provide baseline information for future water resource planning, including continued and improved water quality monitoring in aquaculture areas.

Impact of Large-Scale Fire and Habitat Type on Ant Nest Density and Species Abundance in Biebrza National Park, Poland

Fire can have negative effects on the ant community by reducing species abundance through direct mortality, changes in resource availability, or foraging activity. Fire can also have positive effects, especially for opportunistic species preferring open or disturbed habitats. We assessed the direct effects of a large-scale fire on ant communities in open habitats (grassland and Carex) and moist forested peatland (birch and alder) sites in Biebrza National Park, testing three hypotheses: (i) the large-scale fire had more significant effects on ant nest density in forests than in open habitats, (ii) the post-fire ant diversity changes within sites are stronger in forests than open habitats, and (iii) ant species preferring disturbed habitats are favoured by the fire event. The fire had negative effects on ant nest density only in the Carex and grassland sites but not in the birch and alder sites, suggesting that fire had a stronger impact in open habitats than in forests. Temporal post-fire ant diversity changes within sites were stronger in forests than in open habitats. We observed higher beta diversity changes between the first and second year of the study in the burned forest sites due to colonisation, indicating a greater fire impact on species community composition followed by a higher recolonisation rate. Ant species preferring disturbed habitats were favoured by the fire. The seed-eating ant species Tetramorium caespitum, a thermophilous and opportunistic species, dominated the burned grassland site. This contrasts with other species, e.g., Lasius alienus, for which nest density decreased after fire, underlining the importance of food resource availability as a major driver of community changes after fire. Our study also underlines the importance of periodic biodiversity monitoring in conservation areas for assessing the recovery of the original status after disturbances and revealing possible habitat changes endangering the survival of local biotic communities.

VEGF-delivering PEG hydrogels promote vascularization in the porcine subcutaneous space.

For cell therapies, the subcutaneous space is an attractive transplant site due to its large surface area and accessibility for implantation, monitoring, biopsy, and retrieval. However, its poor vascularization has catalyzed research to induce blood vessel formation within the site to enhance cell revascularization and survival. Most studies focus on the subcutaneous space of rodents, which does not recapitulate important anatomical features and vascularization responses of humans. Herein, we evaluate biomaterial-driven vascularization in the porcine subcutaneous space. Additionally, we report the first use of cost-effective fluorescent microspheres to quantify perfusion in the porcine subcutaneous space. We investigate the vascularization-inducing efficacy of vascular endothelial growth factor (VEGF)-delivering synthetic hydrogels based on 4-arm poly(ethylene) glycol macromers with terminal maleimides (PEG-4MAL). We compare three groups: a non-degradable hydrogel with a VEGF-releasing PEG-4MAL gel coating (Core+VEGF gel); an uncoated, non-degradable hydrogel (Core-only); and naïve tissue. After 2 weeks, Core+VEGF gel has significantly higher tissue perfusion, blood vessel area, blood vessel density, and number of vessels compared to both Core-only and naïve tissue. Furthermore, healthy vital signs during surgery and post-procedure metrics demonstratethe safety of hydrogel delivery. We demonstrate that VEGF-delivering synthetic hydrogels induce robust vascularization and perfusion in the porcine subcutaneous space.

CNN-based plant disease recognition using colour space models

ABSTRACT The growing population increases the demand for agricultural production. Owing to some plant diseases, this production is continuously decreasing. Detecting and recognising these diseases at the initial stage is crucial for the sake of high yields from crops and plants. The conventional methods involve manual detection, which can be error-prone and laborious. Automatic recognition paves a way for the regular monitoring of huge areas of crops in less time. The deep learning-based approaches have entered in a big way in the detection of diseases in plants and crops because of their ability to overcome the limitation of regular manual monitoring. The use of colour space models helps demarcate the affected area ofimages of plants and crops prior to inputting them to the CNN model so as to improve the detection accuracy. For this, different colour space models that include RGB, HSL, HSV, LAB, LUV, XYZ and YUV are investigated. However, HSL-CNN joint model performs the best by achieving 98.97% accuracy, 98.61% precision, and 99.28% F1-score.

GNSS-IR water level monitoring toward particular narrow scenarios: Application to South-to-North Water Diversion Project in China

River water level monitoring plays a crucial role in hydrological practice. Global Navigation Satellite Systems Interferometry Reflectometry (GNSS-IR) has been demonstrated to help retrieve absolute water levels in expansive and unobstructed scenarios. However, how to measure in rivers remains a significant challenge for practical use due to the restricted reflection area. To address these issues, we propose the Dynamic Masking Elevation Threshold Selection Method (DMETSM), which effectively broadens the selection of available reflective signals. Through analyzing actual field data collected along the South-to-North Water Diversion Project, we have found that DMETSM almost doubles the effective monitoring area compared to the classical method. Furthermore, the multi-GNSS water level retrievals at two sites can achieve high accuracy, with root-mean-square errors of 1.36 cm and 2.57 cm, respectively. Results show that it improves accuracy by 30.6 % and 42.6 %. This highlights the considerable potential and value of applications in narrow and irregular areas.

Remote sensing dynamic monitoring of the flood season area of Poyang Lake over the past two decades

Drought and flood disasters occur frequently in the Poyang Lake basin during the flood season, making it significantly important to monitor the lake's flood season area using time-series remote sensing. This research employed multisource remote sensing datasets from Landsat, ALOS, and Sentinel-1 across the time span of 2000–2022. Using the MNDWI method and adaptive global threshold segmentation, the flood season area of Poyang Lake was extracted. The spatiotemporal variation characteristics of the flood season area were analysed, and correlations with precipitation and temperature were assessed. Moreover, this study explored the characterization of its response to drought and flood events. The results revealed a strong fluctuation in the lake during the flood season, with the maximum and minimum area differences exceeding 3000 ​km2, and spatial changes were mainly concentrated in the southwestern lake region. There is a significant positive correlation between area changes and precipitation and a significant negative correlation with temperature. By analysing the response characteristics of the flood season area changes to drought and flood events, in years when the flood season area of Poyang Lake exceeds 4500 ​km2, extreme flood disasters usually occur. Areas between 3900 ​km2 and 4500 ​km2 are prone to floods, areas between 2000 ​km2 and 3000 ​km2 are prone to drought events, and areas below 2000 ​km2 typically experience extreme drought disasters.

National action plans on antimicrobial resistance in Latin America: an analysis via a governance framework.

In 2015, the World Health Assembly adopted a global action plan (GAP) on antimicrobial resistance (AMR). Member states were encouraged to develop their own national action plans (NAPs) in alignment with the GAP. To-date, in systematic assessments of NAPs, the Latin American specific context has not been previously analysed. Here we examined 11 Latin American NAPs published between 2015 and 2021 using content analysis. We focused on two approaches: (1) alignment between the strategic objectives and actions defined in the GAP, and those outlined in the NAPs via a content indicator; and (2) assessment of the NAPs via a governance framework covering 'policy design', 'implementation tools' and 'monitoring and evaluation' areas. We observed a high alignment with the strategic objectives of the GAP; however, the opposite was observed for the corresponding actions. Our results showed that the governance aspects contained within coordination and participation domains were addressed by every Latin American NAP, whereas monitoring and assessment areas, as well as incorporating the environment, would need more attention in subsequent NAPs. Given that AMR is a global health threat and collective efforts across regions are necessary to combat it, our findings can benefit member states by highlighting how to strengthen the AMR strategies in Latin America, while also supporting global policy formulation.

Exploiting the Potential of Urban DAS Grids: Ambient-Noise Subsurface Imaging Using Joint Rayleigh and Love Waves

Abstract Distributed acoustic sensing (DAS) data become important for seismic monitoring of subsurface structures in urban areas. Different from the previous studies that only focused on Rayleigh waves, we report successful observation and analysis of both Rayleigh and Love waves extracted from ambient-noise interferometry, using orthogonal segments of fiber-optic cables in San Jose, California. Theoretical angular responses of DAS ambient-noise cross correlation, together with numerical experiments, help identify DAS channel pairs expected to record stronger Love waves than Rayleigh waves. Based on these waveforms, we further obtain clear Rayleigh- and Love-wave dispersion maps, including both phase and group velocities, with various channel pair orientations. Finally, we perform a joint inversion of Rayleigh- and Love-wave dispersion curves to obtain depth-dependent subsurface velocity structures of the top 100 m. Our inversion result is consistent with the model from the previous study based on Rayleigh-wave dispersion and horizontal-to-vertical spectral ratio. In addition, the joint inversion of Love and Rayleigh is more robust than that of the independent inversion of either type of wave. Our new study demonstrates the potential of surface-wave analysis on fiber-optic cables with complex geometry, which can further advance the seismic monitoring of urban areas.

EVALUATION OF SPECTRAL INDICES FOR DETECTION OF BURNED AREAS IN AN ENVIRONMENTAL PROTECTION AREA USING SPOT-5 IMAGES

The Cerrado biome has great importance in ecological biodiversity, but deforestation has accelerated in recent decades. The Rio Preto-BA Environmental Preservation Area, known for the high agricultural activity of grains, continually suffers from forest fires and loss of native vegetation. Satellite remote sensing is proposed as an alternative to accurately locate and quantify fire-affected surfaces and their impacts on the landscape. With the recent free availability of SPOT-5 images, it has made it possible to detect burned areas with considerable spatial and spectral resolution. The objective of the present study was to determine the ideal spectral index for detection of the burned area inserted in the APA Rio Preto through two SPOT-5 scenes and the application of the Support Vector Machines (SVM) model. The burned areas detected were submitted to the calculation of five spectral indices, BAI, BAIM, NBR, NDVI and EVI2. The ability of each index to discriminate burned areas was estimated by comparing them with each other using a statistical separability index, SVM regression and accuracy analysis. BAIM was identified as the index with the greatest potential for discriminating burnt areas with maximum separability and classification accuracy above 90%, while the NDVI and EVI2 indices had low performance. It is hoped that these results can be used to evaluate and prioritize monitoring areas, contribute to the implementation of a fire management plan in the APA and to support subsequent studies on fire dynamics in forest systems integrated with advanced computational technologies.