Satellite Image Analysis Research Articles

Glacier Cover Estimation: a Multitemporal Retrospective Analysis of the Uruashraju Snow-capped Mountain (Ancash)

Objectives: To estimate the evolution of the glacier cover of the Uruashraju snow-capped mountain (Áncash, Peru) between the years 2014 and 2024, Theoretical framework: The research is framed in the context of climate change, specifically in the reduction of tropical glaciers. Andean glaciers are key indicators of global warming, and their retreat affects the availability of water resources, impacting sectors such as agriculture, human consumption and local biodiversity. Method: A cartographic analysis of satellite images obtained through the "Landsat 8-9 OLI/TIRS C2 L2" mission for the years 2014, 2016, 2018, 2020, 2022 and 2024 was used. The images were downloaded from the USGS Earth Explorer platform and selected from the months of July to maintain temporal homogeneity. The spatial resolution used was 30 meters in visible, near infrared (NIR) and shortwave infrared (SWIR) bands. Results and discussion: The results reveal a significant reduction of 37.28% in the glacier surface of the Uruashraju snow-capped mountain between 2014 and 2024. Despite some periods of temporary stabilization, the general trend is one of retreat due to climate change. This phenomenon affects water availability and poses risks for essential activities such as agriculture. Implications of the research: The research highlights the urgent need to take measures to mitigate the effects of climate change on Andean glaciers, since their loss compromises the water and economic security of local communities that depend on glacial resources. Originality/Value: This study offers a detailed and updated analysis of the evolution of glacier cover on the Uruashraju snow-capped mountain, providing relevant data for water resource planning and climate change adaptation strategies in the Andean region.

Evaluation of Effects of Cotton Growing on the Environment and the Population in the Koutiala Circle

Since 1960, cotton cultivation has experienced considerable expansion in the Koutiala district of Mali. This expansion has not been without consequences on people’s health and natural resources in terms of soil, water and natural vegetation. Based on the analysis of satellite images and a socio-economic survey of production unit chiefs, this study highlights the degradation of soils, biological diversity, population health, and pollution of groundwater and surface water. To reduce these effects, the adoption of good agroecological practices, the organic cotton farming, the reduction of the use of chemicals, and the sustainable management of water and soil are becoming a necessity to ensure sustainable management of environmental resources and the preservation of the livelihoods of local producers.

Phytoclimatological study in the high plains of Sétif: application of the bioclimatic classification system (Algeria)

The Global Bioclimatic Classification System (WBCS) by Rivas-Martínez is an effective approach to reflect and study the role of climate in determining the potential distribution of natural vegetation at various temporal and spatial scales. In particular, the diversity of physical characteristics in the Setifian high plains leads to the complexity of large-scale phytogeographic belts. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), have been created for the study area based on Rivas-Martínez's global bioclimatic classification system for current and future climate scenarios, using the parallel climate model from CMIP5 (Coupled Model Intercomparison Project) under the intermediate greenhouse gas emission scenario (RCP4.5). Precipitation and temperature data from the "WorldClim" dataset were used as the data source. These climatic variables were reduced to a spatial resolution of 1 km. The objective is to understand how the climate is evolving in this region, what the consequences are, and what the future holds for these natural ecosystems. A phytosociological study complemented by satellite image analysis reveals a high diversity of pre-forestry formations. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and the magnitude of change, 2) identify and locate the new projected isobioclimates, and 3) explore the compositional changes in vegetation types among analogous isobioclimatic zones. The ordination of the relationships between vegetation and bioclimates shows a strong correlation between Rivas-Martinez indices and the distribution and composition of vegetation. Changes in ombrotype, thermotype, bioclimate, ombrotype, and isobioclimate differed between the current and future series. The resulting map presents 9 isobioclimatic units, which are advantageous for confirming the diagnosis of bioclimatic characteristics and describing the relationships between climatic variables and the corresponding distributions of natural vegetation. We identified eight different isobioclimates for the current period (1979-2013) and seven for the future period (2050), three thermotype horizons for both the current and future periods, and finally, four ombrotype horizons for the period (1979-2013), while two ombrohorizons represent the period (2050). This approach is useful for explaining territorial diversity in environmental applications related to ecological adaptation assessment, nature conservation, landscape regionalization, and planning.

ANÁLISE DO COMPORTAMENTO EROSIVO E CARACTERIZAÇÃO SEDIMENTOLÓGICA DA BARRA ARENOSA NA FOZ DO RIO ITABAPOANA, PRESIDENTE KENNEDY-ES

The state of Espírito Santo, despite being the smallest in the Southeast region, presents a significant diversity in the variations between the effects of retrogradation and coastal progradation. This dynamic is influenced by a complex interplay of variable factors, such as coastal geomorphology, hydrodynamics, and geology, which directly affect coastal cities and their development. The objectives of this study are to understand the phenomenon of coastal erosion and to analyze the morphological behavior of the sandy bar at the mouth of the Itabapoana River and at Praia das Neves, generating relevant information for the preservation of the coastal environment and minimizing material losses in urban areas adjacent to the sea. This work used tools such as the Ground Penetrating Radar (GPR) for the interpretation of radarfacies, as well as remote sensing and satellite image geoprocessing methodologies, combined with sedimentological characterization studies applied to Environmental Geology. The integration of GPR data revealed a complex sedimentary dynamic, with reflectors that indicate the progradation of beach deposits, as well as eolian, fluvial and marine influences, observing the presence of filled paleochannels and fluvial deposits. The analysis of satellite images allowed us to identify variations in the morphology of the beach and the location of the sandy bar at the mouth of the Itabapoana River, which shows migration patterns in a north-south direction. The compilation of the results suggests that coastal erosion in the region is cyclical, alternating between moments of progradation and retrogradation throughout the analyzed period, reflecting a complex coastal environment that involves climatic factors and marine and fluvial dynamics. The sediments analyzed were well selected, ranging from fine to medium fraction, with heavy fine sediments from the Araçuaí-Ribeira Orogen, showing low textural maturity.

Influence of lithodynamics of coastal area on the safety of railway operation on the Tuapse-Adler section of the North Caucasus Railway

The present paper considers the railroad bed on the Tuapse-Adler section of the North Caucasus Railway (Black Sea coast) in terms of its protection from wave scouring. Aim. To evaluate the influence of coastal lithodynamics on the safety of the railway operation on the section under consideration. The paper describes lithodynamic processes in the sea coastal zone and demonstrates the influence of coastal protection structures produced on lithodynamics in general and on adjacent sections, as exemplified by a specific section of the coast (1907–1910 km). The study involves a retrospective analysis of the step-by-step construction of trapping structures, and sea groins without full-fledged dumping of beach-forming material into the inter-groin compartments. The investigation and analysis of satellite images of 1907–1910 km coast within the Vodopadny-Lazarevskoye section indicate that lithodynamic processes remained unconsidered during the intensive construction of bank protection structures, which led to the beach erosion and the emergency condition of the seawalls along 1909–1910 km section. The paper provides recommendations for considering lithodynamic processes in the construction of railway protection structures, thereby increasing the safety of the railway operation.

Environmental Change Documented in the Fluvial Landscape: A Case Study of the Late Neolithic Bršadin–Pašnjak Pod Selom Site (NE Croatia)

ABSTRACT The formation of Neolithic tell settlements in wetlands or near watercourses is documented in the published literature, but their research is not often based on environmental study. In this paper, we present the results from two sediment cores (BR1, BR2) collected from the case study archaeological site, located on the former bank of one of the Danube's tributaries in the southern Carpathian Basin. Although it has been suggested that a waterlogged environment was deliberately selected for this type of settlement in the regional Late Neolithic, the results of this study, based on both archaeological and environmental data, indicate dry and cool conditions prior and during the initial phase of the settlement formation. The abandonment of the settlement, possibly in the late 5th millennium, probably occurred due to alternating dry and wet episodes, rather than a gradual increase in wet conditions, as suggested elsewhere in the region. A large ditch encircling the settlement, not documented by archaeological research, can be indirectly confirmed by the BR2 core results and the analysis of aerial and satellite images. In general, there is a good correlation of results with the major global climate events, but there are differences in regional and wider south-eastern European context.

Remote Sensing Data-Based Satellite Image Analysis in Water Quality Detection for Public Health Data Modelling

Remote Sensing Data-Based Satellite Image Analysis in Water Quality Detection for Public Health Data Modelling

ASSESSING URBAN HEAT ISLAND IMPACT AND IDENTIFYING VULNERABILITY ZONES THROUGH GEOSPATIAL AND GEO-STATISTICAL TECHNIQUES

An urban heat island emerged due to micro urban temperature variations are also referred to as urban heat islands or urban hot spots. The high-rise buildings along the roads form "Urban Canyons" that inhibit reflected radiation from the built-up surface. Urban heat island develops over the cities due to man-made activity and the landscape. An understanding of the urban heat island and its formation is not only helpful in understanding urban thermal characteristics but also helps in understanding human comfort. A geospatial technique has the ability to acquire updated and cost-effective data over large regions. For urban climatology studies, remote sensing and geographic information systems are an important source of information and an effective methodology. Since 1971, the city of Krishnanagar and its vicinity have been witnessing rapid urban growth. Due to its dense population, urban climate and rapid urban expansion, they cause environmental degradation. Appraisal and Impact of urbanization on micro-climate in the Krishnanagar city complex based on satellite derived parameters. For the years 1995, 2007 and 2018, several satellite image analysis approaches such as NDVI, NDWI and NDVI were computed. Significant differences in land surface temperature were observed between 1995 and 2007, as compared to 2007 and 2018.

Applicability of Remote Sensing Techniques in Drought Predicting: A Case Study in Ben Tre Province, Vietnam

Background: Drought poses significant threats to ecosystems, agriculture and the environment, including reduced crop yields, habitat degradation and increased risk of forest fires and soil erosion. In addressing this issue, remote sensing technology (RST) has emerged as a valuable tool for studying and monitoring drought phenomena, offering advantages over traditional research methods. Methods: This study focuses on the application of RST, specifically utilizing Landsat satellite images, to calculate drought indices and develop drought maps for the Ben Tre province in Vietnam. The research involved the analysis of Landsat satellite images collected between 2000 and 2020, using various drought indices such as TCI, VCI, SAVI and WSVI. Result: By employing these indices, the study was able to classify the levels of drought and generate a drought map for the study area. The findings revealed that the coastal regions encompassing Thanh Phu, Ba Tri and Binh Dai districts face a high risk of drought during the dry season.

Deep Learning for Pavement Condition Evaluation Using Satellite Imagery

Civil infrastructure systems cover large land areas and need frequent inspections to maintain their public service capabilities. Conventional approaches of manual surveys or vehicle-based automated surveys to assess infrastructure conditions are often labor-intensive and time-consuming. For this reason, it is worthwhile to explore more cost-effective methods for monitoring and maintaining these infrastructures. Fortunately, recent advancements in satellite systems and image processing algorithms have opened up new possibilities. Numerous satellite systems have been employed to monitor infrastructure conditions and identify damages. Due to the improvement in the ground sample distance (GSD), the level of detail that can be captured has significantly increased. Taking advantage of these technological advancements, this research evaluated pavement conditions using deep learning models for analyzing satellite images. We gathered over 3000 satellite images of pavement sections, together with pavement evaluation ratings from the TxDOT’s PMIS database. The results of our study show an accuracy rate exceeding 90%. This research paves the way for a rapid and cost-effective approach for evaluating the pavement network in the future.

Vegetation health and its relationship with Organic Pollution of the Santa Rosa Wetland, Chancay – Lima, 2023 [Salud de la vegetación y su relación con la Contaminación Orgánica del Humedal Santa Rosa, Chancay – Lima, 2023

The present research aimed to: Determine the Health of Vegetation and its relationship with Organic Pollution of the Santa Rosa Wetland, located in the district of Chancay, in the year 2023. The study is of a mixed type, with a descriptive level by analyzing satellite images to determine the Normalized Difference Vegetation Index (NDVI), with an experimental design, by taking water samples and analyzing them in the laboratory to identify the levels of organic material pollution. Results: From the satellite image analysis, it was determined that the NDVI decreased in 2023, (value of 0.132) between the months of June to October, and in the water quality analysis, the parameters of chemical oxygen demand were measured, with results ranging from 48.50 to 100.50 mg/L, total suspended solids from 30 to 31 mg/L, and biochemical oxygen demand between 19.34 to 33.50 mg/L, indicating that there is pollution (DS. N° 004-2017-MINAM). At the same time, the results were reaffirmed by measuring the extent of the vegetation with a supervised classification analysis of the satellite images, obtaining that the vegetation of the wetland (duckweed and water lentil) increased from 66.08% to 86.64% between the months of June to October. According to the obtained data, it is concluded that there is a relationship between both variables; if pollution decreases the vigor of the indicator plants also decreases as they act biologically as phytoremediators.

LANDSCAPES DYNAMICS OF NORTH-EASTERN UZBEKISTAN IN THE CONTEXT OF CLIMATE AND LAND USE CHANGES

The article examines the causes and results of the dynamics of the Western Tien Shan landscapes in the context of climatic and institutional changes. Based on field studies, analysis of multi temporal satellite images over 30 years and sociological surveys of the local people, changes in the landcover and land use of the region were identified. That includes degradation of glacial and subnival landscapes, an increase in the area and change in the structure of agricultural lands, expansion of recreational infrastructure and growth of recreational load, etc. The results obtained can contribute to the development of recommendations for landscape planning of the region and the resolution of conflicts in environmental management, taking into account the interests and needs of the local people.

Levels of Land Cover Density on Carbon Reserves and Income in Dongo Baru Community Forest (HKm)

Community Forest (HKm) in Dongo Baru, Mount Rinjani forest area, in land management applies a mixed agroforestry pattern. The application of this pattern is the result of forest rehabilitation activities covering 138 ha in 2019. This HKm has a variety of different types of land management in one management area. This study aims to describe the condition of HKm using an environmental approach by estimating carbon stock data and economic value by looking at the value of arrive efficiency. The strategy utilized in this inquire about is graphic method by means of observation, Center Gather Discourse, and interviews, to 27 respondents / owners of land economic aspects by taking carbon stock data to 27 farmer-owned land. The environmental assessment to measure carbon stocks used a sample of 27 plots, measuring 50m x 20m for trees, 10m x 10m for poles, and 5m x 5m for saplings. The plots represent the density level of the forest area, i.e. dense, medium, not dense. Determination of forest density classification using Landsat-7 satellite image analysis in 2022. Based on the comes about within the ponder, it can be concluded that there are 3 density classifications that exist in the Dongo Baru HKm forest area, namely Meeting density, Moderately Meeting density and Not Meeting density. their respective incomes are meeting land density (Rp. 21,273,889), Moderately Meeting land density (Rp. 19,210,333) and Not Meeting land density (Rp. 22,431,556). Meeting land has carbon stock (256.86 tonnes/ha), Moderately Meeting land has carbon stock (95.34), and Not Meeting land has carbon stock (52.90 tonnes/ha). Land management with the density of Rapat land is considered to have fulfilled the principles of forest management from the economic and environmental aspects.

SAR images change detection using proposed lamina attention-based noise-resistant UNet advance network (LANRUNet++)

In the past few years, change detection techniques using Convolutional Neural Networks (CNNs) and conventional methods have garnered considerable attention in satellite image analysis. However, both categories of existing approaches have their respective shortcomings. For instance, methods based on CNNs tend to overlook the interactions amongst multilayer convolutions, while traditional methods may contain errors in the initial classification stage that limit the optimization of network. To address these limitations, we propose a new attentionbased, noise-resistant advanced UNet model named as Lamina Attention-Based Noise-Resistant UNet Advance Network (LANRUNet++)for detecting changes in satellite imagery. UNet++ is a unique neural network structure composed of an encoder and decoder, that are linked by a sequence of dense convolutional blocks nested within each other. A core principle underlying the proposed LANRUNet++ is to effectively bridge the semantic disparity between the encoder and decoder feature maps prior to their fusion. We present a lamina attention mechanism within UNet++, which dynamically assigns weights to features extracted from various convolutional layers. This facilitates improved incorporation of spatial context information. Moreover, we added a loss function that is robust to noise and can effectively minimize the influence of inaccurate annotations. As a result, our model becomes less susceptible to errors in initial classification outcomes. Furthermore, we added a Pixel to Density Ratio Parameter that further reduces noisy labels, improving the robustness of the model.We conducted a comprehensive performance assessment of LANRUNet++ on SAR images and conducted a comparative analysis against a range of cutting-edge techniques currently available. The results of our experiments demonstrate that our proposed approach surpasses other existing methods in its ability to detect changes, achieving a higher level of accuracy with various metrics.

IDENTIFIKASI PERMUKIMAN DI KAWASAN PESISIR UNTUK MENDUKUNG KEBIJAKAN DALAM PENGURANGAN RISIKO BENCANA DI PESISIR PANTAI SINE, KABUPATEN TULUNGAGUNG

The research was conducted in the coastal area of Sine Beach, Tulungagung Regency which is one of the coastal areas in the southern part of Java Island and has a high risk level of tsunami disaster. The purpose of this study, (1) to analyse the level of population settlement density, (2) to identify the type of population settlement. The method in this research uses a qualitative descriptive method. Data sources were obtained from secondary data and primary data, with data collection techniques analysing satellite images and field surveys. The results showed that (2) the level of settlement density in the coastal area of Sine Beach is the densest among coastal settlements in Tulungagung. While (2) the type of settlement is dominated by the settlement of fishermen with diverse settlement types, which are dominated by non-harvesting, semi-permanent and permanent settlements. Based on the level of settlement density and the type of settlement, the settlements in the coastal area of Sine Beach include the potential risk of exposure to coastal disasters such as high waves and Tsunami waves. So it is necessary to take action planning for coastal disaster risk reduction, such as disaster education, training, increasing public awareness in responding to disasters and minimising the risk of coastal disasters.

An Analysis on Intelligent Systems for Remote Sensing Satellite Image Processing and Classification

The integration of intelligent systems to the remote sensing satellite image processing and classification has greatly changed. This paper offers a synthesis of the subject, with respect to intelligent systems’ contribution to the improvement of these processes’ accuracy and speed. Accuracy of different methods such as machine learning algorithms, artificial neural networks, and deep learning techniques in the extraction of information from satellite image comprehension is considered a research interest. The presented problems and open issues are data complexity, feature extraction, and classification accuracy over the data, along with new methods in enhancing the intelligent systems to minimize those problems. It expands knowledge of intelligent systems’ contribution to remote sensing applications by outlining how these advancements have influenced the progression of image analysis for the given research goals. This research work gives the summary of our research by outlining the techniques used in the study, the problems solved, and the general outcomes of incorporating intelligent systems in the area of remote sensing and satellite image analysis. Accuracy analysis results for the SVM based methodology with spatial-spectral features include 90% of accuracy, 88% of the precision, and 90% of the F1-score, which in turn makes it easy to make sound decisions when using satellite imagery in different fields like agriculture, urban development, and environment.

Examining the effect of urbanization on various land cover classes and environmental quality using remote sensing and GIS methods

It is vital for public awareness and decision-makers to investigate the impact caused by changes in urban land use and land cover on ecosystem service values (ESVs) in order to promote sustainable urban development, protect the environment, protect public health, and ensure communities’ long-term well-being. Changes in ecosystem services brought on by changes in land use and cover (LULC) are a crucial early indicator and warning sign of ecological shifts. Using remote sensing and GIS tools, this study examined the shifting dynamics of ESVs in the Haridwar district in Uttarakhand state, India. The evaluation of land use land cover (LULC) changes was carried out by analyzing satellite images of the research region from 2001 to 2021. In addition, we examined changes in ecosystem services according to the study area’s LULC classifications. Using a random forest machine learning classifier, satellite images were classified into five categories of land cover: water bodies, forests, built-up areas, agricultural land, and bare land. The findings showed that from 2001 to 2021, forest cover and water bodies fell by 15.35% and 41.50%, respectively, while urban area and agricultural area rose by 69.24% and 12.31%, respectively. Due to increased urbanization and degradation of water bodies and forest areas, ESV fell from 103.19 USD ha −1 year −1 in 2001 to 70.53 USD ha −1 year −1 in 2021. The combination of LULC with the value of ecosystem services may improve our knowledge of several difficulties in an urban ecosystem. As a result, we advocate for the incorporation of LULC and ESVs as a tool that might be useful to urban planners and land managers in the future for sustainable development of natural resources.

Evaluation of Watershed Carrying Capacity on Flood Management in Greater Malang East Java Indonesia

Purpose: The over-depletion of natural resources in the Ambang watershed is the recent cause of the flooding in the region. The Ambang watershed, located in the larger Malang region of Indonesia's East Java Province, is the subject of this article because of the importance of this resource to local residents.This study follows the rules set out by Regulation No. P.61/2014 of the Indonesian Ministry of Forestry, which governs the assessment and monitoring of watershed management, in order to determine the Ambang watershed's effectiveness. Finding out how much water the Ambang watershed can hold and how well the regulation works to control floods were the two main goals of this research Method: This study primarily uses data on floods, conservation initiatives, land use, and water value in the Ambang river basin. Data and information on floods, conservation regulations, and the worth of water infrastructure comes from government sources and community discussions. The data on land usage was derived from the analysis of satellite images. Literature reviews and reports from key government agencies (such as the regional agricultural agency, the regional environmental protection agency, and the district government) were used to gather secondary data for the Ambang watershed management study Results and Conclusion: Land cover, as a percentage, can reduce run-off rates and enhance infiltration capacity in a watershed, hence monitoring it is crucial for assessing the state of land carrying capacity. With an area of 86,783.77 ha, the Ambang sub-watershed has 27,311.79 ha of vegetative land cover (PPV), which is classed as poor, falling between 20 and 40%. The result is expressed as a percentage. One way to measure the difference between allowed and actual erosion is via the Erosion Index. Based on the analysis, the Ambang sub-watershed, which covers an area of 86,783.77 ha, experiences heavy erosion on average with 190.8 tons/ha/year. The erosion index is 14.2, and the IE classification is > 2, which is very bad. This is due to factors such as steep to very steep slopes in some areas, poor to moderate soil conservation, and the presence of annual plants on the land, with some exceeding 25%. Research Implications: In order to better educate the public about the conservation and restoration efforts of different stakeholders and to improve the recommendations for potential conservation and restoration actions in each of the Ambang watershed regions, a series of investigations and experimental projects are planned. Laws enacted by the Indonesian government (number 37/2012) and the Ministry of Forestry (number 6061/2014) control the administration of water-related regions in the country. Before receiving any funds from the National State Budget, regional (provincial) governments must develop a management plan that takes into account the watershed's ability to sustain initiatives. Our investigation showed that Regulation 61/2014, issued by the Federal Forestry Minister, does not adequately evaluate the Ambang watershed's harbor capacity. Especially in arid regions, further studies should help Indonesian watersheds better gauge the potential of their water supplies.

Unraveling the decadal–scale coastal evolution and hazards of the Salamanca Barrier (Colombia)

This study aims to characterize the primary coastal hazards operating at both medium-term and episodic scales along the Salamanca barrier in the Caribbean coast of Colombia. On a medium-term (decadal) scale, we analyzed satellite images spanning the past 40 years to characterize shoreline evolution, the associated coastal sediment budget and the responsible sediment transport pattern. At this scale, the barrier has experienced intense shoreline retreat, with erosion rates gradually decreasing over time. For the last analyzed period, 2009–2019, maximum erosion rates have exceeded −20 m/yr. This erosion is primarily driven by a net longshore sediment transport pattern directed towards the west, induced by a wave climate concentrated in a narrow direction arc from the NE. Peak transport rates, reaching an order of magnitude of 106 m3/yr, have been estimated for the westernmost (more exposed) part of the barrier. At an episodic scale, we estimated hazards by evaluating storm-induced erosion and flooding potential. The eastern zone of the barrier showed greater susceptibility to overwash, while potential erosion was only relevant in the western and central sectors. Notably, the most impactful events were associated with waves from directions of 30 and 40°. The cumulative contribution of hazards operating at both scales contribute to various challenges affecting infrastructures, ecosystems, and communities along the Salamanca barrier.

Exploring economic activity from outer space: A Python notebook for processing and analyzing satellite nighttime lights

Nighttime lights (NTL) data are widely recognized as a useful proxy for monitoring national, subnational, and supranational economic activity. These data offer advantages over traditional economic indicators such as GDP, including greater spatial granularity, timeliness, lower cost, and comparability between regions regardless of statistical capacity or political interference. However, despite these benefits, the use of NTL data in regional science has been limited. This is in part due to the lack of accessible methods for processing and analyzing satellite images. To address this issue, this paper presents a user-friendly geocomputational notebook that illustrates how to process and analyze satellite NTL images. First, the notebook introduces a cloud-based Python environment for visualizing, analyzing, and transforming raster satellite images into tabular data. Next, it presents interactive tools to explore the space-time patterns of the tabulated data. Finally, it describes methods for evaluating the usefulness of NTL data in terms of their cross-sectional predictions, time-series predictions, and regional inequality dynamics.