Changes In Vegetation Density Research Articles

Impact of drought on vegetation over inner Mongolia autonomous region

Abstract In recent years, remote sensing technology has become an important tool for monitoring vegetation changes in semi-arid regions. By using data collected by satellites to calculate vegetation indices, researchers can track changes in vegetation density and productivity over time. This can help identify areas of potential desertification or degraded land degradation and develop management strategies to restore degraded ecosystems. The objectives of this paper are to use multi-temporal MODIS data to extract vegetation distribution characteristics and dynamics in Inner Mongolia Autonomous Region. This study summarized the rainfall data of Inner Mongolia Autonomous Region from 2000 to 2019, and found the driest year 2001 and the wettest year 2012. The NDVI data of 4 districts of Xingan League in 2001 and 2012 were selected for analysis, and the average NDVI value and standard deviation of the 4 districts were obtained. NDVI data was combined with elevation data and vegetation data for analysis. The relationship between precipitation and NDVI is helpful to understand the impact of drought on vegetation in Inner Mongolia and provide reference for regional environmental management.

Tree species explain only half of explained spatial variability in plant water sensitivity.

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Spatiotemporal Analysis of Land Surface Temperature Changes by Vegetation Density in Central Lombok Regency

Abstract Land surface temperature is different from air temperature and is caused by various things, one of which is due to changes in vegetation density. Central Lombok Regency is one of the locations that has experienced massive and well-known development in Indonesia. Based on these circumstances, this research was conducted with several objectives, namely: to determine changes in vegetation density, as well as changes in land surface temperature in Central Lombok Regency in 2018 and 2023, and prove the relationship between vegetation density and changes in land surface temperature. The research method used in this research is descriptive quantitative because it involves numerical data, to find the relationship of vegetation density to changes in land surface temperature. In addition, this research also uses the NDVI method to determine the level of vegetation density, and LST to determine the land surface temperature there. The results showed changes in vegetation density and changes in land surface temperature in Central Lombok Regency. The average change in vegetation density and land surface temperature occurred in the Central region of Central Lombok Regency which is the economic center area. Then there is a strong relationship between vegetation density and land surface temperature changes.

Analysis of Vegetation Density Changes on Coastline Changes in the Glagah Coastal Area, Kulon Progo Regency 2018 and 2023

Abstract The construction of Yogyakarta International Airport, which is only 400 meters from Glagah Beach, means that the Kulon Progo Regency Government must pay more attention to guarding the coastline, so that abrasion does not reach Yogyakarta International Airport and the surrounding settlements. The objectives of this research are (1) to identify changes in vegetation density, (2) to identify changes in coastlines, (3) to analyze the relationship between the two in the Glagah Coastal Area, Kulon Progo Regency in 2018 and 2023. The method used in this research is integration between remote sensing and geographic information systems. Remote sensing is used to obtain the Normalized Difference Vegetation Index (NDVI), while the geographic information system is used to analyze shoreline changes using Digital Shoreline Analysis System (DSAS) tools. Based on the 2018 NDVI values, it is known that the area of non-vegetation is 28.2 Ha, low vegetation is 35.2 Ha, medium vegetation is 22.2 Ha, and high vegetation is 26 Ha. The area of each ndvi class in 2023, namely non-vegetation 20.3 Ha, low vegetation 38.2 Ha, medium vegetation 37.9 Ha, and high vegetation 17.7 Ha. The largest amount of abrasion along the Glagah coastline occurred in Sindutan Urban Village, reaching - 56.43 meters and the largest accretion occurred in Jangkaran Urban Village, reaching 65.64 meters. The results of linear regression (0.256) and F test (0.172) show that there is no influence between changes in vegetation density on changes in coastlines in the Glagah coastal area. Even though the results show there is no correlation between vegetation density and changes in coastlines, the role of vegetation is very important in preventing abrasion.

Utilization of Multitemporal Landsat Images for Analysis Urban Heat Island Based on Google Earth Engine in Cimahi City

Cimahi City is physically part of the Bandung-Cimahi core city conurbation of the system of cities in the Bandung City Basin Region so has high development activity. This condition causes an increase in the surface temperature of Cimahi City, especially in the downtown area and triggers the Urban heat island phenomenon. This research was conducted to map multi temporal spatial changes in the vegetation index (MSAVI) and land surface temperature (LST) in Cimahi City in 2015, 2019 and 2023 and to analyze their relationship to the phenomenon and the widespread distribution of urban heat island using Landsat 8 imagery by integrating cloud techniques. computing Google Earth Engine. The results of surface temperature (LST) were correlated with vegetation density (MSAVI) using a simple regression test to determine how much influence changes in vegetation density had on surface temperature (LST). The distribution of urban heat islands was obtained from the classification of LST processing with urban heat island threshold values. The results showed that there was an increase in the distribution area of the urban heat island phenomenon with a total area of urban heat island increasing by 1319.94 Ha in 2015, 3389.04 Ha in 2019, and 3634.04 Ha in 2023. The areas that are dominated by urban impacts The heat island occurred in South Cimahi District with an area affected of 1440.43 Ha.

Analisis Perubahan Kerapatan Vegetasi DAS Air Dingin Akibat Migrasi Penduduk Pasca Gempa Padang 30 September 2009

The aim of this research is to determine changes in vegetation density due to population migration in the Air Cool watershed using the Normalized Difference Vegetation Index (NDVI) method. This research is descriptive research using a quantitative approach. Determining the level of vegetation density in the Air Winter watershed is carried out using the vegetation index score classification by Marwoto & Ginting (2009) which consists of Non-Vegetation, Low Vegetation, Medium Vegetation and High Vegetation density classes. The location of this research is in the Air Cold Watershed, Lubuk Minturun Village, Koto Tangah District, Padang City. Based on the results of the research conducted, several things can be concluded as follows. The results of the analysis of vegetation density levels obtained from image data for 2016 and 2022 consist of Non Vegetation density classes covering 102.86 ha and 12.46 ha, Low Vegetation 730.71 ha and 1279.74 ha, Medium Vegetation 399.76 ha and 5301.17 ha and High Vegetation 11559.82 ha and 6199.63 ha. This change in Vegetation Density was then also followed by an increase in population by 2493 people in Lubuk Minturun Village and 3856 people from Balai Gadang Village, as well as a reduction in the number of people living in areas close to the coastline. This significant population movement of course triggers land clearing for settlements and other land clearing activities so that the Vegetation Density changes along with population growth in an area.

Wild mice in an urbanized world: Effects of light at night under natural and laboratory conditions in the single-striped grass mouse (Lemniscomys rosalia)

ABSTRACT Urbanization, and the accompanying artificial light at night (ALAN), can disrupt the activity of animals. Such disruptions at the base of a food web can ripple through the ecosystem. Most studies of ALAN are performed in the laboratory. Thus, we lack basic information about the circadian responses of animals under natural environmental conditions to fully evaluate the impact of ALAN. We studied the behaviour and activity of wild-caught, peri-urban single-striped grass mice (Lemniscomys rosalia) under a natural treatment and in a standard laboratory treatment, including dim light at night to mimic conditions that they could experience. The species exhibited predominantly crepuscular activity under all experimental treatments. It showed the highest level of activity under the natural treatment, whereas ALAN significantly suppressed its activity. Males were more active than females under all experimental treatments. The marked changes in activity under ALAN is of particular concern since global change in combination with urbanization can lead to a change in vegetation density and composition that will decrease the number of suitable microhabitats and expose small mammals to novel habitat changes. We suggest that the single-striped mice could become vulnerable because of urbanization, leading to impacts on its ecosystem broadly.

Turbulence characteristics in partially vegetated open channels with alternating sparse and dense patches

A large amount of vegetation in nature exists in the form of heterogeneous vegetation patches, and variations in vegetation characteristics significantly affect water flow structures. The objective of this study is to investigate the effect of alternating sparse and dense patches on turbulence characteristics. Multiple sets of heterogeneous vegetation scenarios were designed for numerical simulation analysis, and a comparison was made with homogeneous vegetation. Results indicate that compared with that of homogeneous vegetation, the arrangement of heterogeneous vegetation alters the distribution of flow velocities in the vegetation zone and the main channel, promoting material exchange between these regions. The vegetation density difference between sparse and dense vegetation patches in heterogeneous vegetation effect on the main channel increases with larger vegetation density differences, but the magnitude of the effect is limited and generally remains within 10% of the vegetation width. In the balance equation of turbulent kinetic energy, the terms are influenced differently by changes in vegetation density. As vegetation density difference increases, the convective term gradually increases, while the production and diffusion terms exhibit a “lower in the middle, higher at both ends” pattern. The dissipation term demonstrates a reduction effect at low-density differences, gradually increases with larger differences, and ultimately exhibits an amplification effect. Furthermore, this study determines that using data from mid-height to represent the entire cross section for heterogeneous vegetation may result in a maximum error of up to 11%.

Analysis of Vegetation Changes Using Satellite Imagery and Normalized Difference Vegetation Index (NDVI): A Case Study in Tuntang District, Semarang District

Changes in land use from agriculture to residential and industry continue to occur in Tuntang District, and analysis is needed to identify areas experiencing the most significant changes. Development growth triggered by an increase in population can cause significant changes, such as the conversion of land from forests to agricultural land or plantations, as well as from agricultural land to residential and industrial areas. To monitor land changes, Remote Sensing is used as an effective tool. This method allows data analysis without direct contact with the object being studied. The use of Landsat-8 imagery, as a remote sensing tool, can help identify variations in vegetation. Analysis using the Normalized Difference Vegetation Index (NDVI) calculation method can provide information about the level of vegetation density in the area. The research results show significant changes in vegetation density in Tuntang District from 2019 to 2022. This change is believed to be related to the increase in population, which may be a driving force for several areas to experience development and changes in land function.

The Mapping of Vegetation Density Changes Based on the Normalized Difference Vegetation Index Using Landsat OLI in The Coastal Region of Aceh Barat

Damage to coastal vegetation caused by the tsunami occurred rapidly, despite the critical role of vegetation in supporting life. Vegetation density is quantified through the use of an index known as the NDVI (Normalized Difference Vegetation Index). This index can be applied to assess changes in vegetation density over several years in coastal regions. The focus of this study was to analyze the changes in vegetation density along the coast of West Aceh in the years 2013, 2015, and 2020. The findings indicated that vegetation density in 2013 was notably low, with NDVI values falling within the range of -0.1495 to 0.1591, indicating a lack of vegetation. Furthermore, the percentage of areas with moderate vegetation density appears to have increased steadily year by year, with values of 26.73% in 2013, 27.50% in 2015, and a notable acceleration to 37.61% in 2020.

Hybrid model-based prediction of biomass density in case studies in Turkiye

Growing global concern over natural resource degradation due to urbanisation and population growth emphasizes the critical need for innovative solutions. Addressing this imperative, our study pioneers the integration of cutting-edge artificial intelligence (AI) methods to investigate crucial changes in vegetation density. In this context, a hybrid model, which harmoniously integrates conventional artificial neural network (ANN) models with the innovative Wavelet-ANN (W-ANN) approach, was employed in two case pilot areas, namely on Alanya in Antalya and Iznik in Bursa, Turkiye, renowned for their distinct ecosystems and land cover patterns. By employing diverse data sources, encompassing satellite-derived metrics such as the Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST) from the MODIS/Terra satellite, alongside atmospheric data, our investigation intricately models temporal vegetation dynamics extending to the year 2030. Remarkably, the W-ANN model demonstrates better predictive performance compared to conventional methodologies. It anticipates a substantial 21.4% reduction in vegetation biomass density for Iznik, achieving a minimal 5.4% error probability. Similarly, for Alanya, the model forecasts a notable 6.6% decrease with a remarkably low 2% error probability, both projections extending to the year 2030. Our study reveals a significant reduction in vegetation biomass density by comparing the projected values of the W-ANN model for 2030 with the observed data from 2018. These findings gain further support from an analysis of the Normalised Difference Built-up Index (NDBI) derived from Landsat satellites, affirming the exceptional efficacy of our innovative AI-driven approach in advancing the understanding of urbanisation's impact on ecosystems.

Spatial Analysis of Changes in Normalization Differences Vegetation Index in Protected Forest Areas of South Lore District, Poso Regency

Detection of changes in vegetation density generally uses the vegetation index parameter. The value of the vegetation index can provide information on the proportion of vegetation cover, live plant index, plant biomass, cooling capacity, and estimation of carbon dioxide absorption. This study aims to analyze changes in the level of vegetation density using Sentinel 2-A imagery in the protected forest area of South Lore District. This study used the method of calculating the Normalized Difference Vegetation Index (NDVI) to identify changes in density over 5 years. The results of the NDVI analysis are the largest in the range of -0.92960 to 0.871725. The vegetation density class in the Protected Forest Area of South Lore District in 2017 is in the dense class with an area of 15,322.24 Ha or around 47.66%, while the smallest in the non-vegetation class, which is 103.11 Ha or 0.32%, while the largest vegetation density class is in the Protected Forest Area of South Lore District in 2022, namely in the medium/quite dense class with an area of 19,948.18 Ha or 62.01% while the smallest in the non-vegetation class of 219.17 Ha or 0.68%. The largest increase in area was in the moderate/quite dense class of 4,892.33 Ha or 15.20% while the largest decrease in area was in the dense class with an area of 6,651.16 Ha or 20.67% of the total area of the Protected Forest Area of South Lore District.

토석류 예측 모델을 이용한 재해취약 지역에서의 토사재해에 관한 연구

Torrential rains occurring during the unpredictable climate change cause many mountain disasters in vulnerable areas. This study is to analyze the debris flow mechanism by applying the multiplier of the vulnerable area debris flow prediction model presented by USACE to the erosion or sedimentation model. The higher the typhoon category, the higher the debris flow peak value, and the frequency of peaks of flow discharge with long durations increased. Analysis of changes in vegetation density showed that the initial peak value of the debris flow reaching the bottom was highest due to dense vegetation, and high-amplitude fluctuations appeared due to energy dissipation. In the case of heavy rainfall, the peak value of debris flow increased by more than 22%, and fluctuations of flow discharge occurred earlier at the elapsed time. In addition, debris flow fluctuations with high wave heights appeared, and the high-amplitude band width also appeared to be quite long. The analysis of present study will provide information for developing and prevention disaster reduction measures in vulnerable areas.

Analysis of changes in vegetation density with sentinel-2a image on Malino sub-watershed

Changes in vegetation density, especially in sub-watershed areas, will continue to occur over time. This is due to increasing human activities impacting land use change. The Malino sub-watershed one part of the Jeneberang watershed, almost all located in Tinggimoncong District. Monitoring changes in vegetation density in the Malino Sub-watershed is carried out by utilizing remote sensing technology in the form of sentinel-2A imagery and using the NDVI type of vegetation index method. This study aims to determine the distribution and changes in vegetation density in the Malino Sub-watershed in 2017, 2019, and 2021. From the analysis results conducted using the NDVI vegetation index, the distribution of vegetation density in the Malino Sub-watershed is divided into four classes, namely the non- vegetation, sparse vegetation, medium vegetation, and dense vegetation. Changes in vegetation density in the Malino sub-watershed from 2017 to 2019 occurred in the dense vegetation density class of 2.21% or 192.69 ha, while the smallest occurred in the non-vegetation density class of 0.24% or 20. 97 ha. Meanwhile, the most significant change in vegetation density in the Malino sub-watershed from 2019 to 2021 occurred in the dense vegetation density class of 11.64% or 1,016.60 ha, while the smallest occurred in the non-vegetation density class of 0.12% or 10.46 ha.

Upper thermal limits predict herpetofaunal responses to forest edge and cover

AbstractAmphibians and reptiles are sensitive to changes in the thermal environment, which varies considerably in human‐modified landscapes. Although it is known that thermal traits of species influence their distribution in modified landscapes, how herpetofauna respond specifically to shifts in ambient temperature along forest edges remains unclear. This may be because most studies focus on local‐scale metrics of edge exposure, which only account for a single edge or habitat patch. We predicted that accounting for the combined effect of multiple habitat edges in a landscape would best explain herpetofaunal response to thermally mediated edge effects. We (1) surveyed herpetofauna at two lowland, fragmented forest sites in central Colombia, (2) measured the critical thermal maximum (CTmax) of the species sampled, (3) measured their edge exposure at both local and landscape scales, and (4) created a thermal profile of the landscape itself. We found that species with low CTmax occurred both further from forest edges and in areas of denser vegetation, but were unaffected by the landscape‐scale configuration of habitat edges. Variation in the thermal landscape was driven primarily by changes in vegetation density. Our results suggest that amphibians and reptiles with low CTmax are limited by both canopy gaps and proximity to edge, making them especially vulnerable to human modification of tropical forest.Abstract in Spanish is available with online material.

Kajian Perubahan Kerapatan Vegetasi Pada Kawasan Taman Wisata Alam Ruteng Site Hutan Lok Pahar Akibat Perambahan Hutan

The activity of encroaching on the forest that occurs in the Ruteng Natural Park area site LokPahar forest to be used as agricultural land has had an impact, namely changes in the density ofvegetation in the forest area. This study aims to examine changes in vegetation density in the RutengNature Park area site Lok Pahar forest due to forest encroachment and examine efforts to prevent andcontrol forest encroachment. The results showed that there was a change in vegetation density in theRuteng Nature Park area based on the results of overlay NDVI (Normalized Difference VegetationIndex) on 2 Landsat 8 images, namely Landsat 8 Imagery in 2014 and in 2021. Changes in vegetationdensity in the Tourism Park area Alam Ruteng based on the results of the NDVI (NormalizedDifference Vegetation Index) overlay on 2 Landsat 8 images, namely Landsat 8 Imagery in 2014 andLandsat 8 Imagery 2021. The results of the 2014 Landsat Image NDVI calculation, the forest densityarea in the sparse vegetation density class is 49 .95 ha, and decreased by 1.29% in 2021 to 32.46 ha.In 2014 the medium-level vegetation density class was 384.39 ha, and in 2021 it increased by 2.74%,the medium-level vegetation density class was 421.64 ha. Then, in the dense vegetation density classof 926.73 ha, it decreased by 1.45% so that the area of dense vegetation density class became 906.97ha.

Influence of combined stem vegetation distribution and discretization on the hydraulic characteristics of overland flow

Vegetation has important functions of conserving water sources, reducing surface sediment transport, slowing down the process of soil erosion, purifying soil quality and filtering pollutants, and plays an important role in soil and water conservation and environmental protection governance. Accurate simulation of the slope runoff process is important in the research of hydrological models. Existing distributed hydrological models use a single factor, slope vegetation, to determine the vegetation distribution pattern between slope grid units; thus, the homogenization process does not consider the influence of slope vegetation on the hydraulic characteristics. To clarify the effects of the combination and discrete distribution of stem-type vegetation on the hydraulic characteristics of overland flow, this study conducted 768 sets of indoor flume tests through six combined distributions, six discrete distributions, four slopes, and 16 flow discharges. The results show that: 1) Under the experimental conditions, overland flow is located in the transition and turbulent flow regions, and the flow pattern is mutually restricted by the combined distribution of vegetation, discrete distribution of vegetation, and slope. 2) The Darcy–Weisbach resistance coefficient increases with the increase in the combined diameter and dispersion of vegetative stems, which verifies that the results of the study on complex and varied vegetation overland flows obtained via generalized simulations of homogeneous vegetation deviate from the physical reality of overland flow. 3) An increase in the thickness of the integrated vegetation stems and the increase in the degree of dispersion of vegetation both lead to an increase in the vegetation coverage density. The change in vegetation density initiates the change in the flow pattern and resistance of the overland flow. 4) The total resistance under the combined vegetation cover is divided into morphological resistance and particle resistance. The proportion of particle resistance is smaller than that of morphological resistance and decreases with an increase in flow. 5) The influence of stem diameter, Reynolds number, and slope of the combined vegetation was considered comprehensively, and a flow-resistance calculation model was established.

Changes in the vegetation density of Purwodadi Botanic Garden year 2015 - 2020 with Normalized Difference Vegetation Index (NDVI)

Purwodadi Botanical Gardens is one of the botanical gardens in Indonesia that used for conserve dry tropical plants and absorbs CO2 emissions. Therefore, it is important to know the changes that have occurred in the vegetation density in the Purwodadi Botanical Gardens in the last multi-temporal year (2015 – 2020). Qualitative descriptive research method is used in conducting this research. Field observations were carried out using the quadratic transect method in order to validate the data from Landsat-8 image processing and identifying the absolute density and relative density in the field. Secondary data is also used to determine changes in vegetation density using remote sensing techniques with radiometric correction processes to improve image quality due to surface reflection errors and NDVI (Normalized Difference Vegetation Index) which is used as the final analysis to obtain the results of vegetation density. The results of vegetation density increased from 2015 - 2020 due to the number of trees that grew and developed well, coupled with the regular planting of trees and other plants every year. This certainly has an impact on the air produced being cleaner and lower in temperature so that it can provide convenience for Purwodadi Botanical Garden tourists.

Bio-Physical Controls on Wave Transformation in Coastal Reed Beds: Insights From the Razelm-Sinoe Lagoon System, Romania

Coastal wetlands are dynamic bio-physical systems in which vegetation affects the movement of water and sediment, which in turn build and maintain the landform and ecosystem. Wetlands are an effective buffer against coastal erosion and flooding, enhance water quality and human health and wellbeing. Numerous field and laboratory experiments have quantified the reduction of waves by coastal ecosystems. Numerical models, however, are only able to capture observed reduction in wave energy when calibration coefficients are obtained by comparison with measured dissipation rates. A deeper understanding of how wave attenuation varies over time, with local flow conditions and ecosystem properties, is still lacking and should be acquired from a greater range of ecosystem types and geographical settings. Few studies have observed the detailed seasonal variations in how coastal wetlands function as wave buffers and how such seasonal variations might be explained. Equally, few studies have focused on the effect of coastal reed beds on wave dynamics. This study addresses both: i) seasonal variability in wave dissipation through reed vegetation and ii) intricate connections between reed vegetation and the physical context (meteorological and topographical) that might explain such variability. We present observations of wind generated wave transformation through two Phragmites australis reed beds in the Razelm-Sinoe Lagoon System, Danube Delta, Romania. We find that seasonal changes in vegetation density and biomass, as well as meteorological conditions, affect observed wave conditions within the first few meters of the reed beds. Our results also show a preferential reduction of higher frequency waves, irrespective of reed stem diameter or density and suggest the potential importance of seasonal vegetation debris to observed wave dissipation. Such complex and non-linear biogeomorphic effects on wave dissipation are not currently well understood or captured in the parameterisation of vegetation-induced wave dissipation. Our study highlights the importance of an accurate and temporally granular quantification of nearshore bathymetry, wetland topography, and vegetation to fully understand, model, and manage bio-physical interactions in coastal wetlands. More specifically, our results point towards the need for spatially and temporally explicit wave decay functions in emergent reed vegetation. This is particularly critical where the accurate evaluation of the flood and erosion risk contribution of any wetland is required as part of nature-based coastal protection solutions.

Raster correlation method for vegetation density and surface temperature in Kupang City

The phenomenon of urban heat is caused by global warming that occurred in Kupang City. This causes changes in vegetation density and microclimate especially surface temperature. The study aims to known determine the value of vegetation density and surface temperature in Kupang City in 2010, 2015, and 2021. The raster correlation method was used to study the changes in vegetation density and surface temperature in Kupang City. The research was using the data from Landsat 7 ETM+ satellite imagery in 2010, Landsat 8 OLI TIRS in 2015, and 2020. The changes in vegetation density in the Kupang City area could be seen from the results of processing the satellite image data obtained in 2010 was medium vegetation (the vegetated land cover was in the form of coconut plantation and mixed plantation), in 2015 and 2020 was dominated by low vegetation (grasses and bushes). The results of this study showed that in 2010 the dominant temperature class was 26°C - 28°C. However, the temperature class increased until 2015 and 2020 where the dominant temperature was 29°C - 31°C. The regression coefficient value is negative, the meaning is when the vegetation is denser, the surface temperature value will be lower.