Part contributive de la densité démographique au reverdissement de certaines zones fortement anthropisées du Sahel : cas des Communes d’Aguié et d’Ibohamane au Niger

Cette étude porte sur l’analyse de la dimension humaine dans l’explication du reverdissement observé dans le paysage de certaines zones fortement anthropisées du Sahel. A cet effet, la commune d’Aguié et celle d’Ibohamane ont été choisies en prenant en compte leur forte densité démographique. La méthodologie utilisée repose sur l’application d’une analyse corrélative couplée à des tests statistiques sur les valeurs de pluies annuelles, les densités démographiques et les valeurs de l’indice normalisé de végétation sur la série chronologique 1980-2018. Les résultats obtenus mettent en évidence deux séquences pluviométriques sèche et humide statistiquement significatives. Pour autant, la période humide récente bien installée à partir de la décennie 90 n’explique pas en totalité l’expression du reverdissement de ces zones. Des taux de 60% et 45% de ce changement sont associés à la densité démographique respectivement au niveau de la commune d’Aguié et celle d’Ibohamane. Ces résultats permettent de replacer le rôle central de la dimension humaine dans la mutation paysagère récente de certaines zones sahéliennes. A ce titre ils peuvent canaliser les réflexions sur la recherche des facteurs et conditions favorables à la mise à l’échelle du reverdissement.Mots clés : NDVI, Pluviométrie, Anthropisation, Reverdissement, RUE. English Title: Contributing part of population density to the regreening of certain highly anthropized area of the Sahel: the case of Agué and Ibohamane municipalities in NigerThis study focuses on human dimension in the explanation of the the regreening process observed in certain areas of the Sahel region. For this purpose, the municipalities of Aguié and Ibohamane were chosen according to their high population density. The methodology used is based on the application of the correlative analysis coupled with statistical test on the annual rainfall values, population density values and the normalized vegetation index values, over 1980-2018 time series. The results obtained highlight two significant dry and wet sequences. However, the recent wet period, well established from the 1990s does not fully explain the regreening of these areas. Rates of 60% and 45% of this change are due to population density respectively in Aguié and Ibohamane case. These results replace the central role of human dimension in the dynamic change of sahelian landscapes and provide the keys that can guide the reflection on the search of factors and conditions favorable of scaling up of regreening.Keywords: NDVI, Rainfall, Anthropization, Regreening, RUE.

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Annually Urban Fractional Vegetation Cover Dynamic Mapping in Hefei, China (1999–2018)

Remote Sensing ◽

10.3390/rs13112126 ◽

2021 ◽

Vol 13 (11) ◽

pp. 2126

Author(s):

Yuliang Wang ◽

Mingshi Li

Keyword(s):

Standard Deviation ◽

Vegetation Cover ◽

Vegetation Index ◽

Dynamic Range ◽

Dynamic Change ◽

Estimation Model ◽

Sparse Vegetation ◽

Fractional Vegetation Cover ◽

Dynamic Mapping ◽

Multi Temporal

Vegetation measures are crucial for assessing changes in the ecological environment. Fractional vegetation cover (FVC) provides information on the growth status, distribution characteristics, and structural changes of vegetation. An in-depth understanding of the dynamic changes in urban FVC contributes to the sustainable development of ecological civilization in the urbanization process. However, dynamic change detection of urban FVC using multi-temporal remote sensing images is a complex process and challenge. This paper proposed an improved FVC estimation model by fusing the optimized dynamic range vegetation index (ODRVI) model. The ODRVI model improved sensitivity to the water content, roughness degree, and soil type by minimizing the influence of bare soil in areas of sparse vegetation cover. The ODRVI model enhanced the stability of FVC estimation in the near-infrared (NIR) band in areas of dense and sparse vegetation cover through introducing the vegetation canopy vertical porosity (VCVP) model. The verification results confirmed that the proposed model had better performance than typical vegetation index (VI) models for multi-temporal Landsat images. The coefficient of determination (R2) between the ODRVI model and the FVC was 0.9572, which was 7.4% higher than the average R2 of other typical VI models. Moreover, the annual urban FVC dynamics were mapped using the proposed improved FVC estimation model in Hefei, China (1999–2018). The total area of all grades FVC decreased by 33.08% during the past 20 years in Hefei, China. The areas of the extremely low, low, and medium grades FVC exhibited apparent inter-annual fluctuations. The maximum standard deviation of the area change of the medium grade FVC was 13.35%. For other grades of FVC, the order of standard deviation of the change ratio was extremely low FVC > low FVC > medium-high FVC > high FVC. The dynamic mapping of FVC revealed the influence intensity and direction of the urban sprawl on vegetation coverage, which contributes to the strategic development of sustainable urban management plans.

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Identifikasi Ketersediaan Ruang Terbuka Hijau Kecamatan Kramat Jati Kodya Jakarta Timur Menggunakan Citra Pleiades

Jurnal Planologi ◽

10.30659/jpsa.v16i2.5005 ◽

2019 ◽

Vol 16 (2) ◽

pp. 158

Author(s):

Mukhoriyah Mukhoriyah ◽

Nurwita Mustika Sari ◽

Maya Sharika ◽

Lidya Nur Hanifati

Keyword(s):

Land Use ◽

Open Space ◽

Vegetation Index ◽

Green Space ◽

Rapid Development ◽

Image Data ◽

Vegetation Density ◽

Radiometric Correction ◽

Key Word ◽

Density Values

ABSTRACTThe development of big cities in Indonesia especially Jakarta City which is developing very rapidly is marked by the rapid development of physical development, thus affecting the increasing population and land use resulting in a decrease in the amount of vegetation cover. The main problem of the existence of Open Green Space (RTH) in Jakarta is the increasingly reduced / limited land and inconsistencies in implementing spatial planning. The reduced green space is caused by changes in land use that is relatively significant so that green space in Jakarta has not met the target of 30% of the total area, especially in the District of Kramatjati. The purpose of this study is to calculate the need for green space within a district. The method used is the initial data processing (radiometric correction, pancarrage, mosaic, cropping) and calculation of vegetation density values based on Normalized Defference Vegetation Index (NDVI). Based on the results of NDVI calculations using Pleiades Image Data in 2015, that in Kramat Jati Subdistrict there were 225.17 ha as vegetation areas, while 918.93 ha were non-vegetation areas. The results of the calculation are then divided into density levels, ie, a rare density of 48,595 ha, medium density of 34,446 ha, and high density of 160,609 ha. The conclusion obtained is that green open space in Kramat Jati Sub-district is planned to cover 12.38% of the entire Kramat Jati area. However, based on NDVI results, green open space in Kramatjati has reached 19.68% of the entire district area. And terms of quantity, then the amount of green space has been fulfilled. Key Word : open green space (RTH), Normalized Defference Vegetation Index (NDVI), Pleiades Image ABSTRAKPerkembangan kota-kota besar di Indonesia khususnya Kota Jakarta yang berkembang dengan sangat pesat ditandai perkembangan pembangunan fisik yang cepat, Sehingga mempengaruhi semakin meningkatnya jumlah penduduk dan pemanfaatan lahan yang mengakibatkan berkurangnya jumlah tutupan vegetasi. Permasalahan utama keberadaan Ruang Terbuka Hijau (RTH) di Kota Jakarta adalah semakin berkurangnya/keterbatasan lahan dan ketidak konsisten dalam menerapkan tata ruang. Berkurangnya RTH disebabkan oleh perubahan penggunaan lahan yang relatif signifikan sehingga RTH Jakarta belum memenuhi target 30% dari total luas wilayahnya terutama di Kecamatan Kramatjati. Tujuan dari penelitian ini adalah untuk menghitung kebutuhan RTH dalam satu lingkup kecamatan. Metode yang digunakan adalah pengolahan data awal (koreksi radiometrik, pansharpen, mozaik, cropping) dan perhitungan nilai kerapatan vegetasi berdasarkan Normalized Defference Vegetation Indeks (NDVI). Berdasarkan hasil perhitungan NDVI dengan menggunakan data Citra Pleiades Tahun 2015, bahwa di Kecamatan Kramat Jati terdapat 225,17 ha merupakan daerah vegetasi, sedangkan 918,93 ha adalah daerah non vegetasi. Hasil perhitungan tersebut kemudian di bagi dalam tingkat kerapatan yaitu kerapatan jarang sebesar 48.595 ha, kerapatan menengah sebesar 34.446 ha, dan kerapatan tinggi sebesar 160.609 ha. Kesimpulan yang diperoleh adalah RTH di Kecamatan Kramat Jati direncanakan seluas 12,38 % dari seluruh wilayah Kramat Jati. Namun, berdasarkan hasil NDVI, RTH di Kramatjati sudah mencapai 19,68% dari seluruh luas kecamatan dan dari segi kuantitas, maka jumlah RTH telah terpenuhi. Kata Kunci: Ruang Terbuka Hijau (RTH), Normalized Defference Vegetation Indeks (NDVI), Citra Pleiades

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Dynamic Vulnerability Analysis of Mountain Settlements Exposed to Geological Hazards: A Case Study of the Upper Min River, China

Advances in Civil Engineering ◽

10.1155/2020/8887487 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Mingtao Ding ◽

Chuan Tang ◽

Tao Huang ◽

Zemin Gao

Keyword(s):

Population Density ◽

Dynamic Change ◽

Evaluation Index System ◽

Geological Hazards ◽

Road Density ◽

Important Indicator ◽

Min River ◽

Vulnerability Evaluation ◽

Mountain Settlements ◽

Economic Density

The upper reaches of Min River (The upper Min River) is located in Southwest China with significant mountain settlements, which are vulnerable to frequent geological hazards. Based on a field investigation, collation of yearbook data, and analysis through the use of SPSS statistical software, a vulnerability evaluation index system of geological hazards was devised. According to the actual field situation and the acquired data of the study area in 2006, 2009, and 2015, 16 indicators were selected as settlement vulnerability evaluation indexes of geological hazards. The indexes included population density, building coverage, and economic density. Based on the comprehensive evaluation model of entropy value, the dynamic change in the settlement vulnerability of geological hazards was analyzed. The results showed that population density, building coverage, economic density, and road density were the factors that affected the settlement vulnerability of geological hazards the most—Wenchuan earthquake caused considerable damage to the upper Min River, making the area the most vulnerable in 2009. However, its vulnerability decreased in 2015, which indicated that postearthquake reconstruction achieved significant results. Thus, the vulnerability has emerged as an important indicator reflecting the safety and healthy development of mountain settlements.

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Rainfall Trend and Its Relationship with Normalized Difference Vegetation Index in a Restored Semi-Arid Wetland of South Africa

Sustainability ◽

10.3390/su12218919 ◽

2020 ◽

Vol 12 (21) ◽

pp. 8919

Author(s):

Florence M. Murungweni ◽

Onisimo Mutanga ◽

John O. Odiyo

Keyword(s):

South Africa ◽

Quantile Regression ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Rainfall Data ◽

Ecosystem Change ◽

Annual Rainfall ◽

Rainfall Trend ◽

Vegetation Productivity ◽

Rainfall Trends

Clearance of terrestrial wetland vegetation and rainfall variations affect biodiversity. The rainfall trend–NDVI (Normalized Difference Vegetation Index) relationship was examined to assess the extent to which rainfall affects vegetation productivity within Nylsvley, Ramsar site in Limpopo Province, South Africa. Daily rainfall data measured from eight rainfall stations between 1950 and 2016 were used to generate seasonal and annual rainfall data. Mann-Kendall and quantile regression were applied to assess trends in rainfall data. NDVI was derived from satellite images from between 1984 and 2003 using Zonal statistics and correlated with rainfall of the same period to assess vegetation dynamics. Mann-Kendall and Sen’s slope estimator showed only one station had a significant increasing rainfall trend annually and seasonally at p < 0.05, whereas all the other stations showed insignificant trends in both rainfall seasons. Quantile regression showed 50% and 62.5% of the stations had increasing annual and seasonal rainfall, respectively. Of the stations, 37.5% were statistically significant at p < 0.05, indicating increasing and decreasing rainfall trends. These rainfall trends show that the rainfall of Nylsvley decreased between 1995 and 2003. The R2 between rainfall and NDVI of Nylsvley is 55% indicating the influence of rainfall variability on vegetation productivity. The results underscore the impact of decadal rainfall patterns on wetland ecosystem change.

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Changes in the Transmission Dynamic of Chikungunya Virus in Southeastern Senegal

Viruses ◽

10.3390/v12020196 ◽

2020 ◽

Vol 12 (2) ◽

pp. 196 ◽

Cited By ~ 1

Author(s):

Abdourahmane Sow ◽

Birgit Nikolay ◽

Oumar Faye ◽

Simon Cauchemez ◽

Jorge Cano ◽

...

Keyword(s):

Population Density ◽

Rural Areas ◽

Gold Mining ◽

Chikungunya Virus ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Transmission Dynamic ◽

Sylvatic Cycle ◽

Mining Sites ◽

Semivariogram Analysis

In Senegal, chikungunya virus (CHIKV) is maintained in a sylvatic cycle and causes sporadic cases or small outbreaks in rural areas. However, little is known about the influence of the environment on its transmission. To address the question, 120 villages were randomly selected in the Kedougou region of southeastern Senegal. In each selected village, 10 persons by randomly selected household were sampled and tested for specific anti-CHIKV IgG antibodies by ELISA. We investigated the association of CHIKV seroprevalence with environmental variables using logistic regression analysis and the spatial correlation of village seroprevalence based on semivariogram analysis. Fifty-four percent (51%–57%) of individuals sampled during the survey tested positive for CHIKV-specific IgG. CHIKV seroprevalence was significantly higher in populations living close to forested areas (Normalized Difference Vegetation Index (NDVI), Odds Ratio (OR) = 1.90 (1.42–2.57)), and was negatively associated with population density (OR = 0.76 (0.69–0.84)). In contrast, in gold mining sites where population density was >400 people per km2, seroprevalence peaked significantly among adults (46% (27%–67%)) compared to all other individuals (20% (12%–31%)). However, traditional gold mining activities significantly modify the transmission dynamic of CHIKV, leading to a potential increase of the risk of human exposition in the region.

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Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades

Remote Sensing ◽

10.3390/rs13204063 ◽

2021 ◽

Vol 13 (20) ◽

pp. 4063

Author(s):

Jie Xue ◽

Yanyu Wang ◽

Hongfen Teng ◽

Nan Wang ◽

Danlu Li ◽

...

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Dynamic Change ◽

Google Earth ◽

Arid Areas ◽

Climate Data ◽

Northern Margin ◽

The Past

Climate change has proven to have a profound impact on the growth of vegetation from various points of view. Understanding how vegetation changes and its response to climatic shift is of vital importance for describing their mutual relationships and projecting future land–climate interactions. Arid areas are considered to be regions that respond most strongly to climate change. Xinjiang, as a typical dryland in China, has received great attention lately for its unique ecological environment. However, comprehensive studies examining vegetation change and its driving factors across Xinjiang are rare. Here, we used the remote sensing datasets (MOD13A2 and TerraClimate) and data of meteorological stations to investigate the trends in the dynamic change in the Normalized Difference Vegetation Index (NDVI) and its response to climate change from 2000 to 2019 across Xinjiang based on the Google Earth platform. We found that the increment rates of growth-season mean and maximum NDVI were 0.0011 per year and 0.0013 per year, respectively, by averaging all of the pixels from the region. The results also showed that, compared with other land use types, cropland had the fastest greening rate, which was mainly distributed among the northern Tianshan Mountains and Southern Junggar Basin and the northern margin of the Tarim Basin. The vegetation browning areas primarily spread over the Ili River Valley where most grasslands were distributed. Moreover, there was a trend of warming and wetting across Xinjiang over the past 20 years; this was determined by analyzing the climate data. Through correlation analysis, we found that the contribution of precipitation to NDVI (R2 = 0.48) was greater than that of temperature to NDVI (R2 = 0.42) throughout Xinjiang. The Standardized Precipitation and Evapotranspiration Index (SPEI) was also computed to better investigate the correlation between climate change and vegetation growth in arid areas. Our results could improve the local management of dryland ecosystems and provide insights into the complex interaction between vegetation and climate change.

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Research Progress on Remote Sensing Classification Methods for Farmland Vegetation

AgriEngineering ◽

10.3390/agriengineering3040061 ◽

2021 ◽

Vol 3 (4) ◽

pp. 971-989

Author(s):

Dongliang Fan ◽

Xiaoyun Su ◽

Bo Weng ◽

Tianshu Wang ◽

Feiyun Yang

Keyword(s):

Remote Sensing ◽

Agricultural Development ◽

Vegetation Index ◽

Crop Yields ◽

Dynamic Change ◽

Practical Significance ◽

Research Progress ◽

Remote Sensing Classification ◽

Advantages And Disadvantages ◽

Crop Planting

Crop planting area and spatial distribution information have important practical significance for food security, global change, and sustainable agricultural development. How to efficiently and accurately identify crops in a timely manner by remote sensing in order to determine the crop planting area and its temporal–spatial dynamic change information is a core issue of monitoring crop growth and estimating regional crop yields. Based on hundreds of relevant documents from the past 25 years, in this paper, we summarize research progress in relation to farmland vegetation identification and classification by remote sensing. The classification and identification of farmland vegetation includes classification based on vegetation index, spectral bands, multi-source data fusion, artificial intelligence learning, and drone remote sensing. Representative studies of remote sensing methods are collated, the main content of each technology is summarized, and the advantages and disadvantages of each method are analyzed. Current problems related to crop remote sensing identification are then identified and future development directions are proposed.

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Using remote sensing data in population density estimation

10.25743/sdm.2021.34.56.066 ◽

2021 ◽

Author(s):

E.G. Shvetsov ◽

N.M. Tchebakova ◽

E.I. Parfenova

Keyword(s):

Remote Sensing ◽

Spatial Distribution ◽

Population Density ◽

Vegetation Index ◽

Census Data ◽

Remote Sensing Data ◽

Satellite System ◽

Population Census ◽

Krasnoyarsk Krai ◽

Using Data

In recent decades, remote sensing methods have often been used to estimate population density, especially using data on nighttime illumination. Information about the spatial distribution of the population is important for understanding the dynamics of cities and analyzing various socio-economic, environmental and political factors. In this work, we have formed layers of the nighttime light index, surface temperature and vegetation index according to the SNPP/VIIRS satellite system for the territory of the central and southern regions of the Krasnoyarsk krai. Using these data, we have calculated VTLPI (vegetation temperature light population index) for the year 2013. The obtained values of the VTLPI calculated for a number of settlements of the Krasnoyarsk krai were compared with the results of the population census conducted in 2010. In total, we used census data for 40 settlements. Analysis of the data showed that the relationship between the value of the VTLPI index and the population density in the Krasnoyarsk krai can be adequately fitted (R 2 = 0.65) using a linear function. In this case, the value of the root-meansquare error was 345, and the relative error was 0.09. Using the obtained model equation and the spatial distribution of the VTLPI index using GIS tools, the distribution of the population over the study area was estimated with a spatial resolution of 500 meters. According to the obtained model and the VTLPI index, the average urban population density in the study area exceeded 500 people/km2 . Comparison of the obtained data on the total population in the study area showed that the estimate based on the VTLPI index is about 21% higher than the actual census data.

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LONG-TERM MONITORING OF WATER DYNAMICS IN THE SAHEL REGION USING THE MULTI-SAR-SYSTEM

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b8-313-2016 ◽

2016 ◽

Vol XLI-B8 ◽

pp. 313-320 ◽

Cited By ~ 1

Author(s):

A. Bertram ◽

A. Wendleder ◽

A. Schmitt ◽

M. Huber

Keyword(s):

Climate Change ◽

Human Population ◽

Dynamic Change ◽

Open Water ◽

Water Dynamics ◽

Long Term Monitoring ◽

Sar Data ◽

Sahel Region ◽

Term Monitoring

Fresh water is a scarce resource in the West-African Sahel region, seasonally influenced by droughts and floods. Particularly in terms of climate change, the importance of wetlands increases for flora, fauna, human population, agriculture, livestock and fishery. Hence, access to open water is a key factor. Long-term monitoring of water dynamics is of great importance, especially with regard to the spatio-temporal extend of wetlands and drylands. It can predict future trends and facilitate the development of adequate management strategies. Lake Tabalak, a Ramsar wetland of international importance, is one of the most significant ponds in Niger and a refuge for waterbirds. Nevertheless, human population growth increased the pressure on this ecosystem, which is now degrading for all uses. The main objective of the study is a long-term monitoring of the Lake Tabalak’s water dynamics to delineate permanent and seasonal water bodies, using weather- and daytime-independent multi-sensor and multi-temporal Synthetic Aperture Radar (SAR) data available for the study area. Data of the following sensors from 1993 until 2016 are used: Sentinel-1A, TerraSARX, ALOS PALSAR-1/2, Envisat ASAR, RADARSAT-1/2, and ERS-1/2. All SAR data are processed with the Multi-SAR-System, unifying the different characteristics of all above mentioned sensors in terms of geometric, radiometric and polarimetric resolution to a consistent format. The polarimetric representation in Kennaugh elements allows fusing single-polarized data acquired by older sensors with multi-polarized data acquired by current sensors. The TANH-normalization guarantees a consistent and therefore comparable description in a closed data range in terms of radiometry. The geometric aspect is solved by projecting all images to an earth-fixed coordinate system correcting the brightness by the help of the incidence angle. The elevation model used in the geocoding step is the novel global model produced by the TanDEM-X satellite mission. The advantage of the Multi-SAR-System is that it comprises ortho-rectification, radiometric enhancement, normalization and Kennaugh decomposition, independent from sensors, modes, polarizations or acquisition date of SAR data. In addition, optical satellite data can be included as well, to fill gaps where SAR data are missing due to the special normalization scheme. This kind of pre-processing is exclusively implemented at the Earth Observation Center of the German Aerospace Center in Oberpfaffenhofen, Germany. Therefore, the dynamic change of the open water of the Lake Tabalak could be classified over dry and rainy seasons and years, using different SAR data. The study provides a unique database and contributes to a better understanding of wetland systems in the Sahel region influenced by human pressure and climate change.

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Dynamics of woody plant cover in the Sahelian agroecosystems of the northern region of Burkina Faso since the 1970s–1980s droughts

Canadian Journal of Forest Research ◽

10.1139/cjfr-2019-0247 ◽

2020 ◽

Vol 50 (7) ◽

pp. 659-669

Author(s):

Wendpouiré Arnaud Zida ◽

Farid Traoré ◽

Babou André Bationo ◽

Jean-Philippe Waaub

Keyword(s):

Burkina Faso ◽

Woody Plants ◽

Vegetation Index ◽

Woody Plant ◽

Plant Cover ◽

Northern Region ◽

Climatic Conditions ◽

Landsat Images ◽

Sahel Region ◽

Effective Conservation

This study was carried out in the northern region of Burkina Faso under Sahelian climatic conditions. The area was particularly affected by the 1970s–1980s droughts that led to the degradation of land and vegetation. Since the early 1990s, a gradual return of rainfall has been observed throughout the Sahel region. In this new environmental context, understanding the development of woody plants is important for effective conservation and management. We analyzed the dynamics of woody plant cover over the 30 years following the end of the 1970s–1980s droughts by using Landsat images from 1986, 1999, and 2015 with 30 m spatial resolution and taking into account changes in rainfall and land use. The change in the enhanced vegetation index 1 (EVI1) at the beginning of the dry season was used as a proxy for the change in photosynthetic activity of woody plants. Results showed an improvement in EVI1 on 98% of the study area, with a mean increase of 0.20 from 1986 to 2015. This improvement was accompanied by an increase in agroforestry and was weakly correlated with rainfall. The improvement in EVI1 was unstable, however, with a decline from 1999 to 2015 in the areas undergoing regreening.

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