Assessing the spatial heterogeneity in ecological quality using remote sensing (Case Study: Gharesoo Watershed)

Document Type : Research Article

Authors

1 Master of land evaluation and land use planning Gorgan University of Agricultural Sciences and Natural Resources Iran

2 Assistant Professor, Gorgan University of Agricultural Sciences and Natural Resources Iran

Abstract

The environment is currently experiencing different changes that are caused by both nature-induced and anthropogenic processes. Land use changes in Gharesoo Watershed noted that there is a necessary need to study ecological quality in this region. In this paper, a remote sensing-based ecological index (RSEI) based on the pressure-state-response (PSR) framework, using the average data of summer images of Landsat satellite in 1989 and 2018 (ETM +/OLI/TIRS sensors), was used to evaluate the changes in ecological quality in Gharasoo watershed of Golestan province. Google Earth Engine (GEE) is used for acquiring and preparing indices, including an indicator of environmental pressure (NDBI), an indicator of environmental state (NDVI) and indicators of local climate changes in response to environmental changes and concerns (LST and LSM). After preparing the indices, the weight of each index was extracted using the principal component analysis (PCA), and then the ecological quality index was created based on the first component of PCA. Analysis of the first component changes using the thresholding method showed a decrease in ecological quality. So that the average RSEI index in 1989 was 0.57 and in 1397 this value reached 0.48, which indicates a decrease in RSEI. Also, the area of very good class in 1989 and 2018 is 32821.83 (16.267%) and 36879.66 (18.27%) hectares, respectively. Spatial variation analysis showed that the poor level of RSEI distributed mostly in the northern areas, and the ecological degradation was  attributed to the fast expansion of the built-up area, characterized by increasing greatly in the value of the normalized differential built up index (NDBI) in such areas.
 

Keywords


 راحلی نمین، بهناز؛ مرتضوی، ثمر؛ 1397. پیش‌بینی روند تغییرات مکانی کاربری اراضی و توسعه مناطق مسکونی با استفاده از مدل زنجیرهای CA مارکوف و روش ژئومد، مطالعة موردی: حوزه آبخیز قره‌سو، استان گلستان. فصلنامه علمی - پژوهشی فضای جغرافیایی. 18 (62). صص 169-159.
رباطی، م. 1394. سنجش کیفیت محیط­زیست شهری با به‌کارگیری مدل شاخص ترکیبی (موردمطالعه: کلان‌شهر تهران). آمایشسرزمین. شماره 7 (2). صص 275-255.
صیدی، سمیه؛ عبدی قروچای، ناهید؛ حسن‌زاده، امین؛ ۱۳۹۷. ارزیابی وضعیت کیفیت محیط شهری با استفاده از شاخص­های سنجش‌ازدور. فصلنامه پژوهش­های علوم جغرافیایی، معماری و شهرسازی. شماره 2 (13). صص 113-126.
مختاری، محمدحسین؛ عابدیان، سحر؛ قلی­پور، مصطفی؛ 1398. آشکارسازی و مدلسازی روند تغییرات کاربری اراضی جنگلی حوزه آبخیز قره­سو با استفاده از سنجه­های سیمای سرزمین. بومشناسیکاربردی. شماره 4. صص 18-1.
مهری، آزاده؛ سلمان ماهینی، عبدالرسول؛ میکاییلی تبریزی، علیرضا؛ میرکریمی، سید حامد؛ 1397. ارزیابی اثرات بوم‌شناختی تغییر کاربری سرزمین بر ساختار طبیعی حوضه رودخانه قره‌سو. آمایش سرزمین. شماره 10 (1). صص 116-93.
 
Avdan U, Jovanovska G., 2016. Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data. Journal of Sensors 26: 1-8.
Barsi J, Schott J, Hook S, Raqueno N, Markham B, Radocinski R. 2014. Landsat-8 thermal infrared sensor (TIRS) vicarious radiometric calibration. Remote Sensing 6 (11): 11607-11626.‏
Behling R, Bochow M, Foerster S, Roessner S, Kaufmann, H., 2015. Automated GIS-based derivation of urban ecological indicators using hyperspectral remote sensing and height information. Ecological indicators 48: 218-234.‏
Binh TNKD, Vromant N, Hung NT, Hens L, Boon EK., 2005. Land cover changes between 1968 and 2003 in Cai Nuoc, Ca Mau peninsula, Vietnam. Environment, Development and Sustainability 7 (4): 519-536.‏
Dale VH, Beyeler SC., 2001. Challenges in the development and use of ecological indicators. Ecological indicators 1 (1): 3-10.‏
Eastman JR. 201. TerrSet tutorial. Clark University.
Foley JA, De Fries R, Asner GP, Barford C, Bonan G, Carpenter SR, Chapin FS, Coe MT, Daily GC, Gibbs HK, Helkowski JH, Holloway T, Howard EA, Kucharik CJ, Monfreda C, Patz JA, Prentice IC, Ramankutty N, Snyder P. K. 2005. Global consequences of land use. Science. 309 :570–574.
Gessesse, A. A., & Melesse, A. M., (2019). Temporal relationships between time series CHIRPS-rainfall estimation and eMODIS-NDVI satellite images in Amhara Region, Ethiopia. In Extreme Hydrology and Climate Variability (pp. 81-92). Elsevier.
Halmy MWA., 2019. Assessing the impact of anthropogenic activities on the ecological quality of arid Mediterranean ecosystems (case study from the northwestern coast of Egypt). Ecological Indicators 101: 992-1003.‏
Heinz IIIHJ., 2002. The State of the Nation's Ecosystems: Measuring the Lands, Waters, and Living Resources of the United States: Cambridge University Press.‏
Hu X, Xu H., 2018. A new remote sensing index for assessing the spatial heterogeneity in urban ecological quality: A case from Fuzhou City, China. Ecological indicators 89: 11-21.‏
Huang C, Wylie B, Yang L, Homer C, Zylstra G., 2002. Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance. International journal of remote sensing 23 (8): 1741-1748.‏
Jing Y, Zhang F, He Y, Johnson VC, & Arikena, M., (2020). Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China. Ecological Indicators 110, 105874.‏
Kaplan G, Avdan U, Avdan ZY., 2018. Urban heat island analysis using the landsat 8 satellite data: A case study in Skopje, Macedonia. In Multidisciplinary Digital Publishing Institute Proceedings 2 (7).
Koh CN, Lee PF, Lin RS., 2006. Bird species richness patterns of northern Taiwan: primary productivity, human population density, and habitat heterogeneity. Diversity and Distributions 12 (5): 546-554.‏
Lin T, Ge R, Huang J, Zhao Q, Lin J, Huang N, Zhang G, Li X, Ye H, Yin K., 2016. A quantitative method to assess the ecological indicator system's effectiveness: a case study of the Ecological Province Construction Indicators of China. Ecological indicators 62: 95-100.‏
Lin T, Lin JY, Cui SH, Cameron S., 2009. Using a network framework to quantitatively select ecological indicators. Ecological Indicators 9 (6) : 1114-1120.‏
Musse MA, Barona DA, Rodriguez LMS., 2018. Urban environmental quality assessment using remote sensing and census data. International journal of applied earth observation and geoinformation 71: 95-108.‏
Niemi GJ, McDonald ME., 2004. Application of ecological indicators. Annu. Rev. Ecol. Evol. Syst 35: 89-111.‏
Rajeshwari A, Mani ND., 2014. Estimation of land surface temperature of Dindigul district using Landsat 8 data. International Journal of Research in Engineering and Technology 3 (5): 122-126.
Seddon AW, Macias-Fauria M, Long PR, Benz D, Willis KJ., 2016. Sensitivity of global terrestrial ecosystems to climate variability. Nature 531 (7593).
Tsou J, Zhuang J, Li Y, Zhang Y., 2017. Urban heat island assessment using the Landsat 8 data: a case study in Shenzhen and Hong Kong. Urban Science 1 (1): 1-20.
USGS ., 2013. United States Geological Survey, Landsat 8: U.S. Geological Survey Fact Sheet 2013–3060. http://pubs.usgs.gov/fs/2013/3060.
Wang L, Qu JJ., 2007. NMDI: A normalized multi‐band drought index for monitoring soil and vegetation moisture with satellite remote sensing. Geophysical Research Letters 34 (20).‏
Wen X, Ming Y, Gao Y, Hu X., 2020. Dynamic Monitoring and Analysis of Ecological Quality of Pingtan Comprehensive Experimental Zone, a New Type of Sea Island City, Based on RSEI. Sustainability 12 (1), 21.‏
Xu H, Ding F, Wen X., 2009. Urban expansion and heat island dynamics in the Quanzhou region, China. IEEE Journal of selected topics in applied earth observations and remote sensing 2  (2): 74-79.‏
Xu H. 2008. A new index for delineating built‐up land features in satellite imagery. International Journal of Remote Sensing 29 (14): 4269-4276.‏
Yue H, Liu Y, Li Y, Lu Y., 2019. Eco-environmental quality assessment in China’s 35 major cities based on remote sensing ecological index. IEEE Access 7: 51295-51311.‏
Zhang J, Zhu Y, Fan F., 2016. Mapping and evaluation of landscape ecological status using geographic indices extracted from remote sensing imagery of the Pearl River Delta, China, between 1998 and 2008. Environmental Earth Sciences 75 (4): 1-16.
 
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