Application of Mann-Kendall trend test and Normalized Difference Vegetation Index (NDVI) in hydroclimatological change detection – A Case Study of Urmia Lake watershed, Iran

2020 ◽  
Author(s):  
Roshanak Tootoonchi ◽  
Vahid Nourani ◽  
Soghra Andaryani ◽  
Faranak Tootoonchi
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urmia Lake ◽  
Trend Test ◽  
Vegetation Changes ◽  
Agricultural Activities ◽  
Increasing Trend ◽  
West Azerbaijan ◽  
East Azerbaijan

<p>Urmia Lake watershed, which is located at the northwest of Iran has gone through crucial hydroclimatological changes that resulted in Urmia Lake Desiccation. Long term average temperature and precipitation trends, precipitation pattern transition and changes in precipitation-snow timing are some of the hydroclimatological changes that have occurred in this watershed. Aforementioned changes are provoked by anthropogenic activities such as land cover changes, booming urbanization, unauthorized exploitations of Urmia Lake and inefficient crop management, followed by natural factors that could be caused by climate change.</p><p>In this study we aim to address contributing hydroclimatological factors and vegetation changes that resulted in Urmia Lake desiccation. In order to examine the vegetation changes in this watershed, we analyzed remote sensing data. In this regard, normalized difference vegetation index (NDVI)-based models for two sub-basins in East Azerbaijan province and West Azerbaijan -located at two sides of Urmia Lake watershed- are developed by an ensemble of satellite data from 1990 to 2019. Data of Landsat 5 TM satellite from 1990 to 2013 and Landsat 8 OLI/TIRS satellite from 2013 to 2019, are collected and analyzed to consider vegetation changes. Hydrological data for precipitation, temperature and Urmia Lake water level elevation are also considered for analyzing hydroclimatic impacts. The adequacy of NDVI-based models and long term hydrological time series are checked by Mann-Kendall trend test.</p><p>The evaluation of NDVI-based models shows an increasing trend in vegetation. In comparison, the studied sub-basin in West Azerbaijan province has a higher level of increasing trend than the sub-basin in East Azerbaijan province. The evaluation of precipitation time series shows a decreasing trend and temperature data exhibit an increasing trend. The trend pattern changes validates the hypothesis that increasing trend of vegetation in Urmia Lake watershed is in proportion to the escalating agricultural activities. Furthermore, the escalation of land use is higher in West Azerbaijan province where there exists more agricultural activities.</p>

scholarly journals Forage Production of the Argentine Pampa Region Based on Land Use and Long-Term Normalized Difference Vegetation Index Data

2009 ◽  
Vol 62 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Carlos M. Di Bella ◽  
Ignacio J. Negri ◽  
Gabriela Posse ◽  
Florencia R. Jaimes ◽  
Esteban G. Jobbágy ◽  
...  
Keyword(s):  
Land Use ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Forage Production ◽  
Index Data ◽  
Pampa Region

Inter-comparison of remotely-sensed actual evapotranspiration products in the Zayandehrud river basin, Iran

2021 ◽  
Author(s):  
Neda Abbasi ◽  
Hamideh Nouri ◽  
Sattar Chavoshi Borujeni ◽  
Pamela Nagler ◽  
Christian Opp ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Measurements ◽  
Water Shortage ◽  
Remotely Sensed ◽  
Irrigation Scheduling ◽  
Accurate Estimation ◽  
Agricultural Areas ◽  
Eta Products

<p>Accurate estimation of evapotranspiration (ET) helps to create a better understanding of water allocation, irrigation scheduling, and crop management especially in arid and semiarid regions where agricultural areas are far more affected by water shortage and drought events. Remote sensing (RS) facilitates estimating the ET in regions where long-term field measurements are missed.  In this study, we compare the performance of free open-access remotely sensed actual ET products at eleven counties of the Zayandehrud basin. The Zayandehrud basin, one of the major watersheds of Iran, suffers from recurrent droughts and long-term impacts of aridity. The RS products used in this study are namely WaPOR (2009-2019), MOD16A2 (2003-2019), SSEBOp (2003-2019). We also merged the two products of SSEBOp and WaPOR and assessed its performance. To prepare the Merged ETa Product (MEP), WaPOR was resampled to the spatial resolution of SSEBOp. Then, the average pixel values of the resampled ETa product and SSEBOp were calculated. To compare ETa estimations over croplands in each county, maximum Normalized Difference Vegetation Index (NDVI) maps at annual scale (2003-2019) were prepared using LANDSAT 5, 7, and 8 images. Annual mean ETa estimations were then extracted over croplands by using annual maximum NDVI layers. We compared the RS-based ETa with reported long-term ETa values extracted from the local available literature. Our results showed a consistent underestimation of MOD16A2 in all counties. The MEP and WaPOR outperformed other products in the estimation of ETa in seven. Estimations of WaPOR and SSEBOp agreed in most of the counties. Our analysis displayed that, although MOD16A2 underestimated ETa values, it could together with SSEBOp capture the drought better than that of WaPOR and MEP in the lower reaches of the basin. Further study is needed to evaluate the monthly and seasonal performance of RS-based ETa products.</p>

scholarly journals LAND USE/LAND COVER CHANGES IN SEMI-ARID MOUNTAIN LANDSCAPE IN SOUTHERN INDIA: A GEOINFORMATICS BASED MARKOV CHAIN APPROACH

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 231-237 ◽  
Author(s):  
S. A. Rahaman ◽  
S. Aruchamy ◽  
K. Balasubramani ◽  
R. Jegankumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
Forest Cover ◽  
Normalized Difference Vegetation Index ◽  
Southern India ◽  
Vegetation Changes ◽  
Land Use Land Cover ◽  
Mountain Landscape ◽  
Semi Arid

Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.

scholarly journals Phenological behavior of Atlas cedar (Cedrus atlantica) forest to snow and precipitation variability in Boutaleb and Babors Mountains, Algeria

2019 ◽  
Vol 21 (1) ◽  
Author(s):  
Khaled Missaoui ◽  
Rachid Gharzouli ◽  
Yamna Djellouli ◽  
Frençois Messner
Keyword(s):  
Time Series ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Descriptive Analysis ◽  
Precipitation Variability ◽  
Monthly Precipitation ◽  
Cedrus Atlantica ◽  
The Past

Abstract. Missaoui K, Gharzouli R, Djellouli Y, Messner F. 2020. Phenological behavior of Atlas cedar (Cedrus atlantica)  forest to snow and precipitation variability in Boutaleb and Babors Mountains, Algeria. Biodiversitas 21: 239-245. Understanding the changes in snow and precipitation variability and how forest vegetation response to such changes is very important to maintain the long-term sustainability of the forest. However, relatively few studies have investigated this phenomenon in Algeria. This study was aimed to find out the response of Atlas cedar (Cedrus atlantica (Endl.) G.Manetti ex Carrière) forest in two areas (i.e Boutaleb and Babors Mountains) and their response to the precipitation and snow variability. The normalized difference vegetation index (NDVI) generated from satellite images of MODIS time series was used to survey the changes of the Atlas cedar throughout the study area well as dataset of monthly precipitation and snow of the province of Setif (northeast of Algeria) from 2000 to 2018. Descriptive analysis using Standarized Precipitation Index (SPI) showed the wetter years were more frequent in the past than in the last two decades. The NDVI values changes in both areas with high values were detected in Babors Mountains with statistically significant differences. Our findings showed important difference in Atlas cedar phenology from Boutaleb mountains to Babors Mountains which likely related to snow factor.

scholarly journals Determination of Normalized Difference Vegetation Index (NDVI) by Applying Disco-Pro AG Drones in Vineyards

2021 ◽  
pp. 123-126
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Field Model ◽  
Agricultural Activities ◽  
Land Utilization ◽  
Planning And Control ◽  
Efficient Planning ◽  
And Control ◽  
The Given

Reliable and up-to-date data on every soil segment of the land areas cultivated for the contemporary land utilization is of vital significance. Currently, the efficient planning and control over the agricultural activities is hardly possible without any reliable and updated information on the yield and agricultural soil types, whereas implementation of drones in the field of land management and in agriculture, on the whole, is one of the most perspective directions, since unlike the artificial sattelites, they provide more precise and guided images for the given location. The aim of the research is to produce the digital field model and NDVI map for the crops by applying Parrot Disco-Pro AG drone kit.

scholarly journals INVESTIGATING MANGROVE FRAGMENTATION CHANGES USING LANDSCAPE METRICS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 159-162
Author(s):  
M. Baharlouii ◽  
D. Mafi Gholami ◽  
M. Abbasi
Keyword(s):  
Climate Change ◽  
Landscape Metrics ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat Images ◽  
Surrounding Water ◽  
Maximum Likelihood Classification ◽  
High Degree ◽  
Drought Occurrence

Abstract. Generally, investigation of long-term mangroves fragmentation changes can be used as an important tool in assessing sensitivity and vulnerability of these ecosystems to the multiple environmental hazards. Therefore, the aim of this study was to reveal the trend of mangroves fragmentation changes in Khamir habitat using satellite imagery and Fragstats software during a 30-year period (1986–2016). To this end, Landsat images of 1986, 1998, and 2016 were used and after computing the normalized difference vegetation index (NDVI) to distinguish mangroves from surrounding water and land areas, images were further processed and classified into two types of land cover (i.e., mangrove and non-mangrove areas) using the maximum likelihood classification method. By determining the extent of mangroves in the Khamir habitat in the years of 1986, 1998 and 2017, the trend of fragmentation changes was quantified using CA, NP, PD and LPI landscape metrics. The results showed that the extent of mangroves in Khamir habitat (CA) decreased in the period post-1998 (1998–2016). The results also showed that, the NP and PD increased in the period of post-1998 and in contrast, the LPI decrease in this period. These results revealed the high degree of vulnerability of mangroves in Khamir habitat to the drought occurrence and are thus threatened by climate change. We hope that the results of this study stimulate further climate change adaptation planning efforts and help decision-makers prioritize and implement conservative measures in the mangrove ecosystems on the northern coasts of the PG and the GO and elsewhere.

scholarly journals Assessing the Effectiveness for Achieving Policy Objectives of Land Consolidation in China: Evidence from Project Practices in Jiangsu Province from 2001 to 2017

2021 ◽  
Vol 13 (24) ◽  
pp. 13891
Author(s):  
Yan Sun ◽  
Xiaojun Song ◽  
Jing Ma ◽  
Haochen Yu ◽  
Xiaoping Ge ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
National Level ◽  
Jiangsu Province ◽  
Land Consolidation ◽  
Investment Funds ◽  
Strategic Factors ◽  
Implementation Scheme ◽  
Policy Objectives

Land consolidation (LC) is an important measure taken to increase the quantity and productivity of farmland while reducing land fragmentation and ensuring food security. However, long-term land consolidation project (LCP) practices are rarely analyzed to assess the effectiveness for achieving current policy objectives of LC in China. Taking the practices of LCPs in Jiangsu Province from 2001 to 2017 as a case study, we used the spatial self-related analysis, the consistency analysis, and the redundant analysis (RDA), and found that the construction scale and the investment amount of LC in Jiangsu Province displayed varying trends, and that the newly increased farmland rate is clearly divided into three stages and gradually decreases. The newly increased farmland area, the investment funds, and reserved land resources for farmlands are not spatially synchronized in Jiangsu Province. Only the positive relationship between the LC rate and the Normalized Difference Vegetation Index (NDVI) growth rate continue to rise. The earlier stage of land consolidation projects (LCPs)’s practices is mainly affected by natural and social factors, and the late stage is mainly affected by economic and strategic factors. Finally, a new implementation scheme framework of LC planning has been proposed. This framework provides reference for top-level design, planning, and management of LC policies at the national level in China and other developing countries. Check meaning retained.

scholarly journals Satellite-Derived Estimation of Grassland Aboveground Biomass in the Three-River Headwaters Region of China during 1982–2018

2021 ◽  
Vol 13 (15) ◽  
pp. 2993
Author(s):  
Ruiyang Yu ◽  
Yunjun Yao ◽  
Qiao Wang ◽  
Huawei Wan ◽  
Zijing Xie ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Aboveground Biomass ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growth Period ◽  
Spatiotemporal Variation ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Ancillary Data

The long-term estimation of grassland aboveground biomass (AGB) is important for grassland resource management in the Three-River Headwaters Region (TRHR) of China. Due to the lack of reliable grassland AGB datasets since the 1980s, the long-term spatiotemporal variation in grassland AGB in the TRHR remains unclear. In this study, we estimated AGB in the grassland of 209,897 km2 using advanced very high resolution radiometer (AVHRR), MODerate-resolution Imaging Spectroradiometer (MODIS), meteorological, ancillary data during 1982–2018, and 75 AGB ground observations in the growth period of 2009 in the TRHR. To enhance the spatial representativeness of ground observations, we firstly upscaled the grassland AGB using a gradient boosting regression tree (GBRT) model from ground observations to a 1 km spatial resolution via MODIS normalized difference vegetation index (NDVI), meteorological and ancillary data, and the model produced validation results with a coefficient of determination (R2) equal to 0.76, a relative mean square error (RMSE) equal to 88.8 g C m−2, and a bias equal to −1.6 g C m−2 between the ground-observed and MODIS-derived upscaled AGB. Then, we upscaled grassland AGB using the same model from a 1 km to 5 km spatial resolution via AVHRR NDVI and the same data as previously mentioned with the validation accuracy (R2 = 0.74, RMSE = 57.8 g C m−2, and bias = −0.1 g C m−2) between the MODIS-derived reference and AVHRR-derived upscaled AGB. The annual trend of grassland AGB in the TRHR increased by 0.37 g C m−2 (p < 0.05) on average per year during 1982–2018, which was mainly caused by vegetation greening and increased precipitation. This study provided reliable long-term (1982–2018) grassland AGB datasets to monitor the spatiotemporal variation in grassland AGB in the TRHR.

scholarly journals Automated Mapping for Long-Term Analysis of Shifting Cultivation in Northeast India

2021 ◽  
Vol 13 (6) ◽  
pp. 1066
Author(s):  
Pulakesh Das ◽  
Sujoy Mudi ◽  
Mukunda D. Behera ◽  
Saroj K. Barik ◽  
Deepak R. Mishra ◽  
...  
Keyword(s):  
Shifting Cultivation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Dynamics ◽  
Google Earth ◽  
Land Restoration ◽  
North East ◽  
Crop Suitability ◽  
Suitability Maps

Assessment of the spatio-temporal dynamics of shifting cultivation is important to understand the opportunities for land restoration. The past studies on shifting cultivation mapping of North-East (NE) India lack systematic assessment techniques. We have developed a decision tree-based multi-step threshold (DTMT) method for consistent and long-term mapping of shifting cultivation using Landsat data from 1975 to 2018. Widely used vegetation indices such as normalized difference vegetation index (NDVI), Normalized Burn Ratio (NBR) and its relative difference NBR (RdNBR) were integrated with the suitable thresholds in the classification, which yielded overall accuracy above 85%. A significant decrease in total shifting cultivation area was observed with an overall reduction of 75% from 1975–1976 to 2017–2018. The methodology presented in this study is reproducible with minimal inputs and can be useful to map similar changes by optimizing the index threshold values to accommodate relative differences for other landscapes. Furthermore, the crop-suitability maps generated by incorporating climate and soil factors prioritizes suitable land use of shifting cultivation plots. The Google Earth Engine (GEE) platform was employed for automatic mapping of the shifting cultivation areas at desired time intervals for facilitating seamless dissemination of the map products. Besides the novel DTMT method, the shifting cultivation and crop-suitability maps generated in this study, can aid in sustainable land management.

Sign in / Sign up

Export Citation Format

Share Document