Spatio-Temporal Forest Change Assessment Using Time Series Satellite Data in Palamu District of Jharkhand, India

被引:4
|
作者
Singh, Beependra [1 ]
Jeganathan, C. [2 ]
机构
[1] Indian Inst Sci, Ctr Ecol Sci, Bangalore 560012, Karnataka, India
[2] Birla Inst Technol, Dept Remote Sensing, Ranchi 835215, Bihar, India
关键词
Forest change; Anomaly; Time series; MODIS; EVI; Palamu district; COVER CHANGE DETECTION; CLIMATE-CHANGE; VEGETATION; DROUGHT; REGION;
D O I
10.1007/s12524-015-0538-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Free availability of time-series satellite data enabled the current study to quantify decadal macro-variations (i.e., trend and percent change) in vegetation vigour in the forested environment of Palamu district based on 11 years (2001 to 2011) of fortnightly data of Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI; 250 m). Further, Landsat ETM+ data of year 2001 and 2011 were also used to extract micro-level changes and as a validation reference. The inter-year comparison about standard anomalies revealed an alarming situation about persistent stress in the vegetation, especially after 2008. However, the degradation rate is slow as per anomaly frequency but steadily increasing after 2008. The study estimated that there is a loss of 293 km(2) forest which is close to the FSI estimate of 333 km(2). The current study provides a quick mechanism to reveal the spatial pattern of temporal changes in the forested region with reliable and reproducible methods.
引用
收藏
页码:573 / 581
页数:9
相关论文
共 50 条
  • [21] A SPATIO-TEMPORAL APPROACH TO DETECTING LAND COVER CHANGE USING AN EXTENDED KALMAN FILTER ON MODIS TIME SERIES DATA
    Kleynhans, W.
    Olivier, J. C.
    Salmon, B. P.
    Wessels, K. J.
    van den Bergh, F.
    [J]. 2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2010, : 1972 - 1975
  • [22] Vulnerability Assessment for Forest Ecosystem to Climate Change Based on Spatio-temporal Information
    Byun, Jungyeon
    Lee, Woo-Kyun
    Choi, Sungho
    Oh, Suhyun
    Yoo, Seongjin
    Kwon, Taesung
    Sung, Joohan
    Woo, Jaewook
    [J]. KOREAN JOURNAL OF REMOTE SENSING, 2012, 28 (01) : 159 - 169
  • [23] Detecting hydroclimatic change using spatio-temporal analysis of time series in Colorado River Basin
    Kumar, Mukesh
    Duffy, Christopher J.
    [J]. JOURNAL OF HYDROLOGY, 2009, 374 (1-2) : 1 - 15
  • [24] SVM spatio-temporal classification of HR satellite image time series using graph based kernel
    Rejichi, Safa
    Chaabane, Ferdaous
    [J]. 2014 1ST INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES FOR SIGNAL AND IMAGE PROCESSING (ATSIP 2014), 2014, : 390 - 395
  • [25] Measures of spatio-temporal accuracy for time series land cover data
    Tsutsumida, Narumasa
    Comber, Alexis J.
    [J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2015, 41 : 46 - 55
  • [26] Assessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices
    Gangalakunta P. Obi Reddy
    Nirmal Kumar
    Nisha Sahu
    Rajeev Srivastava
    Surendra Kumar Singh
    Lekkala Gopala Krishnama Naidu
    Gajjala Ravindra Chary
    Chandrashekhar M. Biradar
    Murali Krishna Gumma
    Bodireddy Sahadeva Reddy
    Javaji Narendra Kumar
    [J]. Arabian Journal of Geosciences, 2020, 13
  • [27] Spatio-temporal Trend Detection of Rainfall for Climate Change Assessment in Ahmedabad-Gandhinagar District of Gujarat State, India
    Joshi, Geeta S.
    Makhasana, Payal
    [J]. JOURNAL OF CLIMATE CHANGE, 2021, 7 (01) : 69 - 78
  • [28] Assessment of spatio-temporal vegetation dynamics in tropical arid ecosystem of India using MODIS time-series vegetation indices
    Reddy, Gangalakunta P. Obi
    Kumar, Nirmal
    Sahu, Nisha
    Srivastava, Rajeev
    Singh, Surendra Kumar
    Naidu, Lekkala Gopala Krishnama
    Chary, Gajjala Ravindra
    Biradar, Chandrashekhar M.
    Gumma, Murali Krishna
    Reddy, Bodireddy Sahadeva
    Kumar, Javaji Narendra
    [J]. ARABIAN JOURNAL OF GEOSCIENCES, 2020, 13 (15)
  • [29] A Spatio-Temporal Encoding Neural Network for Semantic Segmentation of Satellite Image Time Series
    Zhang, Feifei
    Wang, Yong
    Du, Yawen
    Zhu, Yijia
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (23):
  • [30] SELF-SUPERVISED SPATIO-TEMPORAL REPRESENTATION LEARNING OF SATELLITE IMAGE TIME SERIES
    Dumeur, Iris
    Valero, Silvia
    Inglada, Jordi
    [J]. IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 642 - 645