{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T00:30:03Z","timestamp":1773102603832,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T00:00:00Z","timestamp":1609891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A dynamic habitat index (DHI) based on satellite derived biophysical proxy (fraction of absorbed photosynthetically active radiation, FAPAR) was used to evaluate the vegetation greenness pattern across deserts to alpine ecosystems in India that account to different biodiversity. The cumulative (DHI-cum), minimum (DHI-min), and seasonal (DHI-sea) DHI were generated using Moderate Resolution Imaging Spectroradiometer (MODIS)-based FAPAR. The higher DHI-cum and DHI-min represented the biodiversity hotspots of India, whereas the DHI-sea was higher in the semi-arid, the Gangetic plain, and the Deccan peninsula. The arid and the trans-Himalaya are dominated with grassland or barren land exhibit very high DHI-sea. The inter-year correlation demonstrated an increase in vegetation greenness in the semi-arid region, and continuous reduction in greenness in the Northeastern region. The DHI components validated using field-measured plant richness data from four biogeographic regions (semi-arid, eastern Ghats, the Western Ghats, and Northeast) demonstrated good congruence. DHI-cum that represents the annual greenness strongly correlated with the plant richness (R2 = 0.90, p-value &lt; 0.001), thereby emerging as a suitable indicator for assessing plant richness in large-scale biogeographic studies. Overall, the FAPAR-based DHI components across Indian biogeographic regions provided understanding of natural variability of the greenness pattern and its congruence with plant diversity.<\/jats:p>","DOI":"10.3390\/rs13020159","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T20:45:42Z","timestamp":1609965942000},"page":"159","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Satellite Based Fraction of Absorbed Photosynthetically Active Radiation Is Congruent with Plant Diversity in India"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5230-731X","authenticated-orcid":false,"given":"Swapna","family":"Mahanand","sequence":"first","affiliation":[{"name":"School of Water Resources, IIT Kharagpur, Kharagpur 721302, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9976-6270","authenticated-orcid":false,"given":"Mukunda Dev","family":"Behera","sequence":"additional","affiliation":[{"name":"School of Water Resources, IIT Kharagpur, Kharagpur 721302, India"},{"name":"SAM Lab, Centre for Oceans, Rivers, Atmosphere and Land Sciences, IIT Kharagpur, Kharagpur 721302, India"}]},{"given":"Partha Sarathi","family":"Roy","sequence":"additional","affiliation":[{"name":"World Resources Institute, New Delhi 110016, India"}]},{"given":"Priyankar","family":"Kumar","sequence":"additional","affiliation":[{"name":"SAM Lab, Centre for Oceans, Rivers, Atmosphere and Land Sciences, IIT Kharagpur, Kharagpur 721302, India"}]},{"given":"Saroj Kanta","family":"Barik","sequence":"additional","affiliation":[{"name":"CSIR-National Botanical Research Institute, Lucknow 226001, India"}]},{"given":"Prashant Kumar","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, India"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1620","DOI":"10.1890\/1051-0761(2000)010[1620:IDVCWG]2.0.CO;2","article-title":"Incorporating dynamic vegetation cover within global climate models","volume":"10","author":"Foley","year":"2000","journal-title":"Ecol. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Cui, L., and Shi, J. (2010). Temporal and spatial response of vegetation NDVI to temperature and precipitation in eastern China. J. Geogr. Sci.","DOI":"10.1007\/s11442-010-0163-4"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"111218","DOI":"10.1016\/j.rse.2019.111218","article-title":"Remote sensing of terrestrial plant biodiversity","volume":"231","author":"Wang","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, C., Cai, D., Guo, S., Guan, Y., Fraedrich, K., Nie, Y., Liu, X., and Bian, X. (2016). Spatial-temporal dynamics of China\u2019s terrestrial biodiversity: A dynamic habitat index diagnostic. Remote Sens., 8.","DOI":"10.3390\/rs8030227"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Erdelen, W.R. (2020). Shaping the Fate of Life on Earth: The Post-2020 Global Biodiversity Framework. Glob. Policy.","DOI":"10.1111\/1758-5899.12773"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"\u0160\u00edmov\u00e1, I., Li, Y.M., and Storch, D. (2013). Relationship between species richness and productivity in plants: The role of sampling effect, heterogeneity and species pool. J. Ecol.","DOI":"10.1111\/1365-2745.12011"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"16024","DOI":"10.1038\/nplants.2016.24","article-title":"Monitoring plant functional diversity from space","volume":"2","author":"Jetz","year":"2016","journal-title":"Nat. Plants"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1080\/01431168608948944","article-title":"Satellite remote sensing of primary production","volume":"7","author":"Tucker","year":"1986","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","unstructured":"Waring, R.H., and Running, S.W. (1998). Forest ecosystems: Analysis at multiple scales. Choice Rev. Online."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.rse.2006.06.011","article-title":"Evaluation of satellite based primary production modelling in the semi-arid Sahel","volume":"105","author":"Fensholt","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1890\/090179","article-title":"Biophysical considerations in forestry for climate protection","volume":"9","author":"Anderson","year":"2011","journal-title":"Front. Ecol. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Jackson, R.B., Randerson, J.T., Canadell, J.G., Anderson, R.G., Avissar, R., Baldocchi, D.D., Bonan, G.B., Caldeira, K., Diffenbaugh, N.S., and Field, C.B. (2008). Protecting climate with forests. Environ. Res. Lett.","DOI":"10.1088\/1748-9326\/3\/4\/044006"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Oindo, B.O., and Skidmore, A.K. (2002). Interannual variability of NDVI and species richness in Kenya. Int. J. Remote Sens.","DOI":"10.1080\/01431160010014819"},{"key":"ref_14","unstructured":"Huston, M.A. (1994). Biological diversity: The coexistence of species on changing landscapes. Biol. Divers. Coexistence Species Chang. Landsc."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Muchoney, D.M. (2008). Earth observations for terrestrial biodiversity and ecosystems. Remote Sens. Environ.","DOI":"10.1016\/j.rse.2008.01.003"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Thakur, T.K., Padwar, G.K., Patel, D.K., and Bijalwan, A. (2019). Monitoring land use, species composition and diversity of moist tropical environ in Achanakmaar Amarkantak Biosphere reserve, India using satellite data. Biodivers. Int. J.","DOI":"10.15406\/bij.2019.03.00141"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mahanand, S., and Behera, M.D. (2017). Relationship between Field-Based Plant Species Richness and Satellite-Derived Biophysical Proxies in the Western Ghats, India. Proc. Natl. Acad. Sci. India Sect. A Phys. Sci., 87.","DOI":"10.1007\/s40010-017-0460-8"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Chitale, V.S., Behera, M.D., and Roy, P.S. (2019). Deciphering plant richness using satellite remote sensing: A study from three biodiversity hotspots. Biodivers. Conserv.","DOI":"10.1007\/s10531-019-01761-4"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"20069","DOI":"10.1029\/2000JD000115","article-title":"Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999","volume":"106","author":"Zhou","year":"2001","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Nemani, R.R., Keeling, C.D., Hashimoto, H., Jolly, W.M., Piper, S.C., Tucker, C.J., Myneni, R.B., and Running, S.W. (2003). Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science.","DOI":"10.1126\/science.1082750"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1016\/j.rse.2012.01.017","article-title":"Greenness in semi-arid areas across the globe 1981-2007 - an Earth Observing Satellite based analysis of trends and drivers","volume":"121","author":"Fensholt","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1038\/s41893-019-0220-7","article-title":"China and India lead in greening of the world through land-use management","volume":"2","author":"Chen","year":"2019","journal-title":"Nat. Sustain."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Mondal, P., Jain, M., Robertson, A.W., Galford, G.L., Small, C., and DeFries, R.S. (2014). Winter crop sensitivity to inter-annual climate variability in central India. Clim. Chang.","DOI":"10.1007\/s10584-014-1216-y"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.scitotenv.2017.02.156","article-title":"Greening and browning of the Himalaya: Spatial patterns and the role of climatic change and human drivers","volume":"587\u2013588","author":"Mishra","year":"2017","journal-title":"Sci. Total Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.apgeog.2014.10.007","article-title":"Spatio-temporal analysis of trends in seasonal vegetation productivity across Uttarakhand, Indian Himalayas, 2000-2014","volume":"56","author":"Mishra","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1111\/j.1365-2486.2011.02578.x","article-title":"Trend changes in global greening and browning: Contribution of short-term trends to longer-term change","volume":"18","author":"Verbesselt","year":"2012","journal-title":"Glob. Chang. Biol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2485","DOI":"10.1002\/ldr.3019","article-title":"Spatial patterns of long-term vegetation greening and browning are consistent across multiple scales: Implications for monitoring land degradation","volume":"29","author":"Murthy","year":"2018","journal-title":"Land Degrad. Dev."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1016\/j.ecolind.2017.11.032","article-title":"Persistent negative changes in seasonal greenness over different forest types of India using MODIS time series NDVI data (2001\u20132014)","volume":"85","author":"Chakraborty","year":"2018","journal-title":"Ecol. Indic."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.rse.2007.03.018","article-title":"Effects of spatial and spectral resolution in estimating ecosystem \u03b1-diversity by satellite imagery","volume":"111","author":"Rocchini","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_30","unstructured":"Mackey, B., Bryan, J., and Randall, L. (2003). Australia\u2019 s Dynamic Habitat Template for 2003, ANU Research Publications."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1016\/j.ecolind.2008.11.003","article-title":"Demonstration of a satellite-based index to monitor habitat at continental-scales","volume":"9","author":"Coops","year":"2009","journal-title":"Ecol. Indic."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Wright, D.H. (1983). Species-Energy Theory: An Extension of Species-Area Theory. Oikos.","DOI":"10.2307\/3544109"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.1111\/j.1461-0248.2004.00671.x","article-title":"Predictions and tests of climate-based hypotheses of broad-scale variation in taxonomic richness","volume":"7","author":"Currie","year":"2004","journal-title":"Ecol. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hurlbert, A.H. (2006). Linking species-area and species-energy relationships in Drosophila microcosms. Ecol. Lett.","DOI":"10.1111\/j.1461-0248.2005.00870.x"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Connell, J.H., and Orias, E. (1964). The Ecological Regulation of Species Diversity. Am. Nat.","DOI":"10.1086\/282335"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Hu, G., Jin, Y., Liu, J., and Yu, M. (2014). Functional diversity versus species diversity: Relationships with habitat heterogeneity at multiple scales in a subtropical evergreen broad-leaved forest. Ecol. Res.","DOI":"10.1007\/s11284-014-1178-6"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Mason, N.W.H., Mouillot, D., Lee, W.G., and Wilson, J.B. (2005). Functional richness, functional evenness and functional divergence: The primary components of functional diversity. Oikos.","DOI":"10.1111\/j.0030-1299.2005.13886.x"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Williams, S.E., and Middleton, J. (2008). Climatic seasonality, resource bottlenecks, and abundance of rainforest birds: Implications for global climate change. Divers. Distrib.","DOI":"10.1111\/j.1472-4642.2007.00418.x"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Coops, N.C., Fontana, F.M.A., Harvey, G.K.A., Nelson, T.A., and Wulder, M.A. (2014). Monitoring of a national-scale indirect indicator of biodiversity using a long time-series of remotely sensed imagery. Can. J. Remote Sens.","DOI":"10.1080\/07038992.2014.945826"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"133","DOI":"10.3390\/d6010133","article-title":"Predicting climate change impacts to the canadian boreal forest","volume":"6","author":"Nelson","year":"2014","journal-title":"Diversity"},{"key":"ref_41","unstructured":"Berry, S., Mackey, B., and Brown, T. (2021, January 04). Potential applications of remotely sensed vegetation greenness to habitat analysis and the conservation of dispersive fauna. Available online: https:\/\/www.publish.csiro.au\/PC\/PC070120."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Berry, S.L., and Roderick, M.L. (2002). Estimating mixtures of leaf functional types using continental-scale satellite and climatic data. Glob. Ecol. Biogeogr.","DOI":"10.1046\/j.1466-822X.2002.00183.x"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Cramer, M.J., and Willig, M.R. (2005). Habitat heterogeneity, species diversity and null models. Oikos.","DOI":"10.1111\/j.0030-1299.2005.12944.x"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Turner, M.G., Donato, D.C., and Romme, W.H. (2013). Consequences of spatial heterogeneity for ecosystem services in changing forest landscapes: Priorities for future research. Landsc. Ecol.","DOI":"10.1007\/s10980-012-9741-4"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s42965-020-00078-6","article-title":"Studies on ecosystem function and dynamics in Indian sub-continent and emerging applications of satellite remote sensing technique","volume":"61","author":"Barik","year":"2020","journal-title":"Trop. Ecol."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Zhao, M., Heinsch, F.A., Nemani, R.R., and Running, S.W. (2005). Improvements of the MODIS terrestrial gross and net primary production global data set. Remote Sens. Environ.","DOI":"10.1016\/j.rse.2004.12.011"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Heinsch, F.A., Zhao, M., Running, S.W., Kimball, J.S., Nemani, R.R., Davis, K.J., Bolstad, P.V., Cook, B.D., Desai, A.R., and Ricciuto, D.M. (2006). Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations. IEEE Trans. Geosci. Remote Sens.","DOI":"10.1109\/TGRS.2005.853936"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Tian, Y., Zhang, Y., Knyazikhin, Y., Myneni, R.B., Glassy, J.M., Dedieu, G., and Running, S.W. (2000). Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data. IEEE Trans. Geosci. Remote Sens.","DOI":"10.1109\/36.868895"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Coops, N.C., Wulder, M.A., Duro, D.C., Han, T., and Berry, S. (2008). The development of a Canadian dynamic habitat index using multi-temporal satellite estimates of canopy light absorbance. Ecol. Indic.","DOI":"10.1016\/j.ecolind.2008.01.007"},{"key":"ref_50","unstructured":"Roy, P.S., Kushwaha, S.P.S., Murthy, M.S.R., Roy, A., Kushwaha, D., Reddy, C.S., Behera, M.D., Mathur, V.B., Padalia, H., and Saran, S. (2012). Biodiversity Characterisation at Landscape Level: National Assessment, Indian Institute of Remote Sensing."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Tripathi, P., Dev Behera, M., and Roy, P.S. (2017). Optimized grid representation of plant species richness in India-Utility of an existing national database in integrated ecological analysis. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0173774"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Schwartz, M.D., Ahas, R., and Aasa, A. (2006). Onset of spring starting earlier across the Northern Hemisphere. Glob. Chang. Biol.","DOI":"10.1111\/j.1365-2486.2005.01097.x"},{"key":"ref_53","unstructured":"Gaston, K.J., and Blackburn, T.M. (2021, January 04). Pattern and Process in Macroecology. Available online: https:\/\/www.wiley.com\/en-ag\/Pattern+and+Process+in+Macroecology-p-9780470999592."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1016\/j.tree.2011.05.009","article-title":"Does conservation on farmland contribute to halting the biodiversity decline?","volume":"26","author":"Kleijn","year":"2011","journal-title":"Trends Ecol. Evol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jclepro.2018.05.237","article-title":"Assessment of fuelwood diversity and consumption patterns in cold desert part of Indian Himalaya: Implication for conservation and quality of life","volume":"196","author":"Negi","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"4391","DOI":"10.3390\/rs70404391","article-title":"El Drought variability and land degradation in semiarid regions: Assessment using remote sensing data and drought indices (1982-2011)","volume":"7","author":"Cabello","year":"2015","journal-title":"Remote Sens."},{"key":"ref_57","unstructured":"MEA (2021, January 04). Ecosystems and Human Well-Being. Synthesis. Available online: http:\/\/www.bioquest.org\/wp-content\/blogs.dir\/files\/2009\/06\/ecosystems-and-health.pdf."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Saikia, A. (2009). NDVI variability in North East India. Scottish Geogr. J.","DOI":"10.1080\/14702540903071113"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2401","DOI":"10.3390\/rs70302401","article-title":"Development of decadal (1985-1995-2005) land use and land cover database for India","volume":"7","author":"Roy","year":"2015","journal-title":"Remote Sens."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Pasha, S.V., Behera, M.D., Mahawar, S.K., Barik, S.K., and Joshi, S.R. (2020). Assessment of shifting cultivation fallows in Northeastern India using Landsat imageries. Trop. Ecol.","DOI":"10.1007\/s42965-020-00062-0"},{"key":"ref_61","first-page":"250","article-title":"Assessment of biological richness in different altitudinal zones in the Eastern Himalayas, Arunachal Pradesh, India","volume":"88","author":"Roy","year":"2005","journal-title":"Curr. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/2\/159\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:07:26Z","timestamp":1760159246000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/2\/159"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,6]]},"references-count":61,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,1]]}},"alternative-id":["rs13020159"],"URL":"https:\/\/doi.org\/10.3390\/rs13020159","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,6]]}}}