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GUEST POST: A Very Brief History of Optical High Resolution Satellite Imaging

The history of the optical high resolution satellite images starts from classified military satellite systems of the United States of America that captured earth’s surface from 1960 to 1972. All these images were declassified by Executive Order 12951 in 1995 and made publically available (Now freely available through the USGS EarthExplorer data platform under the category of declassified data). From 1999 onward, commercial multispectral and panchromatic datasets have been available for public. Launch of Keyhole Earthviewer in 2001, later renamed as Google Earth in 2005, opened a new avenue for the layman to visualize earth features through optical high resolution satellite images.

A comparison of declassified Corona (1974) vs. GeoEye-1 (2014) image. Image credits: EarthExplorer (Corona) and Google Earth (GeoEye-1).

In the current era, most high resolution satellite images are commercially available, and are being used as a substitute to aerial photographs. The launch of SPOT, IKONOS, QuickBird, OrbView, GeoEye, WorldView, KOMPSAT etc. offer data at fine resolutions in digital format to produce maps in much simpler, cost effective and efficient manner in terms of mathematical modeling. A number of meaningful products are being derived from high resolution datasets, e.g., extraction of high resolution Digital Elevation Models (DEMs) with 3D building models, detailed change assessments of land cover and land use, habitat suitability, biophysical parameters of trees, detailed assessments of pre and post-disaster conditions, among others.

Both aerial photographs and high resolution images are subject to weather conditions but satellites offer the advantage of repeatedly capturing same areas on a reliable basis by considering the user demand without being restricted by considering borders and logistics, as compared to aerial survey.

Pansharpening / resolution merge provides improved visualization and is also used for detecting certain features in a better manner. Pansharpening / resolution merge is a fusion process of co-georegistered panchromatic (high resolution) and multispectral (comparatively lower resolution) satellite data to produce high-resolution color multispectral image. In high resolution satellite data, the spectral resolution is being increased and more such sensors with enhanced spectral sensitivity are being planned in the future.

List of the Spaceborne Sensors with <5 m Spatial Resolution

Sensors Agency/Country Launch Date Platform altitude (km) GSD Pan/MSS (m) Pointing capability (o) Swath width at nadir (km)
IKONOS-2 GeoEye Inc./USA 1999 681 0.82/3.2 Free View 11.3
EROS A1 ImageSat Int./Cyprus (Israel) 2000 480 1.8 Free View 12.6
QuickBird DigitalGlobe/USA 2001 450 0.61/2.44 Pan and MSS alternative Free View 16.5
HRS SPOT Image/France 2002 830 5X10 Forward/left +20/-20 120
HRG SPOT Image/France 2002 830 5(2.5)x10 sideways up to ±27 60
OrbViw-3 GeoEye Inc./USA 2003 470 1/4 Free View 8
FORMOSAT 2 NSPO/China, Taiwan 2004 890 2/8 Free View 24
PAN (Cartosat-1) ISRO/India 2005 613 2.5 Forward/aft 26/5 Free view to side up to 23 27
TopSat Telescope BNSC/UK 2005 686 2.8/5.6 Free View 15/10
PRISM JAXA/Japan 2005 699 2.5 Forward/Nadir/aft -24/0/+24 Free view to side 70 35 (Triplet stereo observations
PAN(BJ-1) NRSCC (CAST)/China 2005 686 4/32 Free View 24/640
EROS B ImageSat Int./Cyprus (Israel) 2006 508 0.7/- Free View 7
Geoton-L1Resurs-DK1 Roscosmos/Russia 2006 330-585 1/3 for h = 330km Free View 30 for h = 330km
KOMPSAT-2 KARI/South Korea 2006 685 1/4 sideways up to ±30 15 km
CBERS-2B CNSA/INPE China/Brazil 2007 778 2.4/20 Free View 27/113
WorldView-1 DigitalGlobe/USA 2007 494 0.45/- Free View 17.6
THEOS GISTDA/Thailand 2008 822 2/15 Free View 22/90
AlSat-2 Algeria 2008 680 2.5 up to 30 cross track Free view 17.5
GeoEye-1 GeoEye Inc./USA 2008 681 0.41/1.65 Free View 15.2
WorldView-2 DigitalGlobe/USA 2009 770 0.45/1.8 Free View 16.4
PAN (Cartosat-2, 2A, 2B) ISRO/India Cartosat 2-2007 Cartosat 2A-2008 Cartosat   2B-2010 631 0.82/- Free View 9.6
KOMPSAT-3 KARI/South Korea 2012 685 0.7/2.8 ±45º into any direction (cross-track or along-track) 15
WorldView-3 DigitalGlobe/USA 2014 617 0.3/1.24/3.7/30 13.1

 Conflicts of Interest: The findings reported stand as scientific study and observations of the author and do not necessarily reflect as the views of author’s organizations.

 About this post: This is a guest post by Hammad Gilani. Learn more about this blog’s authors here

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Suspected Sep. 2017 Oil Spill in Clifton, Karachi: A Follow-up Analysis with SAR Images

On the third day of Eid-ul-Azha, September 4, 2017, beachgoers in Karachi reported oil or oil-like substance washing ashore on the Clifton Beach. Geo News reported the incident here.

As a researcher in the field of radar remote sensing, it got me thinking whether we can spot it on satellite images, if incidentally acquired by a space-borne Synthetic Aperture Radar (SAR) sensor. Interestingly, I found some acquisitions acquired by the European Space Agency (ESA)’s Sentinel-1A sensor. Unfortunately there was no acquisition on the 4th of September. The closest acquisition before the suspected spill is on 01.09.2017 @ 01:26, and the latest is on 10.09.2017 @ 13:35. The good news is that the latest image shows no sign of ‘low brightness’ characteristic of oil slicks. However, in the image on 01.09, we do see some dark areas which are somewhat troubling.

 

Referring to the figure below, the dark areas immediately below the Clifton area made me nervous — if that is oil spill traveling towards the shoreline, it’s huge! But it’s probably not, since it’s just too huge to have gotten ignored! It’s likely a ‘look-alike’ [1], which may appear in the radar image indicating local calmness of the water. However, I’m no expert in oceanography, so I don’t make any claim about it. Nonetheless, it does cause to raise an eyebrow.

Karachi_clifton_suspectedOilSlick5

Sentinel-1 C-Band SAR images, projected in map coordinates, and overlaid in Google Earth. No clear evidence of oil slick close to Clifton Beach. Two patches of probable oil slick detected on 01.09.2017, 15-30 km southwards of the beach.

At the same time, there are two instances (marked in red) which do seem to be oil spills, perhaps in the wake of the very same vessels passing nearby. In each case, it extends more than 6 km. Since the image is now 12 days old, and we don’t observe the suspected spill in the latest image — it may have dispersed by now — the main lesson is that the “authorities should keep a closer look” in future!

Karachi_clifton_suspectedOilSlick7

A close-up of the suspected oil spill marked in red in the figure above.

I am open to feedback/comments from other fellow scientists/experts in the field of SAR/Remote-Sensing/Oceanography, especially if they fear I may have missed something.

Disclaimer: This is an analysis performed from “remote” sensing images. Authorities must confirm or reject the suspicions on the basis of local forensic evaluation.

About this post: This is a guest post by M. Adnan Siddique.

کیا اس سال سیلاب آئے گا؟

سنہ2017 کی ایک عالمی رپورٹ کے مطابق موسمیاتی تبدیلیوں سے شدیدمتا ثر ہونے والے  ملکوں میں بنگلہ دیش پہلے  پاکستان     16ویں جبکہ  چین 49 ویں نمبرپر ہے اور ناروے سب سے کم متاثرہ ہونے کی وجہ سے 170 ویں نمبر پر ہے۔ پاکستان ان شدید  موسمیاتی تبدیلیوں کی وجہ   سےسیلاب، خشک سالی، زلزلوں جیسی قدرتی آفات کی زد میں رہتا ہے۔  پاکستان میں سیلاب کی تاریخ کافی پرانی ہے۔ وفاقی سیلابی ادارے  کی ایک رپورٹ کے مطابق پچھلے 68 سالوںمیں  سیلاب سے ہونے والے نقصان کا تخمینہ تقریبا 38 بلین ڈالر ہے   جبکہ اسی رقم سے 3 دیامیر بھاشا ڈیم تعمیر کیے جاسکتے ہیں۔ پاکستان کی حالیہ تاریخ میں 1952، 1973، 1976، 1978، 1988، 1992، 1997 اور 2010 کے سیلاب شدید ترین نوعیت کے تھے۔  صرف 2010 کے سیلاب سے 2000 اموات واقع ہوئی  اور 0.16 ملین زرخیز زمین زیر آب آ گئی۔ پاکستان میں کل سیلابی نقصان کا 42 فیصد 210-2015 کے دوران وقوع پزیر ہونے والے سیلابوں  کی کارستانی ہے۔ اقوام متحدہ کے ایک محتاط اندازے کے مطابق 2010 کے سیلاب میں 18 ملین افراد متاثر ہوئے جس میں آبادی کے لحاظ سے صوبہ سندھ اور اموات کے لحاظ سے  صوبہ خیبر پختونخوا سب سے زیادہ متاثر ہوئے۔

Flood 2010

سنہ 2017 میں پاکستان میں مون سون سے سیلاب کے خطرے کی جانچ کیلئے پاکستان کے موسمیاتی ادارے کی 14 جون2017 کو شائع ہونے والی رپورٹ کا جائزہ از حد ضروری ہے۔ اس موسمی پیش گوئی کی رپورٹ کے مطابق   اس سال پاکستان میں مون سون بارشیں جولائی میں نارمل ہوں گی اور اگست اور ستمبر میں یہ نارمل سے بھی کم ہوں گی۔پاکستان کے جنوبی علاقوں میں بارش کی کمی کی وجہ سے خشک سالی کا بھی خطرہ  ہو سکتا ہے۔ اس کے ساتھ یہ بھی امکاں ہے کی پہاڑی اور نیم  پہاڑی علاقوں میں سیلابی ریلوں کے خطرات موجود رہیں۔

سیلاب کی صورتحال کی عکاسی کے لیئے  پاکستان میں موجود دریاوں کے خدوخال کی وضاحت ضروری ہے۔ پاکستان میں سیلابی پانی کو ذخیرہ کرنے کیلئے صرف دو ڈیم  تربیلا اور منگلا ہیں جن میں ایک خاص حد تک پانی ذخیرہ کیا جا سکتا ہے،  جبکہ باقی تین دریاوں ستلج، راوی اور چناب پر کوئی پانی ذخیرہ کرنے کی سہولت میسر نہیں ہے۔ سیلابی پانی سے آبادی کو بچانے کیلئےدریاوں کے ساتھ سیلابی پشتے تعمیر کیے جاتے ہیں اور ان پشتوں کے اندرونی علاقے بیٹ یا کچا کے علاقے کہلاتے ہیں جہان مستقل تعمیرات کی اجازت نہی۔ان علاقوں میں مون سون کے دنوں میں عموماٰ ان علاقوں سیلابی پانی آسانی سے داخل ہو جاتا ہے اور وہاں کے رہائشی اس موسم میں نقل مکانی کے عادی ہیں۔ سیلابی صورتحال اس وقت گھمبیر ہو جاتی ہے جب پانی ان پشتوں سے باہر نقل کر آبادی اور زرخیز زمینوں میں داخل ہوتاہے اور جانی ومالی نقصان کا باعث بنتا ہے۔

اگر چہ محکمہ موسمیات کی پیشین گوئی کو مد نظر رکھا جائے تو اس سال سیلاب کے امکانات کم ہیں،  تاہم مون سون کے غیر معمولی برتاو کی وجہ سے سیلاب کے خطرہ کو یکسر مسترد نہیں کیا جاسکتا۔  اس کی ایک وجہ  یہ  ہے کہ مون سون کی بارشیں کسی ایک وقت میں کم اور دوسرے وقت میں زیادہ ہوں اور بحیثیت مجموعی ان کا    رویہ نارمل ہو۔اسی ضمن میں اگر 2010 کے سیلاب کی صورتحال کو مد نظر رکھا جائے تو مندرجہ ذیل حقیقت واضح ہوتی ہے: جولائی 2010 میں شمالی علاقہ جات میں نارمل سے چار گنا زیادہ بارشیں ہوئیں اور ان بارشوں کی شدت 36 گھنٹوں میں 300 ملی میٹر تک ریکارڈ کی  گئی۔ایک قلیل وقت میں اتنی زیادہ مقدار میں پانی کو سنبھالے کی استعداد  اور سکت ہماری انتظامی مشینری میں نہیں تھی جس کا نتیجہ 2010 کے سیلاب کی صورت میں بھگتنا پڑا۔ اقوام متحدہ نے 2010 کے سیلاب کو  موجودہ تاریخ کا بدترین انسانی بحران قرار دیا اور اس وقت سیکریٹری بان کی مون بذات خود پاکستان میں صورتحال کا جا ئزہ لینےکیلئے تشریف لائے۔ موجودہ چیف جسٹس لاہور ہائی کورٹ جسٹس منصور علی شاہ کی قیادت میں2010 میں بننے والے سیلابی کمیشن نے یہ نتیجہ اخذ کیا تھا کہ سیلاب سے نمٹنے کیلے متعلقہ محکموں کےپاس  نہ ہی درکار استعداد تھی اور  نہ ہی منظم فیصلہ سازی کی صلاحیت تھی۔ اس کے علاوہ   سرکاری اہل کاروں  کی غفلت اور سیلابی پشتوں کی  غیر مناسب دیکھ بھال اور تعمیر میں ناقص مواد کا استعمال بڑی تباہی کا باعث بنے۔

سیلاب سے نمٹنے کیلے ضروری ہے  ملک میں نئے ڈیم تعمیر کیے جائیں، اداروں کی استعداد کار میں اضافہ کیا جائے، سیلابی پشتوں کی مناسب دیکھ بھال کا  شفاف نظام وضع کیا جائے اور جدید مہارتوں کے استعمال سے نقصانات کو کم سے کم سطح پر لایا جائے۔

Imagery Downlinked from Satellite to Ground in 6 Minutes

Some months ago, I had written about the EDRS SpaceDataHighway and real-time provision of Sentinel-1 satellite imagery through laser link and satellite relay. Now, ESA has done an experiment with Sentinel-2B to deliver imagery to the ground moments after it was capture by the satellite. The captured image strip was downlinked in just 6 minutes. This experiment brings us closer to the amazing future when we would be able to access satellite imagery as non-defence / non-strategic users in near-real-time.

See more details here:

http://www.esa.int/Our_Activities/Observing_the_Earth/Copernicus/Sentinel-2/First_Sentinel-2B_images_delivered_by_laser

Aperture Synthesis and Azimuth Resolution in Synthetic Aperture Radar – Lecture Notes

Teaching the fundamentals of Synthetic Aperture Radar (SAR) system design and imaging mechanism to remote sensing students / professionals is always a difficult task. Remote sensing students / professionals generally do not have an in-depth background of signal processing and radar system design, and as an instructor, I always have to think over how much I need to tell them about SAR system design, without diving into the detailed mathematics of signal processing and imaging mechanism. Normally, I go in-depth towards the imaging geometry and an understanding of the Doppler history curve, and briefly go over the signal-processing heavy concepts like pulse compression and matched filtering. A good fundamental understanding of the SAR system design, imaging geometry, and image formation is essential for remote sensing students / professionals to have a background context knowledge when they select SAR data and process / analyze it for different remote sensing applications.

For the past few years, I have been teaching a graduate course in Radar Remote Sensing and also run an annual Summer School on Earth Remote Sensing with SAR at our research group GREL. One of the core issues in understanding the aperture synthesis process is the requirement for enhancement of the azimuth / along-track resolution. It is always interesting to discuss in class how in normal imaging radar the azimuth resolution depends inversely on the antenna along-track length, while in fully-focussed SAR the azimuth resolution becomes half of the antenna along-track length. This is a significant reversal: In normal imaging radar, we need a bigger antenna in along-track dimension to get better azimuth resolution, while in SAR, the smaller the antenna in the along-track dimension, the better the azimuth resolution.

AzimuthResolutionSAR

To explain how aperture synthesis changes the azimuth resolution to half of the along-track antenna length, I have made some detailed notes for my ongoing graduate class on Radar Remote Sensing. These notes require just basic knowledge of geometry, algebra, and sum series in mathematics. I would like to share them with the wider scientific audience, please access the PDF notes here: Aperture Synthesis and Azimuth Resolution.

ApertureSynthesis

The synthetic aperture length is defined in the figure above. The azimuth resolution in fully-focussed SAR becomes half of the antenna along-track dimension.

I have taken the help of two excellent resources on SAR remote sensing in developing these notes:

For more in-depth understanding and analysis of how SAR is used for remote sensing, you can consider attending the next Summer School on Earth Remote Sensing with SAR, which I will be offering this summer. The summer school is coming up in July, 2018, and it will be open for international participants; formal dates will be announced soon. Keep watching the GREL website for updates.

Big Earth Data Documentary

Recently I ran into this wonderful documentary about how scientists are handling the huge amounts of remote sensing and earth science data being collected in the current age.

The documentary spends a lot of time talking about how remote sensing is used for oceanography and marine security monitoring, looking at concerns like monster waves, oil spills, surface ice content, ship routing through polar oceans, etc.

The EarthServer project is mentioned, which establishes “big earth data analytics, rapid ad-hoc processing and filtering on massive geodata.” Satellite images are shown to be useful also for automatic counting of houses or camps, and for disaster damage assessment. The use of GRACE satellite system for Earth gravimetry and water content measurement is mentioned.

For background information regarding the documentary, go here.

 

GUEST POST: Time to Map and Monitor Pakistan’s Forests at the National Scale – Transparency and Accuracy

In Pakistan, too often, forested lands are treated as “free wastelands”. Deforestation and forest degradation is occurring primarily due to institutional negligence. An eye-opening example is massive deforestation in just four months observed in National Zoo-cum Park & Botanical Garden, Bani Gala, right in the capital territory of Islamabad. (see Fig. 1).

Figure1

Figure 1: A massive deforestation in four months (May-Oct, 2016) in National Zoo-cum Park & Botanical Garden, Bani Gala, Islamabad (Source of satellite images: Google Earth)

In Pakistan, many people consider real estate as the best investment, and this gives incentives for encroachers to intrude on state-owned land. Forested lands, due to their natural beauty and as a source of a double benefit, i.e., timber and land, are especially threatened by illegal land grabbers. Another example of forest degradation in Murree, Galliat region can be seen in Fig. 2, where 7.58 km2 of forest land was destroyed by  housing societies.

Figure2

Figure 2: Illegal encroachments in state-owned forests from 2005 to 2011: Bahria Golf City (Above) and OGDC Housing Society (Below). (Source of satellite images: Google Earth). See more detail in this published research article.

On the bright side, in recent years Pakistan has taken gigantic steps towards tree plantation under national (Green Pakistan Programme) and provincial (Billion Tree Tsunami in Khyber Pakhtunkhwa) initiates. These initiates have been well received and recognised globally. As an example, in 2009, Pakistan received a certificate from Guinness Book of World Records in acknowledgment of planting 541,176 mangrove plants in a single day in Keti Bunder (Indus Delta), Thatta district, Sindh province (see Fig. 3).

Figure3

Figure 3: Monitoring mangrove plantations: Repeat terrestrial photographs taken on May 2010 and May 2015 (left) and satellite images showing afforestation and conversion of mudflats into new mangroves (right). (Source of photographs: WWF-Pakistan; source of satellite images: Google Earth).

We should not forget that since 2011, Pakistan is part of UN-REDD (United National- Reducing Emission from Deforestation and Forest Degradation) program. Under the REDD program, developing countries receive performance-based incentives (payments) for reducing emissions of greenhouse gasses from forestlands. National Forest Monitoring System (NFMS) and Forest Reference Emission Level (FREL) / Forest Reference Level (FRL) systems are mandatory elements for REDD reporting system to get the financial benefits. Accurate and up-to-date information about the size, distribution, composition, and condition of forests and woodlands is essential for developing and monitoring policies and guidance to support their sustainable management. Although, in Pakistan, many independent researchers and organizations are conducting a number of scattered and local studies (e.g. Mapping Deforestation and Forest Degradation Patterns in Western Himalaya, Pakistan), however, a fundamental question remains:

How can we, in a systematic and transparent manner, map and monitor wall to wall Pakistan land cover and forest areas at the national scale?

Over the years, the use of satellite remote sensing data has become most popular among researchers and policy makers, for both smaller and larger scales. Consistent time series medium resolution freely available remote sensing data (e.g. Landsat, Sentinel-2 etc.) provide frequent, synoptic, and accurate measurements, monitoring, and simulation of earth surface features, especially forests. Unbiased ground information (field surveys, photographs, forest inventory, etc.) are very much necessary for the accuracy and evaluation of any product derived from satellite images. Under the REDD program, for FREL/FRL construction and reporting, Pakistan has to follow the guidance and guidelines of IPCC and the UNFCCC. For reporting to international bodies, Pakistan has to combine remote sensing and ground-based forest carbon inventory approaches for estimating, as appropriate, anthropogenic forest-related greenhouse gas emissions by sources and removals by sinks, forest carbon stocks, and forest area changes.

So, in my view, without further delay, Pakistan needs to take five steps for better forest management and policy formulations on the national scale:

  1. To operationalize satellite-based annual forest monitoring system for spatial quantification of deforestation, forest degradation, and afforestation
  2. To conduct comprehensive forest inventories for accuracy assessment, current forest stock, and greenhouse gas inventory
  3. To assess satellite-based land cover and land use changes at 5 years interval as an activity data for FRL reporting
  4. To map forest type and biomass/carbon stocks through integration of satellite and forest inventory data for spatial identification and quantification of habitats of tree species
  5. To develop a web-based visualization and dissemination tool using geospatial and socio-economic data for transparency and consistency

Conflicts of Interest: The findings reported stand as scientific study and observations of the author and do not necessarily reflect as the views of author’s organizations.

About this post: This is a guest post by Hammad Gilani. Learn more about this blog’s authors here.